Advantage of whole-mount histopathology in prostate cancer: current applications and future prospects

Montironi R, Cheng L, Mazzucchelli R, Scarpelli M, Kirkali Z, Montorsi F, Lopez-Beltran A. Critical evaluation of the prostate from cystoprostatectomies for bladder cancer: insights from a complete sampling with the whole mount technique. Eur Urol. 2009;55(6):1305–9.

Article  PubMed  Google Scholar 

Cimadamore A, Cheng L, Lopez-Beltran A, Mazzucchelli R, Lucianò R, Scarpelli M, Montorsi F, Montironi R. Added clinical value of whole-mount histopathology of radical prostatectomy specimens: a collaborative review. Eur Urol Oncol. 2021;4(4):558–69.

Article  PubMed  Google Scholar 

Filter ER, Gabril MY, Gomez JA, Wang PZT, Chin JL, Izawa J, Moussa M. Incidental prostate adenocarcinoma in cystoprostatectomy specimens: partial Versus Complete prostate sampling. Int J Surg Pathol. 2017;25(5):414–20.

Article  PubMed  Google Scholar 

Collette ERP, den Bakker MA, Klaver SO, Vis AN, Kliffen M. Partial versus complete prostatectomy specimen sampling: prospective non-inferiority study for pT3a tumours and surgical margin involvement. BMJ Open. 2019;9(4):e024524.

Article  PubMed  PubMed Central  Google Scholar 

Ward AD, Crukley C, McKenzie CA, Montreuil J, Gibson E, Romagnoli C, Gomez JA, Moussa M, Chin J, Bauman G, et al. Prostate: registration of digital histopathologic images to in vivo MR images acquired by using endorectal receive coil. Radiology. 2012;263(3):856–64.

Article  PubMed  Google Scholar 

Ageeli W, Wei C, Zhang X, Szewcyk-Bieda M, Wilson J, Li C, Nabi G. Quantitative ultrasound shear wave elastography (USWE)-measured tissue stiffness correlates with PIRADS scoring of MRI and Gleason score on whole-mount histopathology of prostate cancer: implications for ultrasound image-guided targeting approach. Insights Imaging. 2021;12(1):96.

Article  PubMed  PubMed Central  Google Scholar 

Wibulpolprasert P, Raman SS, Hsu W, Margolis DJA, Asvadi NH, Khoshnoodi P, Moshksar A, Tan N, Ahuja P, Maehara CK, et al. Detection and localization of prostate Cancer at 3-T multiparametric MRI using PI-RADS segmentation. AJR Am J Roentgenol. 2019;212(6):W122–w131.

Article  PubMed  Google Scholar 

Schaudinn A, Gawlitza J, Mucha S, Linder N, Franz T, Horn LC, Kahn T, Busse H. Comparison of PI-RADS v1 and v2 for multiparametric MRI detection of prostate cancer with whole-mount histological workup as reference standard. Eur J Radiol. 2019;116:180–5.

Article  PubMed  Google Scholar 

Reynolds HM, Tadimalla S, Wang YF, Montazerolghaem M, Sun Y, Williams S, Mitchell C, Finnegan ME, Murphy DG, Haworth A. Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy. Cancer Imaging. 2022;22(1):71.

Article  PubMed  PubMed Central  Google Scholar 

Chatterjee A, Tokdemir S, Gallan AJ, Yousuf A, Antic T, Karczmar GS, Oto A. Multiparametric MRI features and pathologic outcome of Wedge-shaped lesions in the Peripheral Zone on T2-Weighted images of the prostate. AJR Am J Roentgenol. 2019;212(1):124–9.

Article  PubMed  Google Scholar 

Bajgiran AM, Mirak SA, Sung K, Sisk AE, Reiter RE, Raman SS. Apparent diffusion coefficient (ADC) ratio Versus Conventional ADC for detecting clinically significant prostate Cancer with 3-T MRI. AJR Am J Roentgenol. 2019;213(3):W134–w142.

Article  PubMed  Google Scholar 

Gao J, Zhang Q, Zhang C, Chen M, Li D, Fu Y, Lv X, Zhang B, Guo H. Diagnostic performance of multiparametric MRI parameters for Gleason score and cellularity metrics of prostate cancer in different zones: a quantitative comparison. Clin Radiol. 2019;74(11):895e817–26.

Article  Google Scholar 

Broeke NC, Peterson J, Lee J, Martin PR, Farag A, Gomez JA, Moussa M, Gaed M, Chin J, Pautler SE, et al. Characterization of clinical human prostate cancer lesions using 3.0-T sodium MRI registered to gleason-graded whole-mount histopathology. J Magn Reson Imaging. 2019;49(5):1409–19.

Article  PubMed  Google Scholar 

Chatterjee A, Mercado C, Bourne RM, Yousuf A, Hess B, Antic T, Eggener S, Oto A, Karczmar GS. Validation of prostate tissue composition by using hybrid multidimensional MRI: correlation with histologic findings. Radiology. 2022;302(2):368–77.

Article  PubMed  Google Scholar 

Zhang Z, Wu HH, Priester A, Magyar C, Afshari Mirak S, Shakeri S, Mohammadian Bajgiran A, Hosseiny M, Azadikhah A, Sung K, et al. Prostate microstructure in prostate Cancer using 3-T MRI with diffusion-relaxation correlation spectrum imaging: validation with whole-Mount Digital Histopathology. Radiology. 2020;296(2):348–55.

Article  PubMed  Google Scholar 

Sonni I, Felker ER, Lenis AT, Sisk AE, Bahri S, Allen-Auerbach M, Armstrong WR, Suvannarerg V, Tubtawee T, Grogan T, et al. Head-to-Head comparison of (68)Ga-PSMA-11 PET/CT and mpMRI with a Histopathology Gold Standard in the detection, Intraprostatic Localization, and determination of local extension of primary prostate Cancer: results from a prospective single-center imaging trial. J Nucl Med. 2022;63(6):847–54.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bahler CD, Green M, Hutchins GD, Cheng L, Magers MJ, Fletcher J, Koch MO. Prostate specific membrane Antigen targeted Positron Emission Tomography of primary prostate Cancer: assessing accuracy with whole Mount Pathology. J Urol. 2020;203(1):92–9.

Article  PubMed  Google Scholar 

Scheltema MJ, Chang JI, Stricker PD, van Leeuwen PJ, Nguyen QA, Ho B, Delprado W, Lee J, Thompson JE, Cusick T, et al. Diagnostic accuracy of (68) Ga-prostate-specific membrane antigen (PSMA) positron-emission tomography (PET) and multiparametric (mp)MRI to detect intermediate-grade intra-prostatic prostate cancer using whole-mount pathology: impact of the addition of (68) Ga-PSMA PET to mpMRI. BJU Int. 2019;124(Suppl 1):42–9.

Article  CAS  PubMed  Google Scholar 

Gao J, Zhang C, Zhang Q, Fu Y, Zhao X, Chen M, Zhang B, Li D, Shi J, Wang F, et al. Diagnostic performance of (68)Ga-PSMA PET/CT for identification of aggressive cribriform morphology in prostate cancer with whole-mount sections. Eur J Nucl Med Mol Imaging. 2019;46(7):1531–41.

Article  CAS  PubMed  Google Scholar 

Touijer KA, Michaud L, Alvarez HAV, Gopalan A, Kossatz S, Gonen M, Beattie B, Sandler I, Lyaschenko S, Eastham JA, et al. Prospective study of the Radiolabeled GRPR antagonist BAY86-7548 for Positron Emission Tomography/Computed Tomography Imaging of newly diagnosed prostate Cancer. Eur Urol Oncol. 2019;2(2):166–73.

Article  PubMed  Google Scholar 

Alfano R, Bauman GS, Liu W, Thiessen JD, Rachinsky I, Pavlosky W, Butler J, Gaed M, Moussa M, Gomez JA, et al. Histologic validation of auto-contoured dominant intraprostatic lesions on [(18)F] DCFPyL PSMA-PET imaging. Radiother Oncol. 2020;152:34–41.

Article  CAS  PubMed  Google Scholar 

Rezaeijo SM, Chegeni N, Baghaei Naeini F, Makris D, Bakas S. Within-modality synthesis and Novel Radiomic evaluation of Brain MRI scans. Cancers (Basel) 2023, 15(14).

Khanfari H, Mehranfar S, Cheki M, Mohammadi Sadr M, Moniri S, Heydarheydari S, Rezaeijo SM. Exploring the efficacy of multi-flavored feature extraction with radiomics and deep features for prostate cancer grading on mpMRI. BMC Med Imaging. 2023;23(1):195.

Article  PubMed  PubMed Central  Google Scholar 

Lorusso V, Kabre B, Pignot G, Branger N, Pacchetti A, Thomassin-Piana J, Brunelle S, Nicolai N, Musi G, Salem N et al. External validation of the computerized analysis of TRUS of the prostate with the ANNA/C-TRUS system: a potential role of artificial intelligence for improving prostate cancer detection. World J Urol 2022.

Lorusso V, Kabre B, Pignot G, Branger N, Pacchetti A, Thomassin-Piana J, Brunelle S, Gregori A, Salem N, Musi G, et al. Comparison between Micro-ultrasound and Multiparametric MRI regarding the correct identification of prostate Cancer lesions. Clin Genitourin Cancer. 2022;20(4):e339–45.

Article  PubMed  Google Scholar 

Li D, Han X, Gao J, Zhang Q, Yang H, Liao S, Guo H, Zhang B. Deep learning in prostate Cancer diagnosis using Multiparametric magnetic resonance imaging with whole-Mount Histopathology Referenced delineations. Front Med (Lausanne). 2021;8:810995.

Article  PubMed  Google Scholar 

Cao R, Zhong X, Afshari S, Felker E, Suvannarerg V, Tubtawee T, Vangala S, Scalzo F, Raman S, Sung K. Performance of Deep Learning and Genitourinary radiologists in detection of prostate Cancer using 3-T multiparametric magnetic resonance imaging. J Magn Reson Imaging. 2021;54(2):474–83.

Article  PubMed  PubMed Central  Google Scholar 

Seetharaman A, Bhattacharya I, Chen LC, Kunder CA, Shao W, Soerensen SJC, Wang JB, Teslovich NC, Fan RE, Ghanouni P, et al. Automated detection of aggressive and indolent prostate cancer on magnetic resonance imaging. Med Phys. 2021;48(6):2960–72.

Article  PubMed  Google Scholar 

Liu Y, Zheng H, Liang Z, Miao Q, Brisbane WG, Marks LS, Raman SS, Reiter RE, Yang G, Sung K. Textured-based deep learning in prostate Cancer classification with 3T multiparametric MRI: comparison with PI-RADS-Based classification. Diagnostics (Basel) 2021, 11(10).

Gunashekar DD, Bielak L, Hägele L, Oerther B, Benndorf M, Grosu AL, Brox T, Zamboglou C, Bock M. Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology. Radiat Oncol. 2022;17(1):65.

Article  PubMed  PubMed Central  Google Scholar 

Hiremath A, Shiradkar R, Merisaari H, Prasanna P, Ettala O, Taimen P, Aronen HJ, Boström PJ, Jambor I, Madabhushi A. Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps. Eur Radiol. 2021;31(1):379–91.

Article  PubMed  Google Scholar 

Bhattacharya I, Lim DS, Aung HL, Liu X, Seetharaman A, Kunder CA, Shao W, Soerensen SJC, Fan RE, Ghanouni P, et al. Bridging the gap between prostate radiology and pathology through machine learning. Med Phys. 2022;49(8):5160–81.

Article  CAS  PubMed  Google Scholar 

Bettermann AS, Zamboglou C, Kiefer S, Jilg CA, Spohn S, Kranz-Rudolph J, Fassbender TF, Bronsert P, Nicolay NH, Gratzke C, et al. [(68)Ga-]PSMA-11 PET/CT and multiparametric MRI for gross tumor volume delineation in a slice by slice analysis with whole mount histopathology as a reference standard - implications for focal radiotherapy planning in primary prostate cancer. Radiother Oncol. 2019;141:214–9.

Article  PubMed  Google Scholar 

Sun C, Chatterjee A, Yousuf A, Antic T, Eggener S, Karczmar GS, Oto A. Comparison of T2-Weighted imaging, DWI, and dynamic contrast-enhanced MRI for calculation of prostate Cancer Index Lesion volume: correlation with whole-Mount Pathology. AJR Am J Roentgenol. 2019;212(2):351–6.

Article  PubMed  Google Scholar 

Pooli A, Johnson DC, Shirk J, Markovic D, Sadun TY, Sisk AE Jr., Mohammadian Bajgiran A, Afshari Mirak S, Felker ER, Hughes AK, et al. Predicting pathological tumor size in prostate Cancer based on Multiparametric Prostate Magnetic Resonance Imaging and preoperative findings. J Urol. 2021;205(2):444–51.

Article  PubMed  Google Scholar 

Kramer M, Spohn SKB, Kiefer S, Ceci L, Sigle A, Oerther B, Schultze-Seemann W, Gratzke C, Bock M, Bamberg F, et al. Isotropic expansion of the Intraprostatic Gross Tumor volume of primary prostate Cancer patients defined in MRI-A correlation study with whole Mount Histopathological Information as Reference. Front Oncol. 2020;10:596756.

Article  PubMed  PubMed Central 

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