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Journal of Radioanalytical and Nuclear Chemistry

, Volume 319, Issue 2, pp 533–666 | Cite as

Recommended nuclear data for medical radioisotope production: diagnostic positron emitters

  • F. T. Tárkányi
  • A. V. Ignatyuk
  • A. Hermanne
  • R. CapoteEmail author
  • B. V. Carlson
  • J. W. Engle
  • M. A. Kellett
  • T. Kibédi
  • G. N. Kim
  • F. G. Kondev
  • M. Hussain
  • O. Lebeda
  • A. Luca
  • Y. Nagai
  • H. Naik
  • A. L. Nichols
  • F. M. Nortier
  • S. V. Suryanarayana
  • S. Takács
  • M. Verpelli
Open Access
Article
  • 506 Downloads

Abstract

An IAEA coordinated research project that began in 2012 and ended in 2016 was primarily dedicated to the compilation, evaluation and recommendation of cross-section data for the production of medical radionuclides. One significant part of this work focused on diagnostic positron emitters. These particular studies consist of 69 reactions for direct and indirect or generator production of 44Sc(44Ti), 52mMn(52Fe), 52gMn, 55Co, 61Cu, 62Cu(62Zn), 66Ga, 68Ga(68Ge), 72As(72Se), 73Se, 76Br, 82Rb(82Sr), 82mRb, 86Y, 89Zr, 90Nb, 94mTc, 110mIn(110Sn), 118Sb(118Te), 120I, 122I(122Xe), 128Cs(128Ba), and 140Pr(140Nd) medical radionuclides. The resulting reference cross-section data were obtained from Padé fits to selected and corrected experimental data, and integral thick target yields were subsequently deduced. Uncertainties in the fitted results were estimated via a Padé least-squares method with the addition of a 4% assessed systematic uncertainty. Experimental data were also compared with theoretical predictions available from the TENDL-2015 and TENDL-2017 libraries. All of the numerical reference cross-section data with their corresponding uncertainties and deduced integral thick target yields are available on-line at the IAEA-NDS medical portal www-nds.iaea.org/medicalportal and also at the IAEA-NDS web page www-nds.iaea.org/medical/positron_emitters.html.

Keywords

IAEA coordinated research project Diagnostic medical isotopes Positron emitters Cross-section evaluation Uncertainty estimation Padé fit Bayesian inference Recommended σ and yield data 

Introduction

The importance of positron-emitting radionuclides in molecular imaging (Positron Emission Tomography, PET) has constantly increased over the years, especially to follow metabolic processes and to quantify radiation dose in internal radiotherapy. Nuclear data identified with these radionuclides are important for the optimisation of their production routes and medical applications. Judicious selection of the projectile energy range will maximise the yield of the product and minimise that of any radioactive impurities. Several charged-particle and neutron production routes exist for the production of such radionuclides. The International Atomic Energy Agency (IAEA) initiated and supported a Coordinated Research Project (CRP) from 1997 to 2001 with the primary aim of establishing a reference nuclear reaction database for the most important gamma-ray and positron emitters and associated monitor reactions in order to optimise their production [1]. No uncertainties in the recommended data were produced at that time. The list of positron emitters that was included in this earlier effort is shown in Table 1. The reference cross-section data and integral thick target yields were made available in a hard-copy technical document, and later became accessible on the medical portal of the IAEA Nuclear Data Section (IAEA-NDS) with further updates from 2001 to 2007 [2].
Table 1

Earlier evaluated nuclear reactions for the production of diagnostic PET isotopes (1995–1999), and also made available as an IAEA nuclear database [1, 2]

PET radionuclide

Half-life

Decay (%)

End-point energy (keV)

Reaction product

Half-life

Decay (%)

Production reaction

11C

1221.8 s

99.7669 β+

960.4

11C

1221.8 s

99.7669 β+

14N(p,α)11C

13N

9.965 min

99.8036 β+

1198.5

13N

9.965 min

99.8036 β+

16O(p,α)13N

15O

122.24 s

99.9003 β+

1732.0

15O

122.24 s

99.9003 β+

15N(p,n)15O

       

14N(d,n)15O

18F

109.77 min

96.73 β+

633.5

18F

109.77 min

96.73 β+

18O(p,n)18F

       

natNe(d,x)18F

68Ga

67.71 min

88.91 β+

1899.1

68Ge

270.95 d

100 EC

69Ga(p,2n)68Ge

       

natGa(p,xn)68Ge

82Rb

1.2575 min

95.43 β+

3378

82Sr

25.35 d

100 EC

85Rb(p,4n)82Sr

       

natRb(p,xn)82Sr

Decay data as tabulated have been taken from NuDat (NuDat 2.6 or 2.7), a user-friendly form of ENSDF [4, 5]

Over the previous two decades new experimental data have been measured for the earlier evaluated reactions, and numerous new and potentially suitable candidate PET-isotopes have appeared in the literature along with pre-clinical studies. Therefore, a new CRP was initiated at the end of 2012 in order to redefine the production routes and upgrade the production data for the previously studied radionuclides, and to complement the database with the equivalent results for emerging prospective radionuclides. An additional goal of the working programme was to provide uncertainties for the recommended cross sections of all the reactions studied [3]. The results of this evaluation work are summarised for production routes applicable to diagnostic positron emitters, including generator systems for short-lived radionuclides.

Evaluation method

The evaluation process was performed in a similar manner to previous studies [1, 6], and includes the following steps that will be discussed in more detail below:

Thorough compilation of experimental data

Detailed searches for published experimental cross sections were made, including the following sources: primary publications in journals, EXFOR database of IAEA-NDS [7], IAEA INIS database [8], evaluated libraries (ENDF) [9], bibliographies of Brookhaven National Laboratory (Burrows and Dempsey [10], Holden et al. [11], Karlstrom and Christman [12]), reports of the International Atomic Energy Agency (Dmitriev [13], Gandarias-Cruz and Okamoto [14]), Landolt Börnstein Series [15], Landolt Börnstein New Series [16], Tobailem et al. [17], Albert et al. [18], Münzel et al. [19], PhD theses, other relevant evaluations, private communications, etc. All experimental references are cited in each of the subsections that describe specific reaction paths.

The cut-off for inclusion of new data was set at June 2016, and therefore some results published in the final year of this compilation exercise were not added into the already completed fits but are still shown among the datasets retrieved. Duplications of original data published in the numerous review papers on production and/or use of medical radionuclides are explicitly mentioned in this study.

New CRP measurements

Additional experiments were performed by various CRP participants as crucial support in defining the excitation functions of the 45Sc(d,3n)44Ti, natNi(p,x)52Fe, 55Mn(p,4n)52Fe, 50Cr(α,2n)52Fe, 58Ni(p,α)55Co, 61Ni(p,n)61Cu, 60Ni(d,n)61Cu, natGa(p,x)68Ge, natGe(p,xn)72As, natGe(d,xn)72As, 89Y(d,2n)89Zr, 93Nb(p,x)90Nb, 92Mo(α,x)94mTc, 110Cd(p,n)110mIn, 107Ag(α,n)110mIn, natSb(p,xn)118Te and 141Pr(d,3n)140Nd reactions. Details of these studies have been reported individually and separately in other dedicated publications (see references for specific reactions given below).

Status of earlier experimental data

Large sets of experimental data are available for some reactions, but only one or two relevant measurements exist for other reactions. Investigation of the published data permits some general remarks and conclusions to be made:
  • Early investigations from 1945 to 1970 were mostly dedicated to the study of nuclear reaction mechanisms, and were performed on accelerators possessing somewhat limited technology of that time. The information on decay data and estimated uncertainties adopted for these experiments are poor in most cases.

  • Production of medical radionuclides used in clinical practice would normally involve monoisotopic or at least enriched targets. However, production cross sections are sometimes determined by evaluators from data obtained with natural targets over limited energy ranges (up to the threshold of the next contributing reaction) in order to derive suitable data for subsequent evaluation. These data are in many cases more reliable due to the higher quality of the targets employed (with respect to thickness and uniformity).

  • Nowadays, excitation functions are commonly measured over a broader energy range by means of the stacked-foil technique. This method possesses significant advantages in irradiation time and the determination of good relative values because of the fixed number of bombarding particles in each sample. However, long stacks suffer from an accumulation of effects caused by uncertainties in foil thicknesses that result in a possible increasing energy shift throughout the stack. The precise energy in each foil can be controlled by simultaneous measurements of the excitation function of reference monitor reactions over the whole energy range, but this is very rarely undertaken.

  • Another possibility is to irradiate a large number of targets simultaneously in conjunction with rotating wheels in which different energy absorbers with well-measured thicknesses are inserted before each target. The number of bombarding particles incident on each target is the same and well controlled, although one disadvantage is the much longer irradiation time needed when compared with stacked-foil irradiations.

  • Overwhelming parts of the datasets exhibit consistent and realistic behaviour, but in some cases points in a given set may disagree significantly from the observed trend and with other data without any obvious reason (although a most probable cause is an incorrect estimation of the real target thickness). These clearly discrepant data points were not considered as valid data during the fitting process.

Knowledge of the energy and energy distribution of the incident particle beam is important in reducing the uncertainty of the energy values of the data points. This information is preferably obtained by prior measurement, However, these incident beam parameters are rarely known for production machines in which the use of high-intensity beams causes changes in target quality (i.e., surface density and uniformity of target atoms). Gas targets are especially sensitive to density reduction caused by the heat generated from high-current beams.

Essentially two methods were used in these experiments to determine the number of incident particles: direct collection of the total charge in a Faraday cup, or indirectly by means of the reference data from a series of monitor reactions. Some experiments involve only the activity of a single monitor foil inserted in front of the target stack compared with the activity of the same foil target measured in a Faraday cup at the same energy. An additional factor of uncertainty is the constancy over time of the number of incident particles, especially when the half-life of the radionuclide investigated is comparable to or shorter than the irradiation time. Not all laboratories have the instrumentation needed to monitor and quantify the beam intensity on the target during the irradiation.

Other factors are the method of detection of the different types of radiation emitted in order to quantify the product nuclei: X-rays, gamma rays, alpha and beta particles, and neutron emissions involve the use of detectors that possess very different energy resolution and efficiency. Nevertheless, recent developments in detector technology have resulted in greater reliability and commensurate reductions in the uncertainties. Compilations and evaluations of the measured results and assessment of the quality of the reported work from different laboratories require all these factors be taken into account, which requires detailed investigations of all of the original publications.

Correction of earlier experimental data

Where possible, published cross sections that rely on outdated decay data were corrected by taking new decay data into account by means of NuDat [4] (with the Evaluated Nuclear Structure Data File (ENSDF) [5] as the data source). This form of correction was also carried out with respect to the decay data associated with the adopted monitor reactions. As any correction with respect to updated half lives has a non-linear impact on the well-known activation equation used to determine the cross section (primarily factors related to time), caution has to be taken when applying such adjustments. They are only possible if timing information is available in the original publication. The correction for other linear factors can be more easily performed, but also requires knowledge of the decay data used by the original authors.

Excitation functions measured over a broad energy range that show often relatively small uncertainties are sometimes significantly different from more reliable data determined over a shorter energy range. These higher energy data were normalised in such cases to the well measured data to produce reference data in a broad energy range. The same method was also adopted in the case of systematic energy shifts observed in the stacked-foil technique, which can be linearly corrected with respect to data measured on accelerators with high-energy definition.

Fitting procedures require reliable uncertainties in the experimental data selected for such statistical analyses. Unfortunately, the uncertainties in the cross-section values and the beam energy are not always appropriately provided as a significant part of the published experimental data. Therefore, missing cross-section uncertainties were estimated on the basis of the measurement methodology and the experience of the compilers/evaluators.

The experimental data for a given reaction measured with similar methods and comparable technology in different laboratories often have significantly different quoted uncertainties. Some studies report uncertainties that are unrealistically low because all contributing statistical or systematic effects have not been taken into account, or are incorrectly estimated. Therefore, such values were corrected to more realistic average uncertainties to avoid incorrect weighting in the fitting procedure.

Comparisons with theoretical predictions

Experimental data were compared with theoretical predictions of activation by charged-particle reactions, as assembled and made available in the online TENDL-2015 and TENDL-2017 libraries [20]. Both of these libraries are based on the reaction modelling adopted in the TALYS code [21]. The TENDL libraries are derived from both default and adjusted TALYS calculations, and occasionally from other sources.

The aim of the comparisons was to obtain a general impression of the shape of each excitation function over a broad energy range, including the magnitude of the maximum cross-section value and the effective threshold of reaction in cases where there were contradicting data. These predictions also permitted extrapolation of the excitation function in cases where experimental data were only available over a short and limited energy range as input for the Bayesian least-square fit (e.g., for the Padé fit). All TENDL predictions are shown along with the experimental data in the various figures of the excitation functions. Recently published results of evaluations for different activation products obtained from fitting by adjustment of theoretical codes to a compilation of existing experimental results (including some from this coordinated research project) have not been considered here, as the Bayesian non-model evaluation is the preferred evaluation method.

Critical comparisons and selection of the most reliable experimental data

Corrected and analysed experimental data were visually compared in figures that also included the theoretical predictions.

Measurement of radioactivity

The main sources of error when determining absolute activity are faulty estimates of the detector efficiency (especially in the low-energy region), self-absorption of low-energy gamma rays, geometry deviations between point source calibrations and the activated spot size on targets, dead-time and pile-up corrections, and the adoption of incorrect decay data.

Determination of the energy scale

Errors in the energy scale are introduced by improper estimation of the energy of the primary beam, uncertainties in the effective thickness of the individual targets, the cumulative effect of the stacked-foil technique, and the ill-defined impact of absorbers introduced to vary the energy of the incoming beam. Accelerators used for data measurements in nuclear physics usually have the necessary facilities to measure the energy of the beams precisely.

Estimation of uncertainties of the cross sections and energy scale

Despite the existence of the JCGM guide for the expression of uncertainty in measurements that experimentalists are strongly advised to follow [22], we have found that no such recommended systematic procedures have been undertaken to estimate properly the uncertainty of the measured cross sections and their energy scale. Various factors contribute to the assessment of the uncertainty associated with cross-section measurements. Unfortunately, authors in many original publications present only the total uncertainty in their tables of cross sections, without discussing or defining the estimated uncertainties of the contributing processes (i.e., no sufficiently detailed uncertainty budget is given).

A number of noteworhy observations were made during the course of the evaluation process:
  • data from different authors often show striking systematic disagreements over the whole energy range;

  • data below the reaction threshold were frequently reported;

  • sometimes the data were extensively scattered, without any explanation;

  • specific laboratories carried out systematic investigations, and as a consequence generated good results for many reactions.

Due to a general lack of information reported in the original publications and earlier compilations, the quality of the data could not be assessed in most cases, nor reasons identified for disagreements with other publications apart from a few exceptions. The most likely sources of disagreement or reasons for discrepancies among the experimental data were as follows:

Beam current. While relying on monitor reactions, the main problem originates from the use of outdated monitor cross sections. Another source of error was improper use of monitors, especially an incorrect estimation of the energy of the bombarding particle in a region where the excitation function curve has a steep slope (which will lead to an under- or overestimation of the beam flux).

Determination of the number of target nuclei. Although difficult to determine the number of target nuclei with high precision, an uncertainty below five percent can be easily achieved. The main challenges in the case of thin solid targets are uncertainties associated with the chemical state caused by surface oxidation, non-uniformity in the thickness of the foil, and improper estimation of the shape or dimensions influencing the thickness derived from weighing. Furthermore, well-known density reductions along the beam due to the heat effect play a very important role in the case of gas targets.

On the basis of emerging inconsistencies and trends, contradictory and scattered data were rejected from the analyses. Such an extensive selection process takes into account many factors, of which a few cannot be formulated in a mathematical manner, but rather are based on invaluable experienced, yet subjective, judgements by the evaluators.

Data fitting and resulting uncertainties- Padé fit of selected experimental data

Previous evaluations of the experimental cross-section data for diagnostic radionuclides were usually fitted by the spline method. Such a procedure is based on a piecemeal approximation of the data between specified points (knots of the spline) based on individual interpolating polynomials. These polynomials match in such a way that the zeroeth, first and second derivatives are continuous at the knots, and are usually selected by the second (quadratic interpolation) or third order (cubic interpolation). A continuous and smooth fit is obtained with minimum twisting (oscillating behaviour) of the fitting curve, which arises from the conditions for continuity. A particular feature of the spline method is that the fit in a selected interval is independent from the data in other intervals.

The spline method is well known (e.g., see Ref. [23] and references therein), and has been applied in nuclear data evaluations. Some known shortcomings relate to the following requirements and inadequacies:
  • knots have to be selected by a user, which makes the fit time consuming with partially arbitrary results;

  • cubic splines are not always adequate for complex-shaped curves.

A more general class of analytical function is the rational function defined as the ratio of two polynomials. Such an approximation was proposed by Padé over one hundred and twenty years ago [24], and has become one of the most important interpolation techniques of statistical mathematics [25, 26]. As a rational function, the Padé approximant can be expressed by a set of real polynomial coefficients, or by a set of real coefficients of the pole expansion
$$ p_{L} (z) = c + \sum\limits_{l} {\tfrac{{a_{l} }}{{z - \eta_{l} }} + \sum\limits_{k} {\frac{{\alpha_{k} (z - \varepsilon_{k} ) + \beta_{k} }}{{(z - \varepsilon_{k} )^{2} + \gamma_{{_{k} }}^{2} }}} } , $$
(1)
where z = x + iy are complex variables, and L is the order of the polynomial representation of the Padé approximant (therefore all coefficients depend implicitly on L) [25, 26]. This equation is also called the resonance expansion, in which εk and γk are the energy and the total half-width of the kth resonance, respectively, while αk and βk are the partial widths and interference parameters. The first sum corresponds to the real poles, while the second sum relates to the complex poles.

Effective codes for practical applications of the Padé approximation were developed by the IPPE, Obninsk group [27]. The simplest version of these codes permits analyses of up to 500 experimental points, with the number of parameters L ≤ 40 and the ratio limit of analysed functions up to fmax/fmin≤ 106. A more detailed description of the method can be found in Ref. [27], and some important questions of application are presented in Refs. [28, 29].

Padé approximations are also very convenient for calculations of the data uncertainties and the corresponding covariance matrices. The fitting procedure is always based on a minimisation of the deviation functional
$$ \chi^{2} = (N - L)^{ - 1} \sum\limits_{j = 1}^{N} {(p_{L} (x_{j} ) - f_{j} )^{2} /\sigma_{j}^{2} } , $$
(2)
where fj are the available experimental data, σj are their total uncertainties (including both systematic and statistical components) and N is the number of analysed points. Such minimisation is carried out iteratively by means of the discrete optimization approach. Minimal deviation for a given L is computed by assessing and selecting L points from the available N points (L < N), and then determining the corresponding approximants from Eq. (2). Once this process has been completed, L is changed and the iteration is repeated until an overall minimum is found from all discrete possibilities available. Some additional details of the method are considered in our earlier paper that focused on the evaluation of charged-particle monitor reactions [30].

Along with a consistent consideration of the statistical uncertainties of experimental data, the Padé method allows the determination of some systematic uncertainties that are usually underestimated by their authors, and also establishes some implicit correlations of the data. The averaged deviation of the full experimental dataset from the approximating function is regarded as the systematic uncertainty, while the variances of deviations around the averaged values are regarded as the statistical uncertainties. An optimal description of all data is achieved by the traditional iteration procedure of minimizing the mean squares deviations with the statistical and systematic uncertainties.

Only total uncertainties are determined in the majority of the experimental studies, and reasonable reconstructions of the corresponding systematic uncertainties are judged to be impossible to achieve in many of these cases. The method described above provides estimates of the systematic uncertainties on the basis of general statistical criteria which are valid for a reasonable number of studies. However, for a small number of the experimental measurements, underestimation of the systematic uncertainties is highly probable. Such underestimations also occur in those cases whereby the same, very similar, or other components of the same experimental equipment are used in a range of different studies, since any related correlations have been neglected.

After analysing the complete set of available data, we have come to the conclusion that realistic total uncertainties cannot be defined as less than 4% for each of the reactions considered. Therefore, an additional systematic uncertainty of 4% has been introduced as part of each systematic uncertainty derived from statistical analyses of all the recommended cross sections.

Integral yields for thick targets as a function of particle energy

Integral thick target yields as a function of energy were calculated from the recommended cross section data. We have quantified the production rates for radionuclides whose half-lives are short relative to the length of irradiation. This rate is also known as the “physical yield”, or “instantaneous production rate”, since the effect of decay of the radionuclide is small compared with the activity being created. Two other yields are also defined on the IAEA medical portal [2], namely the activity of a fixed 1 h and 1 µA irradiation, and the saturation activity at EOB for a 1 µA irradiation.

The activity of a fixed 1 h/1 μA irradiation is meaningful and can be used in practice for longer-lived radionuclides where the activity is increasing linearly with irradiation time. Saturation activity is used in the case of short half-life radionuclides, when a constant activity is obtained for even relatively short irradiations. The definition of these parameters can be found in Bonardi [31], and Otuka and Takács [32]. Thick target yields for the different production routes leading to a given radionuclide are summarised within a figure at the end of every subsection.

Medically relevant radionuclides can be obtained in many cases from the decay of a parent with a different half-life (indirect production, or generator couple). Two separate figures are shown in such cases, corresponding to the yields at EOB for the shorter-lived daughter and the longer-lived parent (often orders of magnitude lower). Depending on the relative half-lives, either time-dependent partial equilibrium (indirect production in which mother and daughter have comparable half-lives), or total equilibrium (long-lived parent/short-lived daughter generators) is obtained.

Results for charged-particle reactions

The list of reactions evaluated in the present studies consists altogether of 69 charged-particle reactions for the production of 23 radionuclides of interest for PET imaging, including 11 generator systems for short-lived medically interesting radioisotopes (Table 2). There are 39 proton reactions, 16 deuteron reactions, one reaction for 3He, and 13 reactions for α particles. Energies of incident particles cover the range from a few MeV up to 100 MeV. Every subsequent subsection contains a summary of the most frequent use of each of the 23 medically relevant radionuclides, and the literature references found for each production route (given in both the text and figures), selected data (text and figures) and the characteristics of the Padé fit (text and figures). As mentioned previously, the physical yields are included in one or two additional figures at the end of each subsection if indirect and/or generator production is being considered.
Table 2

Evaluated nuclear reactions and decay data adopted for production of diagnostic PET radionuclides (2012–2016) [2]. Reaction thresholds for natural targets estimated approximately from the plots, and are given in bold

PET radionuclide

Target

Reaction

Reaction threshold (MeV)

Reaction product

Half-lifea

Decay (%)a

Eγ (keV), Pγ (%)

Order of Padé polynomial L

Comment

44Sc

44Ca

44Ca(p,n)44Sc

4.537

44Sc

3.97 h

EC + β+ 100 (β+94.27)

19

Direct

 

44Ca

44Ca(d,2n)44Sc

6.965

  

γ: 1157.020, 99.9

9

Direct

 

43Ca

43Ca(d,n)44Sc

0

   

5

Direct

 

45Sc

45Sc(p,2n)44Ti

12.65

44Ti

59.1 y

EC 100

7

Generator

 

45Sc

45Sc(d,3n)44Ti

15.25

  

From decay of44Sc

6

Generator

52mMn

natNi

natNi(p,x)52Fe

40

52Fe

8.275 h

EC + β+ 100 +55.49)

11

Generator

 

55Mn

55Mn(p,4n)52Fe

35.00

  

From decay of 52mMn

17

Generator

 

50Cr

50Cr(α,2n)52Fe

16.90

   

9

Generator

 

52Cr

52Cr(p,n)52mMn

5.60

52mMn

21.1 min

EC + β+ 98.22 (β+96.6)

14

Direct

 

52Cr

52Cr(d,2n)52mMn

8.02

  

IT 1.78

γ: 1434.092, 98.2

8

Direct

52Mn

52Cr

52Cr(p,n)52gMn(m+)

5.60

52gMn

5.591 d

EC + β+ 100 (β+29.4)

9

Direct

 

52Cr

52Cr(d,2n)52gMn(m+)

8.02

  

γ: 744.233, 90.0;

935.544, 94.5

8

Direct

55Co

58Ni

58Ni(p,α)55Co

1.358

55Co

17.53 h

EC + β+ 100 (β+ 76)

10

Direct

 

54Fe

54Fe(d,n)55Co

0

  

γ: 931.1, 75;

13

Direct

 

56Fe

56Fe(p,2n)55Co

15.71

  

1316.6, 7.1

8

Direct

61Cu

61Ni

61Ni(p,n)61Cu

3.07

61Cu

3.339 h

EC + β+ 100 (β+61)

12

Direct

 

60Ni

60Ni(d,n)61Cu

0

  

γ: 282.956, 12.2;

16

Direct

 

64Zn

64Zn(p,α)61Cu

0

  

656.008, 10.8;

1185.234, 3.7

12

Direct

62Cu

natCu

63Cu(p,2n)62Znb

13.48

62Zn

9.193 h

EC + β+ 100 (β+8.2)

16

Generator

 

natCu

63Cu(d,3n)62Znb

15.986

  

γ: 548.35, 15.3;

12

Generator

 

natNi

natNi(α,xn)62Zn

18.5

  

596.56, 26

10

Generator

 

62Ni

62Ni(p,n)62Cu

4.818

62Cu

9.67 min

EC + β+ 100 (β+97.83)

12

Direct

 

62Ni

62Ni(d,2n)62Cu

7.192

  

γ: 875.66, 0.147;

1172.97, 0.342

5

Direct

66Ga

66Zn

66Zn(p,n)66Ga

6.049

66Ga

9.49 h

EC + β+ 100 (β+57)

13

Direct

 

63Cu

63Cu(α,n)66Ga

7.980

  

γ: 833.5324, 5.9;

1039.220, 37.0

13

Direct

68Ga

68Zn

68Zn(p,n)68Ga

3.758

68Ga

67.71 min

EC + β+ 100 (β+88.91)

20

Direct

 

65Cu

65Cu(α,n)68Ga

6.183

  

γ: 1077.34, 3.22

10

Direct

 

natGa

natGa(p,xn)68Ge

10.5

68Ge

270.95 d

EC 100

11

Generator

 

69Ga

69Ga(p,2n)68Ge

11.366

  

From decay of 68Ga

8

Generator

72As

75As

75As(p,4n)72Se

30.57

72Se

8.40 d

EC 100

8

Generator

 

natBr

natBr(p,x)72Se

50

  

From decay of 72As

10

Generator

 

natGe

natGe(p,xn)72As

5

72As

26.0 h

EC + β+ 100 (β+87.8)

18

Direct

 

natGe

natGe(d,xn)72As

8

  

γ: 629.92, 8.07;

833.99, 81

10

Direct

73Se

75As

75As(p,3n)73Se

22.024

73Se

7.15 h

EC + β+ 100 (β+65.4)

9

Direct

 

72Ge

72Ge(α,3n)73Se

27.60

  

γ: 67.07, 70;

361.2, 97.0

8

Direct

76Br

76Se

76Se(p,n)76Br

5.821

76Br

16.2 h

EC + β+ 100 (β+55)

8

Direct

 

77Se

77Se(p,2n)76Br

13.336

  

γ: 559.09, 74;

9

Direct

 

75As

75As(α,3n)76Br

25.84

  

657.02, 15.9;

1853.67, 14.7

10

Direct

82Rb

natRb

natRb(p,xn)82Sr

30

82Sr

25.35 d

EC 100

13

Generator

 

85Rb

85Rb(p,4n)82Sr

31.52

  

From decay of 82Rb:

T1/2 = 1.2575 min

EC + β+ 100 (β+ 95.43)

γ: 776.52, 15.08

9

Generator

82mRb

82Kr

82Kr(p,n)82mRb

5.250

82mRb

6.472 h

EC + β+ 100 (β+21.2)

9

Direct

 

82Kr

82Kr(d,2n)82mRb

7.593

  

γ: 554.35, 62.4;

619.11, 37.98;

698.37, 26.3;

776.52, 84.39;

827.83, 21.0;

1044.08, 32.07;

1317.43, 23.7;

1474.88, 15.5

5

Direct

86Y

86Sr

86Sr(p,n)86Y

6.093

86Y

14.74 h

EC + β+ 100 (β+31.9)

9

Direct

 

88Sr

88Sr(p,3n)86Y

25.86

  

γ: 627.72, 32.6;

8

Direct

 

85Rb

85Rb(α,3n)86Y

25.84

  

1076.63, 82.5;

1153.05, 30.5

8

Direct

89Zr

89Y

89Y(p,n)89Zr

3.656

89Zr

78.41 h

EC + β+ 100 (β+22.74)

11

Direct

 

89Y

89Y(d,2n)89Zr

5.972

  

909.15, 99.04

9

Direct

90Nb

93Nb

93Nb(p,x)90Nb

29.08

90Nb

14.60 h

EC + β+ 100 (β+51.2)

9

Direct

 

89Y

89Y(α,3n)90Nb

28.04

  

γ: 132.716, 4.13;

141.178, 66.8;

1129.224, 92.7

16

Direct

94mTc

92Mo

92Mo(α,x)94mTc

16.26

94mTc

52.0 min

EC + β+ 100 (β+70.2)

12

Direct

 

94Mo

94Mo(p,n)94mTc

5.092

  

γ: 871.05, 94.2;

1522.1, 4.5;

1868.68, 5.7

9

Direct

110mIn

natIn

natIn(p,xn)110Sn

30

110Sn

4.154 h

EC 100

17

Generator

 

108Cd

108Cd(α,2n)110Sn

17.76

  

γ: 280.459, 97.06

10

Generator

 

110Cd

110Cd(p,n)110mIn

4.703

110mIn

69.1 min

EC + β+ 100 (β+61.3)

11

Direct

 

110Cd

110Cd(d,2n)110mIn

7.011

  

γ: 2129.40, 2.15;

5

Direct

 

107Ag

107Ag(α,n)110mIn

7.867

  

2211.33, 1.74;

2317.41, 1.285

9

Direct

118Sb

115Sn

115Sn(α,n)118Te

8.262

118Te

6.00 d

EC 100

7

Generator

 

116Sn

116Sn(α,2n)118Te

18.15

  

From decay of 118Sb:

6

Generator

 

natSb

natSb(p,x)118Te

30

  

T1/2 = 3.6 min

12

Generator

 

natSb

natSb(d,x)118Te

34

  

EC + β+ 100 (β+73.5)

4

Generator

      

γ: 1229.33, 2.5

  

120I

120Te

120Te(p,n)120I

6.451

120I

81.6 min

EC + β+ 100 (β+68.2)

18

Direct

 

122Te

122Te(p,3n)120I

23.68

  

γ: 601.1, 5.51;

1523.0, 10.9

7

Direct

122I

124Xe

124Xe(p,x)122Xe

18.60

122Xe

20.1 h

EC 100

5

Generator

 

127I

127I(p,6n)122Xe

45.12

  

γ: 350.065, 7.80; and

7

Generator

 

127I

127I(d,7n)122Xe

47.74

  

from decay of 122I:

T1/2 = 3.63 min

EC + β+ 100 (β+78)

γ: 564.119, 18

12

Generator

128Cs

133Cs

133Cs(p,6n)128Ba

44.16

128Ba

2.43 d

EC 100

γ: 273.44, 14.5; and

from decay of 128Cs:

T1/2 = 3.66 min

EC + β+ 100 (β+68.8)

γ: 442.901, 26.8

18

Generator

140Pr

141Pr

141Pr(p,2n)140Nd

10.68

140Nd

3.37 d

EC 100

10

Generator

 

141Pr

141Pr(d,3n)140Nd

13.02

  

From decay of 140Pr:

9

Generator

 

natCe

natCe(3He,xn)140Nd

16

  

T1/2 = 3.39 min

EC + β+ 100 (β+51)

γ: 306.9, 0.147;

1596.1, 0.49

9

Generator

aDecay data as tabulated have been taken from NuDat (NuDat 2.6 or 2.7), a user-friendly form of ENSDF [4, 5]

bOnly contributing reaction in natural Cu targets at these energies

Half-lives and limited decay-scheme data for the different radionuclides discussed in the following subsections can be found in Table 2. The γ-ray energies in keV and the corresponding absolute emission probabilities (absolute intensities, Pγ(%)) used to identify and quantify the activity of a given radionuclide in the experimental studies (and β+ decay fraction instead of the intensity of the 511 keV annihilation radiation) are listed, and have also been included within each of the primary subsections of this Section.

Reactions for radionuclides present in Table 1 but not considered during the course of this CRP will be evaluated in a similar manner as part of a future series of IAEA-sponsored studies and will be published elsewhere.

Production of 44gSc (T 1/2 = 3.97 h) and long-lived 44Ti parent (T 1/2 = 59.1 y)

Applications: 44Sc (av. Eβ+ = 632.0 keV, 94.27% intensity) has emerged as an attractive radiometal candidate for PET imaging by means of e.g., DOTA-functionalised biomolecules. 44Sc-labelled PET radiopharmaceuticals appear of interest for molecular imaging of medium-lasting physiological processes. Also forms a theranostic pair with therapeutic 47Sc.

44Sc (3.97 h): β+ (94.27%), and Eγ (keV) (Pγ(%)): 1157.020 (99.9).

44Ti (59.1 y): detected by means of radiation emitted by daughter 44Sc.

44Ca(p,n)44Sc, 44Ca(d,2n)44Sc and 43Ca(d,n)44Sc direct reactions and 45Sc(p,2n)44Ti-44Sc, 45Sc(d,3n)44Ti-44Sc generator production routes were evaluated.

44Ca(p,n)44gSc

The six experimental datasets available in the literature are shown in Fig. 1 [33, 34, 35, 36, 37, 38], together with the TENDL calculations. Three sets were rejected Cheng et al. [34] and Mitchell [35] (too high values near the threshold), and Krajewski et al. [37] (strange overall shape)), while the remaining four datasets were used in the statistical fitting procedure. Both the selected data and their experimental uncertainties are shown in Fig. 2 together with the Padé fit (L = 14, N = 49, Χ2 = 1.63) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 1

Six experimental datasets for the 44Ca(p,n)44Sc reaction available in the literature [33, 34, 35, 36, 37, 38], and TENDL calculations

Fig. 2

Three selected experimental datasets for the 44Ca(p,n)44Sc reaction [33, 36, 38] with the Padé fit (L = 19, N = 56, χ2 = 1.86, solid line), and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

44Ca(d,2n) 44gSc

Only one experimental dataset is available in the literature, and is shown in Fig. 3 [39] together with the TENDL calculations. These data and their experimental uncertainties are shown in Fig. 4 together with the Padé fit (L = 9, N = 9, χ2 = 0.53) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 3

One experimental dataset for the 44Ca(d,2n)44gSc reaction available in the literature [39], and TENDL calculations

Fig. 4

Experimental dataset for the 44Ca(d,2n)44gSc reaction [39] with the Padé fit (L = 9, N = 9, χ2 = 0.53, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

43Ca(d,n)44gSc

Only one experimental dataset is available in the literature, and is shown in Fig. 5 [40] together with the TENDL calculations. These data and their experimental uncertainties are shown in Fig. 6 together with the Padé fit (L = 5, N = 16, χ2 = 1.49) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 5

One experimental dataset for the 43Ca(d,n)44gSc reaction available in the literature [40], and TENDL calculations

Fig. 6

Experimental dataset for the 43Ca(d,n)44gSc reaction [40] with the Padé fit (L = 5, N = 16, χ2 = 1.49, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

45Sc(p,2n)44Ti

The five experimental datasets available in the literature are shown in Fig. 7 [36, 41, 42, 43] together with the TENDL calculations—Ref. [42] contains two sets labelled (a) and (b). Three datasets were rejected (both datasets of Ejnisman et al. [42], and McGee et al. [41] exhibit significant disagreement), while the remaining two datasets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 8 together with the Padé fit (L = 7, N = 26, χ2 = 1.58) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 7

Five experimental datasets for the 45Sc(p,2n)44Ti reaction available in the literature [36, 41, 42, 43], and TENDL calculations

Fig. 8

Two selected experimental datasets for the 45Sc(p,2n)44Ti reaction [36, 43] with the Padé fit (L = 7, N = 26, χ2 = 1.58, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

45Sc(d,3n)44Ti

Only one experimental dataset is available in the literature, and is shown in Fig. 9 [44] together with the TENDL calculations. These data and their experimental uncertainties are shown in Fig. 10 together with the Padé fit (L = 6, N = 18, χ2 = 0.406) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 9

One experimental dataset for the 45Sc(d,3n)44Ti reaction available in the literature [44], and TENDL calculations

Fig. 10

One experimental dataset for the 45Sc(d,3n)44Ti reaction [44] with the Padé fit (L = 6, N = 18, χ2 = 0.406, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 44gSc, and long-lived 44Ti parent

See Figs. 11 and 12.
Fig. 11

Thick target yields calculated from the recommended cross sections for the 44Ca(p,n)44gSc, 44Ca(d,2n)44gSc and 43Ca(d,n)44gSc reactions

Fig. 12

Thick target yields calculated from the recommended cross sections for the 45Sc(p,2n)44Ti and 45Sc(d,3n)44Ti reactions to produce long-lived parent for 44Sc generator

Production of 52mMn (T 1/2 = 21.1 min) and longer-lived 52Fe parent (T 1/2 = 8.275 h)

Applications: 52mMn has been suggested for myocardial and cerebral perfusion imaging, more recently for studies similar to Mn-enhanced neuronal MRI, and for diagnosis in other organ systems—bones, spinal cord and the digestive tract.

52mMn (21.1 min): β+ (96.6%), and Eγ (keV) (Pγ(%)): 1434.092 (98.2).

52Fe (8.275 h): detected by means of radiation emitted from daughter 52mMn.

Evaluations have been made of the 52Cr(p,n)52mMn and 52Cr(d,2n)52mMn direct production routes and natNi(p,x)52Fe, 55Mn(p,4n)52Fe and 50Cr(α,2n)52Fe reactions for indirect production through decay of the longer-lived parent.

natNi(p,x)52Fe

The four experimental datasets available in the literature are shown in Fig. 13 [45, 46, 47, 48] together with he TENDL calculations. One set was rejected (Titarenko et al. [47], values too high), and the remaining three datasets were used in the statistical fitting procedure. These selected data and their experimental uncertainties are shown in Fig. 14 together with the Padé fit (L = 11, N = 41, χ2 = 0.57) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 13

Four experimental datasets for the natNi(p,x)52Fe reaction available in the literature [45, 46, 47, 48], and TENDL calculations

Fig. 14

Three selected experimental datasets for the natNi(p,x)52Fe reaction [45, 46, 48] with the Padé fit (L = 11, N = 41, χ2 = 0.57, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

55Mn(p,4n)52Fe

The four experimental datasets available in the literature are shown in Fig. 15 [46, 49, 50, 51] together with the TENDL calculations. All sets were used for the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 16 together with the Padé fit (L = 17, N = 157, χ2 = 1.01) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 15

Four experimental datasets for the 55Mn(p,4n)52Fe reaction available in the literature [46, 49, 50, 51], and TENDL calculations

Fig. 16

Four experimental datasets for the 55Mn(p,4n)52Fe reaction [46, 49, 50, 51] with the Padé fit (L = 17, N = 157, χ2 = 1.01, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

50Cr(α,2n)52Fe

The four experimental datasets available in the literature are shown in Fig. 17 [36, 52, 53, 54] together with the TENDL calculations. Two datasets were rejected (Akiha et al. [52], energy shift; Chowdhury et al. [53], unusual shape,with one outlying data point at 27.3 MeV not represented in Fig. 17), while the remaining two datasets were used in the statistical fitting procedure. Both the selected data and their experimental uncertainties are shown in Fig. 18 together with the Padé fit (L = 9, N = 52, χ2 = 0.616, solid line) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 17

Four experimental datasets for the 50Cr(α,2n)52Fe reaction available in the literature [36, 52, 53, 54], and TENDL calculations

Fig. 18

Two selected experimental datasets for the 50Cr(α,2n)52Fe reaction [36, 54] with the Padé fit (L = 9, N = 52, χ2 = 0.616, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

52Cr(p,n)52mMn

The nine experimental datasets available in the literature are shown in Fig. 19 [36, 55, 56, 57, 58, 59, 60, 61, 62] together with the TENDL calculations. Three datasets were rejected (Blosser and Handley [56], Wing and Huizenga [58], and West et al. [62], all values too high), while the remaining six datasets were used in the statistical fitting procedure. Both the selected data and their experimental uncertainties are shown in Fig. 20 together with the Padé fit (L = 14, N = 68, χ2 = 1.15) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 19

Nine experimental datasets for the 52Cr(p,n)52mMn reaction available in the literature [36, 55, 56, 57, 58, 59, 60, 61, 62], and TENDL calculations

Fig. 20

Six selected experimental datasets for the 52Cr(p,n)52mMn reaction [36, 55, 57, 59, 60, 61] with the Padé fit (L = 14, N = 68, χ2 = 1.15, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

52Cr(d,2n)52mMn

The two experimental datasets available in the literature are shown in Fig. 21 [62, 63] together with the TENDL calculations. Both datasets were used for the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 22 together with the Padé fit (L = 8, N = 16, χ2 = 0.71) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 21

Two experimental datasets for the 52Cr(d,2n)52mMn reaction available in the literature [62, 63], and TENDL calculations

Fig. 22

Two experimental datasets for the 52Cr(d,2n)52mMn reaction [62, 63] with the Padé fit (L = 8, N = 16, χ2 = 0.71, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 52mMn, and long-lived 52Fe parent

See Figs. 23 and 24.
Fig. 23

Thick target yields calculated from the recommended cross sections for the 52Cr(p,n)52mMn and 52Cr(d,2n)52mMn reactions

Fig. 24

Thick target yields calculated from the recommended cross sections for the natNi(p,x)52Fe, 55Mn(p,4n)52Fe and 50Cr(α,2n)52Fe parent reactions

Production of 52gMn (T ½ = 5.591 d)

Applications: The longer-lived 52Mn ground state has potential as a PET tracer for preclinical in vivo neuroimaging and other applications such as cell tracking, immuno-PET and functional β-cell mass quantification. Unfortunately, a half-life of 5.591 d coupled with an extremely high radiation burden that arises from the resulting gamma-ray emissions has limited 52gMn clinical applications.

52gMn (5.591 d): β+ (29.4%), and Eγ (keV) (Pγ(%)): 744.233 (90.0), 935.544 (94.5), 1434.092 (100).

Evaluations have been made of the direct 52Cr(p,n)52gMn(m+) and 52Cr(d,2n)52gMn(m+) production routes, including the partial decay of the simultaneously produced short-lived 52mMn metastable state (IT = 1.78%, noted as (m+)) which has already been assessed and discussed in section “Production of 52mMn (T1/2 = 21.1 min) and longer-lived 52Fe parent (T1/2 = 8.275 h)”.

52Cr(p,n)52gMn (m+)

The thirteen experimental datasets available in the literature are shown in Fig. 25 [36, 55, 56, 58, 59, 61, 62, 64, 65, 66, 67, 68, 69] together with the TENDL calculations. Six sets of data were rejected (Blosser and Handley [56], Tanaka and Furukawa [64], Lindner and James [65], Antropov et al. [66], Buchholz et al. [67], and Zherebchevsky et al. [69], all disagree significantly with the other datasets), while the remaining seven datasets were used in the statistical fitting procedure. These selected data and their experimental uncertainties are shown in Fig. 26 together with the Padé fit (L = 9, N = 103, χ2 = 1.84) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 25

Thirteen experimental datasets for the 52Cr(p,n)52gMn(m+) reaction available in the literature [36, 55, 56, 58, 59, 61, 62, 64, 65, 66, 67, 68, 69], and TENDL calculations

Fig. 26

Seven selected experimental datasets for the 52Cr(p,n)52gMn(m+) reaction [36, 55, 58, 59, 61, 62, 68] with the Padé fit (L = 9, N = 103, χ2 = 1.84, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

52Cr(d,2n)52gMn(m+)

The six experimental datasets available in the literature are shown in Fig. 27 [62, 63, 70, 71, 72, 73] together with the TENDL calculations. Two sets were rejected (Cheng Xiaowu et al. [71], values too low and no contribution from decay of metastable state marked as “g” in Fig. 27, and Nassiff and Münzel [72], values too high), and the remaining four datasets were used in the statistical fitting procedure. These selected data and their experimental uncertainties are shown in Fig. 28 together with the Padé fit (L = 8, N = 36, χ2 = 0.54) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 27

Six experimental datasets for the 52Cr(d,2n)52gMn(m+) reaction available in the literature [62, 63, 70, 71, 72, 73], and TENDL calculations

Fig. 28

Four selected experimental datasets for the 52Cr(d,2n)52gMn(m+) reaction [62, 63, 70, 73] with the Padé fit (L = 8, N = 36, χ2 = 0.54, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 52gMn(m+)

See Fig. 29.
Fig. 29

Thick target yields calculated from the recommended cross sections for the 52Cr(p,n)52gMn(m+) and 52Cr(d,2n)52gMn(m+) reactions

Production of 55Co (T 1/2 = 17.53 h)

Applications: 55Co is a typical example of a positron emitter of sufficient half-life to follow kinetic processes that function over a longer timescale. This radionuclide has been used to target the epidermal growth factor (EGFR) by means of labelled DOTA-conjugated Affibody. Exhibits lower liver and heart uptake for metal-chelate peptide complexes, with improved performance when compared with 68Ga. Also used as a Ca2+ analogue in imaging studies of Alzheimer disease, and shows promise in achieving improved imaging of cancer diseases.

55Co (17.53 h): β+ (76%), and Eγ (keV) (Pγ(%)): 931.1 (75), 1316.6 (7.1).

58Ni(p,α)55Co, 54Fe(d,n)55Co and 56Fe(p,2n)55Co production routes have been evaluated.

58Ni(p,α)55Co

The seventeen experimental datasets available in the literature are shown in Fig. 30 [36, 45, 59, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87] together with the TENDL calculations. One dataset was rejected (Haasbroek et al. [76], values too high), while the remaining sixteen datasets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 31 together with the Padé fit (L = 10, N = 352, χ2 = 1.97) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 30

Seventeen experimental datasets for the 58Ni(p,α)55Co reaction available in the literature [36, 45, 59, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87], and TENDL calculations

Fig. 31

Sixteen selected experimental datasets for the 58Ni(p,α)55Co reaction [36, 45, 59, 74, 75, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87] with the Padé fit (L = 10, N = 352, χ2 = 1.97, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

54Fe(d,n)55Co

The ten experimental datasets available in the literature are shown in Fig. 32 [88, 89, 90, 91, 92, 93, 94, 95, 96, 97] together with the TENDL calculations. One dataset was rejected (Clark et al. [89], values too high), while the remaining nine datasets were used in the statistical fitting procedure (although some very discrepant points around 10 MeV from Hermanne [94] and the highest three points from Zhenlan [91] were also discarded). The selected data and their experimental uncertainties are shown in Fig. 33 together with the Padé fit (L = 13, N = 170, χ2 = 2.14) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 32

Ten experimental datasets for the 54Fe(d,n)55Co reaction available in the literature [88, 89, 90, 91, 92, 93, 94, 95, 96, 97], and TENDL calculations

Fig. 33

Nine selected experimental datasets for the 54Fe(d,n)55Co reaction [88, 90, 91, 92, 93, 94, 95, 96, 97] with the Padé fit (L = 13, N = 170, χ2 = 2.14, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

56Fe(p,2n)55Co

The fifteen experimental datasets available in the literature are shown in Fig. 34 [36, 59, 82, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109] together with the TENDL calculations. Four datasets were rejected (Michel et al. [82], Cohen and Newman [98], Williams and Fulmer [99], and Ditrói et al. [107], all show discrepant values), and the remaining eleven sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 35 together with the Padé fit (L = 8, N = 101, χ2 = 2.74) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 34

Fifteen experimental datasets for the 56Fe(p,2n)55Co reaction available in the literature [36, 59, 82, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109], and TENDL calculations

Fig. 35

Eleven selected experimental datasets for the 56Fe(p,2n)55Co reaction [36, 59, 100, 101, 102, 103, 104, 105, 106, 108, 109] with the Padé fit (L = 8, N = 101, χ2 = 2.74, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 55Co

See Fig. 36.
Fig. 36

Thick target yields calculated from the recommended cross sections for the 58Ni(p,α)55Co, 54Fe(d,n)55Co and 56Fe(p,2n)55Co reactions

Production of 61Cu (T ½ = 3.339 h)

Applications: Copper radionuclides form stable complexes with several chelators that can be conjugated to a wide variety of organic molecules for both imaging (61Cu, 62Cu, 64Cu) and radiotherapy (64Cu, 67Ci). Relatively longer-lived 61Cu (T½ = 3.339 h, 61% β+, 39% EC) possesses very good imaging properties that can be used for blood flow studies in a similar manner to 51Cr. Also has been applied to blood pool imaging (DOTA-human serum albumin) and the study of hypoxia in tumours (coupled to ATSM)—useful for following kinetics processes of the order of a few hours.

61Cu (3.339 h): β+ (61%), and Eγ (keV) (Pγ(%)): 282.956 (12.2), 656.008 (10.8), 1185.234 (3.7).

Evaluations have been made of the 61Ni(p,n)61Cu, 60Ni(d,n)61Cu and 64Zn(p,α)61Cu direct production routes.

61Ni(p,n)61Cu

The seventeen experimental datasets available in the literature are shown in Fig. 37 [45, 56, 59, 64, 78, 79, 84, 87, 110, 111, 112, 113, 114, 115, 116, 117] together with the TENDL calculations. Ref. [112] contains two datasets, labelled (a) and (b). Five datasets were rejected (Blosser and Handley [56], Tanaka and Furukawa [64], Barrandon et al. [59], Michel et al. [78], and Al-Saleh et al. [84], all of these datasets exhibit maximum values that are too high), and the remaining twelve sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 38 together with the Padé fit (L = 12, N = 192, χ2 = 2.81) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 37

Seventeen experimental datasets for the 61Ni(p,n)61Cu reaction available in the literature [45, 56, 59, 64, 78, 79, 84, 87, 110, 111, 112, 113, 114, 115, 116, 117], and TENDL calculations

Fig. 38

Twelve selected experimental datasets for the 61Ni(p,n)61Cu reaction [45, 79, 87, 110, 111, 112, 113, 114, 115, 116, 117] with the Padé fit (L = 12, N = 192, χ2 = 2.81, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

60Ni(d,n)61Cu

The five experimental datasets available in the literature are shown in Fig. 39 [90, 118, 119, 120, 121] together with the TENDL calculations. All datasets were used in the statistical fitting procedure (Cogneau et al. [118] data were normalised, and data above 6-MeV particle beam energy discarded as inconsistent with model calculations). All of the data and their experimental uncertainties are shown in Fig. 40 together with the Padé fit (L = 16, N = 29, χ2 = 1.16) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). This reaction is the main contributor to the formation of 61Cu on natural Ni by deuterons, adopted as a suitable beam monitor (see Ref. [30], Sect. 3.I).
Fig. 39

Five experimental datasets for the 60Ni(d,n)61Cu reaction available in the literature [90, 118, 119, 120, 121], and TENDL calculations

Fig. 40

Five experimental datasets for the 60Ni(d,n)61Cu reaction [90, 118, 119, 120, 121] with the Padé fit (L = 16, N = 29, χ2 = 1.16, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

64Zn(p,α)61Cu

The seven experimental datasets available in the literature are shown in Fig. 41 [36, 59, 122, 123, 124, 125, 126] together with the TENDL calculations. One dataset was rejected (Barrandon et al. [59], discrepant behaviour near maximum), and the remaining six sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 42 together with the Padé (L = 12, N = 72, χ2 = 0.88) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 41

Seven experimental datasets for the 64Zn(p,α)61Cu reaction available in the literature [36, 59, 122, 123, 124, 125, 126], and TENDL calculations

Fig. 42

Six selected experimental datasets [36, 122, 123, 124, 125, 126] for the 64Zn(p,α)61Cu reaction with the Padé fit (L = 12, N = 72, χ2 = 0.88, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 61Cu

See Fig. 43.
Fig. 43

Thick target yields calculated from the recommended cross sections for the 61Ni(p,n)61Cu, 60Ni(d,n)61Cu and 64Zn(p,α)61Cu reactions

Production of 62Cu (T 1/2 = 9.67 min) and longer-lived 62Zn parent (T 1/2 = 9.193 h)

Applications: As stated earlier, copper isotopes form stable complexes with several chelators that can be conjugated to a wide variety of organic molecules for both imaging (61Cu, 62Cu, 64Cu) and therapy (64Cu, 67Ci). Short-lived 62Cu has been proposed for the labelling of PTSM (pyruvaldehyde bis) to undertake myocardial and brain blood flow studies.

62Cu (9.67 min): β+ (97.83%), and Eγ (keV) (Pγ(%)): 875.66 (0.147), 1172.97 (0.342).

62Zn (9.193 h): β+ (8.2%), and Eγ (keV) (Pγ(%)): 548.35 (15.3), 596.56 (26).

Evaluations have been made of the 63Cu(p,2n)62Zn, 63Cu(d,3n)62Zn and natNi(α,xn)62Zn indirect, and 62Ni(p,n)62Cu and 62Ni(d,2n)62Cu direct production routes.

63Cu(p,2n)62Zn

Twenty-four experimental datasets available in the literature are shown in Fig. 44 [36, 82, 98, 99, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146] together with the TENDL calculations. Seven datasets were rejected (Ghoshal [127], Williams and Fulmer [99], Greene and Lebowitz [128], Greenwood and Smither [130], Aleksandrov et al. [132], Levkovskij [36], and Tárkányi et al. [142], all disagree significantly with the other datasets), and the remaining seventeen sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 45 together with the Padé fit (L = 16, N = 213, χ2 = 1.89) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). As the only reaction known to contribute to the formation of 62Zn on natCu for protons below 30 MeV, the fitted data have been adopted as a beam monitor in this energy region (see Ref. [30], Sect. 2.6).
Fig. 44

Twenty-four experimental datasets for the 63Cu(p,2n)62Zn reaction available in the literature [36, 82, 98, 99, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146], and TENDL calculations

Fig. 45

Seventeen selected experimental datasets for the 63Cu(p,2n)62Zn reaction [82, 98, 129, 131, 133, 134, 135, 136, 137, 138, 139, 140, 141, 143, 144, 145, 146] with the Padé fit (L = 16, N = 213, χ2 = 1.89, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

63Cu(d,3n)62Zn

While a known dataset by Bartell et al. [147] is not represented in Fig. 46 because the values are totally discrepant even after arbitrary normalisation, eight other experimental datasets available in the literature are shown [73, 95, 148, 149, 150, 151, 152, 153] together with the TENDL calculations. The data by Fulmer and Williams [148] were subsequently rejected because they disagree significantly with the other datasets (attributed to the normalisation of inadequately defined low-intensity decay data). All of the remaining seven datasets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 47 together with the Padé fit (L = 12, N = 82, χ2 = 1.89) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). As the only reaction known to contribute to the formation of 62Zn on natCu for deuterons below 35 MeV, the fitted data have been adopted as a beam monitor in this energy region (see Ref. [30], Section III E).
Fig. 46

Eight experimental datasets for the 63Cu(d,3n)62Zn reaction available in the literature [73, 95, 148, 149, 150, 151, 152, 153], and TENDL calculations

Fig. 47

Seven selected experimental datasets for the 63Cu(d,3n)62Zn reaction [73, 95, 149, 150, 151, 152, 153] with the Padé fit (L = 12, N = 82, χ2 = 1.89, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natNi(α,xn)62Zn

The nine experimental datasets available in the literature are shown in Fig. 48 [36, 127, 154, 155, 156, 157, 158, 159, 160] together with the TENDL calculations. Three datasets were rejected (Neirinckx [155] (energy shift near threshold), Singh et al. [159] (discrepant values at energies below 35 MeV), and Yadav et al. [160] (value too low)), and the remaining six sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 49 together with the Padé fit (L = 21, N = 45, χ2 = 1.72) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 48

Nine experimental datasets for the natNi(α,xn)62Zn reaction available in the literature [36, 127, 154, 155, 156, 157, 158, 159, 160], and TENDL calculations

Fig. 49

Six selected experimental datasets for the natNi(α,xn)62Zn reaction [36, 127, 154, 156, 157, 158] with the Padé fit (L = 10, N = 45, χ2 = 1.74, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

62Ni(p,n)62Cu

The seven experimental datasets available in the literature are shown in Fig. 50 [36, 45, 66, 110, 161, 162, 163] together with the TENDL calculations. All datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 51 together with the Padé fit (L = 12, N = 77, χ2 = 1.33) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 50

Seven experimental datasets for the 62Ni(p,n)62Cu reaction available in the literature [36, 45, 66, 110, 161, 162, 163], and TENDL calculations

Fig. 51

Seven experimental datasets [36, 45, 66, 110, 161, 162, 163] for the 62Ni(p,n)62Cu reaction with the Padé fit (L = 12, N = 77, χ2 = 1.33, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

62Ni(d,2n)62Cu

The single dataset available in the literature is shown in Fig. 52 [118] together with the TENDL calculations. This dataset was used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 53 together with the Padé fit (L = 5, N = 16, χ2 = 0.83) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 52

Experimental dataset for the 62Ni(d,2n)62Cu reaction available in the literature [118], and TENDL calculations

Fig. 53

Experimental dataset for the 62Ni(d,2n)62Cu reaction [118] with the Padé fit (L = 5, N = 16, χ2 = 0.83, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 62Cu, and 62Zn parent

See Figs. 54 and 55.
Fig. 54

Thick target yields calculated from the recommended cross sections for the 62Ni(p,n)62Cu and 62Ni(d,2n)62Cu reactions

Fig. 55

Thick target yields calculated from the recommended cross sections for the 63Cu(p,2n)62Zn, 63Cu(d,3n)62Zn and natNi(α,xn)62Zn reactions

Production of 66Ga (T ½ = 9.49 h)

Applications: Both 66Ga and 68Ga are positron-emitting radionuclides that can be used in PET imaging. Longer-lived 66Ga has been coupled to monoclonal antibodies (e.g., for tumour angiogenesis studies) and to nanoparticles. This radionuclide has also been proposed in hadron therapy as an in situ marker for the incorporation of Zn in tumours. Obvious disadvantages are the rather high radiation burden and inferior imaging properties caused by the many gamma rays that accompany decay.

66Ga (9.49 h): β+ (57%), and Eγ (keV) (Pγ(%)): 833.5324 (5.9), 1039.220 (37.0).

Evaluations have been made of the 66Zn(p,n)66Ga and 63Cu(α,n)66Ga direct production routes.

66Zn(p,n)66Ga

The twenty experimental datasets available in the literature are shown in Fig. 56 [36, 56, 59, 124, 125, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177] together with the TENDL-2015 and TENDL-2017 calculations. Hermanne [173] contains two datasets labelled (a) and (b).Twelve datasets were rejected (Little and Lagunas-Solar [167] (values too low), Nortier et al. [171] (energy shift), Blosser and Handley [56] (only one data point that can not be checked), Howe [165] (energy shift), Kopecký [168] (values too low), Asad et al. [125] (values too low), Szelecsényi et al. [172] (preliminary results), Hermanne [173] set b (discrepant data points), Barrandon et al. [59] (values too low), Al-Saleh et al. [177] (values too low), Uddin et al. [124] (values too low), and Blaser et al. [164] (discrepant data points)), while the remaining eight sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 57 together with the Padé (L = 13, N = 188, χ2 = 1.87) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 56

Twenty experimental datasets) for the 66Zn(p,n)66Ga reaction available in the literature [36, 56, 59, 124, 125, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177], and TENDL calculations. Ref. [173] contains two datasets labelled (a) and (b)

Fig. 57

Eight selected experimental datasets for the 66Zn(p,n)66Ga reaction [36, 166, 169, 170, 173, 174, 175, 176] with the Padé fit (L = 13, N = 188, χ2 = 1.87, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

63Cu(α,n)66Ga

The twenty-three experimental datasets available in the literature are shown in Fig. 58 [36, 54, 81, 166, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196] together with the TENDL calculations. Seven datasets were rejected (Porges [178] (values too low), Bonesso et al. [188] (values too low), Zhukova et al. [182] (values too low), Singh et al. [190] (values too low), Rizvi et al. [184] (values too low), Porile and Morrison [179] (values too low), and Nassiff and Nassiff [183] (discrepant data points)), and the remaining sixteen sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 59 together with the Padé (L = 13, N = 252, χ2 = 1.34) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). This reaction is also used to monitor α-particle beams (see Ref. [30], Section V D).
Fig. 58

Twenty-three experimental datasets for the 63Cu(α,n)66Ga reaction available in the literature [36, 54, 81, 166, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196], and TENDL calculations

Fig. 59

Sixteen selected experimental datasets for the 63Cu(α,n)66Ga reaction [36, 54, 81, 166, 180, 181, 185, 186, 187, 189, 191, 192, 193, 194, 195, 196] with the Padé fit (L = 13, N = 252, χ2 = 1.34, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 66Ga

See Fig. 60.
Fig. 60

Thick target yields calculated from the recommended cross sections for the 66Zn(p,n)66Ga and 63Cu(α,n)66Ga reactions

Production of 68Ga (T 1/2 = 67.71 min) and long-lived 68Ge parent (T 1/2 = 270.95 d)

Applications: Rather short-lived 68Ga became the first widespread generator-produced positron emitter, thereby competing somewhat with 18F for preferred adoption in PET imaging. First introduced for the imaging of neuroendocrine tumours (68Ga-labelled DOTA-TOC), more recent significant success has been achieved in the form of very efficient imaging agents for prostate cancer diagnosis and staging (68Ga-DOTA-PSMA and derivatives).

68Ga (67.71 min): β+ (88.91%), and Eγ (keV) (Pγ(%)): 1077.34 (3.22).

68Ge (270.95 d): detected by means of radiation from daughter 68Ga.

Evaluations have been undertaken of the 68Zn(p,n)68Ga and 65Cu(α,n)68Ga direct routes and natGa(p,x)68Ge and 69Ga(p,2n)68Ge generator production.

68Zn(p,n)68Ga

The eighteen experimental datasets available in the literature are shown in Fig. 61 [36, 41, 56, 59, 111, 162, 164, 165, 166, 169, 170, 173, 177, 195, 197, 198, 199, 200] together with the TENDL calculations. Five datasets were rejected (Hermanne et al. [170] (energy shift), Blosser and Handley [56] (value too high), McGee et al. [41] (value too low), Hermanne [173] (energy shift), and Barrandon et al. [59] (values too low)), and the remaining thirteen sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 62 together with the Padé (L = 20, N = 282, χ2 = 1.97) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 61

Eighteen experimental datasets for the 68Zn(p,n)68Ga reaction available in the literature [36, 41, 56, 59, 111, 162, 164, 165, 166, 169, 170, 173, 177, 195, 197, 198, 199, 200], and TENDL calculations

Fig. 62

Thirteen selected experimental datasets for the 68Zn(p,n)68Ga reaction [36, 111, 162, 164, 165, 166, 169, 177, 195, 197, 198, 199, 200] with the Padé fit (L = 20, N = 282, χ2 = 1.97, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

65Cu(α,n)68Ga

The fourteen experimental datasets available in the literature are shown in Fig. 63 [36, 54, 166, 178, 179, 180, 184, 186, 188, 190, 195, 196, 201, 202] together with the TENDL calculations. Four datasets were rejected (Porile and Morrison [179] (energy shift), Rizvi et al. [184] (energy shift), Bonesso et al. [188] (values too high), and Porges [178] (values too low)), and the remaining ten sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 64 together with the Padé (L = 10, N = 92, χ2 = 1.21) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 63

Fourteen experimental datasets for the 65Cu(α,n)68Ga reaction available in the literature [36, 54, 166, 178, 179, 180, 184, 186, 188, 190, 195, 196, 201, 202], and TENDL calculations

Fig. 64

Ten selected experimental datasets for the 65Cu(α,n)68Ga reaction [36, 54, 166, 180, 186, 190, 195, 196, 201, 202] with the Padé fit (L = 10, N = 92, χ2 = 1.21, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natGa(p,xn)68Ge

The six experimental datasets available in the literature are shown in Fig. 65 [36, 48, 98, 203, 204] together with the TENDL calculations. Hermanne et al. [48] contains two datasets labelled (a) and (b). One dataset was rejected (Cohen and Newman [98], single data point too low), and the remaining five sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 66 together with the Padé (L = 11, N = 101, χ2 = 1.42) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 65

Six experimental datasets for the natGa(p,xn)68Ge reaction available in the literature [36, 48, 98, 203, 204], and TENDL calculations. Hermanne et al. [48] contains two sets of data labelled (a) and (b)

Fig. 66

Five selected experimental datasets for the natGa(p,xn)68Ge reaction [36, 48, 203, 204] with the Padé fit (L = 11, N = 101, χ2 = 1.42, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

69Ga(p,2n)68Ge

The four experimental datasets available in the literature are shown in Fig. 67 [36, 48, 203, 204] together with the TENDL calculations. All sets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 68 together with the Padé (L = 8, N = 53, χ2 = 1.56) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 67

Four experimental datasets for the 69Ga(p,2n)68Ge reaction available in the literature [36, 48, 203, 204], and TENDL calculations

Fig. 68

Four experimental datasets for the 69Ga(p,2n)68Ge reaction [36, 48, 203, 204] with the Padé fit (L = 8, N = 53, χ2 = 1.56, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for 68Ga, and long-lived 68Ge parent for generator

See Figs. 69 and 70.
Fig. 69

Thick target yields calculated from the recommended cross sections for the 68Zn(p,n)68Ga and 65Cu(α,n)68Ga direct reactions

Fig. 70

Thick target yields calculated from the recommended cross sections for the natGa(p,xn)68Ge and 69Ga(p,2n)68Ge reactions to produce long-lived parent for 68Ga generator

Production of 72As (T 1/2 = 26.0 h) and longer-lived 72Se parent (T 1/2 = 8.40 d)

Applications: 72As is a long-lived positron-emitting radionuclide suitable for imaging the bio-distribution of monoclonal antibodies with long biological half-lives that are promising in PET oncological research. Chemical properties offer the possibility of covalent bonding to thiol groups.

72As (26.0 h): β+ (87.8%), and Eγ (keV) (Pγ(%)): 629.92 (8.07), 833.99 (81).

72Se (8.40 d): detected by means of radiation emitted by daughter 72As.

Evaluations have been undertaken of the 75As(p,4n)72Se and natBr(p,x)72Se routes for parent production, and the natGe(p,xn)72As and natGe(d,xn)72As direct production routes.

75As(p,4n)72Se

The two experimental datasets available in the literature for the energy domain considered are shown in Fig. 71 [205, 206] together with the TENDL calculations. Both datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 72 together with the Padé fit (L = 8, N = 33, χ2 = 1.30) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 71

Two experimental datasets for the 75As(p,4n)72Se reaction available in the literature [205, 206], and TENDL calculations

Fig. 72

Two experimental datasets for the 75As(p,4n)72Se reaction [205, 206] with the Padé fit (L = 8, N = 33, χ2 = 1.30, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natBr(p,x)72Se

The two experimental datasets available in the literature are shown in Fig. 73 [207, 208] together with the TENDL calculations. Both sets of measurements by Fassbender et al. [207] and de Villiers et al. [208] originate from the same experimental study, and should be identical. Therefore, the data of de Villers et al. [208] were set aside, while only the other dataset was used in the statistical fitting procedure. These selected data and their experimental uncertainties are shown in Fig. 74 together with the Padé fit (L = 10, N = 14, χ2 = 0.35) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). The contributions of the similar (p,2pxn) reactions on the two stable isotopes of Br can be clearly distinguished (79Br: 50.69%; 81Br: 49.31%).
Fig. 73

Two experimental datasets for the natBr(p,x)72Se reaction available in the literature [207, 208], and TENDL calculations

Fig. 74

One selected experimental dataset for the natBr(p,x)72Se reaction [207] with the Padé fit (L = 10, N = 14, χ2 = 0.35, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natGe(p,xn)72As

The four experimental datasets available in the literature are shown in Fig. 75 [36, 209, 210, 211] together with the TENDL calculations. All datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 76 together with the Padé (L = 18, N = 123, χ2 = 1.97) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). Contributions of similar (p,xn) reactions with increasing thresholds can be clearly distinguished for the higher abundance 72Ge,74Ge and 76Ge.
Fig. 75

Four experimental datasets for the natGe(p,xn)72As reaction available in the literature [36, 209, 210, 211], and TENDL calculations

Fig. 76

Four experimental datasets for the natGe(p,xn)72As reaction [36, 209, 210, 211] with the Padé fit (L = 18, N = 123, χ2 = 1.97, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natGe(d,xn)72As

The single experimental dataset available in the literature is shown in Fig. 77 [212] together with the TENDL calculations. All data points and their experimental uncertainties are shown in Fig. 78 together with the Padé fit (L = 10, N = 25, χ2 = 1.13) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). The contribitions of the 72Ge(d,2n) and 74Ge(d,4n) reactions on high natural abundance Ge isotopes can be seen in both figures.
Fig. 77

One experimental dataset for the natGe(d,xn)72As reaction available in the literature [212], and TENDL calculations

Fig. 78

One experimental dataset for the natGe(d,xn)72As reaction [212] with the Padé fit (L = 10, N = 25, χ2 = 1.13, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 72As, and 72Se parent

See Figs. 79 and 80.
Fig. 79

Thick target yields calculated from the recommended cross sections for the natGe(p,xn)72As and natGe(d,xn)72As reactions

Fig. 80

Thick target yields calculated from the recommended cross sections for the 75As(p,4n)72Se and natBr(p,x)72Se reactions

Production of 73Se (T 1/2 = 7.15 h)

Applications: 73Se (T½ = 7.15 h; EC = 34.6%, β+ = 65.4%; Eβ+(max) = 1.65 MeV) is an interesting β+-emitting analogue of sulphur suitable for the imaging of enzymatic systems or sulphur-containing amino acids.

73Se(7.15 h): β+ (65.4%), and Eγ (keV) (Pγ(%)): 67.07 (70), 361.2 (97.0).

Evaluations have been made of the 75As(p,3n)73Se and 72Ge(α,3n)73Se direct production routes.

75As(p,3n)73Se

The four experimental datasets available in the literature are shown in Fig. 81 [36, 206, 213, 214] together with the TENDL calculations. One dataset was rejected (Mushtaq et al. [206] (values too low near maximum)), and the remaining three sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 82 together with the Padé (L = 9, N = 64, χ2 = 1.52) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 81

Four experimental datasets for the 75As(p,3n)73Se reaction available in the literature [36, 206, 213, 214], and TENDL calculations

Fig. 82

Three selected experimental datasets for the 75As(p,3n)73Se reaction [36, 213, 214] with the Padé fit (L = 9, N = 64, χ2 = 1.52, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

72Ge(α,3n)73Se

The two experimental datasets available in the literature are shown in Fig. 83 [36, 215] together with the TENDL calculations. Both datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 84 together with the Padé fit (L = 8, N = 27, χ2 = 3.81) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 83

Two experimental datasets for the 72Ge(α,3n)73Se reaction available in the literature [36, 215], and TENDL calculations

Fig. 84

Two experimental datasets for the 72Ge(α,3n)73Se reaction [36, 215] with the Padé fit (L = 8, N = 27, χ2 = 3.81, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 73Se

See Fig. 85.
Fig. 85

Thick target yields calculated from the recommended cross sections for the 75As(p,3n)73Se and 72Ge(α,3n)73Se reactions

Production of 76Br (T 1/2 = 16.2 h)

Applications: Longer-lived positron-emitting radiohalogens were some of the first radionuclides studied to follow processes with kinetics inappropriate for 18F application. 76Br was used in several studies to label monoclonal antibodies, although the large number of accompanying gamma rays that result in a relatively high radiation burden and poor imaging properties has seen a subsequent decline of interest in this radionuclide.

76Br(16.2 h): β+ (55%) and Eγ (keV) (Pγ(%)): 559.09 (74), 657.02 (15.9), 1853.67 (14.7).

Evaluations have been made of the 76Se(p,n)76Br, 77Se(p,2n)76Br and 75As(α,3n)76Br production routes.

76Se(p,n)76Br

The five experimental datasets available in the literature are shown in Fig. 86 [36, 216, 217, 218, 219] together with the TENDL calculations. Two datasets were rejected (Kovács et al. [218] (values too low near maximum), and Hassan et al. [219] (discrepant data near maximum)), and the remaining three sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 87 together with the Padé fit (L = 8, N = 39, χ2 = 1.05) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 86

Five experimental datasets for the 76Se(p,n)76Br reaction available in the literature [36, 216, 217, 218, 219], and TENDL calculations

Fig. 87

Three selected experimental datasets for the 76Se(p,n)76Br reaction [36, 216, 217] with the Padé fit (L = 8, N = 39, χ2 = 1.05, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

77Se(p,2n)76Br

The four experimental datasets available in the literature are shown in Fig. 88 [36, 219, 220, 221] together with the TENDL calculations. Two datasets were rejected (Janssen et al. [220] (values too low), and Hassan et al. [219] (values too high)), and the remaining two sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 89 together with the Padé fit (L = 9, N = 52, χ2 = 1.34) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 88

Four experimental datasets for the 77Se(p,2n)76Br reaction available in the literature [36, 219, 220, 221], and TENDL calculations

Fig. 89

Two selected experimental datasets for the 77Se(p,2n)76Br reaction [36, 221] with the Padé fit (L = 9, N = 52, χ2 = 1.34, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

75As(α,3n)76Br

The five experimental datasets available in the literature are shown in Fig. 90 [216, 217, 222, 223, 224] together with the TENDL calculations. All datasets were used for the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 91 together with the Padé fit (L = 10, N = 70, χ2 = 2.43) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). An additional dataset published after the evaluation cut-off date was also included in the fit (Breunig et al. [224]) and is shown in Fig. 90.
Fig. 90

Five experimental datasets for the 75As(α,3n)76Br reaction available in the literature [216, 217, 222, 223, 224], and TENDL calculations

Fig. 91

Five experimental datasets for the 75As(α,3n)76Br reaction [216, 217, 222, 223, 224] with the Padé fit (L = 10, N = 70, χ2 = 2.43, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for 76Br

See Fig. 92.
Fig. 92

Thick target yields calculated from the recommended cross sections for the 76Se(p,n)76Br, 77Se(p,2n)76Br and 75As(α,3n)76Br reactions

Production of 82Sr parent (T 1/2 = 25.35 d) of short-lived 82Rb (T 1/2 = 1.2575 min)

Applications: Generator-produced 82Rb is widely used in myocardial perfusion imaging, particularly in the USA. This isotope undergoes rapid uptake by myocardiocytes, and therefore is a valuable tool for identifying myocardial ischemia by means of PET. Such a short half-life allows one to perform both stress and rest perfusion studies within 30 min.

82Rb (1.2575 min): β+ (95.43%), and Eγ (keV) (Pγ(%)): 776.52 (15.08).

82Sr (25.35 d): detected by means of radiation emitted by daughter 82Rb.

Evaluations have been undertaken of the natRb(p,xn)82Sr and 85Rb(p,4n)82Sr parent production routes.

natRb(p,xn)82Sr

The seven experimental datasets available in the literature are shown in Fig. 93 [138, 225, 226, 227, 228, 229, 230] together with the TENDL calculations. Two datasets were rejected (Horiguchi et al. [225] (values too high), and Deptula et al. [226] (values too high)), and the remaining five sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 94 together with the Padé fit (L = 13, N = 49, χ2 = 1.15) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 93

Seven experimental datasets for the natRb(p,xn)82Sr reaction available in the literature [138, 225, 226, 227, 228, 229, 230], and TENDL calculations

Fig. 94

Five selected experimental datasets for the natRb(p,xn)82Sr reaction [138, 227, 228, 229, 230] with the Padé fit (L = 13, N = 49, χ2 = 1.15, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

85Rb(p,4n)82Sr

The five experimental datasets available in the literature are shown in Fig. 95 [138, 225, 227, 229, 230] together with the TENDL calculations. All datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 96 together with the Padé fit (L = 9, N = 49, χ2 = 1.60) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 95

Five experimental datasets for the 85Rb(p,4n)82Sr reaction available in the literature [138, 225, 227, 229, 230], and TENDL calculations

Fig. 96

Five experimental datasets for the 85Rb(p,4n)82Sr reaction [138, 225, 227, 229, 230] with the Padé fit (L = 9, N = 49, χ2 = 1.60, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for 82Sr parent of short-lived 82Rb

See Fig. 97.
Fig. 97

Thick target yields calculated from the recommended cross sections for the natRb(p,xn)82Sr and 85Rb(p,4n)82Sr reactions to produce long-lived parent for short-lived 82Rb

Production of 82mRb (T½ = 6.472 h)

Applications: Longer-lived 82mRb isomeric state could possibly act as a substitute for generator-produced 82Rb in PET cardiology centres that operate a cyclotron. However, this isomer suffers from a relatively high radiation burden that arises from the longer half-life and gamma-ray emissions.

82mRb (6.472 h): β+ (21.2%), and Eγ (keV) (Pγ(%)): 554.35 (62.4), 619.11 (37.98), 698.37 (26.3), 776.52 (84.39), 827.83 (21.0), 1044.08 (32.07), 1317.43 (23.7), 1474.88 (15.5).

Evaluations have been undertaken of the 82Kr(p,n)82mRb and 82Kr(d,2n)82mRb reactions.

82Kr(p,n)82mRb

The four experimental datasets available in the literature are shown in Fig. 98 [231, 232] (each reference contains two datasets labelled (a) and (b)), together with the TENDL calculations. All datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 99 together with the Padé fit (L = 9, N = 33, χ2 = 1.13) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 98

Four experimental datasets for the 82Kr(p,n)82mRb reaction available in the literature [231, 232] (each reference contains two datasets labelled (a) and (b)), and TENDL calculations

Fig. 99

Four experimental datasets for the 82Kr(p,n)82mRb reaction [231, 232] with the Padé fit (L = 9, N = 33, χ2 = 1.13, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

82Kr(d,2n)82mRb

A single experimental dataset available in the literature is shown in Fig. 100 [233] together with the TENDL calculations. This one dataset was used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 101 together with the Padé fit (L = 5, N = 14, χ2 = 2.27) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 100

One experimental dataset for the 82Kr(d,2n)82mRb reaction available in the literature [233], and TENDL calculations

Fig. 101

One experimental dataset for the 82Kr(d,2n)82mRb reaction [233] with the Padé fit (L = 5, N = 14, χ2 = 2.27, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 82mRb

See Fig. 102.
Fig. 102

Thick target yields calculated from the recommended cross sections for the 82Kr(p,n)82mRb and 82Kr(d,2n)82mRb reactions

Production of 86Y (T 1/2 = 14.74 h)

Applications: Extensive studies of 86Y have been performed as a positron emitter (31.9%) with 14.74 h half-life that can adopted as a theranostic pair with clinically-established therapeutic beta-emitting 90Y. The role of 86Y is to monitor the localised therapeutic dose distribution in the body for dosimetry calculations. Has also been studied for prostate cancer imaging, and used to label monoclonal antibodies in EGFR targeting. However, interest in this radionuclide has declined because of the high radiation burden and resultant poor imaging properties.

86Y (14.74 h): β+ (31.9%), and Eγ (keV) (Pγ(%)): 627.72 (32.6), 1076.63 (82.5), 1153.05 (30.5).

Evaluations have been made of the 86Sr(p,n)86Y, 88Sr(p,3n)86Y and 85Rb(α,3n)86Y production routes.

86Sr(p,n)86Y

The four experimental datasets available in the literature are shown in Fig. 103 [36, 82, 234, 235] together with the TENDL calculations. One dataset was rejected (Rösch et al. [235] (scattered data, and values too high near maximum)), while the three remaining sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 104 together with the Padé fit (L = 9, N = 28, χ2 = 0.615) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 103

Four experimental datasets for the 86Sr(p,n)86Y reaction available in the literature [36, 82, 234, 235], and TENDL calculations

Fig. 104

Three selected experimental datasets for the 86Sr(p,n)86Y reaction [36, 82, 234] with the Padé fit (L = 9, N = 28, χ2 = 0.615, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

88Sr(p,3n)86Y

The two experimental datasets available in the literature are shown in Fig. 105 [36, 236] together with the TENDL calculations. Both datasets were used in the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 106 together with the Padé fit (L = 8, N = 15, χ2 = 1.27) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 105

Two experimental datasets for the 88Sr(p,3n)86Y reaction available in the literature [36, 236], and TENDL calculations

Fig. 106

Two experimental datasets for the 88Sr(p,3n)86Y reaction [36, 236] with the Padé fit (L = 8, N = 15, χ2 = 1.27, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

85Rb(α,3n)86Y

Five experimental datasets available in the literature are shown in Fig. 107 [36, 237, 238, 239, 240] together with the TENDL calculations. Three datasets were rejected (Guin et al. [239], Iwata [237], and Agarwal et al. [240] (values refer to direct ground state production only, and are not cumulative). The data points of Demeyer et al. [238] below 45 MeV are discrepant, and were also deleted. Thus, the remaining data points for only two datasets were used in the statistical fitting procedure [36, 238]. These selected data and their experimental uncertainties are shown in Fig. 108 together with the Padé fit (L = 8, N = 32, χ2 = 0.91) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 107

Five experimental datasets for the 85Rb(α,3n)86Y reaction available in the literature [36, 237, 238, 239, 240], and TENDL calculations

Fig. 108

Two selected experimental datasets for the 85Rb(α,3n)86Y reaction [36, 238] with the Padé fit (L = 8, N = 32, χ2 = 0.91, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 86Y

See Fig. 109.
Fig. 109

Thick target yields calculated from the recommended cross sections for the 86Sr(p,n)86Y, 88Sr(p,3n)86Y and 85Rb(α,3n)86Y reactions

Production of 89Zr (T 1/2 = 78.41 h)

Applications: Long-lived positron-emitting 89Zr has been extensively studied with respect to following the in vivo behaviour of therapeutic monoclonal antibodies (mAbs) and other biomolecules with slow biokinetics. One significant disadvantage is the limited number of suitable 89Zr chelating agents and difficulties related to their development.

89Zr (78.41 h): β+ (22.74%), and Eγ (keV) (Pγ(%)): 909.15 (99.04).

Evaluations have been made of the 89Y(p,n)89Zr and 89Y(d,2n)89Zr production routes.

89Y(p,n)89Zr

The sixteen experimental datasets available in the literature are shown in Fig. 110 [36, 56, 82, 110, 234, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251] together with the TENDL calculations. Five datasets were rejected (Birattari et al. [244] (energy shift), Blosser and Handley [56] (value too high), Satheesh et al. [250] (energy shift), Delaunay-Olkowsky et al. [234] (value too low), and Saha et al. [242] (values too high)), and the remaining eleven datasets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 111 together with the Padé fit (L = 11, N = 316, χ2 = 3.74) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 110

Sixteen experimental datasets for the 89Y(p,n)89Zr reaction available in the literature [36, 56, 82, 110, 234, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251], and TENDL calculations

Fig. 111

Eleven selected experimental datasets for the 89Y(p,n)89Zr reaction [36, 82, 110, 241, 243, 245, 246, 247, 248, 249, 251] with the Padé fit (L = 11, N = 316, χ2 = 3.74, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

89Y(d,2n)89Zr

The seven experimental datasets available in the literature are shown in Fig. 112 [252, 253, 254, 255, 256, 257, 258] together with the TENDL calculations. Two datasets were rejected (La Gamma and Nassiff [253] (values too low), and Degering et al. [255] (energy shift)), and the remaining five sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 113 together with the Padé fit (L = 9, N = 64, χ2 = 2.95) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 112

Seven experimental datasets for the 89Y(d,2n)89Zr reaction available in the literature [252, 253, 254, 255, 256, 257, 258], and TENDL calculations

Fig. 113

Five selected experimental datasets for the 89Y(d,2n)89Zr reaction [252, 254, 256, 257, 258] with the Padé fit (L = 9, N = 64, χ2 = 2.95, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 89Zr

See Fig. 114.
Fig. 114

Thick target yields calculated from the recommended cross sections for the 89Y(p,n)89Zr and 89Y(d,2n)89Zr reactions

Production of 90Nb (T 1/2 = 14.60 h)

Applications: As a non-conventional positron emitter, 90Nb with a half-life of 14.60 h can be used to visualise and quantify processes with medium and slow kinetics, such as tumour accumulation of antibodies and antibody fragments, or polymers and other nanoparticles. Exhibits promise in immuno-PET, although a search for appropriate chelators is desirable. Also emits several high-energy gamma rays that increase the radiation burden.

90Nb (14.60 h): β+ (51.2%), and Eγ (keV) (Pγ(%)): 132.716 (4.13), 141.178 (66.8), 1129.224 (92.7).

Evaluations have been undertaken of the 93Nb(p,x)90Nb and 89Y(α,3n)90Nb production.

93Nb(p,x)90Nb

The six experimental datasets available in the literature are shown in Fig. 115 [82, 249, 259, 260, 261, 262] together with the TENDL calculations. All datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 116 together with the Padé fit (L = 9, N = 94, χ2 = 3.18) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 115

Six experimental datasets for the 93Nb(p,x)90Nb reaction available in the literature [82, 249, 259, 260, 261, 262], and TENDL calculations

Fig. 116

Six experimental datasets for the 93Nb(p,x)90Nb reaction [82, 249, 259, 260, 261, 262] with the Padé fit (L = 9, N = 94, χ2 = 3.18, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

89Y(α,3n)90Nb

The six experimental datasets available in the literature are shown in Fig. 117 [36, 263, 264, 265, 266, 267] together with the TENDL calculations. Four datasets were rejected (Singh et al. [266], Chaubey and Rizvi [265], Mukherjee et al. [264], and Smend et al. [263], all systematically lower values), while the remaining two sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 118 together with the Padé fit (L = 16, N = 33, χ2 = 1.29) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 117

Six experimental datasets for the 89Y(α,3n)90Nb reaction available in the literature [36, 263, 264, 265, 266, 267], and TENDL calculations

Fig. 118

Two selected experimental datasets for the 89Y(α,3n)90Nb reaction [36, 267] with the Padé fit (L = 16, N = 33, χ2 = 1.29, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 90Nb

See Fig. 119.
Fig. 119

Thick target yields calculated from the recommended cross sections for the 93Nb(p,x)90Nb and 89Y(α,3n)90Nb reactions

Production of 94mTc (T 1/2 = 52.0 min)

Applications: Gamma-ray emitting 99mTc is the most widespread medical radionuclide for diagnosis, whereas 94mTc with a half-life of 52.0 min. is a positron emitter with a positron branch of 70.2% and Eβ+(max) of 2.44 MeV. Therefore, there has been interest in 94mTc as a PET analogue to 99mTc since they both undergo the same chemistry. Obvious disadvantages of 94mTc are the rather short half-life of 52.0 min., with many accompanying gamma rays and the inability to prepare the pure isomer without also generating significant amounts of ground state 94gTc.

94mTc (52.0 min): β+ (70.2%), and Eγ (keV) (Pγ(%)): 871.05 (94.2), 1522.1 (4.5), 1868.68 (5.7).

Evaluations have been made of the 92Mo(α,x)94mTc and 94Mo(p,n)94mTc production routes.

92Mo(α,x)94mTc

The four experimental datasets available in the literature are shown in Fig. 120 [36, 268, 269, 270] together with the TENDL calculations. Three datasets were rejected (Graf and Münzel [268], Denzler et al. [269], and Ditrói et al. [270], all contradictory sets of data), while the remaining single set of Levkovskij [36] was used in the statistical fitting procedure (and also accepted as a standard for the monitoring of α beams). The selected data and their experimental uncertainties are shown in Fig. 121 together with the Padé fit (L = 12, N = 28, χ2 = 1.33) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 120

Four experimental datasets for the 92Mo(α,x)94mTc reaction available in the literature [36, 268, 269, 270], and TENDL calculations

Fig. 121

One selected experimental dataset for the 92Mo(α,x)94mTc reaction [36] with the Padé fit (L = 12, N = 28, χ2 = 1.33, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

94Mo(p,n)94mTc

The seven experimental datasets available in the literature are shown in Fig. 122 [36, 142, 271, 272, 273, 274, 275] together with the TENDL calculations. All datasets were used in the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 123 together with the Padé fit (L = 9, N = 57, χ2 = 1.21) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 122

Seven experimental datasets for the 94Mo(p,n)94mTc reaction available in the literature [36, 142, 271, 272, 273, 274, 275], and TENDL calculations

Fig. 123

Seven experimental datasets for the 94Mo(p,n)94mTc reaction [36, 142, 271, 272, 273, 274, 275] with the Padé fit (L = 9, N = 57, χ2 = 1.21, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 94mTc

See Fig. 124.
Fig. 124

Thick target yields calculated from the recommended cross sections for the 92Mo(α,x)94mTc and 94Mo(p,n)94mTc reactions

Production of 110mIn (T 1/2 = 69.1 min) and longer-lived 110Sn parent (T 1/2 = 4.154 h)

Applications: 110mIn is a positron-emitting analogue for established SPECT 111In. Potential to provide more quantitative diagnostic information as well as in vivo quantification of the uptake kinetics of radiopharmaceuticals (e.g., applied along with 111In-labelled DTPA-D-Phe1-octeotride for neuroendocrine tumours).

110mIn can be produced directly and via parent 110Sn.

110mIn (69.1 min): β+ (61.3%), and Eγ (keV) (Pγ(%)): 2129.40 (2.15), 2211.33 (1.74), 2317.41 (1.285).

110Sn (4.154 h): Eγ (keV) (Pγ(%)): 280.459 (97.06).

Evaluations have been made of the natIn(p,xn)110Sn, 108Cd(α,2n)110Sn, 110Cd(p,n)110mIn, 110Cd(d,2n)110mIn and 107Ag(α,n)110mIn production routes.

natIn(p,xn)110Sn

The four experimental datasets available in the literature are shown in Fig. 125 [276, 277, 278, 279] together with the TENDL calculations. All datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 126 together with the Padé fit (L = 17, N = 112, χ2 = 1.50) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 125

Four experimental datasets for the natIn(p,xn)110Sn reaction available in the literature [276, 277, 278, 279], and TENDL calculations

Fig. 126

Four experimental datasets for the natIn(p,xn)110Sn reaction [276, 277, 278, 279] with the Padé fit (L = 17, N = 112, χ2 = 1.50, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

108Cd(α,2n)110Sn

The four experimental datasets available in the literature are shown in Fig. 127 [280, 281, 282, 283] together with the TENDL calculations. One dataset was rejected (Duchemin et al. [282], values too low), while another became available after the evaluation cut-off date and therefore was not included (Ditrói et al. [283]). The two remaining sets were used in the statistical fitting procedure, and these selected data and their experimental uncertainties are shown in Fig. 128 together with the Padé fit (L = 10, N = 24, χ2 = 1.99) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 127

Four experimental datasets for the 108Cd(α,2n)110Sn reaction available in the literature [280, 281, 282, 283], and TENDL calculations

Fig. 128

Two selected experimental datasets for the 108Cd(α,2n)110Sn reaction [280, 281] with the Padé fit (L = 10, N = 24, χ2 = 1.99, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

110Cd(p,n)110mIn

The three experimental datasets available in the literature for production of the metastable state [164, 284, 285] and the six datasets for simultaneously produced impurity ground state [276, 285, 286, 287, 288, 289] are shown in Fig. 129 together with the TENDL calculations for the separate metastable and ground states. After full assessment, the three datasets were used in the statistical fitting procedure for the metastable state [164, 284, 285]. These data and their experimental uncertainties are shown in Fig. 130 together with the Padé fit (L = 11, N = 29, χ2 = 0.57) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 129

Three experimental datasets for the 110Cd(p,n)110mIn reaction available in the literature [164, 284, 285], along with six experimental datasets for the 110Cd(p,n)110gIn reaction [276, 285, 286, 287, 288, 289], and TENDL calculations

Fig. 130

Three experimental datasets for the 110Cd(p,n)110mIn reaction [164, 284, 285] with the Padé fit (L = 11, N = 29, χ2 = 0.57, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

110Cd(d,2n)110mIn

The two experimental datasets available in the literature for production of the metastable state are shown in Fig. 131 [290, 291] together with two datasets for simultaneous production of the contaminating ground state [291, 292] and the TENDL calculations. Cross sections determined by Usher et al. [290] were normalised to the data of Tárkányi et al. [291], and both datasets were used in the statistical fitting procedure for 110mIn production. These data and their experimental uncertainties are shown in Fig. 132 together with the Padé fit (L = 5, N = 18, χ2 = 0.74) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 131

Two experimental datasets for the 110Cd(d,2n)110mIn reaction available in the literature [290, 291] and two experimental datasets for the contaminating 110Cd(d,2n)110gIn reaction [291, 292], and their TENDL calculations. All data from Ref. [290] have been normalised with respect to the data of Ref. [291]

Fig. 132

Two experimental datasets for the 110Cd(d,2n)110mIn reaction [290, 291] with the Padé fit (L = 5, N = 18, χ2 = 0.74, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

107Ag(α,n)110mIn

The nine experimental datasets available in the literature are shown in Fig. 133 [178, 278, 293, 294, 295, 296, 297, 298, 299] together with the TENDL calculations. Six datasets were rejected (Wasilevsky et al. [295] (discrepant values), Misaelides and Münzel [294] (energy steps too large, can not be controlled), Chaubey et al. [296] (values too high), Fukushima et al. [293] (values too low at higher energy), Patel et al. [297] (values too low), Takács et al. [298] (values too low)), and the remaining three sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 134 together with the Padé fit L = 9, N = 32, χ2 = 1.94) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 133

Nine experimental datasets for the 107Ag(α,n)110mIn reaction available in the literature [178, 278, 293, 294, 295, 296, 297, 298, 299], and TENDL calculations

Fig. 134

Three selected experimental datasets for the 107Ag(α,n)110mIn reaction [178, 278, 299] with the Padé fit (L = 9, N = 32, χ2 = 1.94, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for 110mIn, and 110Sn parent

See Figs. 135 and 136.
Fig. 135

Thick target yields calculated from the recommended cross sections for 110Cd(p,n)110mIn, 110Cd(d,2n)110mIn and 107Ag(α,n)110mIn reactions

Fig. 136

Thick target yields calculated from the recommended cross sections for the natIn(p,xn)110Sn and 108Cd(α,2n)110Sn reactions

Production of 118Te parent (T 1/2 = 6.00 d) of short-lived 118Sb (T 1/2 = 3.6 min)

Applications: EC decay of 118Te produces 3.6 min half-life 118Sb daughter, which decays primarily by positron emission and can be used as a flow tracer.

118Sb (3.6 min): β+ (73.5%), and Eγ (keV) (Pγ(%)): 1229.33 (2.5).

118Te (6.00 d): detected by means of radiation emitted by daughter 118Sb.

Evaluations have been undertaken for the 115Sn(α,n)118Te, 116Sn(α,2n)118Te, natSb(p,xn)118Te and natSb(d,xn)118Te production routes.

115Sn(α,n)118Te

The two experimental datasets available in the literature are shown in Fig. 137 [300, 301] together with the TENDL calculations. These two datasets were used as the basis of the fitting procedure. However, to obtain reasonable cross-section behaviour above ~ 18 MeV, three artificial points were added in accord with the TENDL-2017 calculations for beam energies of 20, 25 and 30 MeV given assigned uncertainties of 25%. The data and their experimental uncertainties are shown in Fig. 138 together with the Padé fit (L = 7, N = 8, χ2 = 1.07) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 137

Two experimental datasets for the 115Sn(α,n)118Te reaction available in the literature [300, 301], and TENDL calculations

Fig. 138

Two experimental datasets for the 115Sn(α,n)118Te reaction [300, 301] with the Padé fit (L = 7, N = 8, χ2 = 1.07, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

116Sn(α,2n)118Te

The two experimental datasets available in the literature are shown in Fig. 139 [300, 302] together with the TENDL calculations. Both datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 140 together with the Padé fit (L = 6, N = 13, χ2 = 1.34) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 139

Two experimental datasets for the 116Sn(α,2n)118Te reaction available in the literature [300, 302], and TENDL calculations

Fig. 140

Two experimental datasets for the 116Sn(α,2n)118Te reaction [300, 302] with the Padé fit (L = 6, N = 13, χ2 = 1.34, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natSb(p,xn)118Te

The three experimental datasets available in the literature are shown in Fig. 141 [303, 304, 305] together with the TENDL calculations. One dataset was normalised and energy-shifted (Lagunas-Solar et al. [304]), and all three sets were used in the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 142 together with the Padé fit (L = 12, N = 43, χ2 = 0.53) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale). Contributions of the 121Sb(p,4n) and 123Sb(p,6n) reactions can clearly be distinguished.
Fig. 141

Three experimental datasets for the natSb(p,xn)118Te reaction available in the literature [303, 304, 305], and TENDL calculations

Fig. 142

Three experimental datasets for the natSb(p,xn)118Te reaction [303, 304, 305] with the Padé fit (L = 12, N = 43, χ2 = 0.53, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale) – dataset from Ref. [304] has been normalised and energy-shifted

natSb(d,xn)118Te

The single experimental dataset available in the literature is shown in Fig. 143 [306] together with the TENDL calculations. This one dataset was used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 144 together with the Padé fit (L = 4, N = 7, χ2 = 0.52) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 143

One experimental dataset for the natSb(d,xn)118Te reaction available in the literature [306], and TENDL calculations

Fig. 144

One experimental dataset for the natSb(d,xn)118Te reaction [306] with the Padé fit (L = 4, N = 7, χ2 = 0.52, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 118Te parent of short-lived 118Sb

See Fig. 145.
Fig. 145

Thick target yields calculated from the recommended cross sections for the 115Sn(α,n)118Te, 116Sn(α,2n)118Te, natSb(p,xn)118Te and natSb(d,xn)118Te reactions

Production of 120I (T ½ = 81.6 min)

Applications: Positron-emitting 120I (T½ = 81.6 min) is a short-lived alternative to 124I and 123I. This iodine radionuclide has a positron abundance more than twice that of 124I and a maximum positron energy of 4.593 MeV. Can be used for radiohalogenation of molecules with rapid kinetics.

120I (81.6 min): β+ (68.2%), and Eγ (keV) (Pγ(%)): 601.1 (5.51). 1523.0 (10.9).

Evaluations have been made of the 120Te(p,n)120I and 122Te(p,3n)120I reactions.

120Te(p,n)120I

The four experimental datasets available in the literature are shown in Fig. 146 [307, 308, 309, 310] together with the TENDL calculations. Two datasets were rejected (El-Azony et al. [308] and Ahmed et al. [310], both exhibit energy shift around 10 MeV), and the remaining two datasets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 147 together with the Padé fit (L = 18, N = 38, χ2 = 0.806) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 146

Four experimental datasets for the 120Te(p,n)120I reaction available in the literature [307, 308, 309, 310], and TENDL calculations

Fig. 147

Two selected experimental datasets for the 120Te(p,n)120I reaction [307, 309] with the Padé fit (L = 18, N = 38, χ2 = 0.806, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

122Te(p,3n)120I

The two experimental datasets available in the literature are shown in Fig. 148 [307, 308] together with the TENDL calculations. These two datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 149 together with the Padé fit (L = 7, N = 18, χ2 = 0.463) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 148

Two experimental datasets for the 122Te(p,3n)120I reaction available in the literature [307, 308], and TENDL calculations

Fig. 149

Two experimental datasets for the 122Te(p,3n)120I reaction [307, 308] with the Padé fit (L = 7, N = 18, χ2 = 0.463, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 120I

See Fig. 150.
Fig. 150

Thick target yields calculated from the recommended cross sections for the 120Te(p,n)120I and 122Te(p,3n)120I reactions

Production of 122Xe parent (T 1/2 = 20.1 h) of short-lived 122I (T 1/2 = 3.63 min)

Applications: 122I with a half-life of 3.63 min. has potential as a generator-produced positron emitter for various PET studies such as brain and heart perfusion.

122I (3.63 min): detected through β+ (78%), and Eγ (keV) (Pγ(%)): 564.119 (18).

122Xe (20.1 h): Eγ (keV) (Pγ(%)): 350.065 (7.80), and radiation emitted by daughter 122I.

Evaluations have been undertaken of the 124Xe(p,x)122Xe, 127I(p,6n)122Xe and 127I(d,7n)122Xe production routes.

124Xe(p,x)122Xe

The two experimental datasets available in the literature are shown in Fig. 151 [311, 312] together with the TENDL calculations. These two datasets were used in the statistical fitting procedure. The data and their experimental uncertainties are shown in Fig. 152 together with the Padé fit (L = 5, N = 15, χ2 = 1.01) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 151

Two experimental datasets for the 124Xe(p,x)122Xe reaction available in the literature [311, 312], and TENDL calculations

Fig. 152

Two experimental datasets for the 124Xe(p,x)122Xe reaction [311, 312] with the Padé fit (L = 5, N = 15, χ2 = 1.01, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

127I(p,6n)122Xe

The three experimental datasets available in the literature are shown in Fig. 153 [313, 314, 315] together with the TENDL calculations. All three datasets were used in the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 154 together with the Padé fit (L = 9, N = 21, χ2 = 0.99) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 153

Three experimental datasets for the 127I(p,6n)122Xe reaction available in the literature [313, 314, 315], and TENDL calculations

Fig. 154

Three experimental datasets for the 127I(p,6n)122Xe reaction [313, 314, 315] with the Padé fit (L = 7, N = 21, χ2 = 1.03, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

127I(d,7n)122Xe

The two experimental datasets available in the literature are shown in Fig. 155 [316, 317] together with the TENDL calculations. After correcting the energy scale of Ref. [316], the two datasets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 156 together with the Padé fit (L = 12, N = 21, χ2 = 1.31) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 155

Two experimental datasets for the 127I(d,7n)122Xe reaction available in the literature [316, 317], and TENDL calculations – with corrected energy scale for Ref. [316] data

Fig. 156

Two experimental datasets for the 127I(d,7n)122Xe reaction [316, 317] with the Padé fit (L = 12, N = 21, χ2 = 1.31, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 122Xe parent of short-lived 122I

See Fig. 157.
Fig. 157

Thick target yields calculated from the recommended cross sections for the 124Xe(p,x)122Xe, 127I(p,6n)122Xe and 127I(d,7n)122Xe reactions

Production of 128Ba parent (T 1/2 = 2.43 d) of short-lived 128Cs (T 1/2 = 3.66 min)

Applications: Short-lived generator-produced 128Cs can be used in a similar manner to 82Rb for myocardial perfusion examinations.

128Cs (3.66 min): β+ (68.8%), and Eγ (keV) (Pγ(%)): 442.901 (26.8).

128Ba (2.43 d): Eγ (keV) (Pγ(%)): 273.44 (14.5), and by means of radiation from daughter 128Cs.

Only the 133Cs(p,6n)128Ba reaction has been evaluated.

133Cs(p,6n)128Ba

The four experimental datasets available in the literature are shown in Fig. 158 [318, 319, 320, 321] together with the TENDL calculations. All four datasets were used in the statistical fitting procedure. These data and their experimental uncertainties are shown in Fig. 159 together with the Padé fit (L = 18, N = 51, χ2 = 1.79) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 158

Four experimental datasets for the 133Cs(p,6n)128Ba reaction available in the literature [318, 319, 320, 321], and TENDL calculations

Fig. 159

Four experimental datasets for the 133Cs(p,6n)128Ba reaction [318, 319, 320, 321] with the Padé fit (L = 18, N = 51, χ2 = 1.79, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for 128Ba parent of short-lived 128Cs

See Fig. 160.
Fig. 160

Thick target yields calculated from the recommended cross sections for the 133Cs(p,6n)128Ba reaction

Production of 140Nd parent (T 1/2 = 3.37 d) of short-lived 140Pr (T 1/2 = 3.39 min)

Applications: EC decay of 140Nd (EC = 100%, T1/2 = 3.37 d) produces short-lived 140Pr (T1/2 = 3.39 min, β+ = 51.0%, Eβ+(max) = 2.366 MeV), which undergoes EC/β+ decay to stable 140Ce. Parent-daughter 140Nd/140Pr has been proposed as a radionuclide generator, or as an in vivo generator system for PET studies.

140Pr (3.39 min): β+ (51.0%), and Eγ (keV) (Pγ(%)): 306.9 (0.147), 1596.1 (0.49).

140Nd (3.37 d): detected by means of radiation emitted by daughter 140Pr.

Evaluations have been undertaken of the 141Pr(p,2n)140Nd, 141Pr(d,3n)140Nd and natCe(3He,xn)140Nd production routes.

141Pr(p,2n)140Nd

The three experimental datasets available in the literature are shown in Fig. 161 [322, 323, 324] together with the TENDL calculations. One dataset was rejected (Hogan [322], values too high), and the remaining two sets were used in the statistical fitting procedure. The selected data and their experimental uncertainties are shown in Fig. 162 together with the Padé fit (L = 10, N = 121, χ2 = 0.78) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 161

Three experimental datasets for the 141Pr(p,2n)140Nd reaction available in the literature [322, 323, 324], and TENDL calculations

Fig. 162

Two selected experimental datasets for the 141Pr(p,2n)140Nd reaction [323, 324] with the Padé fit (L = 10, N = 121, χ2 = 0.78, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

141Pr(d,3n)140Nd

The two experimental datasets available in the literature are shown in Fig. 163 [325, 326] together with the TENDL calculations. Both datasets were used in the statistical fitting procedure, as shown in Fig. 164 together with the Padé fit (L = 9, N = 17, χ2 = 0.466) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 163

Two experimental datasets for the 141Pr(d,3n)140Nd reaction available in the literature [325, 326], and TENDL calculations

Fig. 164

Two experimental datasets for the 141Pr(d,3n)140Nd reaction [325, 326] with the Padé fit (L = 9, N = 17, χ2 = 0.466, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

natCe(3He,xn)140Nd

Only a single experimental dataset has been found in the literature [324], as illustrated in Fig. 165 together with the TENDL calculations. 3He beams are rarely available for use, and therefore TENDL evaluators have not attempted to improve the description of this complicated channel, in which break-up and transfer effects may dramatically change the shape and magnitude of the calculated cross sections. This dataset and associated experimental uncertainties were adopted in the statistical fitting procedure. The results are shown in Fig. 166 together with the Padé fit (L = 9, N = 18, χ2 = 1.59, solid line) and estimated uncertainty in percentages, including 4% systematic uncertainty (right-hand scale).
Fig. 165

One experimental dataset for the natCe(3He,xn)140Nd reaction available in the literature [324], and TENDL calculations

Fig. 166

One experimental dataset for the natCe(3He,xn)140Nd reaction [324] with the Padé fit (L = 9, N = 18, χ2 = 1.59, solid line) and estimated total uncertainties in percentages, including 4% systematic uncertainty (dashed line, right-hand scale)

Thick target yields for production of 140Nd parent of short-lived 140Pr

See Fig. 167.
Fig. 167

Thick target yields calculated from the recommended cross sections for the 141Pr(p,2n)140Nd, 141Pr(d,3n)140Nd and natCe(3He,xn)140Nd reactions

Evaluated excitation functions: an overall assessment

A significant amount of effort has been expended to assemble, evaluate, analyse and recommend suitable cross-section datasets to ensure that a series of radionuclides may be generated with acceptable purity in an optimum manner for PET imaging. Obviously, confidence in such recommended data is highly dependent on their quality and validity as addressed and improved by in-depth evaluations. As derived, these data can also be assessed to identify those cross sections and their resulting excitation functions that can be improved further by means of additional measurements. Additionally, integral measurements (production thick target yields) are very important and need to be performed in order to assist in the benchmaring and validation of the recommended data.

Improved radionuclidic purity may be an issue that emerges from research-based applications in nuclear medicine. Under such circumstances, excitation functions for these radionuclidic impurities are also required to aid in the optimisation of target composition and energy range of the beam within the target in order to avoid or at least minimise their production. These data requirements have not been addressed in the current studies, but remain an important part of what would normally constitute an evolutionary programme of work that may hopefully lead up to regular medical application.

Some critical comments can be justifiably applied as to the quality of any evaluated cross-section data, particularly when the quoted uncertainties of such recommended excitation functions do not reflect the complexity of various underlying and often ill-defined factors. For example, difficulties arise when attempting to judge the quality of experimental data on the basis of only the original publication(s), as significant details on the measurement and associated data evaluations are required for such an exercise but are often omitted from journal papers. Reported uncertainties do not exceed seven or eight percent in many cases for very different types of reaction and measurement methodology that makes such modest percentages effectively unrealistic. Some laboratories are known to possess greater expertise than others, and/or have a better technical background in cross-section studies. Such personnel and facilities most frequently generate more reliable experimental data that implies greater weight should be applied to their datasets in the evaluation process. However, under such circumstances, less reliable data and their questionable uncertainties are considered in many evaluations with the same weighting, and so distort the final recommended values. The thoroughness of compilation, systematic application of all known corrections, and strictness in data selection also depend strongly on the subjective knowledge and analytical behaviour of individual evaluators. This results in a quality difference between the recommendations of evaluators that is not reflected in the uncertainties of their final sets of recommended nuclear data.

Comprehensive comparisons have been made of the measured cross-section results of the 69 reactions studied in this work with the equivalent evolving predictions of the two TENDL libraries based on theoretical cross-section calculations of the TALYS code system. No important changes would appear to have been introduced into the code between 2015 and 2017 that affect these particular reactions because, in the majority of cases, the results for TENDL-2017 are identical to or only marginally differ from the contents of the TENDL-2015 database. A rather surprising observation is that, where large differences exist, the 2017 database exhibits larger disagreements with the experimental results than the 2015 edition (see for example, Figs. 120 and 155). However, the readily available on-line predictions are in acceptable agreement with the overall shape of the measured and evaluated excitation functions, and are therefore useful for the estimation of other unmeasured nuclear processes. The main shortcomings observed in the TENDL libraries and related TALYS reaction modelling can be identified with the following behaviour:
  1. 1.

    Energy shift of high energy reactions with the emission of multiple particles.

     
  2. 2.

    Underestimation of the production of some isomeric states which is reflected in the underestimation of cumulative processes.

     
  3. 3.

    Poor quantification of the magnitude of alpha-particle induced reactions near their maximum and at higher energies.

     
  4. 4.

    Underestimation of the cross section for a single 3He-induced reaction.

     
  5. 5.

    Underestimation of the cross section for deuteron induced reactions, especially from the threshold to the maximum of the excitation function.

     
  6. 6.

    Unexplained strange shapes within some (p,n) reactions (e.g., plateau near maximum).

     

Many of these shortcomings are related to known problems in the theoretical modelling that will be shared by results calculated using different reaction codes.

Additional improved experimental studies of particular production routes are clearly merited, as defined by the nature of some of the existing cross-section data to be found throughout Section Results for charged-particle reactions. However, there are also other reactions that require consideration and analyses of the form undertaken above [327, 328], along with the need for better quantified studies of specific positron and X-ray emission probabilities [329]. New measurements and evaluations are required of the activation cross sections for proton-induced reactions with energies up to 250 MeV: 11C, 13N, 14,15O, 30P and 38K. More extensive cross-section studies would also be beneficial to achieve the optimum production of 34mCl, 43Sc, 45Ti, 48V, 49Cr, 51Mn, 57Ni, 75Br, 77Kr, 81Rb, 83Sr, 95Ru, 121I and 152Tb. Improved decay data are identified with the need for accurate absolute positron and X-ray emission probabilities for 57Ni, 72As, 73Se, 75,76Br, 77Kr, 81,82mRb, 83Sr, 86Y, 89Zr, 94mTc and 120I. On balance, reviews of the nuclear data requirements in nuclear medicine would appear to be appropriate approximately every 10 years to ensure a continued and well-defined international focus on ensuring that the necessary technical information is immediately to hand when required.

Conclusions

Substantial extensions and significant improvements have been made to the IAEA-NDS recommended cross-section database for the production of PET radionuclides. Evaluations were performed on 69 reactions for direct, indirect or generator production of 44Sc, 44Ti, 52Mn, 52mMn, 52Fe, 55Co, 61Cu, 62Cu, 62Zn, 66Ga, 68Ga, 68Ge, 72As, 72Se, 73Se, 76Br, 82Rb, 82mRb, 82Sr, 86Y, 89Zr, 90Nb, 94mTc, 110mIn, 110Sn, 118Sb, 118Te, 120I, 122I, 122Xe, 128Cs, 128Ba, 140Pr and 140Nd. A Padé fitting method was applied to the evaluated datasets selected, and uncertainties for all of the recommended data were deduced. The experimental data were compared with theoretical predictions taken from both the TENDL-2015 and TENDL-2017 libraries, sometimes exhibiting significant disagreements in the magnitude and shape of the resulting excitation functions.

As well as a lack of published data for specific reactions, significant disagreements were also found to exist between various equivalent experimental data. All of the recommended cross-section data were used to derive integral or production thick target yields for direct practical application.

All of the numerical reference cross-section data with their corresponding uncertainties and deduced integral thick target yields are available on-line at the IAEA-NDS medical portal www-nds.iaea.org/medportal/ [2] and also at the IAEA-NDS web page www-nds.iaea.org/medical/positron_emitters.html.

These evaluated experimental data are important for existing and potential applications in nuclear medicine, and may also have useful roles in other fields of non-energy related nuclear studies.

Notes

Acknowledgements

Our sincere thanks are extended to all colleagues who have contributed to and worked on this project over the previous 5 years. The studies undertaken and the preparation of this paper would not have been possible without the full support, hard work and efforts of a large number of individuals and institutions. The IAEA is grateful to all participant laboratories for their assistance in the work and support of the CRP meetings and activities. Work described in this paper would not have been possible without IAEA Member State contributions. Studies at ANL were supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, under contract no. DE-AC-06CH11357.

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Authors and Affiliations

  • F. T. Tárkányi
    • 1
  • A. V. Ignatyuk
    • 2
  • A. Hermanne
    • 3
  • R. Capote
    • 4
    Email author
  • B. V. Carlson
    • 5
  • J. W. Engle
    • 6
  • M. A. Kellett
    • 7
  • T. Kibédi
    • 8
  • G. N. Kim
    • 9
  • F. G. Kondev
    • 10
  • M. Hussain
    • 11
  • O. Lebeda
    • 12
  • A. Luca
    • 13
  • Y. Nagai
    • 14
  • H. Naik
    • 15
  • A. L. Nichols
    • 16
  • F. M. Nortier
    • 6
  • S. V. Suryanarayana
    • 15
  • S. Takács
    • 1
  • M. Verpelli
    • 4
  1. 1.Institute for Nuclear ResearchHungarian Academy of SciencesDebrecenHungary
  2. 2.Institute of Physics and Power Engineering (IPPE)ObninskRussia
  3. 3.Vrije Universiteit BrusselBrusselsBelgium
  4. 4.NAPC, Nuclear Data SectionInternational Atomic Energy AgencyViennaAustria
  5. 5.Instituto Tecnológico de AeronáuticaSão José dos CamposBrazil
  6. 6.Los Alamos National Laboratory (LANL)Los AlamosUSA
  7. 7.Laboratoire National Henri Becquerel (LNHB)CEA SaclayParisFrance
  8. 8.Australian National University (ANU)CanberraAustralia
  9. 9.Kyungpook National UniversityDaeguRepublic of Korea
  10. 10.Argonne National Laboratory (ANL)LemontUSA
  11. 11.Government College UniversityLahorePakistan
  12. 12.Nuclear Physics InstitutePragueCzech Republic
  13. 13.National Institute of Physics and Nuclear Engineering “Horia Hulubei”MăgureleRomania
  14. 14.Japan Atomic Energy Agency (JAEA)Tokaimura NakaJapan
  15. 15.Bhabha Atomic Research Centre (BARC)Trombay, MumbaiIndia
  16. 16.University of SurreyGuildfordUK

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