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Wieslander E, Jóhannesson V, Nilsson P, Kjellén E, Gunnlaugsson A. Ultrahypofractionated Radiation Therapy for Prostate Cancer Including Seminal Vesicles in the Target Volume: A Treatment-planning Study Based on the HYPO-RT-PC Fractionation Schedule. Adv Radiat Oncol 2024; 9:101531. [PMID: 38883997 PMCID: PMC11176962 DOI: 10.1016/j.adro.2024.101531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 04/25/2024] [Indexed: 06/18/2024] Open
Abstract
Purpose Ultrahypofractionated (UHF) radiation therapy (RT) has become a treatment alternative for patients with localized prostate cancer. In more advanced cases, seminal vesicles (SVs) are routinely included in the target volume. The Scandinavian HYPO-RT-PC trial, which compared 42.7 Gy in 7 fractions (fr) to conventional fractionation (CF), did not include SVs in the clinical target volume. The primary objective of the present work was to implement a ultrahypofractionated-simultaneous integrated boost (UHF-SIB) for prostate cancer RT, incorporating SVs into the target volume based on this fractionation schedule. A secondary objective was to analyze the unintentional dose coverage of SVs from state-of-the-art volumetric modulated arc therapy treatments to the prostate gland only. Methods and Materials Two different equieffective UHF-SIB treatment schedules to SVs were derived based on the CF clinical schedule (50.0 Gy/25 fr to elective SVs and 70.0 Gy/35 fr to verified SV-invasion (SVI)) using the linear quadric model with α/β = 2 Gy and 3 Gy. The dose to the prostate was 42.7 Gy/7 fr in both schedules, with 31.2 Gy/37.8 Gy (α/β = 2 Gy) and 32.7 Gy/40.1 Gy (α/β = 3 Gy) to elective SV/verified SVI. Volumetric modulated arc therapy plans to the proximal 10 mm and 20 mm were optimized, and dose-volume metrics for target volumes and organs at risk were evaluated. Results Dose metrics were overall lower for UHF-SIB compared with CF. QUANTEC-based volume criteria were 2% to 7% lower for the rectum and 2% to 4% lower for the bladder in the UHF-SIB. The D98% to elective SV was 7 to 12 Gy3 lower with UHF-SIB, and the corresponding data for verified SVI were approximately 2 to 3 Gy3. The SV(10 mm) V90%/(29.5 Gy) for prostate-only treatments (42.7 Gy) were as follows: median (IQR), 99% (87-100) and 78% (58-99) for the clinical target volume and planning target volume, respectively. Conclusions UHF RT based on the HYPO-RT-PC fractionation schedule, with a SIB technique, to the prostate and the base of the SV can be planned with lower doses (EQD2) to organs at risk, compared with CF. The unintentional dose to the proximal parts of SVs in prostate-only treatment can be substantial.
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Affiliation(s)
- Elinore Wieslander
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden
| | - Vilberg Jóhannesson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Oncology and Pathology, Lund, Sweden
| | - Per Nilsson
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden
| | - Elisabeth Kjellén
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Oncology and Pathology, Lund, Sweden
| | - Adalsteinn Gunnlaugsson
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Lund University, Faculty of Medicine, Department of Clinical Sciences, Lund, Oncology and Pathology, Lund, Sweden
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Du H, Xie W, Chen W, Wang Y, Liao Y, Qiu M, Li J. Independent association between prostate-specific antigen nadir and PSA progression-free survival in first-line abiraterone acetate treatment in castration-resistant prostate cancer patients: a pilot study. Front Oncol 2024; 14:1348324. [PMID: 38898958 PMCID: PMC11186375 DOI: 10.3389/fonc.2024.1348324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 04/24/2024] [Indexed: 06/21/2024] Open
Abstract
Background There is limited evidence regarding the correlation between prostate-specific antigen (PSA) kinetics and clinical outcomes. Therefore, after regulating other covariates, we studied patients with castration-resistant prostate cancer who received abiraterone acetate as the first-line treatment. In this study, we investigated whether time to PSA nadir was independently associated with PSA progression-free survival (PFS). Methods As a retrospective cohort study, this study contained a total of 77 castration-resistant prostate cancer patients who received abiraterone acetate from October 2015 to April 2021 in a Chinese hospital. The dependent variable was PSA-PFS. The objective independent variable was time to PSA nadir (TTPN). Covariates involved in this study included age, duration of androgen deprivation therapy (ADT), PSA level at baseline, time of 50% PSA decline, time of PSA decline to nadir, Gleason score, bone metastasis, previous treatment, PSA decline <50% in 3 months, PSA to nadir in 3 months, PSA decline <90%, PSA decline <0.2 ng/mL, and PSA flare. Results For the 77 subjects, their mean age was 72.70 ± 8.08 years. Fully calibrated linear regression findings indicated that PSA decline and kinetics were positively associated with PFS (months) after adjusting confounders (β = 0.77, 95% CI: 0.11-1.44). A non-linear relationship was not detected between PSA decline or PSA kinetics and progression-free survival. Conclusion According to the data of this study, there was a correlation between early PSA changes and patients treated with abiraterone acetate.
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Affiliation(s)
- Hong Du
- Department of Urology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Wenjuan Xie
- Human Anatomy and Tissue Embryo Experiment Center, Chengdu Medical College, Chengdu, China
| | - Wenqiang Chen
- Department of Urology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Yu Wang
- Department of Urology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Yong Liao
- Department of Urology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Mingxing Qiu
- Department of Urology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Jun Li
- Department of Urology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, China
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van den Berg I, Soeterik TFW, van der Hoeven EJRJ, Claassen B, Brink WM, Baas DJH, Sedelaar JPM, Heine L, Tol J, van der Voort van Zyp JRN, van den Berg CAT, van den Bergh RCN, van Basten JPA, van Melick HHE. The Development and External Validation of Artificial Intelligence-Driven MRI-Based Models to Improve Prediction of Lesion-Specific Extraprostatic Extension in Patients with Prostate Cancer. Cancers (Basel) 2023; 15:5452. [PMID: 38001712 PMCID: PMC10670855 DOI: 10.3390/cancers15225452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
Adequate detection of the histopathological extraprostatic extension (EPE) of prostate cancer (PCa) remains a challenge using conventional radiomics on 3 Tesla multiparametric magnetic resonance imaging (3T mpMRI). This study focuses on the assessment of artificial intelligence (AI)-driven models with innovative MRI radiomics in predicting EPE of prostate cancer (PCa) at a lesion-specific level. With a dataset encompassing 994 lesions from 794 PCa patients who underwent robot-assisted radical prostatectomy (RARP) at two Dutch hospitals, the study establishes and validates three classification models. The models were validated on an internal validation cohort of 162 lesions and an external validation cohort of 189 lesions in terms of discrimination, calibration, net benefit, and comparison to radiology reporting. Notably, the achieved AUCs ranged from 0.86 to 0.91 at the lesion-specific level, demonstrating the superior accuracy of the random forest model over conventional radiological reporting. At the external test cohort, the random forest model was the best-calibrated model and demonstrated a significantly higher accuracy compared to radiological reporting (83% vs. 67%, p = 0.02). In conclusion, an AI-powered model that includes both existing and novel MRI radiomics improves the detection of lesion-specific EPE in prostate cancer.
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Affiliation(s)
- Ingeborg van den Berg
- Department of Urology, St. Antonius Hospital, 3435 CM Nieuwegein, The Netherlands
- Department of Radiation Oncology, Division of Imaging & Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, 7522 NH Enschede, The Netherlands
| | - Timo F. W. Soeterik
- Department of Urology, St. Antonius Hospital, 3435 CM Nieuwegein, The Netherlands
- Department of Radiation Oncology, Division of Imaging & Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | | | - Bart Claassen
- Department of Radiology, Canisius Wilhelmina Hospital, 7522 NH Nijmegen, The Netherlands
| | - Wyger M. Brink
- Magnetic Detection and Imaging Group, Technical Medical Centre, University of Twente, 7522 NH Enschede, The Netherlands
| | - Diederik J. H. Baas
- Department of Urology, Canisius Wilhelmina Hospital, 7522 NH Nijmegen, The Netherlands
| | - J. P. Michiel Sedelaar
- Department of Urology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Lizette Heine
- Quantib B.V., RadNet’s AI Division, 3012 KM Rotterdam, The Netherlands
| | - Jim Tol
- Quantib B.V., RadNet’s AI Division, 3012 KM Rotterdam, The Netherlands
| | | | - Cornelis A. T. van den Berg
- Department of Radiation Oncology, Division of Imaging & Oncology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | | | - Jean-Paul A. van Basten
- Department of Urology, Canisius Wilhelmina Hospital, 7522 NH Nijmegen, The Netherlands
- Department of Urology, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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Heetman JG, van der Hoeven EJRJ, Rajwa P, Zattoni F, Kesch C, Shariat S, Dal Moro F, Novara G, La Bombara G, Sattin F, von Ostau N, Pötsch N, Baltzer PAT, Wever L, Van Basten JPA, Van Melick HHE, Van den Bergh RCN, Gandaglia G, Soeterik TFW. External validation of nomograms including MRI features for the prediction of side-specific extraprostatic extension. Prostate Cancer Prostatic Dis 2023:10.1038/s41391-023-00738-3. [PMID: 37932522 DOI: 10.1038/s41391-023-00738-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/14/2023] [Accepted: 10/05/2023] [Indexed: 11/08/2023]
Abstract
BACKGROUND Prediction of side-specific extraprostatic extension (EPE) is crucial in selecting patients for nerve-sparing radical prostatectomy (RP). Multiple nomograms, which include magnetic resonance imaging (MRI) information, are available predict side-specific EPE. It is crucial that the accuracy of these nomograms is assessed with external validation to ensure they can be used in clinical practice to support medical decision-making. METHODS Data of prostate cancer (PCa) patients that underwent robot-assisted RP (RARP) from 2017 to 2021 at four European tertiary referral centers were collected retrospectively. Four previously developed nomograms for the prediction of side-specific EPE were identified and externally validated. Discrimination (area under the curve [AUC]), calibration and net benefit of four nomograms were assessed. To assess the strongest predictor among the MRI features included in all nomograms, we evaluated their association with side-specific EPE using multivariate regression analysis and Akaike Information Criterion (AIC). RESULTS This study involved 773 patients with a total of 1546 prostate lobes. EPE was found in 338 (22%) lobes. The AUCs of the models predicting EPE ranged from 72.2% (95% CI 69.1-72.3%) (Wibmer) to 75.5% (95% CI 72.5-78.5%) (Nyarangi-Dix). The nomogram with the highest AUC varied across the cohorts. The Soeterik, Nyarangi-Dix, and Martini nomograms demonstrated fair to good calibration for clinically most relevant thresholds between 5 and 30%. In contrast, the Wibmer nomogram showed substantial overestimation of EPE risk for thresholds above 25%. The Nyarangi-Dix nomogram demonstrated a higher net benefit for risk thresholds between 20 and 30% when compared to the other three nomograms. Of all MRI features, the European Society of Urogenital Radiology score and tumor capsule contact length showed the highest AUCs and lowest AIC. CONCLUSION The Nyarangi-Dix, Martini and Soeterik nomograms resulted in accurate EPE prediction and are therefore suitable to support medical decision-making.
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Affiliation(s)
- J G Heetman
- Department of Urology, St. Antonius Hospital, Utrecht, The Netherlands
| | | | - P Rajwa
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | - F Zattoni
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - C Kesch
- Department of Urology, University Hospital Essen, Essen, Germany
| | - S Shariat
- Department of Urology, Medical University of Vienna, Vienna, Austria
- Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
- Department of Special Surgery, The University of Jordan, Amman, Jordan
- Department of Urology, University of Texas Southwestern Medical Center, Dallas, USA
- Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czechia
- Department of Urology, Weill Cornell Medical College, New York, USA
| | - F Dal Moro
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - G Novara
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - G La Bombara
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - F Sattin
- Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy
| | - N von Ostau
- Department of Urology, University Hospital Essen, Essen, Germany
| | - N Pötsch
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - P A T Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - L Wever
- Department of Urology, St. Antonius Hospital, Utrecht, The Netherlands
| | - J P A Van Basten
- Department of Urology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands
| | - H H E Van Melick
- Department of Urology, St. Antonius Hospital, Utrecht, The Netherlands
| | | | - G Gandaglia
- Unit of Urology/Division of Oncology, San Raffaele Hospital, Milan, Italy
| | - T F W Soeterik
- Department of Urology, St. Antonius Hospital, Utrecht, The Netherlands.
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
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5
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Khajir G, Press B, Lokeshwar S, Ghabili K, Rahman S, Gardezi M, Washington S, Cooperberg MR, Sprenkle P, Leapman MS. Prostate cancer risk stratification using magnetic resonance imaging-ultrasound fusion vs systematic prostate biopsy. JNCI Cancer Spectr 2023; 7:pkad099. [PMID: 38085220 PMCID: PMC10733209 DOI: 10.1093/jncics/pkad099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 11/15/2023] [Accepted: 11/17/2023] [Indexed: 12/22/2023] Open
Abstract
BACKGROUND Image-guided approaches improve the diagnostic yield of prostate biopsy and frequently modify estimates of clinical risk. To better understand the impact of magnetic resonance imaging-ultrasound fusion targeted biopsy (MRF-TB) on risk assessment, we compared the distribution of National Comprehensive Cancer Network (NCCN) risk groupings, as calculated from MRF-TB vs systematic biopsy alone. METHODS We performed a retrospective analysis of 713 patients who underwent MRF-TB from January 2017 to July 2021. The primary study objective was to compare the distribution of National Comprehensive Cancer Network risk groupings obtained using MRF-TB (systematic + targeted) vs systematic biopsy. RESULTS Systematic biopsy alone classified 10% of samples as very low risk and 18.7% of samples as low risk, while MRF-TB classified 10.5% of samples as very low risk and 16.1% of samples as low risk. Among patients with benign findings, low-risk disease, and favorable/intermediate-risk disease on systematic biopsy alone, 4.6% of biopsies were reclassified as high risk or very high risk on MRF-TB. Of 207 patients choosing active surveillance, 64 (31%), 91 (44%), 42 (20.2%), and 10 (4.8%) patients were classified as having very low-risk, low-risk, and favorable/intermediate-risk and unfavorable/intermediate-risk criteria, respectively. When using systematic biopsy alone, 204 patients (28.7%) were classified as having either very low-risk and low-risk disease per NCCN guidelines, while 190 men (26.6%) received this classification when using MRF-TB. CONCLUSION The addition of MRF-TB to systematic biopsy may change eligibility for active surveillance in only a small proportion of patients with prostate cancer. Our findings support the need for routine use of quantitative risk assessment over risk groupings to promote more nuanced decision making for localized cancer.
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Affiliation(s)
- Ghazal Khajir
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
| | - Benjamin Press
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
| | - Soum Lokeshwar
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
| | - Kamyar Ghabili
- Department of Radiology, Penn State Hershey Medical Center, Hershey, PA, USA
| | - Syed Rahman
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
| | - Mursal Gardezi
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
| | - Samuel Washington
- Department of Urology, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Matthew R Cooperberg
- Department of Urology, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Preston Sprenkle
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
| | - Michael S Leapman
- Department of Urology, Yale School of Medicine, New Haven, CT, USA
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
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Zhu M, Gao J, Han F, Yin L, Zhang L, Yang Y, Zhang J. Diagnostic performance of prediction models for extraprostatic extension in prostate cancer: a systematic review and meta-analysis. Insights Imaging 2023; 14:140. [PMID: 37606802 PMCID: PMC10444717 DOI: 10.1186/s13244-023-01486-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 07/19/2023] [Indexed: 08/23/2023] Open
Abstract
PURPOSE In recent decades, diverse nomograms have been proposed to predict extraprostatic extension (EPE) in prostate cancer (PCa). We aimed to systematically evaluate the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting EPE in PCa. The purpose of this meta-analysis is to provide baseline summative and comparative estimates for future study designs. MATERIALS AND METHODS The PubMed, Embase, and Cochrane databases were searched up to May 17, 2023, to identify studies on prediction nomograms for EPE of PCa. The risk of bias in studies was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Summary estimates of sensitivity and specificity were obtained with bivariate random-effects model. Heterogeneity was investigated through meta-regression and subgroup analysis. RESULTS Forty-eight studies with a total of 57 contingency tables and 20,395 patients were included. No significant publication bias was observed for either the MRI-inclusive nomograms or clinical nomograms. For MRI-inclusive nomograms predicting EPE, the pooled AUC of validation cohorts was 0.80 (95% CI: 0.76, 0.83). For traditional clinical nomograms predicting EPE, the pooled AUCs of the Partin table and Memorial Sloan Kettering Cancer Center (MSKCC) nomogram were 0.72 (95% CI: 0.68, 0.76) and 0.79 (95% CI: 0.75, 0.82), respectively. CONCLUSION Preoperative risk stratification is essential for PCa patients; both MRI-inclusive nomograms and traditional clinical nomograms had moderate diagnostic performance for predicting EPE in PCa. This study provides baseline comparative values for EPE prediction for future studies which is useful for evaluating preoperative risk stratification in PCa patients. CRITICAL RELEVANCE STATEMENT This meta-analysis firstly evaluated the diagnostic performance of preoperative MRI-inclusive nomograms and clinical nomograms for predicting extraprostatic extension (EPE) in prostate cancer (PCa) (moderate AUCs: 0.72-0.80). We provide baseline estimates for EPE prediction, these findings will be useful in assessing preoperative risk stratification of PCa patients. KEY POINTS • MRI-inclusive nomograms and traditional clinical nomograms had moderate AUCs (0.72-0.80) for predicting EPE. • MRI combined clinical nomogram may improve diagnostic accuracy of MRI alone for EPE prediction. • MSKCC nomogram had a higher specificity than Partin table for predicting EPE. • This meta-analysis provided baseline and comparative estimates of nomograms for EPE prediction for future studies.
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Affiliation(s)
- MeiLin Zhu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - JiaHao Gao
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Fang Han
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - LongLin Yin
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - LuShun Zhang
- Department of Pathology and Pathophysiology, Chengdu Medical College, Development and Regeneration Key Laboratory of Sichuan Province, Chengdu, 610500, China
| | - Yong Yang
- School of Big Health & Intelligent Engineering, Chengdu Medical College, Chengdu, 610500, China.
| | - JiaWen Zhang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China.
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Calimano-Ramirez LF, Virarkar MK, Hernandez M, Ozdemir S, Kumar S, Gopireddy DR, Lall C, Balaji KC, Mete M, Gumus KZ. MRI-based nomograms and radiomics in presurgical prediction of extraprostatic extension in prostate cancer: a systematic review. Abdom Radiol (NY) 2023; 48:2379-2400. [PMID: 37142824 DOI: 10.1007/s00261-023-03924-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/13/2023] [Accepted: 04/18/2023] [Indexed: 05/06/2023]
Abstract
PURPOSE Prediction of extraprostatic extension (EPE) is essential for accurate surgical planning in prostate cancer (PCa). Radiomics based on magnetic resonance imaging (MRI) has shown potential to predict EPE. We aimed to evaluate studies proposing MRI-based nomograms and radiomics for EPE prediction and assess the quality of current radiomics literature. METHODS We used PubMed, EMBASE, and SCOPUS databases to find related articles using synonyms for MRI radiomics and nomograms to predict EPE. Two co-authors scored the quality of radiomics literature using the Radiomics Quality Score (RQS). Inter-rater agreement was measured using the intraclass correlation coefficient (ICC) from total RQS scores. We analyzed the characteristic s of the studies and used ANOVAs to associate the area under the curve (AUC) to sample size, clinical and imaging variables, and RQS scores. RESULTS We identified 33 studies-22 nomograms and 11 radiomics analyses. The mean AUC for nomogram articles was 0.783, and no significant associations were found between AUC and sample size, clinical variables, or number of imaging variables. For radiomics articles, there were significant associations between number of lesions and AUC (p < 0.013). The average RQS total score was 15.91/36 (44%). Through the radiomics operation, segmentation of region-of-interest, selection of features, and model building resulted in a broader range of results. The qualities the studies lacked most were phantom tests for scanner variabilities, temporal variability, external validation datasets, prospective designs, cost-effectiveness analysis, and open science. CONCLUSION Utilizing MRI-based radiomics to predict EPE in PCa patients demonstrates promising outcomes. However, quality improvement and standardization of radiomics workflow are needed.
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Affiliation(s)
- Luis F Calimano-Ramirez
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Mayur K Virarkar
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Mauricio Hernandez
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Savas Ozdemir
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Sindhu Kumar
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Dheeraj R Gopireddy
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - Chandana Lall
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA
| | - K C Balaji
- Department of Urology, University of Florida College of Medicine, Jacksonville, FL, 32209, USA
| | - Mutlu Mete
- Department of Computer Science and Information System, Texas A&M University-Commerce, Commerce, TX, 75428, USA
| | - Kazim Z Gumus
- Department of Radiology, University of Florida College of Medicine Jacksonville, Jacksonville, FL, 32209, USA.
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Kwong JCC, Khondker A, Meng E, Taylor N, Kuk C, Perlis N, Kulkarni GS, Hamilton RJ, Fleshner NE, Finelli A, van der Kwast TH, Ali A, Jamal M, Papanikolaou F, Short T, Srigley JR, Colinet V, Peltier A, Diamand R, Lefebvre Y, Mandoorah Q, Sanchez-Salas R, Macek P, Cathelineau X, Eklund M, Johnson AEW, Feifer A, Zlotta AR. Development, multi-institutional external validation, and algorithmic audit of an artificial intelligence-based Side-specific Extra-Prostatic Extension Risk Assessment tool (SEPERA) for patients undergoing radical prostatectomy: a retrospective cohort study. Lancet Digit Health 2023; 5:e435-e445. [PMID: 37211455 DOI: 10.1016/s2589-7500(23)00067-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 02/11/2023] [Accepted: 03/22/2023] [Indexed: 05/23/2023]
Abstract
BACKGROUND Accurate prediction of side-specific extraprostatic extension (ssEPE) is essential for performing nerve-sparing surgery to mitigate treatment-related side-effects such as impotence and incontinence in patients with localised prostate cancer. Artificial intelligence (AI) might provide robust and personalised ssEPE predictions to better inform nerve-sparing strategy during radical prostatectomy. We aimed to develop, externally validate, and perform an algorithmic audit of an AI-based Side-specific Extra-Prostatic Extension Risk Assessment tool (SEPERA). METHODS Each prostatic lobe was treated as an individual case such that each patient contributed two cases to the overall cohort. SEPERA was trained on 1022 cases from a community hospital network (Trillium Health Partners; Mississauga, ON, Canada) between 2010 and 2020. Subsequently, SEPERA was externally validated on 3914 cases across three academic centres: Princess Margaret Cancer Centre (Toronto, ON, Canada) from 2008 to 2020; L'Institut Mutualiste Montsouris (Paris, France) from 2010 to 2020; and Jules Bordet Institute (Brussels, Belgium) from 2015 to 2020. Model performance was characterised by area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), calibration, and net benefit. SEPERA was compared against contemporary nomograms (ie, Sayyid nomogram, Soeterik nomogram [non-MRI and MRI]), as well as a separate logistic regression model using the same variables included in SEPERA. An algorithmic audit was performed to assess model bias and identify common patient characteristics among predictive errors. FINDINGS Overall, 2468 patients comprising 4936 cases (ie, prostatic lobes) were included in this study. SEPERA was well calibrated and had the best performance across all validation cohorts (pooled AUROC of 0·77 [95% CI 0·75-0·78] and pooled AUPRC of 0·61 [0·58-0·63]). In patients with pathological ssEPE despite benign ipsilateral biopsies, SEPERA correctly predicted ssEPE in 72 (68%) of 106 cases compared with the other models (47 [44%] in the logistic regression model, none in the Sayyid model, 13 [12%] in the Soeterik non-MRI model, and five [5%] in the Soeterik MRI model). SEPERA had higher net benefit than the other models to predict ssEPE, enabling more patients to safely undergo nerve-sparing. In the algorithmic audit, no evidence of model bias was observed, with no significant difference in AUROC when stratified by race, biopsy year, age, biopsy type (systematic only vs systematic and MRI-targeted biopsy), biopsy location (academic vs community), and D'Amico risk group. According to the audit, the most common errors were false positives, particularly for older patients with high-risk disease. No aggressive tumours (ie, grade >2 or high-risk disease) were found among false negatives. INTERPRETATION We demonstrated the accuracy, safety, and generalisability of using SEPERA to personalise nerve-sparing approaches during radical prostatectomy. FUNDING None.
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Affiliation(s)
- Jethro C C Kwong
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON, Canada
| | - Adree Khondker
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Eric Meng
- Faculty of Medicine, Queen's University, Kingston, ON, Canada
| | - Nicholas Taylor
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Cynthia Kuk
- Division of Urology, Department of Surgery, Mount Sinai Hospital, Sinai Health System, Toronto, ON, Canada
| | - Nathan Perlis
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Girish S Kulkarni
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON, Canada
| | - Robert J Hamilton
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Neil E Fleshner
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Antonio Finelli
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Theodorus H van der Kwast
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada; Laboratory Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Amna Ali
- Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada
| | - Munir Jamal
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Frank Papanikolaou
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Thomas Short
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - John R Srigley
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Valentin Colinet
- Division of Urology, Department of Surgery, Jules Bordet Institute, Brussels, Belgium
| | - Alexandre Peltier
- Division of Urology, Department of Surgery, Jules Bordet Institute, Brussels, Belgium
| | - Romain Diamand
- Division of Urology, Department of Surgery, Jules Bordet Institute, Brussels, Belgium
| | - Yolene Lefebvre
- Department of Medical Imagery, Jules Bordet Institute, Brussels, Belgium
| | - Qusay Mandoorah
- Division of Urology, Department of Surgery, L'Institut Mutualiste Montsouris, Paris, France
| | - Rafael Sanchez-Salas
- Division of Urology, Department of Surgery, L'Institut Mutualiste Montsouris, Paris, France
| | - Petr Macek
- Division of Urology, Department of Surgery, L'Institut Mutualiste Montsouris, Paris, France
| | - Xavier Cathelineau
- Division of Urology, Department of Surgery, L'Institut Mutualiste Montsouris, Paris, France
| | - Martin Eklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Alistair E W Johnson
- Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON, Canada; Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Vector Institute, Toronto, ON, Canada
| | - Andrew Feifer
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Institute for Better Health, Trillium Health Partners, Mississauga, ON, Canada
| | - Alexandre R Zlotta
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada; Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Division of Urology, Department of Surgery, Mount Sinai Hospital, Sinai Health System, Toronto, ON, Canada.
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A side-specific nomogram for extraprostatic extension may reduce the positive surgical margin rate in radical prostatectomy. World J Urol 2022; 40:2919-2924. [DOI: 10.1007/s00345-022-04191-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 10/08/2022] [Indexed: 11/09/2022] Open
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Gatti M, Faletti R, Gentile F, Soncin E, Calleris G, Fornari A, Oderda M, Serafini A, Strazzarino GA, Vissio E, Bergamasco L, Cirillo S, Papotti MG, Gontero P, Fonio P. mEPE-score: a comprehensive grading system for predicting pathologic extraprostatic extension of prostate cancer at multiparametric magnetic resonance imaging. Eur Radiol 2022; 32:4942-4953. [PMID: 35290508 PMCID: PMC9213375 DOI: 10.1007/s00330-022-08595-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 01/18/2022] [Accepted: 01/20/2022] [Indexed: 11/24/2022]
Abstract
Objective To investigate the diagnostic accuracy of the PI-RADS v2.1 multiparametric magnetic resonance imaging (mpMRI) features in predicting extraprostatic extension (mEPE) of prostate cancer (PCa), as well as to develop and validate a comprehensive mpMRI-derived score (mEPE-score). Methods We retrospectively reviewed all consecutive patients admitted to two institutions for radical prostatectomy for PCa with available records of mpMRI performed between January 2015 and December 2020. Data from one institution was used for investigating diagnostic performance of each mEPE feature using radical prostatectomy specimens as benchmark. The results were implemented in a mEPE-score as follows: no mEPE features: 1; capsular abutment: 2; irregular or spiculated margin: 3; bulging prostatic contour, or asymmetry of the neurovascular bundles, or tumor-capsule interface > 1.0 cm: 4; ≥ 2 of the previous three parameters or measurable extraprostatic disease: 5. The performance of mEPE features was evaluated using the five diagnostic parameters and ROC curve analysis. Results Two-hundred patients were enrolled at site 1 and 76 at site 2. mEPE features had poor sensitivities ranging from 0.08 (0.00–0.15) to 0.71 (0.59–0.83), whereas specificity ranged from 0.68 (0.58–0.79) to 1.00. mEPE-score showed excellent discriminating ability (AUC > 0.8) and sensitivity = 0.82 and specificity = 0.77 with a threshold of 3. mEPE-score had AUC comparable to ESUR-score (p = 0.59 internal validation; p = 0.82 external validation), higher than or comparable to mEPE-grade (p = 0.04 internal validation; p = 0.58 external validation), and higher than early-and-late-EPE (p < 0.0001 internal and external validation). There were no significant differences between readers having different expertise with EPE-score (p = 0.32) or mEPE-grade (p = 0.45), but there were significant differences for ESUR-score (p = 0.02) and early-versus-late-EPE (p = 0.03). Conclusions The individual mEPE features have low sensitivity and high specificity. The use of mEPE-score allows for consistent and reliable assessment for pathologic EPE. Key Points • Individual PI-RADS v2.1 mpMRI features had poor sensitivities ranging from 0.08 (0.00–0.15) to 0.71 (0.59–0.83), whereas Sp ranged from 0.68 (0.58–0.79) to 1.00. • mEPE-score is an all-inclusive score for the assessment of pEPE with excellent discriminating ability (i.e., AUC > 0.8) and Se = 0.82, Sp = 0.77, PPV = 0.74, and NPV = 0.84 with a threshold of 3. • The diagnostic performance of the expert reader and beginner reader with pEPE-score was comparable (p = 0.32). Supplementary Information The online version contains supplementary material available at 10.1007/s00330-022-08595-9.
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Affiliation(s)
- Marco Gatti
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy.
| | - Riccardo Faletti
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | - Francesco Gentile
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | - Enrico Soncin
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | - Giorgio Calleris
- Urology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Alberto Fornari
- Radiology Unit, Mauriziano Umberto I Hospital, 10128, Turin, Italy
| | - Marco Oderda
- Urology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Alessandro Serafini
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
| | | | - Elena Vissio
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Laura Bergamasco
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Stefano Cirillo
- Radiology Unit, Mauriziano Umberto I Hospital, 10128, Turin, Italy
| | - Mauro Giulio Papotti
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Paolo Gontero
- Urology Unit, Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Paolo Fonio
- Department of Surgical Sciences, Radiology Unit, University of Turin, Via Genova 3, 10126, Turin, Italy
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Wibmer AG, Nikolovski I, Chaim J, Lakhman Y, Lefkowitz RA, Sala E, Carlsson SV, Fine SW, Kattan MW, Hricak H, Vargas HA. Local Extent of Prostate Cancer at MRI versus Prostatectomy Histopathology: Associations with Long-term Oncologic Outcomes. Radiology 2021; 302:595-602. [PMID: 34931855 PMCID: PMC8893181 DOI: 10.1148/radiol.210875] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background It is unknown how the imperfect accuracy of MRI for local staging of prostate cancer relates to oncologic outcomes. Purpose To analyze how staging discordances between MRI and histopathologic evaluation relate to recurrence and survival after radical prostatectomy. Materials and Methods Health Insurance Portability and Accountability Act-compliant retrospective analysis of preprostatectomy T2-weighted prostate MRI (January 2001 to December 2006). Extraprostatic extension and seminal vesicle invasion were assessed by using five-point Likert scales; scores of 4 or higher were classified as positive. Biochemical recurrence (BCR), metastases, and prostate cancer-specific mortality rates were estimated with Kaplan-Meier and Cox models. Results A total of 2160 patients (median age, 60 years; interquartile range, 55-64 years) were evaluated. Among patients with histopathologic extraprostatic (pT3) disease (683 of 2160; 32%), those with organ-confined disease at MRI (384 of 683; 56%) experienced better outcomes than those with concordant extraprostatic disease at MRI and pathologic analysis: 15-year risk for BCR, 30% (95% CI: 22, 40) versus 68% (95% CI: 60, 75); risk for metastases, 14% (95% CI: 8.4, 24) versus 32% (95% CI: 26, 39); risk for prostate cancer-specific mortality, 3% (95% CI: 1, 6) versus 15% (95% CI: 9.5, 23) (P < .001 for all comparisons). Among patients with histopathologic organ-confined disease (pT2) (1477 of 2160; 68%), those with extraprostatic disease at MRI (102 of 1477; 7%) were at higher risk for BCR (27% [95% CI: 19, 37] vs 10% [95% CI: 8, 14]; P < .001), metastases (19% [95% CI: 6, 48] vs 3% [95% CI: 1, 6]; P < .001), and prostate cancer-specific mortality (2% [95% CI: 1, 9] vs 1% [95% CI: 0, 5]; P = .009) than those with concordant organ-confined disease at MRI and pathologic analysis. At multivariable analyses, tumor extent at MRI (hazard ratio range, 4.1-5.2) and histopathologic evaluation (hazard ratio range, 3.6-6.7) was associated with the risk for BCR, metastases, and prostate cancer-specific mortality (P < .001 for all analyses). Conclusion The local extent of prostate cancer at MRI is associated with oncologic outcomes after prostatectomy, independent of pathologic tumor stage. This might inform a strategy on how to integrate MRI into a clinical staging algorithm. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Gottlieb in this issue.
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Prostate Magnetic Resonance Imaging Analyses, Clinical Parameters, and Preoperative Nomograms in the Prediction of Extraprostatic Extension. Clin Pract 2021; 11:763-774. [PMID: 34698089 PMCID: PMC8544353 DOI: 10.3390/clinpract11040091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 08/27/2021] [Accepted: 09/30/2021] [Indexed: 11/25/2022] Open
Abstract
Introduction: Proper planning of laparoscopic radical prostatectomy (RP) in patients with prostate cancer (PCa) is crucial to achieving good oncological results with the possibility of preserving potency and continence. Aim: The aim of this study was to identify the radiological and clinical parameters that can predict the risk of extraprostatic extension (EPE) for a specific site of the prostate. Predictive models and multiparametric magnetic resonance imaging (mpMRI) data from patients qualified for RP were compared. Material and methods: The study included 61 patients who underwent laparoscopic RP. mpMRI preceded transrectal systematic and cognitive fusion biopsy. Martini, Memorial Sloan-Kettering Cancer Center (MSKCC), and Partin Tables nomograms were used to assess the risk of EPE. The area under the curve (AUC) was calculated for the models and compared. Univariate and multivariate logistic regression analyses were used to determine the combination of variables that best predicted EPE risk based on final histopathology. Results: The combination of mpMRI indicating or suspecting EPE (odds ratio (OR) = 7.49 (2.31–24.27), p < 0.001) and PSA ≥ 20 ng/mL (OR = 12.06 (1.1–132.15), p = 0.04) best predicted the risk of EPE for a specific side of the prostate. For the prediction of ipsilateral EPE risk, the AUC for Martini’s nomogram vs. mpMRI was 0.73 (p < 0.001) vs. 0.63 (p = 0.005), respectively (p = 0.131). The assessment of a non-specific site of EPE by MSKCC vs. Partin Tables showed AUC values of 0.71 (p = 0.007) vs. 0.63 (p = 0.074), respectively (p = 0.211). Conclusions: The combined use of mpMRI, the results of the systematic and targeted biopsy, and prostate-specific antigen baseline can effectively predict ipsilateral EPE (pT3 stage).
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