PSMA-PET radiomic model for discrimination of high risk prostate cancer patients
DOI:
https://doi.org/10.37004/sefm/2022.23.2.002Keywords:
Prostate Cancer, PSMA-PET, radiomic models, Gleason scoreAbstract
In patients with prostate cancer (PCa), the characterization of the Gleason score (GS) by radiomic models is of special interest as a non-invasive alternative to biopsy and because it allows stratifying the level of risk and supporting treatment decision. Our aim was to obtain a [68Ga]-Prostate Specific-Membrane-Antigen (PSMA) Positron-Emission-Tomography (PET) radiomic model to characterize GS in PCa. In 60 patients, tumors were manually segmented and for the 20 prospective patients, histopathological co-registration was additionally segmented. For 133 radiomic features (RFs) we evaluated: intrinsic dependence with volume and with different PET/TC equipment, their values inside and outside the prostatic tumor and the GS characterization. Wilcoxon signed-rank test, Spearman correlation and logistic regression were used as methods of analysis. The results show that 50 RFs were intrinsically volume independent and discriminated the tumor from the rest of the prostate, regardless of the segmentation method applied. The GS was characterized (G < 8 vs G ≥ 8) by a RF with area-under-the-curve (AUC) of 0.91/0.84 for the initial/validation cohort and by a radiomic signature (AUC 0.93/0.78). It can be concluded that noninvasive characterization of GS with 68Ga- PSMA-PET radiomic models is feasible.
References
Source: ECIS - European Cancer Information System From https://ecis.jrc.ec.europa.eu © European Union, 2022
Hoeks, C. M., Barentsz, J. O., Hambrock, T. et al. Prostate cancer: Multiparametric MR imaging for detection, localization, and staging. Radiology 2011, 26,46–66, doi:10.1148/radiol.11091822.
Cutaia G, La Tona G, Comelli A, et al. Radiomics and Prostate MRI: Current Role and Future Applications. J Imaging. 2021;7(2):34. Published 2021 Feb 11. doi:10.3390/jimaging7020034
Eiber M, Maurer T, Souvatzoglou M, et al. Evaluation of Hybrid 68Ga-PSMA Ligand PET/CT in 248 Patients with Biochemical Recurrence After Radical Prostatectomy [published correction appears in J Nucl Med. 2016 Aug;57(8):1325]. J Nucl Med. 2015;56(5):668-674.doi:10.2967/jnumed.115.154153
Rhee H, Thomas P, Shepherd B, et al. Prostate Specific Membrane Antigen Positron Emission Tomography May Improve the Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging in Localized Prostate Cancer. J Urol. 2016;196(4):1261-1267. doi:10.1016/j.juro.2016.02.3000
Berger I, Annabattula C, et al. 68Ga-PSMA PET/CT vs. mpMRI for locoregional prostate cancer staging: correlation with final histopathology. Prostate cancer and prostatic diseases vol. 21,2 (2018): 204-211. doi:10.1038/s41391-018-0048-7
Donato P, Roberts MJ, Morton A, et al. Improved specificity with 68Ga PSMA PET/CT to detect clinically significant lesions "invisible" on multiparametric MRI of the prostate: a single institution comparative analysis with radical prostatectomy histology. Eur J Nucl Med Mol Imaging vol. 46,1 (2019): 20-30. doi:10.1007/s00259-018-4160-7
Epstein JI, Allsbrook WC Jr, Amin MB, Egevad LL; ISUP Grading Committee. The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. Am J Surg Pathol. 2005;29(9):1228-1242. doi:10.1097/01.pas.0000173646.99337.b1
Fehr D, Veeraraghavan H, Wibmer A, et al. Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images. Proc. Natl. Acad. Sci. USA 2015, 112, 6265–6273, doi:10.1073/pnas.1505935112.52
Cuocolo R, Stanzione A, et al. Clinically significant prostate cancer detection on MRI: A radiomic shape features study. Eur. J. Radiol. 2019, 116, 144–149,doi:10.1016/j.ejrad.2019.05.006.
Rahbar K, Weckesser M, Huss S, et al. Correlation of Intraprostatic Tumor Extent with 68Ga-PSMA Distribution in Patients with Prostate Cancer. J Nucl Med. 2016;57(4):563-567. doi:10.2967/jnumed.115.169243
Hoffmann MA, Miederer M, Wieler HJ, Ruf C, Jakobs FM, Schreckenberger M. Diagnostic performance of (68) Gallium-PSMA-11 PET/CT to detect significant prostate cancer and comparison with (FEC)-F-18 PET/CT. Oncotarget. 2017; 8: 111073-83.
Zamboglou C, Carles M, Fechter T, et al. Radiomic features from PSMA PET for non-invasive intraprostatic tumor discrimination and characterization in patients with intermediate and high-risk prostate cancer - a comparison study with histology reference. Theranostics. 2019;9(9):2595-2605. Published 2019 Apr 13. doi:10.7150/thno.32376
Surti S, Kuhn A, Werner ME, Perkins AE, Kolthammer J, Karp JS. Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities. J Nucl Med. 2007;48(3):471–80.
Rausch I, Ruiz A, Valverde-Pascual I, Cal-González J, Beyer T, Carrio I. Performance Evaluation of the Vereos PET/CT System According to the NEMA NU2-2012 Standard. J Nuc Med. 2019;60(4):561–7. https://doi.org/10.2967/jnumed.118.215541. Epub 2018 Oct 25
Zamboglou C, Schiller F, Fechter T, et al. (68)Ga-HBED-CC-PSMA PET/CT Versus Histopathology in Primary Localized Prostate Cancer: A Voxel-Wise Comparison. Theranostics. 2016; 6: 1619-28.
Vallières M, Freeman CR, Skamene SR, El Naqa I. A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities. Phys Med Biol. 2015; 60: 5471-96.
Vallières M, Zwanenburg A, Badic B, Cheze Le Rest C, Visvikis D, Hatt M. Responsible Radiomics Research for Faster Clinical Translation. J Nucl Med. 2018;59(2):189-193. doi:10.2967/jnumed.117.200501
Carles M, Bach T, Torres-Espallardo I, Baltas D, Nestle U, Martí-Bonmatí L. Significance of the impact of motion compensation on the variability of PET image features. Phys Med Biol. 2018; 63: 065013
Benjamini Y, Hochberg Y. Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing. J R Stat Soc Series B Stat Methodol. 1995; 57: 289-300.
Zamboglou C, Fassbender TF, Steffan L, et al. Validation of different PSMA-PET/CT-based contouring techniques for intraprostatic tumor definition using histopathology as standard of reference. Radiother Oncol. 2019;141:208-213. doi:10.1016/j.radonc.2019.07.002.
Sue M. Evans, Varuni Patabendi Bandarage, Caroline Kronborg, Arul Earnest, Jeremy Millar, David Clouston, Gleason group concordance between biopsy and radical prostatectomy specimens: A cohort study from Prostate Cancer Outcome Registry – Victoria, Prostate International, 2016, 4(4): 145-151. doi.org/10.1016/j.prnil.2016.07.004.
Pfaehler E, van Sluis J, Merema BBJ, van Ooijen P, Berendsen RCM, van Velden FHP, Boellaard R. Experimental Multicenter and Multivendor Evaluation of the Performance of PET Radiomic Features Using 3-Dimensionally Printed Phantom Inserts. J Nucl Med. 2020 Mar;61(3):469-476. doi: 10.2967/jnumed.119.229724. Epub 2019 Aug 16. PMID: 31420497; PMCID: PMC7067530.
Jha, A.K., Mithun, S., Jaiswar, V. et al. Repeatability and reproducibility study of radiomic features on a phantom and human cohort. Sci Rep 11, 2055 (2021). https://doi.org/10.1038/s41598-021-81526-8
Carles, M., Fechter, T., Martí-Bonmatí, L. et al. Experimental phantom evaluation to identify robust positron emission tomography (PET) radiomic features. EJNMMI Phys 8, 46 (2021). https://doi.org/10.1186/s40658-021-00390-7
Carles M, Bach T, Torres-Espallardo I, Baltas D, Nestle U, Martí-Bonmatí L. Significance of the impact of motion compensation on the variability of PET image features. Phys Med Biol. 2018;63(6):065013. https://doi.org/10.1088/1361-6560/aab180
Zamboglou C, Drendel V, Jilg CA, et al. Comparison of 68Ga-HBED-CC PSMA-PET/CT and multiparametric MRI for gross tumour volume detection in patients with primary prostate cancer based on slice-by-slice comparison with histopathology. Theranostics. 2017;7(1):228-237. Published 2017 Jan 1. doi:10.7150/thno.16638.
