Skip to main content
Log in

Effect of radiation dose level on the detectability of pulmonary nodules in chest tomosynthesis

  • Chest
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To investigate the detectability of pulmonary nodules in chest tomosynthesis at reduced radiation dose levels.

Methods

Eighty-six patients were included in the study and were examined with tomosynthesis and computed tomography (CT). Artificial noise was added to simulate that the tomosynthesis images were acquired at dose levels corresponding to 12, 32, and 70 % of the default setting effective dose (0.12 mSv). Three observers (with >20, >20 and three years of experience) read the tomosynthesis cases for presence of nodules in a free-response receiver operating characteristics (FROC) study. CT served as reference. Differences between dose levels were calculated using the jack-knife alternative FROC (JAFROC) figure of merit (FOM).

Results

The JAFROC FOM was 0.45, 0.54, 0.55, and 0.54 for the 12, 32, 70, and 100 % dose levels, respectively. The differences in FOM between the 12 % dose level and the 32, 70, and 100 % dose levels were 0.087 (p = 0.006), 0.099 (p = 0.003), and 0.093 (p = 0.004), respectively. Between higher dose levels, no significant differences were found.

Conclusions

A substantial reduction from the default setting dose in chest tomosynthesis may be possible. In the present study, no statistically significant difference in detectability of pulmonary nodules was found when reducing the radiation dose to 32 %.

Key Points

A substantial radiation dose reduction in chest tomosynthesis may be possible.

Pulmonary nodule detectability remained unchanged at 32 % of the effective dose.

Tomosynthesis might be performed at the dose of a lateral chest radiograph.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

JAFROC:

Jack-knife alternative free-response receiver operating characteristics

LLF:

Lesion localisation fraction

NLF:

Non-lesion localisation fraction

References

  1. Dobbins JT III, Godfrey DJ (2003) Digital x-ray tomosynthesis: current state of the art and clinical potential. Phys Med Biol 48:R65–R106

    Article  PubMed  Google Scholar 

  2. Dobbins JT III (2009) Tomosynthesis imaging: at a translational crossroads. Med Phys 36:1956–1967

    PubMed Central  PubMed  Google Scholar 

  3. Tingberg A (2010) X-ray tomosynthesis: a review of its use for breast and chest imaging. Radiat Prot Dosim 139:100–107

    Google Scholar 

  4. Johnsson AA, Vikgren J, Båth M (2014) Chest tomosynthesis: technical and clinical perspectives. Semin Respir Crit Care Med 35:17–26

    PubMed  Google Scholar 

  5. Sabol JM (2009) A Monte Carlo estimation of effective dose in chest tomosynthesis. Med Phys 36:5480–5487

    PubMed  Google Scholar 

  6. Båth M, Svalkvist A, von Wrangel A, Rismyhr-Olsson H, Cederblad Å (2010) Effective dose to patients from chest examinations with tomosynthesis. Radiat Prot Dosim 139:153–158

    Google Scholar 

  7. Samei E, Flynn MJ, Eyler WR (1999) Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology 213:727–734

    CAS  PubMed  Google Scholar 

  8. Samei E, Flynn MJ, Peterson E, Eyler WR (2003) Subtle lung nodules: influence of local anatomic variations on detection. Radiology 228:76–84

    PubMed  Google Scholar 

  9. Båth M, Håkansson M, Börjesson S et al (2005) Nodule detection in digital chest radiography: introduction to the RADIUS chest trial. Radiat Prot Dosim 114:85–91

    Google Scholar 

  10. Håkansson M, Båth M, Börjesson S et al (2005) Nodule detection in digital chest radiography: effect of nodule location. Radiat Prot Dosim 114:92–96

    Google Scholar 

  11. Håkansson M, Båth M, Börjesson S, Kheddache S, Johnsson ÅA, Månsson LG (2005) Nodule detection in digital chest radiography: effect of system noise. Radiat Prot Dosim 114:97–101

    Google Scholar 

  12. Båth M, Håkansson M, Börjesson S et al (2005) Nodule detection in digital chest radiography: part of image background acting as pure noise. Radiat Prot Dosim 114:102–108

    Google Scholar 

  13. Båth M, Håkansson M, Börjesson S et al (2005) Nodule detction in digital chest radiography: effect of anatomical noise. Radiat Prot Dosim 114:109–113

    Google Scholar 

  14. Håkansson M, Båth M, Börjesson S et al (2005) Nodule detection in digital chest radiography: summary of the RADIUS chest trial. Radiat Prot Dosim 114:114–120

    Google Scholar 

  15. Vikgren J, Zachrisson S, Svalkvist A et al (2008) Comparison of chest tomosynthesis and chest radiography for detection of pulmonary nodules: human observer study of clinical cases. Radiology 249:1034–1041

    PubMed  Google Scholar 

  16. Yamada Y, Jinzaki M, Hasegawa I et al (2011) Fast scanning tomosynthesis for the detection of pulmonary nodules: diagnostic performance compared with chest radiography, using multidetector-row computed tomography as the reference. Invest Radiol 46:471–477

    PubMed  Google Scholar 

  17. Zachrisson S, Vikgren J, Svalkvist A et al (2009) Effect of clinical experience of chest tomosynthesis on detection of pulmonary nodules. Acta Radiol 50:884–891

    CAS  PubMed  Google Scholar 

  18. Asplund S, Johnsson ÅA, Vikgren J et al (2011) Learning aspects and potential pitfalls regarding detection of pulmonary nodules in chest tomosynthesis and proposed related quality criteria. Acta Radiol 52:503–512

    PubMed  Google Scholar 

  19. Kim EY, Chung MJ, Lee HY, Koh W-J, Jung HN, Lee KS (2010) Pulmonary mycobacterial disease: diagnostic performance of low-dose digital tomosynthesis as compared with chest radiography. Radiology 257:269–277

    PubMed  Google Scholar 

  20. Quaia E, Baratella E, Cioffi V et al (2010) The value of digital tomosynthesis in the diagnosis of suspected pulmonary lesions on chest radiography: analysis of diagnostic accuracy and confidence. Acad Radiol 17:1267–1274

    PubMed  Google Scholar 

  21. Jung HN, Chung MJ, Koo JH, Kim HC, Lee KS (2012) Digital tomosynthesis of the chest: utility for detection of lung metastasis in patients with colorectal cancer. Clin Radiol 67:232–238

    CAS  PubMed  Google Scholar 

  22. Lee G, Jeong YJ, Kim KI et al (2013) Comparison of chest digital tomosynthesis and chest radiography for detection of asbestos-related pleuropulmonary disease. Clin Radiol 68:376–382

    CAS  PubMed  Google Scholar 

  23. Yamada Y, Jinzaki M, Hashimoto M et al (2013) Tomosynthesis for the early detection of pulmonary emphysema: diagnostic performance compared with chest radiography, using multidetector computed tomography as reference. Eur Radiol 23:2118–2126

    PubMed  Google Scholar 

  24. Vult von Steyern K, Björkman-Burtscher IM, Höglund P, Bozovic G, Wiklund M, Geijer M (2012) Description and validation of a scoring system for tomosynthesis in pulmonary cystic fibrosis. Eur Radiol 22:2718–2728

    PubMed  Google Scholar 

  25. Vult von Steyern K, Björkman-Burtscher I, Geijer M (2012) Tomosynthesis in pulmonary cystic fibrosis with comparison to radiography and computed tomography: a pictorial review. Insights Imaging 3:81–89

    PubMed Central  PubMed  Google Scholar 

  26. (2007) The 2007 Recommendations of the International Commission on Radiological Protection. ICRP publication 103. Ann ICRP 37:1–332

  27. Mettler FA, Huda W, Yoshizumi TT, Mahesh M (2008) Effective doses in radiology and diagnostic nuclear medicine: a catalog. Radiology 248:254–263

    PubMed  Google Scholar 

  28. Hwang HS, Chung MJ, Lee KS (2013) Digital tomosynthesis of the chest: comparison of patient exposure dose and image quality between standard default setting and low dose setting. Korean J Radiol 14:525–531

    PubMed Central  PubMed  Google Scholar 

  29. Börjesson S, Håkansson M, Båth M et al (2005) A software tool for increasing efficiency in observer performance studies in radiology. Radiat Prot Dosim 114:45–52

    Google Scholar 

  30. Håkansson M, Svensson S, Zachrisson S, Svalkvist A, Båth M, Månsson LG (2010) ViewDEX: an efficient and easy-to-use software for observer performance studies. Radiat Prot Dosim 139:42–51

    Google Scholar 

  31. Båth M, Håkansson M, Tingberg A, Månsson LG (2005) Method of simulating dose reduction for digital radiographic systems. Radiat Prot Dosim 114:253–259

    Google Scholar 

  32. Svalkvist A, Båth M (2010) Simulation of dose reduction in tomosynthesis. Med Phys 37:258–269

    PubMed  Google Scholar 

  33. Bunch PC, Hamilton JF, Sanderson GK, Simmons AH (1978) A free-response approach to the measurement and characterization of radiographic-observer performance. J Appl Photogr Eng 4:156–171

    Google Scholar 

  34. Kallergi M, Pianou N, Georgakopoulos A, Kafiric G, Pavlouc S, Chatziioanno S (2012) Quantitative evaluation of the memory bias effect in ROC studies with PET/CT. Proc SPIE 8318:83180D–1–8

  35. Hansell DM, Bankier AA, Mcloud TC, Müller NL, Remy J (2008) Fleischner Society: glossary of terms for thoracic imaging. Radiology 246:697–722

    PubMed  Google Scholar 

  36. MacMahon H, Austin JH, Gamsu G et al (2005) Radiology guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology 237:395–400

    PubMed  Google Scholar 

  37. Chakraborty DP (2011) New developments in observer performance methodology in medical imaging. Semin Nucl Med 41:401–418

    PubMed Central  PubMed  Google Scholar 

  38. JAFROC [computer program] Version 4.1. University of Pittsburgh, Pittsburgh, PA. Available at: http://www.devchakraborty.com/. Published 2008. Accessed 30 Feb 2013

  39. DBM MRMC [Computer program] Version 2.2. The University of Chicago, Chicago, IL. Available at: http://metz-roc.uchicago.edu/MetzROC. Published June 24, 2008. Accessed 4 Apr 2013

  40. Johnsson ÅA, Svalkvist A, Vikgren J et al (2010) A phantom study of nodule size evaluation with chest tomosynthesis and computed tomography. Radiat Prot Dosim 139:140–143

    CAS  Google Scholar 

  41. Johnsson ÅA, Fagman E, Vikgren J et al (2012) Pulmonary nodule size evaluation with chest tomosynthesis. Radiology 265:273–282

    PubMed  Google Scholar 

  42. Spahn M (2005) Flat detectors and their clinical applications. Eur Radiol 15:1934–1947

    PubMed  Google Scholar 

  43. Dobbins JT III, McAdams HP, Song J-W et al (2008) Digital tomosynthesis of the chest for lung nodule detection: interim sensitivity results from an ongoing NIH-sponsored trial. Med Phys 35:2554–2557

    PubMed Central  Google Scholar 

  44. Quaia E, Baratella E, Cernic S et al (2012) Analysis of the impact of digital tomosynthesis on the radiological investigation of patients with suspected pulmonary lesions on chest radiography. Eur Radiol 22:1912–1922

    PubMed  Google Scholar 

  45. Kim SM, Chung MJ, Lee KS et al (2013) Digital tomosynthesis of the thorax: the influence of respiratory motion artifacts on lung nodule detection. Acta Radiol 54:634–639

    PubMed  Google Scholar 

  46. Quaia E, Baratella E, Poillucci G, Kus S, Cioffi V, Cova MA (2013) Digital tomosynthesis as a problem-solving imaging technique to confirm or exclude potential thoracic lesions based on chest X-ray radiography. Acad Radiol 20:546–553

    PubMed  Google Scholar 

  47. Johnsson ÅA, Vikgren J, Svalkvist A et al (2010) Overview of two years of clinical experience of chest tomosynthesis at sahlgrenska university hospital. Radiat Prot Dosim 139:124–129

    CAS  Google Scholar 

Download references

Acknowledgments

The scientific guarantor of this publication is Magnus Båth. The authors of this manuscript declare relationships with the following companies: Jenny Vikgren and Marianne Boijsen declare financial activities not related to the present article as speakers for GE (2013). Other relationships: None declared. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. This study has received funding by grants from the Swedish Research Council [2011/488, 2013-3477], the Swedish Radiation Safety Authority [2008/2232, 2009/1689, 2010/4363, 2012/2021, 2013/2982], the King Gustav V Jubilee Clinic Cancer Research Foundation, the Swedish Federal Government under the LUA/ALF agreement [ALFGBG-136281] and the Health & Medical Care Committee of the Region Västra Götaland [VGFOUREG-12046, VGFOUREG-27551, VGFOUREG-81341]. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Some study subjects or cohorts have been previously reported in Svalkvist et al. “Evaluation of an improved method of simulating lung nodules in chest tomosynthesis”. Acta Radiol. 2012;53:874–84. Five of the 86 patients included in the present study have previously been included in the study by Svalkvist et al. In that study, simulated nodules were inserted into the images and the appearance of them was thereby altered. The inclusion of them in the present study was therefore considered justified. Methodology: prospective, experimental, performed at one institution.

The authors would like to acknowledge Dev P Chakraborty, Department of Radiology, University of Pittsburgh, PA, for consulting regarding the JAFROC analysis and Christina Söderman, Department of Radiation Physics, Sahlgrenska Academy at University of Gothenburg, Sweden, for assistance in controlling the detection study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sara A. Asplund.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Asplund, S.A., Johnsson, Å.A., Vikgren, J. et al. Effect of radiation dose level on the detectability of pulmonary nodules in chest tomosynthesis. Eur Radiol 24, 1529–1536 (2014). https://doi.org/10.1007/s00330-014-3182-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-014-3182-1

Keywords

Navigation