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Comparison of 18F-Choline PET/CT and MRI functional parameters in prostate cancer

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Abstract

Aim

18F-Choline (FCH) uptake parameters are strong indicators of aggressive disease in prostate cancer. Functional parameters derived by magnetic resonance imaging (MRI) are also correlated to aggressive disease. The aim of this work was to evaluate the relationship between metabolic parameters derived by FCH PET/CT and functional parameters derived by MRI.

Materials and methods

Fourteen patients with proven prostate cancer who underwent FCH PET/CT and multiparametric MRI were enrolled. FCH PET/CT consisted in a dual phase: early pelvic list-mode acquisition and late whole-body acquisition. FCH PET/CT and multiparametric MRI examinations were registered and tumoral volume-of-interest were drawn on the largest lesion visualized on the apparent diffusion coefficient (ADC) map and projected onto the different multiparametric MR images and FCH PET/CT images. Concerning the FCH uptake, kinetic parameters were extracted with the best model selected using the Akaike information criterion between the one- and two-tissue compartment models with an imaging-derived plasma input function. Other FCH uptake parameters (early SUVmean and late SUVmean) were extracted. Concerning functional parameters derived by MRI scan, cell density (ADC from diffusion weighting imaging) and vessel permeability (Ktrans and Ve using the Tofts pharmakinetic model from dynamic contrast-enhanced imaging) parameters were extracted. Spearman’s correlation coefficients were calculated to compare parameters.

Results

The one-tissue compartment model for kinetic analysis of PET images was selected. Concerning correlation analysis between PET parameters, K1 was highly correlated with early SUVmean (r = 0.83, p < 0.001) and moderately correlated with late SUVmean (r = 0.66, p = 0.010) and early SUVmean was highly correlated with late SUVmean (r = 0.90, p < 0.001). No significant correlation was found between functional MRI parameters. Concerning correlation analysis between PET and functional MRI parameters, K1 (from FCH PET/CT imaging) was moderately correlated with Ktrans (from perfusion MR imaging) (r = 0.55, p = 0.041).

Conclusions

No significant correlation was found between FCH PET/CT and multiparametric MRI metrics except FCH influx which is moderately linked to the vessel permeability in prostate cancer.

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References

  1. Zhou CK, Check DP, Lortet-Tieulent J, Laversanne M, Jemal A, Ferlay J, et al. Prostate cancer incidence in 43 populations worldwide: an analysis of time trends overall and by age group. Int J Cancer. 2016;138(6):1388–400.

    Article  CAS  Google Scholar 

  2. Schaefferkoetter JD, Wang Z, Stephenson MC, Roy S, Conti M, Eriksson L, et al. Quantitative 18F-fluorocholine positron emission tomography for prostate cancer: correlation between kinetic parameters and Gleason scoring. EJNMMI Res. 2017;7(1):25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Palard-Novello X, Blin AL, Bourhis D, Garin E, Salaun PY, Devillers A, et al. Comparison of choline influx from dynamic (18)F-Choline PET/CT and clinicopathological parameters in prostate cancer initial assessment. Ann Nucl Med. 2018;32(4):281–87.

    Article  CAS  PubMed  Google Scholar 

  4. Tamada T, Prabhu V, Li J, Babb JS, Taneja SS, Rosenkrantz AB. Prostate cancer: diffusion-weighted MR imaging for detection and assessment of aggressiveness-comparison between conventional and kurtosis models. Radiology. 2017;284(1):100–8.

    Article  Google Scholar 

  5. Peng Y, Jiang Y, Yang C, Brown JB, Antic T, Sethi I, et al. Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score—a computer-aided diagnosis development study. Radiology. 2013;267(3):787–96.

    Article  PubMed  Google Scholar 

  6. Oto A, Yang C, Kayhan A, Tretiakova M, Antic T, Schmid-Tannwald C, et al. Diffusion-weighted and dynamic contrast-enhanced MRI of prostate cancer: correlation of quantitative MR parameters with Gleason score and tumor angiogenesis. AJR Am J Roentgenol. 2011;197(6):1382–90.

    Article  PubMed  Google Scholar 

  7. Hauth E, Halbritter D, Jaeger H, Hohmuth H, Beer M. Diagnostic value of semi-quantitative and quantitative analysis of functional parameters in multiparametric MRI of the prostate. Br J Radiol. 2017;90(1078):20170067.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Vos EK, Litjens GJ, Kobus T, Hambrock T, Hulsbergen-van de Kaa CA, Barentsz JO, et al. Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T. Eur Urol. 2013;64(3):448–55.

    Article  PubMed  Google Scholar 

  9. Hotker AM, Mazaheri Y, Aras O, Zheng J, Moskowitz CS, Gondo T, et al. Assessment of prostate cancer aggressiveness by use of the combination of quantitative DWI and dynamic contrast-enhanced MRI. AJR Am J Roentgenol. 2016;206(4):756–63.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Piert M, Montgomery J, Kunju LP, Siddiqui J, Rogers V, Rajendiran T, et al. 18F-Choline PET/MRI: the additional value of PET for MRI-guided transrectal prostate biopsies. J Nucl Med Off Publ Soc Nucl Med. 2016;57(7):1065–70.

    CAS  Google Scholar 

  11. Pinkawa M, Piroth MD, Holy R, Klotz J, Djukic V, Corral NE, et al. Dose-escalation using intensity-modulated radiotherapy for prostate cancer—evaluation of quality of life with and without (18)F-choline PET-CT detected simultaneous integrated boost. Radiat Oncol. 2012;7:14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. DeGrado TR, Baldwin SW, Wang S, Orr MD, Liao RP, Friedman HS, et al. Synthesis and evaluation of (18)F-labeled choline analogs as oncologic PET tracers. J Nucl Med Off Publ Soc Nucl Med. 2001;42(12):1805–14.

    CAS  Google Scholar 

  13. DeGrado TR, Reiman RE, Price DT, Wang S, Coleman RE. Pharmacokinetics and radiation dosimetry of 18F-fluorocholine. J Nucl Med Off Publ Soc Nucl Med. 2002;43(1):92–6.

    CAS  Google Scholar 

  14. Jadvar H. Prostate cancer: PET with 18F-FDG, 18F- or 11C-acetate, and 18F- or 11C-choline. Journal of nuclear medicine: official publication. Soc Nucl Med. 2011;52(1):81–9.

    Article  Google Scholar 

  15. Bhakoo KK, Williams SR, Florian CL, Land H, Noble MD. Immortalization and transformation are associated with specific alterations in choline metabolism. Cancer Res. 1996;56(20):4630–5.

    CAS  Google Scholar 

  16. Massaro A, Ferretti A, Secchiero C, Cittadin S, Milan E, Tamiso L, et al. Optimising 18F-choline PET/CT acquisition protocol in prostate cancer patients. N Am J Med Sci. 2012;4:416–20.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Chondrogiannis S, Marzola MC, Grassetto G, Maffione AM, Rampin L, Veronese E, et al. New acquisition protocol of 18F-choline PET/CT in prostate cancer patients: review of the literature about methodology and proposal of standardization. Biomed Res Int. 2014;2014:215650.

    PubMed  PubMed Central  Google Scholar 

  18. Palard-Novello X, Blin AL, Le Jeune F, Garin E, Salaun PY, Devillers A, et al. Optimization of temporal sampling for (18)F-choline uptake quantification in prostate cancer assessment. EJNMMI Res. 2018;8(1):49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging JMRI. 1999;10(3):223–32.

    Article  CAS  PubMed  Google Scholar 

  20. Glatting G, Kletting P, Reske SN, Hohl K, Ring C. Choosing the optimal fit function: comparison of the Akaike information criterion and the F-test. Med Phys. 2007;34(11):4285–92.

    Article  CAS  PubMed  Google Scholar 

  21. Plathow C, Weber WA. Tumor cell metabolism imaging. J Nucl Med Off Publ Soc Nucl Med. 2008;49(Suppl 2):43S–63S.

    CAS  Google Scholar 

  22. Michel V, Yuan Z, Ramsubir S, Bakovic M. Choline transport for phospholipid synthesis. Exp Biol Med. 2006;231(5):490–504.

    Article  CAS  Google Scholar 

  23. de Perrot T, Rager O, Scheffler M, Lord M, Pusztaszeri M, Iselin C, et al. Potential of hybrid (1)(8)F-fluorocholine PET/MRI for prostate cancer imaging. Eur J Nucl Med Mol Imaging. 2014;41(9):1744–55.

    Article  CAS  PubMed  Google Scholar 

  24. Rakheja R, Chandarana H, DeMello L, Jackson K, Geppert C, Faul D, et al. Correlation between standardized uptake value and apparent diffusion coefficient of neoplastic lesions evaluated with whole-body simultaneous hybrid PET/MRI. AJR American J Roentgenol. 2013;201(5):1115–9.

    Article  Google Scholar 

  25. Heusch P, Buchbender C, Kohler J, Nensa F, Beiderwellen K, Kuhl H, et al. Correlation of the apparent diffusion coefficient (ADC) with the standardized uptake value (SUV) in hybrid 18F-FDG PET/MRI in non-small cell lung cancer (NSCLC) lesions: initial results. RoFo: Fortschritte auf dem Gebiete der Rontgenstrahlen der Nuklearmedizin. 2013;185(11):1056–62.

    Article  CAS  Google Scholar 

  26. Byun BH, Kong CB, Lim I, Choi CW, Song WS, Cho WH, et al. Combination of 18F-FDG PET/CT and diffusion-weighted MR imaging as a predictor of histologic response to neoadjuvant chemotherapy: preliminary results in osteosarcoma. J Nucl Med Off Publ Soc Nucl Med. 2013;54(7):1053–9.

    CAS  Google Scholar 

  27. Vadi SK, Singh B, Basher RK, Watts A, Sood AK, Lal A, et al. 18F-fluorocholine PET/CT complementing the role of dynamic contrast-enhanced MRI for providing comprehensive diagnostic workup in prostate cancer patients with suspected relapse following radical prostatectomy. Clin Nucl Med. 2017;42(8):e355-e36.

    Google Scholar 

  28. Metser U, Berlin A, Halankar J, Murphy G, Jhaveri KS, Ghai S, et al. 18F-fluorocholine PET whole-body MRI in the staging of high-risk prostate cancer. AJR Am J Roentgenol. 2018;210(3):635–40.

    Article  PubMed  Google Scholar 

  29. Verwer EE, Oprea-Lager DE, van den Eertwegh AJ, van Moorselaar RJ, Windhorst AD, Schwarte LA, et al. Quantification of 18F-fluorocholine kinetics in patients with prostate cancer. J Nucl Med Off Publ Soc Nucl Med. 2015;56(3):365–71.

    CAS  Google Scholar 

  30. Choi JY, Yang J, Noworolski SM, Behr S, Chang AJ, Simko JP, et al. 18f fluorocholine dynamic time-of-flight PET/MR imaging in patients with newly diagnosed intermediate- to high-risk prostate cancer: initial clinical-pathologic comparisons. Radiology. 2017;282(2):429–36.

    Article  PubMed  Google Scholar 

  31. Grkovski M, Gharzeddine K, Sawan P, Schoder H, Michaud L, Weber WA, et al. 11C-choline pharmacokinetics in recurrent prostate cancer. J Nucl Med. 2018. https://doi.org/10.2967/jnumed.118.210088.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Takesh M. Kinetic modeling application to (18)F-fluoroethylcholine positron emission tomography in patients with primary and recurrent prostate cancer using two-tissue compartmental model. World J Nucl Med. 2013;12(3):101–10.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Iorio E, Mezzanzanica D, Alberti P, Spadaro F, Ramoni C, D’Ascenzo S, et al. Alterations of choline phospholipid metabolism in ovarian tumor progression. Cancer Res. 2005;65(20):9369–76.

    Article  CAS  PubMed  Google Scholar 

  34. Cho E, Chung DJ, Yeo DM, Sohn D, Son Y, Kim T, et al. Optimal cut-off value of perfusion parameters for diagnosing prostate cancer and for assessing aggressiveness associated with Gleason score. Clin Imaging. 2015;39(5):834–40.

    Article  Google Scholar 

  35. **ao H, Tan F, Goovaerts P, Adunlin G, Ali A, Huang Y, et al. Factors associated with time-to-treatment of prostate cancer in Florida. J Health Care Poor Underserved. 2013;24(4 Suppl):132–46.

    PubMed  PubMed Central  Google Scholar 

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Correspondence to Xavier Palard-Novello.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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For this type of study (retrospective), the local ethics committee waived the requirement for informed consent.

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Palard-Novello, X., Beuzit, L., Gambarota, G. et al. Comparison of 18F-Choline PET/CT and MRI functional parameters in prostate cancer. Ann Nucl Med 33, 47–54 (2019). https://doi.org/10.1007/s12149-018-1302-8

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  • DOI: https://doi.org/10.1007/s12149-018-1302-8

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