Prospective evaluation of 18F-FACBC PET/CT and PET/MRI versus multiparametric MRI in intermediate- to high-risk prostate cancer patients (FLUCIPRO trial)

  • Ivan JamborEmail author
  • Anna Kuisma
  • Esa Kähkönen
  • Jukka Kemppainen
  • Harri Merisaari
  • Olli Eskola
  • Jarmo Teuho
  • Ileana Montoya Perez
  • Marko Pesola
  • Hannu J. Aronen
  • Peter J. Boström
  • Pekka Taimen
  • Heikki Minn
Original Article



The purpose of this study was to evaluate 18F-FACBC PET/CT, PET/MRI, and multiparametric MRI (mpMRI) in detection of primary prostate cancer (PCa).


Twenty-six men with histologically confirmed PCa underwent PET/CT immediately after injection of 369 ± 10 MBq 18F-FACBC (fluciclovine) followed by PET/MRI started 55 ± 7 min from injection. Maximum standardized uptake values (SUVmax) were measured for both hybrid PET acquisitions. A separate mpMRI was acquired within a week of the PET scans. Logan plots were used to calculate volume of distribution (VT). The presence of PCa was estimated in 12 regions with radical prostatectomy findings as ground truth. For each imaging modality, area under the curve (AUC) for detection of PCa was determined to predict diagnostic performance. The clinical trial registration number is NCT02002455.


In the visual analysis, 164/312 (53%) regions contained PCa, and 41 tumor foci were identified. PET/CT demonstrated the highest sensitivity at 87% while its specificity was low at 56%. The AUC of both PET/MRI and mpMRI significantly (p < 0.01) outperformed that of PET/CT while no differences were detected between PET/MRI and mpMRI. SUVmax and VT of Gleason score (GS) >3 + 4 tumors were significantly (p < 0.05) higher than those for GS 3 + 3 and benign hyperplasia. A total of 442 lymph nodes were evaluable for staging, and PET/CT and PET/MRI demonstrated true-positive findings in only 1/7 patients with metastatic lymph nodes.


Quantitative 18F-FACBC imaging significantly correlated with GS but failed to outperform MRI in lesion detection. 18F-FACBC may assist in targeted biopsies in the setting of hybrid imaging with MRI.


18F-FACBC Prostate cancer Diffusion-weighted imaging PET/CT PET/MRI 



This work was funded in part by the Finnish Cancer Foundation, Turku University Hospital Research Funds (EVO), TYKS-SAPA research fund, Instrumentarium Research Foundation, Sigrid Jusélius Foundation, Finnish Cancer Society, and the Finnish Cultural Foundation Southwest Finland Regional Fund. We thank the staff of Turku PET Centre and Department of Urology, Turku University Hospital, for practical assistance. We thank Jaakko Liippo (Turku University Hospital, Turku, Finland) for his help in scanning the histological slides and David Gauden (Blue Earth Diagnostics, Oxford, UK) for providing the FastLab cassettes used in radiosynthesis.

Compliance with ethical standards

The study was approved by the local ethics committee and each patient gave written informed consent. The study registration number is NCT02002455.

Supplementary material

259_2017_3875_MOESM1_ESM.pdf (1.1 mb)
ESM 1 (PDF 1.13 mb).


  1. 1.
    Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66:7–30.CrossRefPubMedGoogle Scholar
  2. 2.
    Johnson DC, Reiter RE. Multi-parametric magnetic resonance imaging as a management decision tool. Transl Androl Urol. 2017;6:472–82.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Carroll PR, Parsons JK, Andriole G, et al. Prostate cancer early detection, version 2.2015. J Natl Compr Cancer Netw. 2015;13:1534–61.CrossRefGoogle Scholar
  4. 4.
    Nepple KG, Wahls TL, Hillis SL, Joudi FN. Gleason score and laterality concordance between prostate biopsy and prostatectomy specimens. Int Braz J Urol. 2009;35:559–64.CrossRefPubMedGoogle Scholar
  5. 5.
    Jambor I, Borra R, Kemppainen J, et al. Functional imaging of localized prostate cancer aggressiveness using 11C-acetate PET/CT and 1H-MR spectroscopy. J Nucl Med. 2010;51:1676–83.CrossRefPubMedGoogle Scholar
  6. 6.
    Mena E, Turkbey B, Mani H, et al. 11C-acetate PET/CT in localized prostate cancer: A study with MRI and Histopathologic correlation. J Nucl Med. 2012.Google Scholar
  7. 7.
    Souvatzoglou M, Weirich G, Schwarzenboeck S, et al. The sensitivity of 11C-choline PET/CT to localize prostate cancer depends on the tumor configuration. Clin Cancer Res. 2011;17:3751–9.CrossRefPubMedGoogle Scholar
  8. 8.
    Umbehr MH, Muntener M, Hany T, Sulser T, Bachmann LM. The role of 11C-choline and 18F-fluorocholine positron emission tomography (PET) and PET/CT in prostate cancer: A systematic review and meta-analysis. Eur Urol. 2013;64:106–17.CrossRefPubMedGoogle Scholar
  9. 9.
    Kaira K, Oriuchi N, Imai H, et al. L-type amino acid transporter 1 and CD98 expression in primary and metastatic sites of human neoplasms. Cancer Sci. 2008;99:2380–6.CrossRefPubMedGoogle Scholar
  10. 10.
    Huang C, McConathy J. Radiolabeled amino acids for oncologic imaging. J Nucl Med. 2013;54:1007–10.CrossRefPubMedGoogle Scholar
  11. 11.
    Schuster DM, Taleghani PA, Nieh PT, et al. Characterization of primary prostate carcinoma by anti-1-amino-2-[(18)F] -fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F] FACBC) uptake. Am J Nucl Med Mol Imaging. 2013;3:85–96.PubMedPubMedCentralGoogle Scholar
  12. 12.
    Nanni C, Zanoni L, Pultrone C, et al. F-FACBC (anti1-amino-3-F-fluorocyclobutane-1-carboxylic acid) versus C-choline PET/CT in prostate cancer relapse: results of a prospective trial. Eur J Nucl Med Mol Imaging. 2016.Google Scholar
  13. 13.
    Turkbey B, Mena E, Shih J, et al. Localized prostate cancer detection with 18F FACBC PET/CT: Comparison with MR imaging and histopathologic analysis. Radiology. 2013;270:849–56.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Bettinardi V, Presotto L, Rapisarda E, Picchio M, Gianolli L, Gilardi MC. Physical performance of the new hybrid PET/CT Discovery-690. Med Phys. 2011;38:5394–411.CrossRefPubMedGoogle Scholar
  15. 15.
    Schulz V, Torres-Espallardo I, Renisch S, et al. Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data. Eur J Nucl Med Mol Imaging. 2011;38:138–52.CrossRefPubMedGoogle Scholar
  16. 16.
    Jambor I, Pesola M, Merisaari H, et al. Relaxation along fictitious field, diffusion-weighted imaging, and T2 mapping of prostate cancer: Prediction of cancer aggressiveness. Magn Reson Med. 2016;75:2130–40.CrossRefPubMedGoogle Scholar
  17. 17.
    Merisaari H, Toivonen J, Pesola M, et al. Diffusion weighted imaging of prostate cancer: Effect of b-value distribution on repeatability and cancer characterization. Magn Reson Imaging Magn Reson Imaging. 2015;33:1212–8.CrossRefPubMedGoogle Scholar
  18. 18.
    Jambor I, Merisaari H, Taimen P, et al. Evaluation of different mathematical models for diffusion-weighted imaging of normal prostate and prostate cancer using high b-values: A repeatability study. Magn Reson Med. 2015;73:1988–98.CrossRefPubMedGoogle Scholar
  19. 19.
    Toivonen J, Merisaari H, Pesola M, et al. Mathematical models for diffusion-weighted imaging of prostate cancer using b values up to 2000 s/mm2: Correlation with Gleason score and repeatability of region of interest analysis. Magn Reson Med. 2015;74:1116–24.CrossRefPubMedGoogle Scholar
  20. 20.
    Merisaari H, Jambor I. Optimization of b-value distribution for four mathematical models of prostate cancer diffusion-weighted imaging using b values up to 2000 s/mm2: Simulation and repeatability study. Magn Reson Med. 2015;73:1954–69.CrossRefPubMedGoogle Scholar
  21. 21.
    Jambor I, Pesola M, Taimen P, et al. Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction. Magn Reson Med. 2016;75:337–44.CrossRefPubMedGoogle Scholar
  22. 22.
    Jambor I, Kahkonen E, Taimen P, et al. Prebiopsy multiparametric 3T prostate MRI in patients with elevated PSA, normal digital rectal examination, and no previous biopsy. J Magn Reson Imaging. 2015;41:1394–404.CrossRefPubMedGoogle Scholar
  23. 23.
    Jambor I, Bostrom PJ, Taimen P, et al. Novel biparametric MRI and targeted biopsy improves risk stratification in men with a clinical suspicion of prostate cancer (IMPROD trial). J Magn Reson Imaging. 2017;46:1089–95.CrossRefPubMedGoogle Scholar
  24. 24.
    Jambor I, Merisaari H, Aronen HJ, et al. Optimization of b-value distribution for biexponential diffusion-weighted MR imaging of normal prostate. J Magn Reson Imaging. 2014;39:1213–22.CrossRefPubMedGoogle Scholar
  25. 25.
    Kahkonen E, Jambor I, Kemppainen J, et al. In vivo imaging of prostate cancer using [68Ga]-Labeled bombesin analog BAY86–7548. Clin Cancer Res. 2013.Google Scholar
  26. 26.
    Jambor I, Borra R, Kemppainen J, et al. Improved detection of localized prostate cancer using co-registered MRI and 11C-acetate PET/CT. Eur J Radiol. 2012;81:2966–72.CrossRefPubMedGoogle Scholar
  27. 27.
    Rosenkrantz AB, Kim S, Lim RP, et al. Prostate cancer localization using multiparametric MR imaging: Comparison of prostate imaging reporting and data system (PI-RADS) and Likert scales. Radiology. 2013;269:482–92.CrossRefPubMedGoogle Scholar
  28. 28.
    Logan J. Graphical analysis of PET data applied to reversible and irreversible tracers. Nucl Med Biol. 2000;27:661–70.CrossRefPubMedGoogle Scholar
  29. 29.
    Epstein JI, Allsbrook WC Jr, Amin MB, Egevad LL. The 2005 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma. Am J Surg Pathol. 2005;29:1228–42.CrossRefPubMedGoogle Scholar
  30. 30.
    Epstein JI. An update of the Gleason grading system. J Urol. 2010;183:433–40.CrossRefPubMedGoogle Scholar
  31. 31.
    Rutter CM. Bootstrap estimation of diagnostic accuracy with patient-clustered data. Acad Radiol. 2000;7:413–9.CrossRefPubMedGoogle Scholar
  32. 32.
    Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology. 1983;148:839–43.CrossRefPubMedGoogle Scholar
  33. 33.
    Wibmer AG, Burger IA, Sala E, Hricak H, Weber WA, Vargas HA. Molecular imaging of prostate cancer. Radiographics. 2016;36:142–59.CrossRefPubMedGoogle Scholar
  34. 34.
    Ren J, Yuan L, Wen G, Yang J. The value of anti-1-amino-3-18F-fluorocyclobutane-1-carboxylic acid PET/CT in the diagnosis of recurrent prostate carcinoma: A meta-analysis. Acta Radiol. 2016;57:487–93.CrossRefPubMedGoogle Scholar
  35. 35.
    Gleason DF. Classification of prostatic carcinomas. Cancer Chemother Rep 1. 1966;50:125–8.Google Scholar
  36. 36.
    Sakata T, Ferdous G, Tsuruta T, et al. L-type amino-acid transporter 1 as a novel biomarker for high-grade malignancy in prostate cancer. Pathol Int. 2009;59:7–18.CrossRefPubMedGoogle Scholar
  37. 37.
    Li R, Younes M, Frolov A, et al. Expression of neutral amino acid transporter ASCT2 in human prostate. Anticancer Res. 2003;23:3413–8.PubMedGoogle Scholar
  38. 38.
    Fendler WP, Eiber M, Beheshti M, et al. 68Ga-PSMA PET/CT: Joint EANM and SNMMI procedure guideline for prostate cancer imaging: Version 1.0. Eur J Nucl Med Mol Imaging. 2017;44:1014–24.CrossRefPubMedGoogle Scholar
  39. 39.
    Afshar-Oromieh A, Holland-Letz T, Giesel FL, et al. Diagnostic performance of 68Ga-PSMA-11 (HBED-CC) PET/CT in patients with recurrent prostate cancer: Evaluation in 1007 patients. Eur J Nucl Med Mol Imaging. 2017;44:1258–68.CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Uprimny C, Kroiss AS, Decristoforo C, et al. 68Ga-PSMA-11 PET/CT in primary staging of prostate cancer: PSA and Gleason score predict the intensity of tracer accumulation in the primary tumour. Eur J Nucl Med Mol Imaging. 2017;44:941–9.CrossRefPubMedGoogle Scholar
  41. 41.
    Zamboglou C, Wieser G, Hennies S, et al. MRI versus 68Ga-PSMA PET/CT for gross tumour volume delineation in radiation treatment planning of primary prostate cancer. Eur J Nucl Med Mol Imaging. 2016;43:889–97.CrossRefPubMedGoogle Scholar
  42. 42.
    Meyer C, Ma B, Kunju LP, Davenport M, Piert M. Challenges in accurate registration of 3-D medical imaging and histopathology in primary prostate cancer. Eur J Nucl Med Mol Imaging. 2013;40(Suppl 1):S72–8.CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Ivan Jambor
    • 1
    • 2
    • 3
    Email author
  • Anna Kuisma
    • 4
  • Esa Kähkönen
    • 5
  • Jukka Kemppainen
    • 3
    • 6
  • Harri Merisaari
    • 1
    • 3
    • 7
  • Olli Eskola
    • 3
  • Jarmo Teuho
    • 3
  • Ileana Montoya Perez
    • 1
    • 7
    • 8
  • Marko Pesola
    • 1
  • Hannu J. Aronen
    • 1
    • 8
  • Peter J. Boström
    • 5
  • Pekka Taimen
    • 9
  • Heikki Minn
    • 3
    • 4
  1. 1.Department of Diagnostic RadiologyUniversity of TurkuTurkuFinland
  2. 2.Department of RadiologyUniversity of Massachusetts Medical School – BaystateSpringfieldUSA
  3. 3.Turku PET CentreTurkuFinland
  4. 4.Department of Oncology and RadiotherapyTurku University HospitalTurkuFinland
  5. 5.Department of UrologyTurku University HospitalTurkuFinland
  6. 6.Department of Clinical Physiology and Nuclear MedicineTurku University HospitalTurkuFinland
  7. 7.Department of Information TechnologyUniversity of TurkuTurkuFinland
  8. 8.Medical Imaging Centre of Southwest FinlandTurku University HospitalTurkuFinland
  9. 9.Department of PathologyUniversity of Turku and Turku University HospitalTurkuFinland

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