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Cheng X, Chen Y, Xu H, Ye L, Tong S, Li H, Zhang T, Tian S, Qi J, Zeng H, Yao J, Song B. Avoiding Unnecessary Systematic Biopsy in Clinically Significant Prostate Cancer: Comparison Between MRI-Based Radiomics Model and PI-RADS Category. J Magn Reson Imaging 2023; 57:578-586. [PMID: 35852438 DOI: 10.1002/jmri.28333] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 06/15/2022] [Accepted: 06/16/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND MRI-targeted biopsy (MRTB) improves the clinically significant prostate cancer (csPCa) detection rate with fewer biopsy cores in men with suspected PCa. However, whether concurrent systematic biopsy (SB) can be avoided in patients undergoing MRTB remains unclear. PURPOSE To evaluate the potential value of MRI-based radiomics models in avoiding unnecessary SB in biopsy-naïve patients. STUDY TYPE Retrospective. POPULATION A total of 226 patients (mean age 66.6 ± 9.02 years) with suspicion of PCa (PI-RADS score ≥ 3) and received combined cognitive MRTB with SB were retrospectively recruited and randomly divided into training (N = 180) and test (N = 46) cohorts at an 8:2 ratio. FIELD STRENGTH/SEQUENCE A 3.0 T, biparametric MRI (bpMRI) including T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) map. ASSESSMENT The whole prostate gland (PG) and the index lesion (IL) were delineated. Three radiomics models of bpMRIPG , bpMRIIL , and bpMRIPG+IL were constructed, respectively, and the performance of each radiomics model was compared with that of PI-RADS assessment. STATISTICAL TESTS The least absolute shrinkage and selection operator (LASSO) regression method was used to select texture features. The area under the curve (AUC) and decision curve analysis were used to estimate the models. RESULTS The bpMRIPG+IL radiomics model exhibited good discrimination, calibration, and net benefits, which would reduce the SB biopsy in 71.2% and 71.4% of men with PI-RADS ≥ 5 lesions in the training and test cohorts, respectively. DATA CONCLUSION A bpMRIPG+IL radiomics model may outperform PI-RADS category in help reducing unnecessary SB in biopsy-naïve patients. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Xueqing Cheng
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuntian Chen
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Hui Xu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Lei Ye
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Shun Tong
- SICE, University of Electronic Science and Technology of China, China
| | | | | | | | - Jin Qi
- SICE, University of Electronic Science and Technology of China, China
| | - Hao Zeng
- Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Jin Yao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, Sanya People's Hospital (West China Sanya Hospital of Sichuan University), China
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Temporal changes of PIRADS scoring by radiologists and correlation to radical prostatectomy pathological outcomes. Prostate Int 2022; 10:188-193. [PMID: 36570646 PMCID: PMC9747593 DOI: 10.1016/j.prnil.2022.07.001] [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: 05/26/2022] [Revised: 07/05/2022] [Accepted: 07/12/2022] [Indexed: 12/27/2022] Open
Abstract
Purpose To assess temporal improvement of prostate image reporting and data system (PIRADS) 3-5 lesion correlation to histopathologic findings from radical prostatectomy (RP) in prostate cancer (PCa). Materials and methods A total of 1481 patients who underwent RP for biopsy-proven PCa between 2015 and 2019 were divided into 14 groups of 100 sequential readings for the evaluation of histopathological correlation with PIRADS readings. Temporal trends of PIRADS distribution and predictive performance for RP pathology were evaluated to assess underlying changes in prostate magnetic resonance imaging (MRI) interpretation by radiologists. Results PIRADS 4-5 lesions were significantly correlated with the increasing rates of Gleason Group (GG) upgrade (p = 0.044) and decreasing rate of GG downgrade (p = 0.016) over time. PIRADS ≥3 lesions read after median 2 years of experience were shown to independently predict intermediate-high-risk (GG ≥ 3) PCa (odds ratio 2.93, 95% confidence interval 1.00-8.54; P= 0.049) in RP pathology. Preoperative GG ≥ 3 biopsy lesions with PIRADS 4-5 lesions were significantly more susceptible to GG upgrade (P= 0.035) and GG ≥ 4 RP pathology (p = 0.003) in experienced reads, in contrast to insignificant findings in early readings (p = 0.588 and 0.248, respectively). Conclusion Preoperative MRI reports matched with RP pathology suggest an improved prediction of adverse pathology in PIRADS 3-5 lesions over time, suggesting a temporal change in PIRADS interpretation and predictive accuracy. Institutions with low volume experience should use caution in solely relying on MRI for predicting tumor characteristics. Future prospective trials and larger scale assessments are required to further validate our results.
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A clinical available decision support scheme for optimizing prostate biopsy based on mpMRI. Prostate Cancer Prostatic Dis 2022; 25:727-734. [PMID: 35067674 DOI: 10.1038/s41391-021-00489-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 12/11/2021] [Accepted: 12/16/2021] [Indexed: 01/14/2023]
Abstract
BACKGROUND Combined MRI/Ultrasound fusion targeted biopsy (TBx) and systematic biopsy (SBx) results in better prostate cancer (PCa) detection relative to either TBx or SBx alone, while at the cost of higher number of biopsy cores and greater detection of clinically insignificant PCa. We therefore developed and evaluated a simple decision support scheme for optimizing prostate biopsy based on multiparametric (mp) MRI assessment. METHODS Total 229 patients with suspicion of PCa underwent mpMRI before combined TBx/SBx were retrospectively included. Impacts of MRI characteristics such as Prostate Imaging-Reporting and Data System (PI-RADS) score, lesion size, zonal origination, and location on biopsy performance were evaluated. A clinically available decision support scheme relying on mpMRI assessment was subsequently developed as a triage test to optimize prostate biopsy process. Cost (downgrade, upgrade, and biopsy core)-to-Effectiveness (detection rate) was systemically compared. RESULTS TBx achieved comparable detection rate to combined TBx/SBx in diagnosis of PCa and clinically significant PCa (csPCa) (PCa, 59% [135/229] vs 60.7% [139/229]; csPCa, 45.9% [105/229] vs 47.2% [108/229]; p-values > 0.05) and outperformed SBx (PCa, 42.4% [97/229]; csPCa, 28.4% [65/229]; p-values < 0.001). Specially, in personalized decision support scheme, TBx accurately detected all PCa (72.5% [74/102]) in PI-RADS 5 and larger (≥1 cm) PI-RADS 3-4 observations, adding SBx to TBx only resulted in 1.4% (1/74) upgrading csPCa. For smaller (<1 cm) PI-RADS 3-4 lesions, combined TBx/SBx resulted in relatively higher detection rate (51.2% [65/127] vs 48.0% [61/127]) and lower upgrading rate (30.6% [15/49] vs 36.7% [18/49]) than TBx. CONCLUSIONS The benefit of SBx added to TBx was largely restricted to smaller PI-RADS score 3-4 lesions. Using our personalized strategy of solo TBx for PI-RADS 5 and larger (≥1 cm) PI-RADS score 3-4 lesions would avoid excess SBx in 44.5% (102/229) of all biopsy-naïve patients without compromising detection rate.
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Bhattacharya I, Khandwala YS, Vesal S, Shao W, Yang Q, Soerensen SJ, Fan RE, Ghanouni P, Kunder CA, Brooks JD, Hu Y, Rusu M, Sonn GA. A review of artificial intelligence in prostate cancer detection on imaging. Ther Adv Urol 2022; 14:17562872221128791. [PMID: 36249889 PMCID: PMC9554123 DOI: 10.1177/17562872221128791] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 08/30/2022] [Indexed: 11/07/2022] Open
Abstract
A multitude of studies have explored the role of artificial intelligence (AI) in providing diagnostic support to radiologists, pathologists, and urologists in prostate cancer detection, risk-stratification, and management. This review provides a comprehensive overview of relevant literature regarding the use of AI models in (1) detecting prostate cancer on radiology images (magnetic resonance and ultrasound imaging), (2) detecting prostate cancer on histopathology images of prostate biopsy tissue, and (3) assisting in supporting tasks for prostate cancer detection (prostate gland segmentation, MRI-histopathology registration, MRI-ultrasound registration). We discuss both the potential of these AI models to assist in the clinical workflow of prostate cancer diagnosis, as well as the current limitations including variability in training data sets, algorithms, and evaluation criteria. We also discuss ongoing challenges and what is needed to bridge the gap between academic research on AI for prostate cancer and commercial solutions that improve routine clinical care.
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Affiliation(s)
- Indrani Bhattacharya
- Department of Radiology, Stanford University School of Medicine, 1201 Welch Road, Stanford, CA 94305, USA
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Yash S. Khandwala
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Sulaiman Vesal
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Wei Shao
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Qianye Yang
- Centre for Medical Image Computing, University College London, London, UK
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Simon J.C. Soerensen
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Richard E. Fan
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Pejman Ghanouni
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Christian A. Kunder
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - James D. Brooks
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Yipeng Hu
- Centre for Medical Image Computing, University College London, London, UK
- Wellcome / EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK
| | - Mirabela Rusu
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Geoffrey A. Sonn
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
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MRI-Targeted Prostate Biopsy Techniques: AJR Expert Panel Narrative Review. AJR Am J Roentgenol 2021; 217:1263-1281. [PMID: 34259038 DOI: 10.2214/ajr.21.26154] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Prostate cancer is the second most common malignancy in men worldwide. Systematic transrectal prostate biopsy is commonly used to obtain tissue to establish the diagnosis. However, in recent years, MRI-targeted biopsy (based on an MRI examination performed prior to consideration of biopsy) has been shown to detect more clinically significant cancer and less clinically insignificant cancer compared to systematic biopsy. This approach of performing MRI prior to biopsy has become, or is becoming, a standard of practice in centers throughout the world. This growing use of an MRI-directed pathway is leading to performance of a larger volume of MRI-targeted prostate biopsies. The three common MRI-targeted biopsy techniques are cognitive biopsy, MRI-ultrasound software fusion biopsy, and MRI in-bore guided biopsy. These techniques for using MRI information at the time of biopsy can be performed via a transrectal or transperineal approach. This narrative review presents the three MRI-targeted biopsy techniques along with their advantages and shortcomings. Comparisons among the techniques are summarized based on the available evidence. Studies to date have provided heterogeneous results, and the preferred technique remains debated.
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Wang LL, Henslee BL, Sam PB, LaGrange CA, Boyle SL. Optimal PSA Threshold for Obtaining MRI-Fusion Biopsy in Biopsy-Naïve Patients. Prostate Cancer 2021; 2021:5531511. [PMID: 34306761 PMCID: PMC8266472 DOI: 10.1155/2021/5531511] [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: 02/21/2021] [Accepted: 06/14/2021] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE The study investigates the prostate-specific antigen threshold for adding targeted, software-based, magnetic resonance imaging-ultrasound fusion biopsy during a standard 12-core biopsy in biopsy-naïve patients. It secondarily explores whether the targeted biopsy is necessary in setting of abnormal digital rectal examination. METHODS 260 patients with suspected localized prostate cancer with no prior biopsy underwent prostate magnetic resonance imaging and were found to have Prostate Imaging Reporting and Data System score ≥ 3 lesion(s). All 260 patients underwent standard 12-core biopsy and targeted biopsy during the same session. Clinically significant cancer was Gleason ≥3 + 4. RESULTS Percentages of patients with prostate-specific antigen 0-1.99, 2-3.99, 4-4.99, 5-5.99, 6-9.99, and ≥10 were 3.0%, 4.7%, 20.8%, 16.9%, 37.7%, and 16.9%, respectively. Cumulative frequency of clinically significant prostate cancer increased with the addition of targeted biopsy compared with standard biopsy alone across all prostate-specific antigen ranges. The difference in clinically significant cancer detection between targeted plus standard biopsy compared to standard biopsy alone becomes statistically significant at prostate-specific antigen >4.3 (p=0.031). At this threshold, combination biopsy detected 20 clinically significant prostate cancers, while standard detected 14 with 88% sensitivity and 20% specificity. Excluding targeted biopsy in setting of a positive digital rectal exam would save 12.3% magnetic resonance imaging and miss 1.8% clinically significant cancers in our cohort. CONCLUSIONS In biopsy-naïve patients, at prostate-specific antigen >4.3, there is a significant increase in clinically significant prostate cancer detection when targeted biopsy is added to standard biopsy. Obtaining standard biopsy alone in patients with abnormal digital rectal examinations would miss 1.8% clinically significant cancers in our cohort.
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Affiliation(s)
- Luke L. Wang
- Division of Urology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Brandon L. Henslee
- Division of Urologic Surgery, University of Missouri School of Medicine, Columbia, MO 65212, USA
| | - Peter B. Sam
- Division of Urology, University of New Mexico School of Medicine, Albuquerque, NM 87106, USA
| | - Chad A. LaGrange
- Division of Urology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Shawna L. Boyle
- Division of Urology, University of Nebraska Medical Center, Omaha, NE 68198, USA
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Tosun M, Uslu H. Prebiopsy multiparametric MRI and PI-RADS version 2.0 for differentiating histologically benign prostate disease from prostate cancer in biopsies: A retrospective single-center comparison. Clin Imaging 2021; 78:98-103. [PMID: 33773450 DOI: 10.1016/j.clinimag.2021.03.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 02/24/2021] [Accepted: 03/18/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To investigate the diagnostic performance of Prostate Imaging-Reporting and Data System version 2.0 (PI-RADSv2.0) for differentiating clinically significant prostate cancer (csPCa) from benign prostate disease on prebiopsy multiparametric MRI stratified by total prostate specific antigen (PSA) concentration. MATERIALS AND METHODS 150 patients who had prebiopsy mpMRI, serum PSA concentration and subsequent biopsy were retrospectively analyzed. Patients were stratified by PSA concentration (Group1 ≥ 10 ng/mL; Group2 4.0-<10 ng/mL). MRI findings were assessed using PI-RADSv2.0 by two blinded radiologists. Lesions were graded histopathologically using the International Society of Urological Pathology (ISUP) score. Diagnostic performance of PI-RADSv2.0 was evaluated and compared to PSA and PSA Density (PSAD). The performance of the radiologists was compared including inter-observer agreement for PI-RADSv2.0. The correlation between imaging and histopathological biopsy results was analyzed. RESULTS The differences in total PSA, free/total PSA ratio and PSAD between benign (n = 78) and malignant (n = 72) groups were significant (p < 0.05). The PI-RADSv2.0 scores of the radiologists were strongly correlated (r = 0.912, p < 0.001) with excellent agreement, κ = 0.97 (95%CI: 0.90-1.03; p < 0.005). Receiver operating characteristics curve analysis showed significantly high predictive power for PI-RADSv2.0, total PSA and PSAD alone. Comparison of age, prostate volume, PSAD, free/total PSA ratio and total PSA values between ISUP1 and ISUP ≥ 2 cases revealed significantly increased PSAD (p < 0.001) and total PSA (p = 0.001) in the ISUP ≥ 2 group. CONCLUSION PI-RADSv2.0 had high diagnostic accuracy in both PSA groups. PI-RADSv2.0, PSAD and total PSA alone had significant high predictive power to detect csPCa. However, the combination of PI-RADSv2.0 and PSAD or total PSA for each reader showed no statistically significant improvement when compared to PI-RADSv2.0 alone.
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Affiliation(s)
- Mesude Tosun
- Department of Radiology, Kocaeli University Hospital, Kocaeli, Turkey.
| | - Hande Uslu
- Department of Radiology, Kocaeli University Hospital, Kocaeli, Turkey
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Rahman IA, Nusaly IF, Syahrir S, Nusaly H, Kasim F. Optimizing biopsy strategy for prostate cancer: Bayesian framework of network meta-analysis and hierarchical summary receiver operating characteristic model for diagnostic accuracy. INDIAN JOURNAL OF UROLOGY : IJU : JOURNAL OF THE UROLOGICAL SOCIETY OF INDIA 2021; 37:20-31. [PMID: 33850352 PMCID: PMC8033239 DOI: 10.4103/iju.iju_187_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 07/24/2020] [Accepted: 10/12/2020] [Indexed: 12/09/2022]
Abstract
Overdiagnosis and overtreatment are well known problems in prostate cancer (PCa). The transrectal ultrasound (TRUS) Guided biopsy (GB) as a current gold standard investigation has a low positive detection rate resulting in unnecessary biopsies. The choice of optimal biopsy strategy needs to be defined. Therefore, we undertook a Bayesian network meta analysis (NMA) and Bayesian prediction in the hierarchical summary receiver operating characteristic (HSROC) model to present a method for optimizing biopsy strategy in PCa. Twenty eight relevant studies were retrieved through online databases of EMBASE, MEDLINE, and CENTRAL up to February 2020. Markov chain Monte Carlo simulation and Surface Under the Cumulative RAnking curve were used to calculate the rank probability using odds ratio with 95% credible interval. HSROC model was used to formulate the predicted true sensitivity and specificity of each biopsy strategy. Six different PCa biopsy strategies including transrectal ultrasound GB (TRUS GB), fusion GB (FUS GB), fusion + transrectal ultrasound GB (FUS + TRUS GB), magnetic resonance imaging GB (MRI GB), transperineal ultrasound GB (TPUS GB), and contrast enhanced ultrasound GB were analyzed in this study with a total of 7584 patients. These strategies were analyzed on five outcomes including detection rate of overall PCa, clinically significant PCa, insignificant PCa, complication rate, and HSROC. The rank probability showed that the overall PCa detection rate was higher in FUS + TRUS GB, MRI GB, and FUS GB. In terms of clinically significant PCa detection, FUS + TRUS GB and FUS GB had a relatively higher clinically significant PCa detection rate, whereas TRUS GB had a relatively lower rate for clinically significant PCa detection rate. MRI GB (91% and 81%) and FUS GB (82% and 83%) had the highest predicted true sensitivity and specificity, respectively, whereas TRUS GB (62% and 83%) had a lower predicted true sensitivity and specificity. MRI GB, FUS GB, and FUS + TRUS GB were associated with lower complication rate, whereas TPUS GB and TRUS GB were more associated with higher complication rate. This NMA and HSROC model highlight the important finding that FUS + TRUS GB, FUS GB, and MRI GB were superior compared with other strategies to avoid the overdiagnosis and overtreatment of PCa. FUS GB, MRI GB, and FUS + TRUS GB had lower complication rates. These results may assist in shared decision making between patients, carers, and their surgeons.
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Affiliation(s)
- Ilham Akbar Rahman
- Department of Urology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
| | - Ilham Fauzan Nusaly
- Department of Urology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
| | - Syakri Syahrir
- Department of Urology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
| | - Harry Nusaly
- Department of Urology, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
| | - Firdaus Kasim
- Department of Public Health, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
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Mazzone E, Stabile A, Pellegrino F, Basile G, Cignoli D, Cirulli GO, Sorce G, Barletta F, Scuderi S, Bravi CA, Cucchiara V, Fossati N, Gandaglia G, Montorsi F, Briganti A. Positive Predictive Value of Prostate Imaging Reporting and Data System Version 2 for the Detection of Clinically Significant Prostate Cancer: A Systematic Review and Meta-analysis. Eur Urol Oncol 2020; 4:697-713. [PMID: 33358543 DOI: 10.1016/j.euo.2020.12.004] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 11/26/2020] [Accepted: 12/08/2020] [Indexed: 11/18/2022]
Abstract
CONTEXT The variability of the positive predictive value (PPV) represents a significant factor affecting the diagnostic performance of multiparametric magnetic resonance imaging (mpMRI). OBJECTIVE To analyze published studies reporting mpMRI PPV and the reasons behind the variability of clinically significant prostate cancer (csPCa) detection rates on targeted biopsies (TBx) according to Prostate Imaging Reporting and Data System (PI-RADS) version 2 categories. EVIDENCE ACQUISITION A search of PubMed, Cochrane library's Central, EMBASE, MEDLINE, and Scopus databases, from January 2015 to June 2020, was conducted. The primary and secondary outcomes were to evaluate the PPV of PI-RADS version 2 in detecting csPCa and any prostate cancer (PCa), respectively. Individual authors' definitions for csPCa and PI-RADS thresholds for positive mpMRI were accepted. Detection rates, used as a surrogate of PPV, were pooled using random-effect models. Preplanned subgroup analyses tested PPV after stratification for PI-RADS scores, previous biopsy status, TBx technique, and number of sampled cores. PPV variation over cancer prevalence was evaluated. EVIDENCE SYNTHESIS Fifty-six studies, with a total of 16 537 participants, were included in the quantitative synthesis. The PPV of suspicious mpMRI for csPCa was 40% (95% confidence interval 36-43%), with large heterogeneity between studies (I2 94%, p < 0.01). PPV increased according to PCa prevalence. In subgroup analyses, PPVs for csPCa were 13%, 40%, and 69% for, respectively, PI-RADS 3, 4, and 5 (p < 0.001). TBx missed 6%, 6%, and 5% of csPCa in PI-RADS 3, 4, and 5 lesions, respectively. In biopsy-naïve and prior negative biopsy groups, PPVs for csPCa were 42% and 32%, respectively (p = 0.005). Study design, TBx technique, and number of sampled cores did not affect PPV. CONCLUSIONS Our meta-analysis underlines that the PPV of mpMRI is strongly dependent on the disease prevalence, and that the main factors affecting PPV are PI-RADS version 2 scores and prior biopsy status. A substantially low PPV for PI-RADS 3 lesions was reported, while it was still suboptimal in PI-RADS 4 and 5 lesions. Lastly, even if the added value of a systematic biopsy for csPCa is relatively low, this rate can improve patient risk assessment and staging. PATIENT SUMMARY Targeted biopsy of Prostate Imaging Reporting and Data System 3 lesions should be considered carefully in light of additional individual risk assessment corroborating the presence of clinically significant prostate cancer. On the contrary, the positive predictive value of highly suspicious lesions is not high enough to omit systematic prostate sampling.
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Affiliation(s)
- Elio Mazzone
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy.
| | - Armando Stabile
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Francesco Pellegrino
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Giuseppe Basile
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Daniele Cignoli
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Giuseppe Ottone Cirulli
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Gabriele Sorce
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Francesco Barletta
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Simone Scuderi
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Carlo Andrea Bravi
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Vito Cucchiara
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Nicola Fossati
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Giorgio Gandaglia
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Francesco Montorsi
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Alberto Briganti
- Division of Oncology/Unit of Urology, URI, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
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Detection of prostate cancer using prostate imaging reporting and data system score and prostate-specific antigen density in biopsy-naive and prior biopsy-negative patients. Prostate Int 2020; 8:125-129. [PMID: 33102394 PMCID: PMC7557180 DOI: 10.1016/j.prnil.2020.03.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 02/23/2020] [Accepted: 03/08/2020] [Indexed: 01/27/2023] Open
Abstract
Background Few studies report on indications for prostate biopsy using Prostate Imaging–Reporting and Data System (PI-RADS) score and prostate-specific antigen density (PSAD). No study to date has included biopsy-naïve and prior biopsy-negative patients. Therefore, we evaluated the predictive values of the PI-RADS, version 2 (v2) score combined with PSAD to decrease unnecessary biopsies in biopsy-naïve and prior biopsy-negative patients. Materials and methods A total of 1,098 patients who underwent multiparametric magnetic resonance imaging at our hospital before a prostate biopsy and who underwent their second prostate biopsy with an initial benign negative prostatic biopsy were included. We found factors associated with clinically significant prostate cancer (csPca). We assessed negative predictive values by stratifying biopsy outcomes by prior biopsy history and PI-RADS score combined with PSAD. Results The median age was 65 years (interquartile range: 59-70), and the median PSA was 5.1 ng/mL (interquartile range: 3.8-7.1). Multivariate logistic regression analysis revealed that age, prostate volume, PSAD, and PI-RADS score were independent predictors of csPca. In a biopsy-naïve group, 4% with PI-RADS score 1 or 2 had csPca; in a prior biopsy-negative group, 3% with PI-RADS score 1 or 2 had csPca. The csPca detection rate was 2.0% for PSA density <0.15 ng/mL/mL and 4.0% for PSA density 0.15-0.3 ng/mL/mL among patients with PI-RADS score 3 in a biopsy-naïve group. The csPca detection rate was 1.8% for PSA density <0.15 ng/mL/mL and 0.15-0.3 ng/mL/mL among patients with PI-RADS score 3 in a prior biopsy-negative group. Conclusion Patients with PI-RADS v2 score ≤2, regardless of PSA density, may avoid unnecessary biopsy. Patients with PI-RADS score 3 may avoid unnecessary biopsy through PSA density results.
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Karsiyakali N, Ozgen MB, Ozveren B, Akbal C, Dincer A, Durak H, Turkeri L. Suboptimal Prediction of Clinically Significant Prostate Cancer in Radical Prostatectomy Specimens by mpMRI-Targeted Biopsy. Urology 2020; 148:217-223. [PMID: 32871139 DOI: 10.1016/j.urology.2020.08.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 08/10/2020] [Accepted: 08/17/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVE To investigate the correlation of multiparametric magnetic resonance imaging targeted (TBx) and/or systematic prostate biopsy (SBx) in predicting the presence of clinically significant (cs) prostate cancer (PCa) in radical prostatectomy (RP) specimens. Concordance of mpMRI and RP specimen lesions was also investigated in terms of tumor localization and histopathological features. METHODS A total of 70 male patients with PCa and treated with robot-assisted RP were included in this study between January 2016 and December 2019. All patients underwent mpMRI-TBx and concomitant SBx. Suspicious lesions on mpMRI were scored according to Prostate Imaging-Reporting and Data System version 2 (PI-RADS) criteria. TBx was performed for all suspicious lesions with a PI-RADS score ≥3. RESULTS The median age was 67 (43-77) years. Presence of csPCa in prostatectomy specimens was missed by TBx and SBx specimens in 25.4% and 19.4% of the cases, respectively (P<.001, for each). Combination of both biopsy (CBx) results improved detection by missing only 4.5% of csPCa (P = .250). International Society of Urologic Pathology grade group concordance with RP specimens were 50%, 54.3% and 67.1% for SBx, TBx, and CBx, respectively. There was a statistically significant correlation in terms of tumor localization and histopathological features between prostatectomy specimens and the first 3 lesions, particularly for the index lesions. CONCLUSIONS CBx improved detection rate of csPCa. We propose TBx of 3 lesions with highest PI-RADS score(s) and a combination with SBx for the highest correlation with prostatectomy histopathology.
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Affiliation(s)
- Nejdet Karsiyakali
- Department of Urology, Acibadem M.A. Aydinlar University, Altunizade Hospital, Istanbul, Turkey.
| | - Mahir Bulent Ozgen
- Department of Urology, Acibadem M.A. Aydinlar University, Altunizade Hospital, Istanbul, Turkey
| | - Bora Ozveren
- Department of Urology, Acibadem M.A. Aydinlar University, School of Medicine, Altunizade Hospital, Istanbul, Turkey
| | - Cem Akbal
- Department of Urology, Acibadem M.A. Aydinlar University, School of Medicine, Altunizade Hospital, Istanbul, Turkey
| | - Alp Dincer
- Department of Radiology, Acibadem M.A. Aydinlar University, School of Medicine, Altunizade Hospital, Istanbul, Turkey
| | - Haydar Durak
- Clinical Pathology Laboratory, Acibadem M.A. Aydinlar University, Altunizade Hospital, Istanbul, Turkey
| | - Levent Turkeri
- Department of Urology, Acibadem M.A. Aydinlar University, Altunizade Hospital, Istanbul, Turkey
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Accuracy of Sampling PI-RADS 4–5 Index Lesions Alone by MRI-guided In-bore Biopsy in Biopsy–naive Patients Undergoing Radical Prostatectomy. Eur Urol Focus 2020; 6:249-254. [DOI: 10.1016/j.euf.2019.04.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 04/02/2019] [Accepted: 04/06/2019] [Indexed: 12/22/2022]
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