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van den Kroonenberg DL, Jager A, Garrido-Utrilla A, Reitsma JB, Postema AW, Beerlage HP, Oddens JR. Clinical Validation of Multiparametric Ultrasound for Detecting Clinically Significant Prostate Cancer Using Computer-Aided Diagnosis: A Direct Comparison with the Magnetic Resonance Imaging Pathway. EUR UROL SUPPL 2024; 66:60-66. [PMID: 39050912 PMCID: PMC11267110 DOI: 10.1016/j.euros.2024.06.012] [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] [Accepted: 06/19/2024] [Indexed: 07/27/2024] Open
Abstract
We present the protocol for a study testing the hypothesis that a computer-aided diagnosis (CAD) system for three-dimensional multiparametric ultrasound (3D mpUS) is noninferior to magnetic resonance imaging (MRI) in guiding prostate biopsies for detection of clinically significant prostate cancer (csPCa). The prospective study has a fully paired design for assessment of diagnostic accuracy and is registered on ClinicalTrials.gov as NCT06281769. A total of 438 biopsy-naïve men scheduled for prostate MRI evaluation because of an abnormal digital rectal examination and/or elevated serum prostate-specific antigen will be included. All patients will undergo both MRI (multiparametric or biparametric) and 3D mpUS with CAD (PCaVision). Suspicious lesions will be independently identified using each imaging technique. MRI targeted biopsy (TBx) and/or PCaVision TBx will be performed if suspicious lesions are identified on imaging. When both PCaVision and MRI identify lesions in an individual patient, the TBx order for this patient will be randomized. Three TBx samples per lesion will be taken for a maximum of two lesions per modality. The primary objective is the detection rate for csPCa (International Society of Urological Pathology grade group [GG] ≥2) with the PCaVision versus the MRI TBx pathway. The noninferiority margin for the absolute difference in detection rates is set at a difference of 5%. Secondary outcomes are the proportion of men in whom TBx could have been safely omitted in each pathway. Additional diagnostic accuracy analyses will be performed for different definitions of PCa (GG ≥3; GG ≥2 with cribriform growth and/or intraductal carcinoma; and GG 1). The frequency of insufficient image quality for the two pathways will also be assessed. Lastly, we will determine the diagnostic performance for csPCa detection at various 3D mpUS image quality thresholds for PCaVision.
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Affiliation(s)
| | - Auke Jager
- Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands
| | | | - Johannes B. Reitsma
- Julius Center for Health Sciences and Primary Care, UMC Utrecht, Utrecht, The Netherlands
| | - Arnoud W. Postema
- Department of Urology, Leids Universitair Medisch Centrum, Leiden, The Netherlands
| | | | - Jorg R. Oddens
- Department of Urology, Amsterdam UMC, Amsterdam, The Netherlands
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Kluckert J, Hötker AM, Da Mutten R, Konukoglu E, Donati OF. AI-based automated evaluation of image quality and protocol tailoring in patients undergoing MRI for suspected prostate cancer. Eur J Radiol 2024; 177:111581. [PMID: 38925042 DOI: 10.1016/j.ejrad.2024.111581] [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: 04/12/2024] [Revised: 06/08/2024] [Accepted: 06/16/2024] [Indexed: 06/28/2024]
Abstract
PURPOSE To develop and validate an artificial intelligence (AI) application in a clinical setting to decide whether dynamic contrast-enhanced (DCE) sequences are necessary in multiparametric prostate MRI. METHODS This study was approved by the institutional review board and requirement for study-specific informed consent was waived. A mobile app was developed to integrate AI-based image quality analysis into clinical workflow. An expert radiologist provided reference decisions. Diagnostic performance parameters (sensitivity and specificity) were calculated and inter-reader agreement was evaluated. RESULTS Fully automated evaluation was possible in 87% of cases, with the application reaching a sensitivity of 80% and a specificity of 100% in selecting patients for multiparametric MRI. In 2% of patients, the application falsely decided on omitting DCE. With a technician reaching a sensitivity of 29% and specificity of 98%, and resident radiologists reaching sensitivity of 29% and specificity of 93%, the use of the application allowed a significant increase in sensitivity. CONCLUSION The presented AI application accurately decides on a patient-specific MRI protocol based on image quality analysis, potentially allowing omission of DCE in the diagnostic workup of patients with suspected prostate cancer. This could streamline workflow and optimize time utilization of healthcare professionals.
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Affiliation(s)
- Jonas Kluckert
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland.
| | - Andreas M Hötker
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland
| | - Raffaele Da Mutten
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland
| | - Ender Konukoglu
- Computer Vision Laboratory, Department of Information Technology and Electrical Engineering, ETH Zurich, Sternwartstrasse 7, 8092 Zurich, Switzerland
| | - Olivio F Donati
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, 8091 Zurich, Switzerland; Radiology Octorad / Hirslanden, Witellikerstrasse 40, 8032 Zurich, Switzerland
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Bertelli E, Vizzi M, Marzi C, Pastacaldi S, Cinelli A, Legato M, Ruzga R, Bardazzi F, Valoriani V, Loverre F, Impagliazzo F, Cozzi D, Nardoni S, Facchiano D, Serni S, Masieri L, Minervini A, Agostini S, Miele V. Biparametric vs. Multiparametric MRI in the Detection of Cancer in Transperineal Targeted-Biopsy-Proven Peripheral Prostate Cancer Lesions Classified as PI-RADS Score 3 or 3+1: The Added Value of ADC Quantification. Diagnostics (Basel) 2024; 14:1608. [PMID: 39125483 PMCID: PMC11312064 DOI: 10.3390/diagnostics14151608] [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: 05/31/2024] [Revised: 07/21/2024] [Accepted: 07/25/2024] [Indexed: 08/12/2024] Open
Abstract
BACKGROUND Biparametric MRI (bpMRI) has an important role in the diagnosis of prostate cancer (PCa), by reducing the cost and duration of the procedure and adverse reactions. We assess the additional benefit of the ADC map in detecting prostate cancer (PCa). Additionally, we examine whether the ADC value correlates with the presence of clinically significant tumors (csPCa). METHODS 104 peripheral lesions classified as PI-RADS v2.1 score 3 or 3+1 at the mpMRI underwent transperineal MRI/US fusion-guided targeted biopsy. RESULTS The lesions were classified as PI-RADS 3 or 3+1; at histopathology, 30 were adenocarcinomas, 21 of which were classified as csPCa. The ADC threshold that maximized the Youden index in order to predict the presence of a tumor was 1103 (95% CI (990, 1243)), with a sensitivity of 0.8 and a specificity of 0.59; both values were greater than those found using the contrast medium, which were 0.5 and 0.54, respectively. Similar results were also found with csPCa, where the optimal ADC threshold was 1096 (95% CI (988, 1096)), with a sensitivity of 0.86 and specificity of 0.59, compared to 0.49 and 0.59 observed in the mpMRI. CONCLUSIONS Our study confirms the possible use of a quantitative parameter (ADC value) in the risk stratification of csPCa, by reducing the number of biopsies and, therefore, the number of unwarranted diagnoses of PCa and the risk of overtreatment.
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Affiliation(s)
- Elena Bertelli
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Michele Vizzi
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Chiara Marzi
- Department of Statistics, Informatics and Applications “G. Parenti” (DiSIA), University of Florence, 50134 Florence, Italy;
| | - Sandro Pastacaldi
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Alberto Cinelli
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Martina Legato
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Ron Ruzga
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Federico Bardazzi
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Vittoria Valoriani
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Francesco Loverre
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Francesco Impagliazzo
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Diletta Cozzi
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Samuele Nardoni
- Unit of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital, University of Florence, 50134 Florence, Italy; (S.N.); (D.F.); (S.S.); (L.M.)
| | - Davide Facchiano
- Unit of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital, University of Florence, 50134 Florence, Italy; (S.N.); (D.F.); (S.S.); (L.M.)
| | - Sergio Serni
- Unit of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital, University of Florence, 50134 Florence, Italy; (S.N.); (D.F.); (S.S.); (L.M.)
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy;
| | - Lorenzo Masieri
- Unit of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital, University of Florence, 50134 Florence, Italy; (S.N.); (D.F.); (S.S.); (L.M.)
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy;
| | - Andrea Minervini
- Department of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy;
- Unit of Oncologic Minimally-Invasive Urology and Andrology, Careggi Hospital, 50134 Florence, Italy
| | - Simone Agostini
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
| | - Vittorio Miele
- Department of Radiology, Careggi University Hospital, 50134 Florence, Italy; (M.V.); (S.P.); (A.C.); (M.L.); (R.R.); (F.B.); (V.V.); (F.L.); (F.I.); (D.C.); (S.A.); (V.M.)
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Abramson M, DeMasi M, Zhu D, Hines L, Lin W, Kanmaniraja D, Chernyak V, Agalliu I, Watts KL. Biparametric versus multiparametric MRI for the detection of clinically significant prostate cancer in a diverse, multiethnic population. Abdom Radiol (NY) 2024; 49:2491-2498. [PMID: 38839651 PMCID: PMC11286685 DOI: 10.1007/s00261-024-04332-6] [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: 08/17/2023] [Revised: 04/04/2024] [Accepted: 04/05/2024] [Indexed: 06/07/2024]
Abstract
PURPOSE There is not yet satisfactory performance data comparing multiparametric MRI (mpMRI) versus biparametric MRI (bpMRI) for detecting prostate cancer (PCa), particularly in high-risk populations. We compared both protocols for detecting overall PCa and clinically significant PCa (CS-PCa; defined as Grade Group ≥ 2) in a multiethnic urban population. METHODS We retrospectively reviewed electronic medical record data from men who underwent image-guided fusion prostate biopsy (FB) between 2016 and 2021 at our institution. Patient characteristics, Prostate Imaging Reporting and Data System (PI-RADS) scores, and FB outcomes were analyzed based on MRI protocol. Multivariate mixed-effects logistic regression models were used to examine associations of bpMRI versus mpMRI for detecting overall PCa and CS-PCa in targeted lesions, among all patients and stratified by race/ethnicity. RESULTS Overall, 566 men (44.0% Non-Hispanic Black [NHB]; 27.0% Hispanic) with 975 PI-RADS 3-5 lesions on MRI underwent FB. Of these, 312 (55%) men with 497 lesions underwent mpMRI and 254 (45%) men with 478 lesions underwent bpMRI. On multivariate analyses among all men, the odds of detecting overall PCa (OR = 1.18, 95% CI: 1.05-3.11, p = 0.031) and CS-PCa (OR = 2.15, 95% CI: 1.16-4.00, p = 0.014) on FB were higher for lesions identified on bpMRI than mpMRI. When stratified by race/ethnicity, the odds of detecting overall PCa (OR = 1.86; p = 0.15) and CS-PCa (OR = 2.20; p = 0.06) were not statistically different between lesions detected on bpMRI or mpMRI. CONCLUSION BpMRI has similar diagnostic performance to mpMRI in detecting overall and CS-PCa within a racially/ethnically diverse population. BpMRI can be utilized for evaluating suspected CS-PCa among NHB and Hispanic men.
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Affiliation(s)
- Max Abramson
- Albert Einstein College of Medicine, Bronx, NY, USA
| | - Matthew DeMasi
- Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Denzel Zhu
- Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Urology, University of Rochester Medical Center, Rochester, NY, USA
| | - Laena Hines
- Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Urology, University of Rochester Medical Center, Rochester, NY, USA
| | - Wilson Lin
- Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Urology, New York University Langone Health, New York, NY, USA
| | | | - Victoria Chernyak
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Radiology, Montefiore Medical Center, Bronx, NY, USA
| | - Ilir Agalliu
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Urology, Montefiore Medical Center, Bronx, NY, USA
| | - Kara L Watts
- Albert Einstein College of Medicine, Bronx, NY, USA.
- Department of Urology, Montefiore Medical Center, Bronx, NY, USA.
- Department of Urology, Montefiore Medical Center, Albert Einstein College of Medicine, 1250 Waters Place, Tower 1; Penthouse, Bronx, NY, 10461, USA.
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Cheng Y, Zhang L, Wu X, Zou Y, Niu Y, Wang L. Impact of prostate MRI image quality on diagnostic performance for clinically significant prostate cancer (csPCa). Abdom Radiol (NY) 2024:10.1007/s00261-024-04458-7. [PMID: 38935093 DOI: 10.1007/s00261-024-04458-7] [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: 04/23/2024] [Revised: 06/14/2024] [Accepted: 06/15/2024] [Indexed: 06/28/2024]
Abstract
OBJECTIVES With the widespread clinical application of prostate magnetic resonance imaging (MRI), there has been an increasing demand for lesion detection and accurate diagnosis in prostate MR, which relies heavily on satisfactory image quality. Focusing on the primary sequences involved in Prostate Imaging Reporting and Data System (PI-RADS), this study have evaluated common quality issues in clinical practice (such as signal-to-noise ratio (SNR), artifacts, boundaries, and enhancement). The aim of the study was to determine the impact of image quality on clinically significant prostate cancer (csPCa) detection, positive predictive value (PPV) and radiologist's diagnosis in different sequences and prostate zones. METHODS This retrospective study included 306 patients who underwent prostate MRI with definitive pathological reports from February 2021 to December 2022. All histopathological specimens were evaluated according to the recommendations of the International Society of Urological Pathology (ISUP). An ISUP Grade Group ≥ 2 was considered as csPCa. Three radiologists from different centers respectively performed a binary classification assessment of image quality in the following ten aspects: (1) T2WI in the axial plane: SNR, prostate boundary conditions, the presence of artifacts; (2) T2WI in the sagittal or coronal plane: prostate boundary conditions; (3) DWI: SNR, delineation between the peripheral and transition zone, the presence of artifacts, the matching of DWI and T2WI images; (4) DCE: the evaluation of obturator artery enhancement, the evaluation of dynamic contrast enhancement. Fleiss' Kappa was used to determine the inter-reader agreement. Wilson's 95% confidence interval (95% CI) was used to calculate PPV. Chi-square test was used to calculate statistical significance. A p-value < 0.05 was considered statistically significant. RESULTS High-quality images had a higher csPCa detection rate (56.5% to 64.3%) in axial T2WI, DWI, and DCE, with significant statistical differences in SNR in axial T2WI (p 0.002), the presence of artifacts in axial T2WI (p 0.044), the presence of artifacts in DWI (p < 0.001), and the matching of DWI and T2WI images (p < 0.001). High-quality images had a higher PPV (72.5% to 78.8%) and showed significant statistical significance in axial T2WI, DWI, and DCE. Additionally, we found that PI-RADS 3 (24.0% to 52.9%) contained more low-quality images compared to PI-RADS 4-5 (20.6% to 39.3%), with significant statistical differences in the prostate boundary conditions in axial T2WI (p 0.048) and the presence of artifacts in DWI (p 0.001). Regarding the relationship between csPCa detection and image quality in different prostate zones, this study found that significant statistical differences were only observed between high- (63.5% to 75.7%) and low-quality (30.0% to 50.0%) images in the peripheral zone (PZ). CONCLUSION Prostate MRI quality may have an impact on the diagnostic performance. The poorer image quality is associated with lower csPCa detection rates and PPV, which can lead to an increase in radiologist's ambiguous diagnosis (PI-RADS 3), especially for the lesions located at PZ.
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Affiliation(s)
- Yue Cheng
- Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, 36 Yong'an Rd, Xicheng District, Beijing, 100016, China
| | - Lei Zhang
- Department of Radiology, The Second People's Hospital of Baoshan, Yunnan, China
| | - Xiaohui Wu
- Department of Radiology, Hailar People's Hospital, Hulunbuir City, Inner Mongolia, China
| | - Yi Zou
- Department of Radiology, Hubei University of Science and Technology Affiliated Chibi's Hospital, Hubei, China
| | - Yao Niu
- Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, 36 Yong'an Rd, Xicheng District, Beijing, 100016, China
| | - Liang Wang
- Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, 36 Yong'an Rd, Xicheng District, Beijing, 100016, China.
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Guo E, Xu L, Zhang D, Zhang J, Zhang X, Bai X, Chen L, Peng Q, Zhang G, Jin Z, Sun H. Diagnostic performance of MRI in detecting prostate cancer in patients with prostate-specific antigen levels of 4-10 ng/mL: a systematic review and meta-analysis. Insights Imaging 2024; 15:147. [PMID: 38886256 PMCID: PMC11183000 DOI: 10.1186/s13244-024-01699-4] [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: 12/18/2023] [Accepted: 04/15/2024] [Indexed: 06/20/2024] Open
Abstract
OBJECTIVE To investigate the diagnostic performance of MRI in detecting clinically significant prostate cancer (csPCa) and prostate cancer (PCa) in patients with prostate-specific antigen (PSA) levels of 4-10 ng/mL. METHODS A computerized search of PubMed, Embase, Cochrane Library, Medline, and Web of Science was conducted from inception until October 31, 2023. We included articles on the use of MRI to detect csPCa or PCa at 4-10 ng/mL PSA. The primary and secondary outcomes were MRI performance in csPCa and PCa detection, respectively; the estimates of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were pooled in a bivariate random-effects model. RESULTS Among the 19 studies (3879 patients), there were 10 (2205 patients) and 13 studies (2965 patients) that reported MRI for detecting csPCa or PCa, respectively. The pooled sensitivity and specificity for csPCa detection were 0.84 (95% confidence interval [CI], 0.79-0.88) and 0.76 (95%CI, 0.65-0.84), respectively, for PCa detection were 0.82 (95%CI, 0.75-0.87) and 0.74 (95%CI, 0.65-0.82), respectively. The pooled NPV for csPCa detection was 0.91 (0.87-0.93). Biparametric magnetic resonance imaging also showed a significantly higher sensitivity and specificity relative to multiparametric magnetic resonance imaging (both p < 0.01). CONCLUSION Prostate MRI enables the detection of csPCa and PCa with satisfactory performance in the PSA gray zone. The excellent NPV for csPCa detection indicates the possibility of biopsy decision-making in patients in the PSA gray zone, but substantial heterogeneity among the included studies should be taken into account. CLINICAL RELEVANCE STATEMENT Prostate MRI can be considered a reliable and satisfactory tool for detecting csPCa and PCa in patients with PSA in the "gray zone", allowing for reducing unnecessary biopsy and optimizing the overall examination process. KEY POINTS Prostate-specific antigen (PSA) is a common screening tool for prostate cancer but risks overdiagnosis. MRI demonstrated excellent negative predictive value for prostate cancer in the PSA gray zone. MRI can influence decision-making for these patients, and biparametric MRI should be further evaluated.
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Affiliation(s)
- Erjia Guo
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Lili Xu
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Daming Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Jiahui Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Xiaoxiao Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Xin Bai
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Li Chen
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Qianyu Peng
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China
| | - Gumuyang Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
| | - Zhengyu Jin
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
- National Center for Quality Control of Radiology, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
| | - Hao Sun
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
- National Center for Quality Control of Radiology, Shuaifuyuan No.1, Wangfujing Street, Dongcheng District, Beijing, 100730, China.
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Zhao L, Bao J, Wang X, Qiao X, Shen J, Zhang Y, Jin P, Ji Y, Zhang J, Su Y, Ji L, Li Z, Lu J, Hu C, Shen H, Tian J, Liu J. Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study. J Magn Reson Imaging 2024; 59:2101-2112. [PMID: 37602942 DOI: 10.1002/jmri.28963] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 08/02/2023] [Accepted: 08/02/2023] [Indexed: 08/22/2023] Open
Abstract
BACKGROUND Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP presence. PURPOSE To develop deep learning models for detecting AP presence, and to compare the performance of these models with those of a clinical model (CM) and radiologists' interpretation (RI). STUDY TYPE Retrospective. POPULATION Totally, 616 men from six institutions who underwent radical prostatectomy, were divided into a training cohort (508 patients from five institutions) and an external validation cohort (108 patients from one institution). FIELD STRENGTH/SEQUENCES T2-weighted imaging with a turbo spin echo sequence and diffusion-weighted imaging with a single-shot echo plane-imaging sequence at 3.0 T. ASSESSMENT The reference standard for AP was histopathological extracapsular extension, seminal vesicle invasion, or positive surgical margins. A deep learning model based on the Swin-Transformer network (TransNet) was developed for detecting AP. An integrated model was also developed, which combined TransNet signature with clinical characteristics (TransCL). The clinical characteristics included biopsy Gleason grade group, Prostate Imaging Reporting and Data System scores, prostate-specific antigen, ADC value, and the lesion maximum cross-sectional diameter. STATISTICAL TESTS Model and radiologists' performance were assessed using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The Delong test was used to evaluate difference in AUC. P < 0.05 was considered significant. RESULTS The AUC of TransCL for detecting AP presence was 0.813 (95% CI, 0.726-0.882), which was higher than that of TransNet (0.791 [95% CI, 0.702-0.863], P = 0.429), and significantly higher than those of CM (0.749 [95% CI, 0.656-0.827]) and RI (0.664 [95% CI, 0.566-0.752]). DATA CONCLUSION TransNet and TransCL have potential to aid in detecting the presence of AP and some single adverse pathologic features. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY: Stage 4.
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Affiliation(s)
- Litao Zhao
- School of Engineering Medicine, Beihang University, Beijing, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, China
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Jie Bao
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Ximing Wang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Xiaomeng Qiao
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Junkang Shen
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yueyue Zhang
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Pengfei Jin
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yanting Ji
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
- Department of Radiology, The Affiliated Zhangjiagang Hospital of Soochow University, Zhangjiagang, China
| | - Ji Zhang
- Department of Radiology, The People's Hospital of Taizhou, Taizhou, China
| | - Yueting Su
- Department of Radiology, The People's Hospital of Taizhou, Taizhou, China
| | - Libiao Ji
- Department of Radiology, Changshu No.1 People's Hospital, Changshu, China
| | - Zhenkai Li
- Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, China
| | - Jian Lu
- Department of Urology, Peking University Third Hospital, Beijing, China
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hailin Shen
- Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, China
| | - Jie Tian
- School of Engineering Medicine, Beihang University, Beijing, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, China
| | - Jiangang Liu
- School of Engineering Medicine, Beihang University, Beijing, China
- Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, China
- Beijing Engineering Research Center of Cardiovascular Wisdom Diagnosis and Treatment, Beijing, China
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8
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Tomioka M, Nakane K, Kawase M, Iinuma K, Kato D, Kawase K, Taniguchi T, Tobisawa Y, Sugino F, Kaga T, Kato H, Matsuo M, Kito Y, Saigo C, Suzui N, Ito T, Miyazaki T, Takeuchi T, Koie T. Discrepancy in the Location of Prostate Cancer Indicated on Biparametric Magnetic Resonance Imaging and Pathologically Diagnosed Using Surgical Specimens. Curr Oncol 2024; 31:2846-2855. [PMID: 38785497 PMCID: PMC11119495 DOI: 10.3390/curroncol31050216] [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: 04/19/2024] [Revised: 05/09/2024] [Accepted: 05/14/2024] [Indexed: 05/25/2024] Open
Abstract
Accurate diagnosis of the localization of prostate cancer (PCa) on magnetic resonance imaging (MRI) remains a challenge. We aimed to assess discrepancy between the location of PCa pathologically diagnosed using surgical specimens and lesions indicated as possible PCa by the Prostate Imaging Reporting and Data System on MRI. The primary endpoint was the concordance rate between the site of probable clinically significant PCa (csPCa) identified using biparametric MRI (bpMRI) and location of PCa in the surgical specimen obtained using robot-assisted total prostatectomy. Among 85 lesions identified in 30 patients; 42 (49.4%) were identified as possible PCa on MRI. The 85 PCa lesions were divided into positive and negative groups based on the bpMRI results. None of the patients had missed csPCa. Although the diagnostic accuracy of bpMRI was relatively high for PCas located in the middle of the prostate (p = 0.029), it was relatively low for PCa located at the base of the prostate, all of which were csPCas. Although current modalities can accurately diagnose PCa, the possibility that PCa is present with multiple lesions in the prostate should be considered, even if MRI does not detect PCa.
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Affiliation(s)
- Masayuki Tomioka
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Keita Nakane
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Makoto Kawase
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Koji Iinuma
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Daiki Kato
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Kota Kawase
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Tomoki Taniguchi
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Yuki Tobisawa
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
| | - Fumiya Sugino
- Department of Urology, Gifu Municipal Hospital, Gifu 5008513, Japan;
| | - Tetsuro Kaga
- Department of Radiology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (T.K.); (H.K.); (M.M.)
| | - Hiroki Kato
- Department of Radiology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (T.K.); (H.K.); (M.M.)
| | - Masayuki Matsuo
- Department of Radiology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (T.K.); (H.K.); (M.M.)
| | - Yusuke Kito
- Department of Pathology and Translational Research, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (Y.K.); (C.S.); (T.T.)
| | - Chiemi Saigo
- Department of Pathology and Translational Research, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (Y.K.); (C.S.); (T.T.)
| | - Natsuko Suzui
- Department of Pathology, Gifu University Hospital, Gifu 5011194, Japan; (N.S.); (T.M.)
| | - Takayasu Ito
- Center for Clinical Training and Career Development, Gifu University Graduate School of Medicine, Gifu 5011194, Japan;
| | - Tatsuhiko Miyazaki
- Department of Pathology, Gifu University Hospital, Gifu 5011194, Japan; (N.S.); (T.M.)
| | - Tamotsu Takeuchi
- Department of Pathology and Translational Research, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (Y.K.); (C.S.); (T.T.)
| | - Takuya Koie
- Department of Urology, Gifu University Graduate School of Medicine, Gifu 5011194, Japan; (M.T.); (K.N.); (M.K.); (K.I.); (D.K.); (K.K.); (T.T.); (Y.T.)
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9
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Guo W, Li M. Clinical efficacy of different androgen deprivation therapies for prostate cancer and evaluation based on dynamic-contrast enhanced magnetic resonance imaging. Acta Biochim Pol 2024; 71:12473. [PMID: 38812492 PMCID: PMC11133609 DOI: 10.3389/abp.2024.12473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 04/12/2024] [Indexed: 05/31/2024]
Abstract
Objective To evaluate the clinical efficacy of different androgen deprivation therapies for prostate cancer (PCa) based on dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI). Methods 104 patients with PCa were studied, all of whom were treated with androgen deprivation therapy. The patients were divided into a continuous group (continuous androgen deprivation therapy) and an intermittent group (intermittent androgen deprivation therapy) by random number table method, 52 cases/group. The therapeutic effect and DCE-MRI indices were compared and the relationship between DCE-MRI indices and clinical efficacy and the evaluation value of therapeutic efficacy were analyzed. Results The objective response rate (ORR) of the intermittent group was higher than that of the continuous group (p < 0.05), and there was no significant difference in disease control rate (DCR) between the two groups (p > 0.05). After treatment, volume transfer coefficient (Ktrans), reverse transfer constant (Kep), volume fraction (Ve), blood volume (BV), and blood flow (BF) in both groups were lowered, and those in the intermittent group were lower than the continuous group (p < 0.05). Ktrans, Kep, Ve, BF, and BV in the ORR group were lower than those in the non-ORR group (p < 0.05). Ktrans, Kep, Ve, BF, and BV were correlated with the therapeutic effect of PCa (p < 0.05). The AUC value of the combined detection of DCE-MRI indices in evaluating the therapeutic effect of PCa was greater than that of each index alone (p < 0.05). Conclusion Compared with continuous androgen deprivation therapy, intermittent androgen deprivation therapy has better clinical efficacy in the treatment of PCa, and DCE-MRI indices are related to the treatment efficacy of PCa and have an evaluation value.
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Affiliation(s)
| | - MengZhu Li
- Department of Radiology, Wuhan Fourth Hospital, Wuhan, Hubei, China
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10
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Mayer R, Turkbey B, Simone CB. Autonomous Tumor Signature Extraction Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study. Cancers (Basel) 2024; 16:1822. [PMID: 38791901 PMCID: PMC11120057 DOI: 10.3390/cancers16101822] [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: 04/22/2024] [Revised: 05/07/2024] [Accepted: 05/09/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Accurate, reliable, non-invasive assessment of patients diagnosed with prostate cancer is essential for proper disease management. Quantitative assessment of multi-parametric MRI, such as through artificial intelligence or spectral/statistical approaches, can provide a non-invasive objective determination of the prostate tumor aggressiveness without side effects or potential poor sampling from needle biopsy or overdiagnosis from prostate serum antigen measurements. To simplify and expedite prostate tumor evaluation, this study examined the efficacy of autonomously extracting tumor spectral signatures for spectral/statistical algorithms for spatially registered bi-parametric MRI. METHODS Spatially registered hypercubes were digitally constructed by resizing, translating, and cropping from the image sequences (Apparent Diffusion Coefficient (ADC), High B-value, T2) from 42 consecutive patients in the bi-parametric MRI PI-CAI dataset. Prostate cancer blobs exceeded a threshold applied to the registered set from normalizing the registered set into an image that maximizes High B-value, but minimizes the ADC and T2 images, appearing "green" in the color composite. Clinically significant blobs were selected based on size, average normalized green value, sliding window statistics within a blob, and position within the hypercube. The center of mass and maximized sliding window statistics within the blobs identified voxels associated with tumor signatures. We used correlation coefficients (R) and p-values, to evaluate the linear regression fits of the z-score and SCR (with processed covariance matrix) to tumor aggressiveness, as well as Area Under the Curves (AUC) for Receiver Operator Curves (ROC) from logistic probability fits to clinically significant prostate cancer. RESULTS The highest R (R > 0.45), AUC (>0.90), and lowest p-values (<0.01) were achieved using z-score and modified registration applied to the covariance matrix and tumor signatures selected from the "greenest" parts from the selected blob. CONCLUSIONS The first autonomous tumor signature applied to spatially registered bi-parametric MRI shows promise for determining prostate tumor aggressiveness.
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Affiliation(s)
- Rulon Mayer
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA
- OncoScore, Garrett Park, MD 20896, USA
| | - Baris Turkbey
- Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA;
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11
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Dana J, Reinhold C, Gauvin S. Is PI-RADS Ready for Biparametric Prostate MRI? AJR Am J Roentgenol 2024; 222:e2431094. [PMID: 38506541 DOI: 10.2214/ajr.24.31094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Affiliation(s)
- Jérémy Dana
- McGill University, Montréal, ON, Canada
- Augmented Intelligence & Precision Health Laboratory, McGill University Health Centre Research Institute, Montréal, ON, Canada
- Institut Hospitalo-Universitaire Strasbourg, Université de Strasbourg, Strasbourg, France
- Institut de Recherche sur les Maladies Virales et Hépatiques, Université de Strasbourg, Strasbourg, France
| | - Caroline Reinhold
- McGill University, Montréal, ON, Canada
- Augmented Intelligence & Precision Health Laboratory, McGill University Health Centre Research Institute, Montréal, ON, Canada
| | - Simon Gauvin
- McGill University, Montréal, ON, Canada
- Augmented Intelligence & Precision Health Laboratory, McGill University Health Centre Research Institute, Montréal, ON, Canada
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12
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Pan N, Shi L, He D, Zhao J, Xiong L, Ma L, Li J, Ai K, Zhao L, Huang G. Prediction of prostate cancer aggressiveness using magnetic resonance imaging radiomics: a dual-center study. Discov Oncol 2024; 15:122. [PMID: 38625419 PMCID: PMC11019191 DOI: 10.1007/s12672-024-00980-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 04/11/2024] [Indexed: 04/17/2024] Open
Abstract
PURPOSE The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa. MATERIAL AND METHODS A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic. RESULTS The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively. CONCLUSIONS MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.
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Affiliation(s)
- Nini Pan
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Liuyan Shi
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Diliang He
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Jianxin Zhao
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Lianqiu Xiong
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Lili Ma
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Jing Li
- The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, Gansu, China
| | - Kai Ai
- Clinical and Technical Support, Philips Healthcare, Xi'an, China
| | - Lianping Zhao
- Department of Radiology, Gansu Provincial Hospital, Lanzhou, 730000, Gansu, China
| | - Gang Huang
- Department of Radiology, Gansu Provincial Hospital, Lanzhou, 730000, Gansu, China.
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Sun M, Xu L, Zhang X, Cao L, Chen W, Liu K, Wu H, Xie D. PI-RADS v2.1 evaluation of prostate "nodule in nodule" variants: clinical, imaging, and pathological features. Insights Imaging 2024; 15:79. [PMID: 38499703 PMCID: PMC10948663 DOI: 10.1186/s13244-024-01651-6] [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: 12/14/2023] [Accepted: 02/10/2024] [Indexed: 03/20/2024] Open
Abstract
OBJECTIVES To analyze the correlation among the imaging features of prostate "nodule in nodule," clinical prostate indices, and pathology results. METHODS We retrospectively analyzed the prostate images from 47 male patients who underwent MRI scans and pathological biopsy from January 2022 to July 2023. Two radiologists (R1/R2) evaluated the morphology and signal intensity of the "nodule in nodule" in a double-blind manner and calculated the PI-RADS v2.1 score, which was compared with clinical prostate indices and pathological results. RESULTS 34.04% (16/47) of patients were pathologically diagnosed with clinically significant prostate cancer (csPCa). Total prostate-specific antigen (tPSA), free/t PSA, PSA density (PSAD), and prostate gland volume (PGV) were significantly different between csPCa patients and benign prostatic hyperplasia (BPH) patients with prostate "nodule in nodule". R1/R2 detected 17/17 prostate "nodule in nodule" pathologically confirmed as csPCa on MRI; 10.60% (16/151) (R1) and 11.11% (17/153) (R2) had diffusion-weighted imaging (DWI) PI-RADS v2.1 score of 4, and 0.66% (1/151) (R1) had a score of 3. The percentages of encapsulated, circumscribed, and atypical nodules and obscured margins were 0.00% (0/151), 0.00% (0/151), 5.96% (9/151), and 5.30% (8/151), respectively, for R1, and 0.00% (0/153), 0.00% (0/153), 5.88% (9/153), and 4.58% (7/153) for R2. CONCLUSION When the inner nodules of "nodule in nodule" lesions in PI-RADS v2.1 category 1 in the TZ show incomplete capsulation or obscured margins, they are considered atypical nodules and might be upgraded to PI-RADS v2.1 category 3 if they exhibit marked diffusion restriction. However, further validation is needed. CRITICAL RELEVANCE STATEMENT This study first analyzed the relationship between clinical and pathological findings and the size, margin, and multimodal MRI manifestations of the prostate "nodule in nodule." These findings could improve the diagnostic accuracy of PI-RADS v2.1 for prostate lesions. KEY POINTS • The margin of the prostate inner nodules affects the PI-RADS v2.1 score. • The morphology of prostate "nodule in nodule" is related to their pathology. • The PI-RADS v2.1 principle requires consideration of prostate "nodule in nodule" variants.
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Affiliation(s)
- MingHua Sun
- Department of Radiology, the Fuyang Hospital of Anhui Medical University, Fuyang, People's Republic of China
| | - Li Xu
- Department of Radiology, the Fuyang Hospital of Anhui Medical University, Fuyang, People's Republic of China
| | - XiaoYan Zhang
- Department of Radiology, the Fuyang Hospital of Anhui Medical University, Fuyang, People's Republic of China
| | - LiYu Cao
- Department of Pathology, the Fuyang Hospital of Anhui Medical University, Fuyang, People's Republic of China
| | - WenBao Chen
- Medical Imaging Center, The Fuyang Tumor Hospital, Fuyang, People's Republic of China
| | - Kai Liu
- Department of Radiology, the Fuyang Hospital of Anhui Medical University, Fuyang, People's Republic of China
| | - Hao Wu
- Department of Radiology, the Fuyang Hospital of Anhui Medical University, Fuyang, People's Republic of China
| | - DongDong Xie
- Department of Urology, the Fuyang Hospital of Anhui Medical University, Yingzhou District, No. 99, Mount Huangshan Road, Fuhe Modern Industrial Park, Fuyang, Anhui Province, 236000, People's Republic of China.
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14
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Li S, Ye X, Tian H, Ding Z, Cui C, Shi S, Yang Y, Li G, Chen J, Lin Z, Ni Z, Xu J, Dong F. An artificial intelligence model based on transrectal ultrasound images of biopsy needle tract tissues to differentiate prostate cancer. Postgrad Med J 2024; 100:228-236. [PMID: 38142286 DOI: 10.1093/postmj/qgad127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/25/2023] [Accepted: 11/10/2023] [Indexed: 12/25/2023]
Abstract
PURPOSE We aimed to develop an artificial intelligence (AI) model based on transrectal ultrasonography (TRUS) images of biopsy needle tract (BNT) tissues for predicting prostate cancer (PCa) and to compare the PCa diagnostic performance of the radiologist model and clinical model. METHODS A total of 1696 2D prostate TRUS images were involved from 142 patients between July 2021 and May 2022. The ResNet50 network model was utilized to train classification models with different input methods: original image (Whole model), BNT (Needle model), and combined image [Feature Pyramid Networks (FPN) model]. The training set, validation set, and test set were randomly assigned, then randomized 5-fold cross-validation between the training set and validation set was performed. The diagnostic effectiveness of AI models and image combination was accessed by an independent testing set. Then, the optimal AI model and image combination were selected to compare the diagnostic efficacy with that of senior radiologists and the clinical model. RESULTS In the test set, the area under the curve, specificity, and sensitivity of the FPN model were 0.934, 0.966, and 0.829, respectively; the diagnostic efficacy was improved compared with the Whole and Needle models, with statistically significant differences (P < 0.05), and was better than that of senior radiologists (area under the curve: 0.667). The FPN model detected more PCa compared with senior physicians (82.9% vs. 55.8%), with a 61.3% decrease in the false-positive rate and a 23.2% increase in overall accuracy (0.887 vs. 0.655). CONCLUSION The proposed FPN model can offer a new method for prostate tissue classification, improve the diagnostic performance, and may be a helpful tool to guide prostate biopsy.
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Affiliation(s)
- Shiyu Li
- Department of Ultrasound, The Second Clinical Medical College of Jinan University, China
| | - Xiuqin Ye
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Hongtian Tian
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Zhimin Ding
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Chen Cui
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Siyuan Shi
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Yang Yang
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Guoqiu Li
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Jing Chen
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Ziwei Lin
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Zhipeng Ni
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Jinfeng Xu
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
| | - Fajin Dong
- Department of Ultrasound, The Second Clinical Medical College, Jinan University, Shenzhen People's Hospital, Shenzhen, Guangdong 518020, China
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Ziayee F, Schimmöller L, Boschheidgen M, Kasprowski L, Al-Monajjed R, Quentin M, Radtke JP, Albers P, Antoch G, Ullrich T. Benefit of dynamic contrast-enhanced (DCE) imaging for prostate cancer detection depending on readers experience in prostate MRI. Clin Radiol 2024; 79:e468-e474. [PMID: 38185579 DOI: 10.1016/j.crad.2023.11.026] [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: 07/01/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024]
Abstract
AIM To investigate the relevance of dynamic contrast enhanced imaging (DCE) within multiparametric magnetic resonance imaging (mpMRI) for the detection of clinically significant prostate cancer (csPC) depending on reader experience. MATERIALS AND METHODS Consecutive patients with 3 T mpMRI and subsequent combined MRI/ultrasound fusion-guided targeted and systematic biopsy from January to September 2019 were included. All mpMRI examinations were read separately by two less experienced (R1; <500 prostate MRI) and two expert radiologists (R2; >5,000 prostate MRI) in consensus and blinded re-read as biparametric MRI (bpMRI). The primary endpoint was the performance comparison of mpMRI versus bpMRI of R1 and R2. RESULTS Fifty-three of 124 patients had csPC (43%). The PI-RADS agreement of bpMRI and mpMRI was fair for R1 (κ = 0.373) and moderate for R2 (κ = 0.508). R1 assessed 11 csPC with PI-RADS ≤3 (20.8%) on mpMRI and 12 (22.6%) on bpMRI (R2: 1 [1.9%] and 6 [11.3%], respectively). Sensitivity for csPC of mpMRI was 79.3% (NPV 79.3%) for R1 and 98.1% (NPV 97.5%) for R2 (bpMRI: 77.4% [NVP 75.5%] and 86.8% [NPV 84.4%], respectively). Specificity of mpMRI for csPC was 59.2% for R1 and 54.9% for R2 (bpMRI: 52.1% and 53.5%, respectively). Overall accuracy of mpMRI was 79.8% for R1 compared to bpMRI 66.9% (p=0.017; R2: 87.1% and 81.5%; p=0.230). CONCLUSION Prostate MRI benefits from reader experience. Less experienced readers missed a relevant proportion of csPC with mpMRI and even more with bpMRI. The overall performance of expert readers was comparable for mpMRI and bpMRI but DCE enabled detection of some further ISUP 2 PC.
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Affiliation(s)
- F Ziayee
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - L Schimmöller
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany; Department of Diagnostic, Interventional Radiology and Nuclear Medicine, Marien Hospital Herne, University Hospital of the Ruhr-University Bochum, Herne, Germany.
| | - M Boschheidgen
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - L Kasprowski
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - R Al-Monajjed
- Department of Urology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - M Quentin
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - J P Radtke
- Department of Urology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - P Albers
- Department of Urology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - G Antoch
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
| | - T Ullrich
- Department of Diagnostic and Interventional Radiology, University Dusseldorf, Medical Faculty, D-40225 Dusseldorf, Germany
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Dekker HM, Stroomberg GJ, Van der Molen AJ, Prokop M. Review of strategies to reduce the contamination of the water environment by gadolinium-based contrast agents. Insights Imaging 2024; 15:62. [PMID: 38411847 PMCID: PMC10899148 DOI: 10.1186/s13244-024-01626-7] [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: 09/14/2023] [Accepted: 01/19/2024] [Indexed: 02/28/2024] Open
Abstract
Gadolinium-based contrast agents (GBCA) are essential for diagnostic MRI examinations. GBCA are only used in small quantities on a per-patient basis; however, the acquisition of contrast-enhanced MRI examinations worldwide results in the use of many thousands of litres of GBCA per year. Data shows that these GBCA are present in sewage water, surface water, and drinking water in many regions of the world. Therefore, there is growing concern regarding the environmental impact of GBCA because of their ubiquitous presence in the aquatic environment. To address the problem of GBCA in the water system as a whole, collaboration is necessary between all stakeholders, including the producers of GBCA, medical professionals and importantly, the consumers of drinking water, i.e. the patients. This paper aims to make healthcare professionals aware of the opportunity to take the lead in making informed decisions about the use of GBCA and provides an overview of the different options for action.In this paper, we first provide a summary on the metabolism and clinical use of GBCA, then the environmental fate and observations of GBCA, followed by measures to reduce the use of GBCA. The environmental impact of GBCA can be reduced by (1) measures focusing on the application of GBCA by means of weight-based contrast volume reduction, GBCA with higher relaxivity per mmol of Gd, contrast-enhancing sequences, and post-processing; and (2) measures that reduce the waste of GBCA, including the use of bulk packaging and collecting residues of GBCA at the point of application.Critical relevance statement This review aims to make healthcare professionals aware of the environmental impact of GBCA and the opportunity for them to take the lead in making informed decisions about GBCA use and the different options to reduce its environmental burden.Key points• Gadolinium-based contrast agents are found in sources of drinking water and constitute an environmental risk.• Radiologists have a wide spectrum of options to reduce GBCA use without compromising diagnostic quality.• Radiology can become more sustainable by adopting such measures in clinical practice.
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Affiliation(s)
- Helena M Dekker
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.
| | - Gerard J Stroomberg
- RIWA-Rijn - Association of River Water Works, Groenendael 6, 3439 LV, Nieuwegein, The Netherlands
| | - Aart J Van der Molen
- Department of Radiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
| | - Mathias Prokop
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
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17
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Riedel A, Michael M, Grünberg J, Mehralivand S, Böehm K, Hachtel J, Platzek I, Sommer U, Baunacke M, Thomas C, Borkowetz A. The Role of Multiparametric MRI (mpMRI) in the Prediction of Adverse Prostate Cancer Pathology in Radical Prostatectomy Specimen. Urol Int 2024; 108:146-152. [PMID: 38246150 DOI: 10.1159/000536256] [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: 10/14/2023] [Accepted: 01/09/2024] [Indexed: 01/23/2024]
Abstract
INTRODUCTION Prostate cancer (PCa) risk stratification is essential in guiding therapeutic decision. Multiparametric magnetic resonance tomography (mpMRI) holds promise in the prediction of adverse pathologies (AP) after prostatectomy (RP). This study aims to identify clinical and imaging markers in the prediction of adverse pathology. METHODS Patients with PCa, diagnosed by targeted biopsy after mpMRI and undergoing RP, were included. The predictive accuracy of mpMRI for extraprostatic extension (ECE), seminal vesicle infiltration (SVI), and lymph node positivity was calculated from the final histopathology. RESULTS 846 patients were involved. Independent risk parameters include imaging findings such as ECE (OR 3.12), SVI (OR 2.55), and PI-RADS scoring (4: OR 2.01 and 5: OR 4.34). mpMRI parameters such as ECE, SVI, and lymph node metastases showed a high prognostic accuracy (73.28% vs. 95.35% vs. 93.38%) with moderate sensitivity compared to the final histopathology. The ROC analysis of our combined scoring system (D'Amico classification, PSA density, and MRI risk factors) improves the prediction of adverse pathology (AUC: 0.73 vs. 0.69). CONCLUSION Our study supports the use of mpMRI for comprehensive pretreatment risk assessment in PCa. Due to the high accuracy of factors like ECE, SVI, and PI-RADS scoring, utilizing mpMRI data enabled accurate prediction of unfavorable pathology after RP.
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Affiliation(s)
- Andreas Riedel
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany,
- Department of Internal Medicine II, Hematology, Oncology, Clinical Immunology and Rheumatology, University Hospital Tuebingen, Tuebingen, Germany,
| | - Marlene Michael
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Jenny Grünberg
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Sherif Mehralivand
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Katharina Böehm
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Jakob Hachtel
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Ivan Platzek
- Department of Radiology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Ulrich Sommer
- Department of Pathology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Martin Baunacke
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Christian Thomas
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
| | - Angelika Borkowetz
- Department of Urology, Medical Faculty and University Hospital Carl Gustav Carus Dresden, Dresden, Germany
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18
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Kensler KH, Johnson R, Morley F, Albrair M, Dickerman BA, Gulati R, Holt SK, Iyer HS, Kibel AS, Lee JR, Preston MA, Vassy JL, Wolff EM, Nyame YA, Etzioni R, Rebbeck TR. Prostate cancer screening in African American men: a review of the evidence. J Natl Cancer Inst 2024; 116:34-52. [PMID: 37713266 PMCID: PMC10777677 DOI: 10.1093/jnci/djad193] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 08/25/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND Prostate cancer is the most diagnosed cancer in African American men, yet prostate cancer screening regimens in this group are poorly guided by existing evidence, given underrepresentation of African American men in prostate cancer screening trials. It is critical to optimize prostate cancer screening and early detection in this high-risk group because underdiagnosis may lead to later-stage cancers at diagnosis and higher mortality while overdiagnosis may lead to unnecessary treatment. METHODS We performed a review of the literature related to prostate cancer screening and early detection specific to African American men to summarize the existing evidence available to guide health-care practice. RESULTS Limited evidence from observational and modeling studies suggests that African American men should be screened for prostate cancer. Consideration should be given to initiating screening of African American men at younger ages (eg, 45-50 years) and at more frequent intervals relative to other racial groups in the United States. Screening intervals can be optimized by using a baseline prostate-specific antigen measurement in midlife. Finally, no evidence has indicated that African American men would benefit from screening beyond 75 years of age; in fact, this group may experience higher rates of overdiagnosis at older ages. CONCLUSIONS The evidence base for prostate cancer screening in African American men is limited by the lack of large, randomized studies. Our literature search supported the need for African American men to be screened for prostate cancer, for initiating screening at younger ages (45-50 years), and perhaps screening at more frequent intervals relative to men of other racial groups in the United States.
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Affiliation(s)
- Kevin H Kensler
- Department of Population Health Sciences, Weill Cornell Medical Center, New York, NY, USA
| | - Roman Johnson
- Center for Global Health, Massachusetts General Hospital, Boston, MA, USA
| | - Faith Morley
- Department of Population Health Sciences, Weill Cornell Medical Center, New York, NY, USA
| | - Mohamed Albrair
- Department of Global Health, University of Washington, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Barbra A Dickerman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Roman Gulati
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sarah K Holt
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Hari S Iyer
- Section of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, USA
| | - Adam S Kibel
- Department of Urology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Jenney R Lee
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Mark A Preston
- Department of Urology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Jason L Vassy
- VA Boston Healthcare System, Boston, MA, USA
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Erika M Wolff
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Yaw A Nyame
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Ruth Etzioni
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Timothy R Rebbeck
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
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19
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Abreu-Gomez J, Lim C, Haider MA. Contemporary Approach to Prostate Imaging and Data Reporting System Score 3 Lesions. Radiol Clin North Am 2024; 62:37-51. [PMID: 37973244 DOI: 10.1016/j.rcl.2023.06.008] [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] [Indexed: 11/19/2023]
Abstract
The aim of this article is to review the technical and clinical considerations encountered with PI-RADS 3 lesions, which are equivocal for clinically significant Prostate Cancer (csPCa) with detection rates ranging between 10% and 35%. The number of PI-RADS 3 lesions reported vary according to several factors including MRI quality and radiologist training/expertise among the most influential. PI-RADS v.2.1 updated definitions for scores 2 and 3 in the PZ and scores 1 and 2 in the TZ is reviewed. The role of DWI role is highlighted in the assessment of the TZ with the possibility of upgrading score 2 lesions to score 3 based on DWI score. Given the increased utilization for prostate MRI, biparametric MRI can be considered as an alternative for low-risk patients where there is a need to rule out csPCa acknowledging this technique may increase the number of indeterminate cases going for biopsies. Management of patients with equivocal lesions at mpMRI and factors influencing biopsy decision process remain as an unmet need and additional studies using molecular/imaging markers as well as artificial intelligence tools are needed to further address their role in proper patient selection for biopsy.
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Affiliation(s)
- Jorge Abreu-Gomez
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, 610 University Avenue, Suite 3-920, Toronto, ON M5G 2M9, Canada.
| | - Christopher Lim
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, 2075 Bayview Avenue, Room AB 279, Toronto, ON M4N 3M5, Canada
| | - Masoom A Haider
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System and the Joint Department of Medical Imaging, Sinai Health System, Princess Margaret Hospital, University of Toronto, 600 University Avenue, Toronto, ON, Canada M5G 1X5
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20
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Choi MH, Lee YJ, Han D, Kim DH. Quantitative Analysis of Prostate MRI: Correlation between Contrast-Enhanced Magnetic Resonance Fingerprinting and Dynamic Contrast-Enhanced MRI Parameters. Curr Oncol 2023; 30:10299-10310. [PMID: 38132384 PMCID: PMC10743035 DOI: 10.3390/curroncol30120750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023] Open
Abstract
This research aimed to assess the relationship between contrast-enhanced (CE) magnetic resonance fingerprinting (MRF) values and dynamic contrast-enhanced (DCE) MRI parameters including (Ktrans, Kep, Ve, and iAUC). To evaluate the correlation between the MRF-derived values (T1 and T2 values, CE T1 and T2 values, T1 and T2 change) and DCE-MRI parameters and the differences in the parameters between prostate cancer and noncancer lesions in 68 patients, two radiologists independently drew regions-of-interest (ROIs) at the focal prostate lesions. Prostate cancer was identified in 75% (51/68) of patients. The CE T2 value was significantly lower in prostate cancer than in noncancer lesions in the peripheral zone and transition zone. Ktrans, Kep, and iAUC were significantly higher in prostate cancer than noncancer lesions in the peripheral zone (p < 0.05), but not in the transition zone. The CE T1 value was significantly correlated with Ktrans, Ve, and iAUC in prostate cancer, and the CE T2 value was correlated to Ve in noncancer. Some CE MRF values are different between prostate cancer and noncancer tissues and correlate with DCE-MRI parameters. Prostate cancer and noncancer tissues may have different characteristics regarding contrast enhancement.
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Affiliation(s)
- Moon-Hyung Choi
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea;
| | - Young-Joon Lee
- Department of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea;
| | - Dongyeob Han
- Siemens Healthineers Ltd., Seoul 06620, Republic of Korea;
| | - Dong-Hyun Kim
- School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea;
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21
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Matsuoka Y, Ueno Y, Uehara S, Tanaka H, Kobayashi M, Tanaka H, Yoshida S, Yokoyama M, Kumazawa I, Fujii Y. Deep-learning prostate cancer detection and segmentation on biparametric versus multiparametric magnetic resonance imaging: Added value of dynamic contrast-enhanced imaging. Int J Urol 2023; 30:1103-1111. [PMID: 37605627 DOI: 10.1111/iju.15280] [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: 05/06/2023] [Accepted: 07/30/2023] [Indexed: 08/23/2023]
Abstract
OBJECTIVES To develop diagnostic algorithms of multisequence prostate magnetic resonance imaging for cancer detection and segmentation using deep learning and explore values of dynamic contrast-enhanced imaging in multiparametric imaging, compared with biparametric imaging. METHODS We collected 3227 multiparametric imaging sets from 332 patients, including 218 cancer patients (291 biopsy-proven foci) and 114 noncancer patients. Diagnostic algorithms of T2-weighted, T2-weighted plus dynamic contrast-enhanced, biparametric, and multiparametric imaging were built using 2578 sets, and their performance for clinically significant cancer was evaluated using 649 sets. RESULTS Biparametric and multiparametric imaging had following region-based performance: sensitivity of 71.9% and 74.8% (p = 0.394) and positive predictive value of 61.3% and 74.8% (p = 0.013), respectively. In side-specific analyses of cancer images, the specificity was 72.6% and 89.5% (p < 0.001) and the negative predictive value was 78.9% and 83.5% (p = 0.364), respectively. False-negative cancer on multiparametric imaging was smaller (p = 0.002) and more dominant with grade group ≤2 (p = 0.028) than true positive foci. In the peripheral zone, false-positive regions on biparametric imaging turned out to be true negative on multiparametric imaging more frequently compared with the transition zone (78.3% vs. 47.2%, p = 0.018). In contrast, T2-weighted plus dynamic contrast-enhanced imaging had lower specificity than T2-weighted imaging (41.1% vs. 51.6%, p = 0.042). CONCLUSIONS When using deep learning, multiparametric imaging provides superior performance to biparametric imaging in the specificity and positive predictive value, especially in the peripheral zone. Dynamic contrast-enhanced imaging helps reduce overdiagnosis in multiparametric imaging.
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Affiliation(s)
- Yoh Matsuoka
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Urology, Saitama Cancer Center, Saitama, Japan
| | - Yoshihiko Ueno
- Department of Information and Communications Engineering, Tokyo Institute of Technology, Yokohama, Kanagawa, Japan
| | - Sho Uehara
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hiroshi Tanaka
- Department of Radiology, Ochanomizu Surugadai Clinic, Tokyo, Japan
| | - Masaki Kobayashi
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hajime Tanaka
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Soichiro Yoshida
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Minato Yokoyama
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Itsuo Kumazawa
- Laboratory for Future Interdisciplinary Research of Science and Technology, Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Kanagawa, Japan
| | - Yasuhisa Fujii
- Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan
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22
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Kang Z, Margolis DJ, Wang S, Li Q, Song J, Wang L. Management Strategy for Prostate Imaging Reporting and Data System Category 3 Lesions. Curr Urol Rep 2023; 24:561-570. [PMID: 37936016 DOI: 10.1007/s11934-023-01187-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2023] [Indexed: 11/09/2023]
Abstract
PURPOSE OF REVIEW Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions present a clinical dilemma due to their uncertain nature, which complicates the development of a definitive management strategy. These lesions have an incidence rate of approximately 22-32%, with clinically significant prostate cancer (csPCa) accounting for about 10-30%. Therefore, a thorough evaluation is warranted. RECENT FINDINGS This review highlights the need for radiology peer review, including the confirmation of dynamic contrast-enhanced (DCE) compliance, as the initial step. Additional MRI models such as VERDICT or Tofts need to be verified. Current evidence shows that imaging and clinical indicators can be used for risk stratification of PI-RADS 3 lesions. For low-risk lesions, a safety net monitoring approach involving annual repeat MRI can be employed. In contrast, lesions deemed potentially risky based on prostate-specific antigen density (PSAD), 68 Ga-PSMA PET/CT, MPS, Proclarix, or AI/machine learning models should undergo biopsy. It is recommended to establish a multidisciplinary team that takes into account factors such as age, PSAD, prostate, and lesion size, as well as previous biopsy pathological findings. Combining expert opinions, clinical-imaging indicators, and emerging methods will contribute to the development of management strategies for PI-RADS 3 lesions.
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Affiliation(s)
- Zhen Kang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, 36 Yong'an Rd, Xicheng District, Beijing, 100016, China
| | - Daniel J Margolis
- Department of Radiology, Weill Cornell Medicine/New York Presbyterian, New York, NY, USA
| | - Shaogang Wang
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qiubai Li
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Jian Song
- Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Liang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, 36 Yong'an Rd, Xicheng District, Beijing, 100016, China.
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23
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Inoue T, Shin T. Current magnetic resonance imaging-based diagnostic strategies for prostate cancer. Int J Urol 2023; 30:1078-1086. [PMID: 37592819 DOI: 10.1111/iju.15281] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 08/02/2023] [Indexed: 08/19/2023]
Abstract
Recent developments in multiparametric MRI and MRI-targeted biopsy have made it possible to detect clinically significant cancers more accurately and efficiently than ever before. Furthermore, software that enables easy MRI/US image fusion has been developed and is already available on the market, and this has provided a tailwind for the spread of MRI-based prostate cancer diagnostic strategies. Such precise diagnosis of prostate cancer localization is essential for highly accurate focal therapy. In addition, a recent large-scale study applying MRI to community screening for prostate cancer has reported its usefulness. By contrast, concerns about overdiagnosis and overtreatment, the existence of inter-reader variability in MRI diagnosis, and issues with current MRI-targeted biopsy have emerged. In this article, we review the development of multiparametric MRI and MRI-targeted biopsy to date and the current issues and discuss future directions.
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Affiliation(s)
- Toru Inoue
- Department of Urology, Oita University Faculty of Medicine, Oita, Japan
| | - Toshitaka Shin
- Department of Urology, Oita University Faculty of Medicine, Oita, Japan
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24
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Rehman I, Pang E, Harris AC, Chang SD. Bi-parametric prostate MRI with a recall system for contrast enhanced imaging: Improving accessibility while maintaining quality. Eur J Radiol 2023; 169:111186. [PMID: 37989069 DOI: 10.1016/j.ejrad.2023.111186] [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: 04/26/2023] [Revised: 10/25/2023] [Accepted: 11/02/2023] [Indexed: 11/23/2023]
Abstract
PURPOSE To review the efficacy of a recall system for bi-parametric non-contrast prostate MRI (bp-MRI). METHODS A bi-parametric protocol was instituted in July 2020 for all patients who had a prostate MRI requested, excluding those after treatment of prostate cancer, patients with hip prosthesis or pacemaker, and those who lived out-of-town. The protocol consisted of tri-planar T2-weighted and diffusion weighted images (DWI) (b = 50, 800 s/mm2 for ADC map; b = 1,500 s/mm2 acquired separately) in accordance with the Prostate Imaging Reporting & Data system (PI-RADS) v2.1 guidelines. After interpretation of bp-MRI exams, patients with equivocal (PI-RADS 3) lesions in peripheral zone (PZ) or any technical limitations were recalled for contrast administration. RESULTS Out of 909 bp-MRI scans performed from July 2020 to April 2021, only 52 (5.7 %) were recalled, of which 46 (88.5 %) attended. Amongst these, 41/52 (78.8 %) were recalled for PZ PI-RADS 3 lesions, while the rest of 11 (21.2 %) cases were recalled for technical reasons. Mean time to subsequent recall scan was 11.6 days. On assessment of post-contrast imaging, 29/46 (63 %) cases were upgraded to PI-RADS 4 while 17/46 (37 %) remained PI-RADS 3. This system avoided contrast-agent use in 857 patients, with contrast cost savings of €64,620 (US$68,560) and 214 hours 15 minutes of scanner time was saved. This allowed 255 additional bp-MRI scans to be performed, reducing the waitlist from 1 year to 2-3 weeks. CONCLUSION A bi-parametric prostate MRI protocol with a robust recall system for contrast administration not only saved time eliminating the marked backlog but was also more cost efficient without compromising the quality of patient care.
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Affiliation(s)
- Iffat Rehman
- Department of Radiology, Vancouver General Hospital, University of British Columbia, 899 West 12(th) Avenue Vancouver, BC V5Z 1M9, Canada.
| | - Emily Pang
- Department of Radiology, Vancouver General Hospital, University of British Columbia, 899 West 12(th) Avenue Vancouver, BC V5Z 1M9, Canada
| | - Alison C Harris
- Department of Radiology, Vancouver General Hospital, University of British Columbia, 899 West 12(th) Avenue Vancouver, BC V5Z 1M9, Canada
| | - Silvia D Chang
- Department of Radiology, Vancouver General Hospital, University of British Columbia, 899 West 12(th) Avenue Vancouver, BC V5Z 1M9, Canada
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Guljaš S, Dupan Krivdić Z, Drežnjak Madunić M, Šambić Penc M, Pavlović O, Krajina V, Pavoković D, Šmit Takač P, Štefančić M, Salha T. Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review. Diagnostics (Basel) 2023; 13:3488. [PMID: 37998624 PMCID: PMC10670922 DOI: 10.3390/diagnostics13223488] [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: 08/26/2023] [Revised: 10/30/2023] [Accepted: 11/16/2023] [Indexed: 11/25/2023] Open
Abstract
The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.
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Affiliation(s)
- Silva Guljaš
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (S.G.); (Z.D.K.)
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
| | - Zdravka Dupan Krivdić
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (S.G.); (Z.D.K.)
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
| | - Maja Drežnjak Madunić
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Oncology, University Hospital Centre, 31000 Osijek, Croatia
| | - Mirela Šambić Penc
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Oncology, University Hospital Centre, 31000 Osijek, Croatia
| | - Oliver Pavlović
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Urology, University Hospital Centre, 31000 Osijek, Croatia
| | - Vinko Krajina
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Urology, University Hospital Centre, 31000 Osijek, Croatia
| | - Deni Pavoković
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Urology, University Hospital Centre, 31000 Osijek, Croatia
| | - Petra Šmit Takač
- Clinical Department of Surgery, Osijek University Hospital Centre, 31000 Osijek, Croatia;
| | - Marin Štefančić
- Department of Radiology, National Memorial Hospital Vukovar, 32000 Vukovar, Croatia;
| | - Tamer Salha
- Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia; (M.D.M.); (M.Š.P.); (O.P.); (V.K.); (D.P.)
- Department of Teleradiology and Artificial Intelligence, Health Centre Osijek-Baranja County, 31000 Osijek, Croatia
- Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
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Nong W, Huang Q, Gao Y. Development and validation of a nomogram for predicting prostate cancer based on combining contrast-enhanced transrectal ultrasound and biparametric MRI imaging. Front Oncol 2023; 13:1275773. [PMID: 38044995 PMCID: PMC10691548 DOI: 10.3389/fonc.2023.1275773] [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: 08/10/2023] [Accepted: 11/06/2023] [Indexed: 12/05/2023] Open
Abstract
Objectives This study was to explore the feasibility of combining contrast-enhanced transrectal ultrasound (CE-TRUS) with biparametric MRI (CEUS-BpMRI) score for diagnosing prostate cancer (PCa). Methods A total of 183 patients with suspected PCa who underwent multiparametric MRI (Mp-MRI) and CE-TRUS were included. CEUS-BpMRI score was developed based on the results of Mp-MRI and CE-TRUS. The diagnostic performance was evaluated by the area under the curve (AUC). The diagnostic efficacy of the CEUS-BpMRI score, BpMRI score, and PI-RADS v2.1 score were compared. Total patients were randomly assigned to a training cohort (70%) or validation cohort (30%). A nomogram was constructed based on univariate and multivariate logistic regression. The model was evaluated by AUC and calibration curve. Results The diagnostic performance of CEUS-BpMRI score (AUC 0.857) was comparable to that of PI-RADS v2.1 (AUC 0.862) (P = 0.499), and both were superior to Bp-MRI score (AUC 0.831, P < 0.05). In peripheral zone lesions with Bp-MRI score of 3, there was no statistically significant difference between PI-RADS v2.1 score (AUC 0.728) and CEUS-BpMRI score (AUC 0.668) (P = 0.479). Multivariate analysis showed that age, total prostate specific antigen/free prostate specific antigen (F/T), time to peak (TTP), and CEUS-BpMRI score were independent factors. The AUC of the nomogram was 0.909 in the training cohort and 0.914 in the validation cohort. Conclusions CEUS-BpMRI score has high diagnostic efficacy for diagnosing PCa. A nomogram model established by combining age, F/T, TTP, and CEUS-BpMRI score can achieve the best predictive accuracy for PCa.
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Affiliation(s)
- Wanxian Nong
- Department of Ultrasound, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Qun Huang
- Department of Ultrasound, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
| | - Yong Gao
- Department of Ultrasound, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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Chang CB, Lin YC, Wong YC, Lin SN, Lin CY, Lin YH, Sheng TW, Yang LY, Wang LJ. Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Parameters Could Predict International Society of Urological Pathology Risk Groups of Prostate Cancers on Radical Prostatectomy. Life (Basel) 2023; 13:1944. [PMID: 37763347 PMCID: PMC10532885 DOI: 10.3390/life13091944] [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: 07/16/2023] [Revised: 08/22/2023] [Accepted: 09/19/2023] [Indexed: 09/29/2023] Open
Abstract
BACKGROUND The International Society of Urological Pathology (ISUP) grade and positive surgical margins (PSMs) after radical prostatectomy (RP) may reflect the prognosis of prostate cancer (PCa) patients. This study aimed to investigate whether DCE-MRI parameters (i.e., Ktrans, kep, and IAUC) could predict ISUP grade and PSMs after RP. METHOD Forty-five PCa patients underwent preoperative DCE-MRI. The clinical characteristics and DCE-MRI parameters of the 45 patients were compared between the low- and high-risk (i.e., ISUP grades III-V) groups and between patients with or without PSMs after RP. Multivariate logistic regression analysis was used to identify the significant predictors of placement in the high-risk group and PSMs. RESULTS The DCE parameter Ktrans-max was significantly higher in the high-risk group than in the low-risk group (p = 0.028) and was also a significant predictor of placement in the high-risk group (odds ratio [OR] = 1.032, 95% confidence interval [CI] = 1.005-1.060, p = 0.021). Patients with PSMs had significantly higher prostate-specific antigen (PSA) titers, positive biopsy core percentages, Ktrans-max, kep-median, and kep-max than others (all p < 0.05). Of these, positive biopsy core percentage (OR = 1.035, 95% CI = 1.003-1.068, p = 0.032) and kep-max (OR = 1.078, 95% CI = 1.012-1.148, p = 0.020) were significant predictors of PSMs. CONCLUSION Preoperative DCE-MRI parameters, specifically Ktrans-max and kep-max, could potentially serve as preoperative imaging biomarkers for postoperative PCa prognosis based on their predictability of PCa risk group and PSM on RP, respectively.
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Affiliation(s)
- Chun-Bi Chang
- Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Gueishan, Taoyuan 33305, Taiwan; (C.-B.C.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan
| | - Yu-Chun Lin
- Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Gueishan, Taoyuan 33305, Taiwan; (C.-B.C.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan
| | - Yon-Cheong Wong
- Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Gueishan, Taoyuan 33305, Taiwan; (C.-B.C.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Medical Imaging and Intervention, New Taipei Municipal TuCheng Hospital, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan 33305, Taiwan
| | - Shin-Nan Lin
- Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Gueishan, Taoyuan 33305, Taiwan; (C.-B.C.)
| | | | - Yu-Han Lin
- Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Gueishan, Taoyuan 33305, Taiwan; (C.-B.C.)
| | - Ting-Wen Sheng
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Medical Imaging and Intervention, New Taipei Municipal TuCheng Hospital, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan 33305, Taiwan
| | - Lan-Yan Yang
- Biostatistics Unit of Clinical Trial Center, Chang Gung Memorial Hospital, Gueishan, Taoyuan 33305, Taiwan
| | - Li-Jen Wang
- Department of Medical Imaging and Intervention, Linkou Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Gueishan, Taoyuan 33305, Taiwan; (C.-B.C.)
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Medical Imaging and Intervention, New Taipei Municipal TuCheng Hospital, Chang Gung Memorial Hospital and Chang Gung University, Taoyuan 33305, Taiwan
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Hackenbroch C. Guest-Editorial on The Way of Water Excitation: New Fat Suppression Method for Diffusion-Weighted Breast Imaging at 3 Tesla. Acad Radiol 2023; 30:1784-1785. [PMID: 37391281 DOI: 10.1016/j.acra.2023.05.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 05/30/2023] [Accepted: 05/30/2023] [Indexed: 07/02/2023]
Affiliation(s)
- Carsten Hackenbroch
- Military Hospital of the German Armed Forces, Ulm, Department of Radiology and Neuroradiology, Oberer Eselsberg 40, 89081 Ulm, Germany.
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Zhou X, Fan X, Chatterjee A, Yousuf A, Antic T, Oto A, Karczmar GS. Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard tofts model in the diagnosis of prostate cancer. Phys Eng Sci Med 2023; 46:1215-1226. [PMID: 37432557 DOI: 10.1007/s13246-023-01289-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 06/14/2023] [Indexed: 07/12/2023]
Abstract
The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data and compared with the standard Tofts model. A total of 29 patients with biopsy-confirmed prostate cancer were included in this IRB-approved study. MRI data were acquired on a Philips Achieva 3T-TX scanner. After T2-weighted and diffusion-weighted imaging, DCE data using 3D T1-FFE mDIXON sequence were acquired pre- and post-contrast media injection (0.1 mmol/kg Multihance) for 60 dynamic scans with temporal resolution of 8.3 s/image. The 2TCM has one fast ([Formula: see text] and [Formula: see text]) and one slow ([Formula: see text] and [Formula: see text]) exchanging compartment, compared with the standard Tofts model parameters (Ktrans and kep). On average, prostate cancer had significantly higher values (p < 0.01) than normal prostate tissue for all calculated parameters. There was a strong correlation (r = 0.94, p < 0.001) between Ktrans and [Formula: see text] for cancer, but weak correlation (r = 0.28, p < 0.05) between kep and [Formula: see text]. Average root-mean-square error (RMSE) in fits from the 2TCM was significantly smaller (p < 0.001) than the RMSE in fits from the Tofts model. Receiver operating characteristic (ROC) analysis showed that fast [Formula: see text] had the highest area under the curve (AUC) than any other individual parameter. The combined four parameters from the 2TCM had a considerably higher AUC value than the combined two parameters from the Tofts model. The 2TCM is useful for quantitative analysis of prostate DCE-MRI data and provides new information in the diagnosis of prostate cancer.
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Affiliation(s)
- Xueyan Zhou
- School of Technology, Harbin University, Harbin, China.
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA.
| | - Xiaobing Fan
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA
| | | | - Ambereen Yousuf
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA
| | - Tatjana Antic
- Department of Pathology, University of Chicago, Chicago, IL, 60637, USA
| | - Aytekin Oto
- Department of Radiology, University of Chicago, Chicago, IL, 60637, USA
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Massanova M, Vere R, Robertson S, Crocetto F, Barone B, Dutto L, Ahmad I, Underwood M, Salmond J, Patel A, Celentano G, Bhatt JR. Clinical and prostate multiparametric magnetic resonance imaging findings as predictors of general and clinically significant prostate cancer risk: A retrospective single-center study. Curr Urol 2023; 17:147-152. [PMID: 37448611 PMCID: PMC10337816 DOI: 10.1097/cu9.0000000000000173] [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: 09/17/2021] [Accepted: 03/27/2022] [Indexed: 02/05/2023] Open
Abstract
Background To evaluate the predictive values of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2), prostate-specific antigen (PSA) level, PSA density (PSAD), digital rectal examination findings, and prostate volume, individually and in combination, for the detection of prostate cancer (PCa) in biopsy-naive patients. Methods We retrospectively analyzed 630 patients who underwent transrectal systematic prostate biopsy following prostate multiparametric magnetic resonance imaging. A standard 12-core biopsy procedure was performed. Univariate and multivariate analyses were performed to determine the significant predictors of clinically significant cancer but not PCa. Results The median age, PSA level, and PSAD were 70 years, 8.6 ng/mL, and 0.18 ng/mL/mL, respectively. A total of 374 (59.4%) of 630 patients were biopsy-positive for PCa, and 241 (64.4%) of 374 were diagnosed with clinically significant PCa (csPCa). The PI-RADS v2 score and PSAD were independent predictors of PCa and csPCa. The PI-RADS v2 score of 5 regardless of the PSAD value, or PI-RADS v2 score of 4 plus a PSAD of <0.3 ng/mL/mL, was associated with the highest csPCa detection rate (36.1%-82.1%). Instead, the PI-RADS v2 score of <3 and PSAD of <0.3 ng/mL/mL yielded the lowest risk of csPCa. Conclusion The combination of the PI-RADS v2 score and PSAD could prove to be a helpful and reliable diagnostic tool before performing prostate biopsies. Patients with a PI-RADS v2 score of <3 and PSAD of <0.3 ng/mL/mL could potentially avoid a prostate biopsy.
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Affiliation(s)
- Matteo Massanova
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Rebecca Vere
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Sophie Robertson
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Felice Crocetto
- Department of Neuroscience, Reproductive and Odontostomatological Sciences, School of Medicine, University of Naples “Federico II,” Naples, Italy
| | - Biagio Barone
- Department of Neuroscience, Reproductive and Odontostomatological Sciences, School of Medicine, University of Naples “Federico II,” Naples, Italy
| | - Lorenzo Dutto
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Imran Ahmad
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Mark Underwood
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Jonathan Salmond
- Department of Pathology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Amit Patel
- Department of Radiology, Queen Elizabeth University Hospital, Glasgow, UK
| | - Giuseppe Celentano
- Department of Neuroscience, Reproductive and Odontostomatological Sciences, School of Medicine, University of Naples “Federico II,” Naples, Italy
| | - Jaimin R. Bhatt
- Department of Urology, Queen Elizabeth University Hospital, Glasgow, UK
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Wang Y, Wang L, Tang X, Zhang Y, Zhang N, Zhi B, Niu X. Development and validation of a nomogram based on biparametric MRI PI-RADS v2.1 and clinical parameters to avoid unnecessary prostate biopsies. BMC Med Imaging 2023; 23:106. [PMID: 37582697 PMCID: PMC10426075 DOI: 10.1186/s12880-023-01074-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 08/03/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Biparametric MRI (bpMRI) is a faster, contrast-free, and less expensive MRI protocol that facilitates the detection of prostate cancer. The aim of this study is to determine whether a biparametric MRI PI-RADS v2.1 score-based model could reduce unnecessary biopsies in patients with suspected prostate cancer (PCa). METHODS The patients who underwent MRI-guided biopsies and systematic biopsies between January 2020 and January 2022 were retrospectively analyzed. The development cohort used to derive the prediction model consisted of 275 patients. Two validation cohorts included 201 patients and 181 patients from 2 independent institutions. Predictive models based on the bpMRI PI-RADS v2.1 score (bpMRI score) and clinical parameters were used to detect clinically significant prostate cancer (csPCa) and compared by analyzing the area under the curve (AUC) and decision curves. Spearman correlation analysis was utilized to determine the relationship between International Society of Urological Pathology (ISUP) grade and clinical parameters/bpMRI score. RESULTS Logistic regression models were constructed using data from the development cohort to generate nomograms. By applying the models to the all cohorts, the AUC for csPCa was significantly higher for the bpMRI PI-RADS v2.1 score-based model than for the clinical model in both cohorts (p < 0.001). Considering the test trade-offs, urologists would agree to perform 10 fewer bpMRIs to avoid one unnecessary biopsy, with a risk threshold of 10-20% in practice. Correlation analysis showed a strong correlation between the bpMRI score and ISUP grade. CONCLUSION A predictive model based on the bpMRI score and clinical parameters significantly improved csPCa risk stratification, and the bpMRI score can be used to determine the aggressiveness of PCa prior to biopsy.
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Affiliation(s)
- Yunhan Wang
- Department of Urology, Affiliated Hospital of Chengdu University, Chengdu, 610081, Sichuan, China
| | - Lei Wang
- Department of Radiology, Ninety-Three Hospital, Jiangyou City, 610000, Sichuan, China
| | - Xiaohua Tang
- Department of Radiology, Ninety-Three Hospital, Jiangyou City, 610000, Sichuan, China
| | - Yong Zhang
- Department of Radiology, DeYang People's Hospital, Deyang City, 610000, Sichuan, China
| | - Na Zhang
- Department of General Practice Medicine, Affiliated Hospital of Chengdu University, Chengdu, 610081, Sichuan, China
| | - Biao Zhi
- Department of Interventional Radiology, Affiliated Hospital of Chengdu University, Chengdu, 610081, Sichuan, China
| | - Xiangke Niu
- Department of Interventional Radiology, Affiliated Hospital of Chengdu University, Chengdu, 610081, Sichuan, China.
- Department of Interventional Radiology, School of Medicine, Sichuan Cancer Hospital & Research Institute, University of Electronic Science and Technology of China (UESTC), Chengdu, 610041, China.
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Messina E, Pecoraro M, Laschena L, Bicchetti M, Proietti F, Ciardi A, Leonardo C, Sciarra A, Girometti R, Catalano C, Panebianco V. Low cancer yield in PI-RADS 3 upgraded to 4 by dynamic contrast-enhanced MRI: is it time to reconsider scoring categorization? Eur Radiol 2023; 33:5828-5839. [PMID: 37045981 PMCID: PMC10326099 DOI: 10.1007/s00330-023-09605-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 02/22/2023] [Accepted: 02/26/2023] [Indexed: 04/14/2023]
Abstract
OBJECTIVES To evaluate MRI diagnostic performance in detecting clinically significant prostate cancer (csPCa) in peripheral-zone PI-RADS 4 lesions, comparing those with clearly restricted diffusion (DWI-score 4), and those with equivocal diffusion pattern (DWI-score 3) and positive dynamic contrast-enhanced (DCE) MRI. METHODS This observational prospective study enrolled 389 men referred to MRI and, if positive (PI-RADS 3 with PSA-density [PSAD] ≥ 0.15 ng/mL/mL, 4 and 5), to MRI-directed biopsy. Lesions with DWI-score 3 and positive DCE were classified as "PI-RADS 3up," instead of PI-RADS 4. Univariable and multivariable analyses were implemented to determine features correlated to csPCa detection. RESULTS Prevalence of csPCa was 14.5% and 53.3% in PI-RADS categories 3up and 4, respectively (p < 0.001). MRI showed a sensitivity of 100.0%, specificity 40.9%, PPV 46.5%, NPV 100.0%, and accuracy 60.9% for csPCa detection. Modifying the threshold to consider MRI positive and to indicate biopsy (same as previously described, but PI-RADS 3up only when associated with elevated PSAD), the sensitivity changed to 93.9%, specificity 57.2%, PPV 53.0%, NPV 94.8%, and accuracy 69.7%. Age (p < 0.001), PSAD (p < 0.001), positive DWI (p < 0.001), and PI-RADS score (p = 0.04) resulted in independent predictors of csPCa. CONCLUSIONS Most cases of PI-RADS 3up were false-positives, suggesting that upgrading peripheral lesions with DWI-score 3 to PI-RADS 4 because of positive DCE has a detrimental effect on MRI accuracy, decreasing the true prevalence of csPCa in the PI-RADS 4 category. PI-RADS 3up should not be upgraded and directed to biopsy only if associated with increased PSAD. KEY POINTS • As per PI-RADS v2.1 recommendations, in case of a peripheral zone lesion with equivocal diffusion-weighted imaging (DWI score 3), but positive dynamic contrast-enhanced (DCE) MRI, the overall PI-RADS score should be upgraded to 4. • The current PI-RADS recommendation of upgrading PI-RADS 3 lesions of the peripheral zone to PI-RADS 4 because of positive DCE decreased clinically significant prostate cancer detection rate in our series. • According to our results, the most accurate threshold for setting indication to prostate biopsy is PI-RADS 3 or PI-RADS 3 with positive DCE both associated with increased PSA density.
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Affiliation(s)
- Emanuele Messina
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Martina Pecoraro
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Ludovica Laschena
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Marco Bicchetti
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Flavia Proietti
- Department of Maternal-Infant and Urological Sciences, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Antonio Ciardi
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Costantino Leonardo
- Department of Maternal-Infant and Urological Sciences, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Alessandro Sciarra
- Department of Maternal-Infant and Urological Sciences, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Rossano Girometti
- Institute of Radiology, Department of Medicine, University of Udine, University Hospital S, Maria Della Misericordia; P.Le S. Maria Della Misericordia 15, 33100, Udine, Italy
| | - Carlo Catalano
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy
| | - Valeria Panebianco
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Viale del Policlinico 155, 00185, Rome, Italy.
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He M, Cao Y, Chi C, Yang X, Ramin R, Wang S, Yang G, Mukhtorov O, Zhang L, Kazantsev A, Enikeev M, Hu K. Research progress on deep learning in magnetic resonance imaging-based diagnosis and treatment of prostate cancer: a review on the current status and perspectives. Front Oncol 2023; 13:1189370. [PMID: 37546423 PMCID: PMC10400334 DOI: 10.3389/fonc.2023.1189370] [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: 03/19/2023] [Accepted: 05/30/2023] [Indexed: 08/08/2023] Open
Abstract
Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection and noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging and time-consuming, which may impact sensitivity and specificity. With recent technological advances, artificial intelligence (AI) in the form of computer-aided diagnosis (CAD) based on MRI data has been applied to prostate cancer diagnosis and treatment. Among AI techniques, deep learning involving convolutional neural networks contributes to detection, segmentation, scoring, grading, and prognostic evaluation of prostate cancer. CAD systems have automatic operation, rapid processing, and accuracy, incorporating multiple sequences of multiparametric MRI data of the prostate gland into the deep learning model. Thus, they have become a research direction of great interest, especially in smart healthcare. This review highlights the current progress of deep learning technology in MRI-based diagnosis and treatment of prostate cancer. The key elements of deep learning-based MRI image processing in CAD systems and radiotherapy of prostate cancer are briefly described, making it understandable not only for radiologists but also for general physicians without specialized imaging interpretation training. Deep learning technology enables lesion identification, detection, and segmentation, grading and scoring of prostate cancer, and prediction of postoperative recurrence and prognostic outcomes. The diagnostic accuracy of deep learning can be improved by optimizing models and algorithms, expanding medical database resources, and combining multi-omics data and comprehensive analysis of various morphological data. Deep learning has the potential to become the key diagnostic method in prostate cancer diagnosis and treatment in the future.
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Affiliation(s)
- Mingze He
- Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Yu Cao
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Changliang Chi
- Department of Urology, The First Hospital of Jilin University (Lequn Branch), Changchun, Jilin, China
| | - Xinyi Yang
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Rzayev Ramin
- Department of Radiology, The Second University Clinic, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Shuowen Wang
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Guodong Yang
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Otabek Mukhtorov
- Regional State Budgetary Health Care Institution, Kostroma Regional Clinical Hospital named after Korolev E.I. Avenue Mira, Kostroma, Russia
| | - Liqun Zhang
- School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning, China
| | - Anton Kazantsev
- Regional State Budgetary Health Care Institution, Kostroma Regional Clinical Hospital named after Korolev E.I. Avenue Mira, Kostroma, Russia
| | - Mikhail Enikeev
- Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Kebang Hu
- Department of Urology, The First Hospital of Jilin University (Lequn Branch), Changchun, Jilin, China
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Mayer R, Turkbey B, Choyke PL, Simone CB. Application of Spectral Algorithm Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study. Diagnostics (Basel) 2023; 13:2008. [PMID: 37370903 DOI: 10.3390/diagnostics13122008] [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: 05/09/2023] [Revised: 06/01/2023] [Accepted: 06/07/2023] [Indexed: 06/29/2023] Open
Abstract
Background: Current prostate cancer evaluation can be inaccurate and burdensome. Quantitative evaluation of Magnetic Resonance Imaging (MRI) sequences non-invasively helps prostate tumor assessment. However, including Dynamic Contrast Enhancement (DCE) in the examined MRI sequence set can add complications, inducing possible side effects from the IV placement or injected contrast material and prolonging scanning time. More accurate quantitative MRI without DCE and artificial intelligence approaches are needed. Purpose: Predict the risk of developing Clinically Significant (Insignificant) prostate cancer CsPCa (CiPCa) and correlate with the International Society of Urologic Pathology (ISUP) grade using processed Signal to Clutter Ratio (SCR) derived from spatially registered bi-parametric MRI (SRBP-MRI) and thereby enhance non-invasive management of prostate cancer. Methods: This pilot study retrospectively analyzed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRI (Apparent Diffusion Coefficient, High B-value, T2) were resized, translated, cropped, and stitched to form spatially registered SRBP-MRI. Efficacy of noise reduction was tested by regularizing, eliminating principal components (PC), and minimizing elliptical volume from the covariance matrix to optimize the SCR. MRI guided biopsy (MRBx), Systematic Biopsy (SysBx), combination (MRBx + SysBx), or radical prostatectomy determined the ISUP grade for each patient. ISUP grade ≥ 2 (<2) was judged as CsPCa (CiPCa). Linear and logistic regression were fitted to ISUP grade and CsPCa/CiPCa SCR. Correlation Coefficients (R) and Area Under the Curves (AUC) for Receiver Operator Curves (ROC) evaluated the performance. Results: High correlation coefficients (R) (>0.55) and high AUC (=1.0) for linear and/or logistic fit from processed SCR and z-score for SRBP-MRI greatly exceed fits using prostate serum antigen, prostate volume, and patient age (R ~ 0.17). Patients assessed with combined MRBx + SysBx and from individual MRI scanners achieved higher R (DR = 0.207+/-0.118) than all patients used in the fits. Conclusions: In the first study, to date, spectral approaches for assessing tumor aggressiveness on SRBP-MRI have been applied and tested and achieved high values of R and exceptional AUC to fit the ISUP grade and CsPCA/CiPCA, respectively.
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Affiliation(s)
- Rulon Mayer
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA
- OncoScore, Garrett Park, MD 20896, USA
| | - Baris Turkbey
- National Institutes of Health, Bethesda, MD 20892, USA
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Yilmaz EC, Shih JH, Belue MJ, Harmon SA, Phelps TE, Garcia C, Hazen LA, Toubaji A, Merino MJ, Gurram S, Choyke PL, Wood BJ, Pinto PA, Turkbey B. Prospective Evaluation of PI-RADS Version 2.1 for Prostate Cancer Detection and Investigation of Multiparametric MRI-derived Markers. Radiology 2023; 307:e221309. [PMID: 37129493 PMCID: PMC10323290 DOI: 10.1148/radiol.221309] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 01/21/2023] [Accepted: 02/10/2023] [Indexed: 05/03/2023]
Abstract
Background Data regarding the prospective performance of Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 alone and in combination with quantitative MRI features for prostate cancer detection is limited. Purpose To assess lesion-based clinically significant prostate cancer (csPCa) rates in different PI-RADS version 2.1 categories and to identify MRI features that could improve csPCa detection. Materials and Methods This single-center prospective study included men with suspected or known prostate cancer who underwent multiparametric MRI and MRI/US-guided biopsy from April 2019 to December 2021. MRI scans were prospectively evaluated using PI-RADS version 2.1. Atypical transition zone (TZ) nodules were upgraded to category 3 if marked diffusion restriction was present. Lesions with an International Society of Urological Pathology (ISUP) grade of 2 or higher (range, 1-5) were considered csPCa. MRI features, including three-dimensional diameter, relative lesion volume (lesion volume divided by prostate volume), sphericity, and surface to volume ratio (SVR), were obtained from lesion contours delineated by the radiologist. Univariable and multivariable analyses were conducted at the lesion and participant levels to determine features associated with csPCa. Results In total, 454 men (median age, 67 years [IQR, 62-73 years]) with 838 lesions were included. The csPCa rates for lesions categorized as PI-RADS 1 (n = 3), 2 (n = 170), 3 (n = 197), 4 (n = 319), and 5 (n = 149) were 0%, 9%, 14%, 37%, and 77%, respectively. csPCa rates of PI-RADS 4 lesions were lower than PI-RADS 5 lesions (P < .001) but higher than PI-RADS 3 lesions (P < .001). Upgraded PI-RADS 3 TZ lesions were less likely to harbor csPCa compared with their nonupgraded counterparts (4% [one of 26] vs 20% [20 of 99], P = .02). Predictors of csPCa included relative lesion volume (odds ratio [OR], 1.6; P < .001), SVR (OR, 6.2; P = .02), and extraprostatic extension (EPE) scores of 2 (OR, 9.3; P < .001) and 3 (OR, 4.1; P = .02). Conclusion The rates of csPCa differed between consecutive PI-RADS categories of 3 and higher. MRI features, including lesion volume, shape, and EPE scores of 2 and 3, predicted csPCa. Upgrading of PI-RADS category 3 TZ lesions may result in unnecessary biopsies. ClinicalTrials.gov registration no. NCT03354416 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Goh in this issue.
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Affiliation(s)
- Enis C. Yilmaz
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Joanna H. Shih
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Mason J. Belue
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Stephanie A. Harmon
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Tim E. Phelps
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Charisse Garcia
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Lindsey A. Hazen
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Antoun Toubaji
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Maria J. Merino
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Sandeep Gurram
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Peter L. Choyke
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Bradford J. Wood
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Peter A. Pinto
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
| | - Baris Turkbey
- From the Molecular Imaging Branch (E.C.Y., M.J.B., S.A.H., T.E.P.,
P.L.C., B.T.), Biometric Research Program, Division of Cancer Treatment and
Diagnosis (J.H.S.), Center for Interventional Oncology (C.G., L.A.H., B.J.W.),
Department of Radiology, Clinical Center (C.G., L.A.H., B.J.W.), Laboratory of
Pathology (A.T., M.J.M.), and Urologic Oncology Branch (S.G., P.A.P.), National
Cancer Institute, National Institutes of Health, 10 Center Dr, MSC 1182,
Building 10, Room B3B85, Bethesda, MD 20892
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Zhang J, Xu L, Zhang G, Zhang X, Bai X, Sun H, Jin Z. Effects of dynamic contrast enhancement on transition zone prostate cancer in Prostate Imaging Reporting and Data System Version 2.1. Radiol Oncol 2023; 57:42-50. [PMID: 36655324 PMCID: PMC10039479 DOI: 10.2478/raon-2023-0007] [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: 10/09/2022] [Accepted: 11/18/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND The aim of the study was to analyse the effects of dynamic contrast enhanced (DCE)-MRI on transitional-zone prostate cancer (tzPCa) and clinically significant transitional-zone prostate cancer (cs-tzPCa) in Prostate Imaging Reporting and Data System (PI-RADS) Version 2.1. PATIENTS AND METHODS The diagnostic efficiencies of T2-weighted imaging (T2WI) + diffusion-weighted imaging (DWI), T2WI + dynamic contrast-enhancement (DCE), and T2WI + DWI + DCE in tzPCa and cs-tzPCa were compared using the score of ≥ 4 as the positive threshold and prostate biopsy as the reference standard. RESULTS A total of 425 prostate cases were included in the study: 203 cases in the tzPCa group, and 146 in the cs-tzPCa group. The three sequence combinations had the similar areas under the curves in diagnosing tzPCa and cs-tzPCa (all P < 0.05). The sensitivity of T2WI + DCE and T2WI + DWI + DCE (84.7% and 85.7% for tzPCa; 88.4% and 89.7% for cs-tzPCa, respectively) in diagnosing tzPCa and cs-tzPCa was significantly greater than that of T2WI + DWI (79.3% for tzPCa; 82.9% for cs-tzPCa). The specificity of T2WI + DWI (86.5% for tzPCa; 74.9% for cs-tzPCa) were significantly greater than those of T2WI + DCE and T2WI + DWI + DCE (68.0% and 68.5% for tzPCa; 59.1% and 59.5% for cs-tzPCa, respectively) (all P > 0.05). The diagnostic efficacies of T2WI + DCE and T2WI + DWI + DCE had no significant differences (all P < 0.05). CONCLUSIONS DCE can improve the sensitivity of diagnosis for tzPCa and cs-tzPCa, and it is useful for small PCa lesion diagnosis.
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Affiliation(s)
- Jiahui Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Lili Xu
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Gumuyang Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaoxiao Zhang
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Xin Bai
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Hao Sun
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- National Center for Quality Control of Radiology, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- National Center for Quality Control of Radiology, Beijing, China
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Hsieh PF, Li PI, Lin WC, Chang H, Chang CH, Wu HC, Chang YH, Wang YD, Huang WC, Huang CP. Learning Curve of Transperineal MRI/US Fusion Prostate Biopsy: 4-Year Experience. Life (Basel) 2023; 13:life13030638. [PMID: 36983794 PMCID: PMC10059778 DOI: 10.3390/life13030638] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 03/02/2023] Open
Abstract
This study aimed to evaluate the learning curve of transperineal magnetic resonance imaging (MRI)/ultrasound (US) fusion biopsy in a team composed of a single surgeon, a single radiologist, and a single pathologist. We prospectively enrolled 206 patients undergoing MRI/US fusion prostate biopsy and divided them into four cohorts by the year of biopsy. We analyzed temporal changes in clinically significant prostate cancer (csPC) detection rate, percentage of positive cores on biopsy, and Gleason upgrading rate after radical prostatectomy. The csPC detection rate by MRI/US fusion targeted biopsy (TB) increased significantly (from 35.3% to 60.0%, p = 0.01). With increased experience, the csPC detection rates for small (≤1 cm) and anterior target lesions gradually increased (from 41.2% to 51.6%, p = 0.5; from 54.5% to 88.2%, p = 0.8, respectively). The percentage of positive cores on TB increased significantly (from 18.4% to 44.2%, p = 0.001). The Gleason upgrading rate gradually decreased (from 22.2% to 11.1%, p = 0.4). In conclusion, with accumulated experience and teamwork, the csPC detection rate by TB significantly increased. Multidisciplinary team meetings and a free-hand biopsy technique were the key factors for overcoming the learning curve.
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Affiliation(s)
- Po-Fan Hsieh
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
- School of Medicine, China Medical University, Taichung 404, Taiwan
| | - Po-I Li
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
| | - Wei-Ching Lin
- School of Medicine, China Medical University, Taichung 404, Taiwan
- Department of Radiology, China Medical University Hospital, Taichung 404, Taiwan
| | - Han Chang
- School of Medicine, China Medical University, Taichung 404, Taiwan
- Department of Pathology, China Medical University Hospital, Taichung 404, Taiwan
| | - Chao-Hsiang Chang
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
| | - Hsi-Chin Wu
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
- Department of Urology, China Medical University Beigang Hospital, Yunlin 651, Taiwan
| | - Yi-Huei Chang
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
| | - Yu-De Wang
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
| | - Wen-Chin Huang
- Graduate Institute of Biomedical Sciences, School of Medicine, China Medical University, Taichung 404, Taiwan
- International Master’s Program of Biomedical Sciences, School of Medicine, China Medical University, Taichung 404, Taiwan
- Correspondence: (W.-C.H.); (C.-P.H.); Tel.: +886-4-2205-2121 (ext. 2955) (C.-P.H.)
| | - Chi-Ping Huang
- Department of Urology, China Medical University Hospital, Taichung 404, Taiwan
- School of Medicine, China Medical University, Taichung 404, Taiwan
- Correspondence: (W.-C.H.); (C.-P.H.); Tel.: +886-4-2205-2121 (ext. 2955) (C.-P.H.)
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Iacob R, Stoicescu ER, Cerbu S, Manolescu DL, Bardan R, Cumpănaş A. Could Biparametric MRI Replace Multiparametric MRI in the Management of Prostate Cancer? Life (Basel) 2023; 13:465. [PMID: 36836822 PMCID: PMC9961917 DOI: 10.3390/life13020465] [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: 01/15/2023] [Revised: 02/02/2023] [Accepted: 02/04/2023] [Indexed: 02/11/2023] Open
Abstract
Prostate cancer (PCa) is a worldwide epidemiological problem, since it is one of the most prevalent types of neoplasia among men, and the third-leading cause of cancer-related deaths, after lung and colorectal tumors. Unfortunately, the early stages of PCa have a wide range of unspecific symptoms. For these reasons, early diagnosis and accurate evaluation of suspicious lesions are crucial. Multiparametric MRI (mpMRI) is currently the imaging modality of choice for diagnostic screening and local staging of PCa, but also has a leading role in guiding biopsies and in treatment biparametric MRI (bpMRI) could partially replace mpMRI due to its lack of adverse reactions caused by contrast agents, relatively lower costs, and shorter acquisition time. Further, 31 relevant articles regarding the advantages and disadvantages of the aforementioned imaging techniques were scanned. As a result, while bpMRI has comparable accuracy in detecting PCa, its roles in the other steps of PCa management are limited.
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Affiliation(s)
- Roxana Iacob
- Doctoral School, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
- Discipline of Radiology and Medical Imaging, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
| | - Emil-Robert Stoicescu
- Doctoral School, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
- Discipline of Radiology and Medical Imaging, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
- Research Center for Pharmaco-Toxicological Evaluations, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
| | - Simona Cerbu
- Discipline of Radiology and Medical Imaging, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
| | - Diana-Luminiţa Manolescu
- Discipline of Radiology and Medical Imaging, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
- Center for Research and Innovation in Precision Medicine of Respiratory Diseases (CRIPMRD), “Victor Babeș” University of Medicine and Pharmacy, 300041 Timișoara, Romania
| | - Răzvan Bardan
- Discipline of Urology, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
| | - Alin Cumpănaş
- Discipline of Urology, “Victor Babes” University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square No. 2, 300041 Timisoara, Romania
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Song J, Zhao C, Zhang F, Yuan Y, Wang LM, Sah V, Zhang J, Weng W, Yang Z, Wang Z, Wang L. The diagnostic performance in clinically significant prostate cancer with PI-RADS version 2.1: simplified bpMRI versus standard mpMRI. Abdom Radiol (NY) 2023; 48:704-712. [PMID: 36464756 DOI: 10.1007/s00261-022-03750-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/13/2022] [Accepted: 11/14/2022] [Indexed: 12/07/2022]
Abstract
OBJECTIVES To compare the diagnostic performance for the detection of clinically significant prostate cancer (csPCa) between bpMRI with only axial T2WI (simplified bpMRI) and standard-multiparametric MRI (mpMRI). METHODS A total of 569 patients who underwent mpMRI followed by biopsy or prostatectomy were enrolled in this retrospective study. According to PI-RADS v2.1, three radiologists (A, B, C) from three centers blinded to clinical variables were assigned scores on lesions with simplified bpMRI and then with mpMRI 2 weeks later. Diagnostic performance of simplified bpMRI was compared with mpMRI using histopathology as reference standard. RESULTS For all the three radiologists, the diagnostic sensitivity was significantly higher with mpMRI than with simplified bpMRI (P < 0.001 to P = 0.035); and although specificity was also higher with mpMRI than with simplified bpMRI for radiologist B and radiologist C, it was statistically significant only for radiologist B (P = 0.011, P = 0.359, respectively). On the contrary, for radiologist A, specificity was higher with simplified bpMRI than with mpMRI (P = 0.001). The area under the receiver operating characteristic curve (AUC) was significantly higher for mpMRI than for simplified bpMRI except for radiologist A (radiologist A: 0.903 vs 0.913, P = 0.1542; radiologist B: 0.861 vs 0.834 P = 0.0013; and radiologist C: 0.884 vs 0.848, P = 0.0003). Interobserver reliability of PI-RADS v2.1 showed good agreement for both simplified bpMRI (kappa = 0.665) and mpMRI (kappa = 0.739). CONCLUSION Although the detection of csPCa with simplified bpMRI was comparatively lower than that with mpMRI, the diagnostic performance was still high in simplified bpMRI. Our data justify using mpMRI outperforms simplified bpMRI for prostate cancer screening and imply simplified bpMRI as a potential screening tool.
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Affiliation(s)
- Jihui Song
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- Department of Radiology, Dalian University Affiliated Xinhua Hospital, No.156 Wansui Street, Shahekou District, Dalian, 116021, Liaoning, China
| | - Chenglin Zhao
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Fei Zhang
- Department of Radiology, QUFU City People Hospital, No.111 Chunqiu West Road, Qufu, 273100, Shandong, China
| | - Yingdi Yuan
- Department of Radiology, Ganzhou District People's Hospital, No.705 Beihuan Road, Ganzhou District, Zhangye, 734000, Gansu, China
| | - Lee M Wang
- Carnegie Mellon University, Pittsburgh, USA
| | - Vivek Sah
- ADK Hospital, Sosun Magu, Male, 20070, Maldives
| | - Jun Zhang
- Department of Radiology, The First Hospital of Qinhuangdao, No.258 Wenhua Road, Haigang District, Qinhuangdao, 066000, Hebei, China
| | - Wencai Weng
- Department of Radiology, Dalian University Affiliated Xinhua Hospital, No.156 Wansui Street, Shahekou District, Dalian, 116021, Liaoning, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Liang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
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Index lesion detection in multifocal prostate cancer: Simplified PI-RADS biparametric MRI vs PI-RADS v2.1 multiparametric MRI. Clin Imaging 2023; 94:108-115. [PMID: 36527796 DOI: 10.1016/j.clinimag.2022.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 11/01/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022]
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Sun Z, Wang H, Fu W, Zhu S, Song G. MRI-based analysis of different clinically significant prostate cancer detection rate of prostate imaging reporting and data system score 4 in the peripheral zone. ABDOMINAL RADIOLOGY (NEW YORK) 2023; 48:390-398. [PMID: 36305943 DOI: 10.1007/s00261-022-03712-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 10/08/2022] [Accepted: 10/11/2022] [Indexed: 01/21/2023]
Abstract
PURPOSE To compare the clinically significant prostate cancer (csPCa) detection rate between diffusion-weighted imaging (DWI) 4 and DWI 3 with positive dynamic contrast-enhanced (DCE) (hereinafter called 'DWI 3/DCE+') lesions in the peripheral zone (PZ) and to explore the diagnostic performance of targeted biopsy (TB) or systematic biopsy (SB) in patients with Prostate Imaging Reporting and Data System (PI-RADS) 4 lesions. METHODS We retrospectively enrolled 206 patients who underwent multiparametric magnetic resonance imaging and had at least one PI-RADS 4 lesion in the PZ. All patients subsequently underwent combined magnetic resonance imaging/ultrasound fusion-guided TB and ultrasound-guided 12-core SB. The chi-square test was used to compare the csPCa detection rates between DWI 4 and DWI 3/DCE+ lesions. Based on the TB + SB results as a standard reference, we analyzed the sensitivity, negative predictive value, and diagnostic accuracy of TB alone or SB alone. RESULTS Patients with DWI 4 lesions had higher csPCa detection rate than those with DWI 3/DCE+ lesions when using TB + SB, TB, and SB, and the differences were significant for TB + SB (72.22 vs. 54.84%, p = 0.015) or SB (65.97 vs. 46.77%, p = 0.010). For DWI 3/DCE+ patients whose prostate-specific antigen levels ranged from 4 to 10 ng/mL, TB alone showed the highest negative predictive value (95% Cl 78.12-100). CONCLUSIONS DWI 4 tends to have worse results than DWI 3/DCE+. TB has great diagnostic performances in DWI 3/DCE+ patients, especially for those prostate-specific antigen ranging from 4 to 10 ng/mL.
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Affiliation(s)
- Zhoujie Sun
- Department of Urology, Peking University First Hospital, No.8 Xishiku St. Xicheng District, Beijing, 100034, China
- Institute of Urology, Peking University, Beijing, 100034, China
- The National Urological Cancer Center of China, Beijing, 100034, China
| | - He Wang
- Department of Radiology, Peking University First Hospital, Beijing, 100034, China
| | - Weixiao Fu
- Department of Urology, Peking University First Hospital, No.8 Xishiku St. Xicheng District, Beijing, 100034, China
- Institute of Urology, Peking University, Beijing, 100034, China
- The National Urological Cancer Center of China, Beijing, 100034, China
| | - Sainan Zhu
- Department of Statistics, Peking University First Hospital, Beijing, 100034, China
| | - Gang Song
- Department of Urology, Peking University First Hospital, No.8 Xishiku St. Xicheng District, Beijing, 100034, China.
- Institute of Urology, Peking University, Beijing, 100034, China.
- The National Urological Cancer Center of China, Beijing, 100034, China.
- Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Zhao L, Bao J, Qiao X, Jin P, Ji Y, Li Z, Zhang J, Su Y, Ji L, Shen J, Zhang Y, Niu L, Xie W, Hu C, Shen H, Wang X, Liu J, Tian J. Predicting clinically significant prostate cancer with a deep learning approach: a multicentre retrospective study. Eur J Nucl Med Mol Imaging 2023; 50:727-741. [PMID: 36409317 PMCID: PMC9852176 DOI: 10.1007/s00259-022-06036-9] [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: 04/18/2022] [Accepted: 11/06/2022] [Indexed: 11/22/2022]
Abstract
PURPOSE This study aimed to develop deep learning (DL) models based on multicentre biparametric magnetic resonance imaging (bpMRI) for the diagnosis of clinically significant prostate cancer (csPCa) and compare the performance of these models with that of the Prostate Imaging and Reporting and Data System (PI-RADS) assessment by expert radiologists based on multiparametric MRI (mpMRI). METHODS We included 1861 consecutive male patients who underwent radical prostatectomy or biopsy at seven hospitals with mpMRI. These patients were divided into the training (1216 patients in three hospitals) and external validation cohorts (645 patients in four hospitals). PI-RADS assessment was performed by expert radiologists. We developed DL models for the classification between benign and malignant lesions (DL-BM) and that between csPCa and non-csPCa (DL-CS). An integrated model combining PI-RADS and the DL-CS model, abbreviated as PIDL-CS, was developed. The performances of the DL models and PIDL-CS were compared with that of PI-RADS. RESULTS In each external validation cohort, the area under the receiver operating characteristic curve (AUC) values of the DL-BM and DL-CS models were not significantly different from that of PI-RADS (P > 0.05), whereas the AUC of PIDL-CS was superior to that of PI-RADS (P < 0.05), except for one external validation cohort (P > 0.05). The specificity of PIDL-CS for the detection of csPCa was much higher than that of PI-RADS (P < 0.05). CONCLUSION Our proposed DL models can be a potential non-invasive auxiliary tool for predicting csPCa. Furthermore, PIDL-CS greatly increased the specificity of csPCa detection compared with PI-RADS assessment by expert radiologists, greatly reducing unnecessary biopsies and helping radiologists achieve a precise diagnosis of csPCa.
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Affiliation(s)
- Litao Zhao
- School of Engineering Medicine, Beihang University, Beijing, 100191 China ,Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, 100191 China ,School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191 China
| | - Jie Bao
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
| | - Xiaomeng Qiao
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
| | - Pengfei Jin
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
| | - Yanting Ji
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China ,Department of Radiology, The Affiliated Zhangjiagang Hospital of Soochow University, Zhangjiagang, 215638 Jiangsu China
| | - Zhenkai Li
- Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, 215028 Jiangsu China
| | - Ji Zhang
- Department of Radiology, The People’s Hospital of Taizhou, Taizhou, 225399 Jiangsu China
| | - Yueting Su
- Department of Radiology, The People’s Hospital of Taizhou, Taizhou, 225399 Jiangsu China
| | - Libiao Ji
- Department of Radiology, Changshu No.1 People’s Hospital, Changshu, 215501 Jiangsu China
| | - Junkang Shen
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004 Jiangsu China
| | - Yueyue Zhang
- Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004 Jiangsu China
| | - Lei Niu
- Department of Radiology, The People’s Hospital of Suqian, Suqian, 223812 Jiangsu China
| | - Wanfang Xie
- School of Engineering Medicine, Beihang University, Beijing, 100191 China ,Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, 100191 China ,School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191 China
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
| | - Hailin Shen
- Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiaotong University School of Medicine, Suzhou, 215028 Jiangsu China
| | - Ximing Wang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006 Jiangsu China
| | - Jiangang Liu
- School of Engineering Medicine, Beihang University, Beijing, 100191 China ,Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, 100191 China
| | - Jie Tian
- School of Engineering Medicine, Beihang University, Beijing, 100191 China ,Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing, 100191 China
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Wei X, Zhu L, Zeng Y, Xue K, Dai Y, Xu J, Liu G, Liu F, Xue W, Wu D, Wu G. Detection of prostate cancer using diffusion-relaxation correlation spectrum imaging with support vector machine model - a feasibility study. Cancer Imaging 2022; 22:77. [PMID: 36575555 PMCID: PMC9795630 DOI: 10.1186/s40644-022-00516-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 12/19/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND To evaluate the performance of diffusion-relaxation correlation spectrum imaging (DR-CSI) with support vector machine (SVM) in detecting prostate cancer (PCa). METHODS In total, 114 patients (mean age, 66 years, range, 48-87 years) who received a prostate MRI and underwent biopsy were enrolled in three stages. Thirty-nine were assigned for the exploration stage to establish the model, 18 for the validation stage to choose the appropriate scale for mapping and 57 for the test stage to compare the diagnostic performance of the DR-CSI and PI-RADS. RESULTS In the exploration stage, the DR-CSI model was established and performed better than the ADC and T2 values (both P < 0.001). The validation result shows that at least 2 pixels were required for both the long-axis and short-axis in the mapping procedure. In the test stage, DR-CSI had higher accuracy than PI-RADS ≥ 3 as a positive finding based on patient (84.2% vs. 63.2%, P = 0.004) and lesion (78.8% vs. 57.6%, P = 0.001) as well as PI-RADS ≥ 4 on lesion (76.5% vs. 64.7%, P = 0.029), while there was no significant difference between DR-CSI and PI-RADS ≥ 4 based on patient (P = 0.508). For clinically significant PCa, DR-CSI had higher accuracy than PI-RADS ≥ 3 based on patients (84.2% vs. 63.2%, P = 0.004) and lesions (62.4% vs. 48.2%, P = 0.036). There was no significant difference between DR-CSI and PI-RADS ≥ 4 (P = 1.000 and 0.845 for the patient and lesion levels, respectively). CONCLUSIONS DR-CSI combined with the SVM model may improve the diagnostic accuracy of PCa. TRIAL REGISTRATION This study was approved by the Ethics Committee of our institute (Approval No. KY2018-213). Written informed consent was obtained from all participants.
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Affiliation(s)
- Xiaobin Wei
- grid.16821.3c0000 0004 0368 8293Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Li Zhu
- grid.16821.3c0000 0004 0368 8293Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yanyan Zeng
- Quanzhou Maternity and Children’s Hospital, Fujian, China
| | - Ke Xue
- grid.497849.fCentral Research Institute, MR Collaboration, United Imaging Healthcare, Shanghai, China
| | - Yongming Dai
- grid.497849.fCentral Research Institute, MR Collaboration, United Imaging Healthcare, Shanghai, China
| | - Jianrong Xu
- grid.16821.3c0000 0004 0368 8293Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Guiqin Liu
- grid.16821.3c0000 0004 0368 8293Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Fang Liu
- grid.16821.3c0000 0004 0368 8293Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Xue
- grid.16821.3c0000 0004 0368 8293Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Dongmei Wu
- grid.22069.3f0000 0004 0369 6365Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, Shanghai, China
| | - Guangyu Wu
- grid.16821.3c0000 0004 0368 8293Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Prebiopsy bpMRI and hematological parameter-based risk scoring model for predicting outcomes in biopsy-naive men with PSA 4-20 ng/mL. Sci Rep 2022; 12:21895. [PMID: 36536031 PMCID: PMC9763436 DOI: 10.1038/s41598-022-26242-7] [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: 09/03/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
Excessive prostate biopsy is a common problem for clinicians. Although some hematological and bi-parametric magnetic resonance imaging (bpMRI) parameters might help increase the rate of positive prostate biopsies, there is a lack of studies on whether their combination can further improve clinical detection efficiency. We retrospectively enrolled 394 patients with PSA levels of 4-20 ng/mL who underwent prebiopsy bpMRI during 2010-2021. Based on bpMRI and hematological indicators, six models and a nomogram were constructed to predict the outcomes of biopsy. Furthermore, we constructed and evaluated a risk scoring model based on the nomogram. Age, prostate-specific antigen (PSA) density (PSAD), systemic immune-inflammation index, cystatin C level, and the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 score were significant predictors of prostate cancer (PCa) on multivariable logistic regression analyses (P < 0.05) and the five parameters were used to construct the XYFY nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was 0.916. Based on the nomogram, a risk scoring model (XYFY risk model) was constructed and then we divided the patients into low-(XYFY score: < 95), medium-(XYFY score: 95-150), and, high-risk (XYFY score: > 150) groups. The predictive values for diagnosis of PCa and clinically-significant PCa among the three risk groups were 3.0%(6/201), 41.8%(51/122), 91.5%(65/71); 0.5%(1/201), 19.7%(24/122), 60.6%(43/71), respectively. In conclusion, in this study, we used hematological and bpMRI parameters to establish and internally validate a XYFY risk scoring model for predicting the biopsy outcomes for patients with PSA levels of 4-20 ng/mL and this risk model would support clinical decision-making and reduce excessive biopsies.
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Alver KH, Yagci AB, Utebey AR, Turk NS, Ufuk F. Comparison of Multiparametric and Fast MRI Protocols in Detecting Clinically Significant Prostate Cancer and a Detailed Cost Analysis. J Magn Reson Imaging 2022; 56:1437-1447. [PMID: 35274792 DOI: 10.1002/jmri.28142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 02/20/2022] [Accepted: 02/25/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Due to the long acquisition time and high cost of multiparametric magnetic resonance imaging (mpMRI), biparametric and, more recently, fast prostate magnetic resonance imaging (fpMRI) protocols have been described. However, there is insufficient data about the diagnostic performance and cost of fpMRI. PURPOSE To compare the diagnostic performances and cost analysis of fpMRI and mpMRI in clinically significant prostate cancer (csPCA). STUDY TYPE Retrospective. POPULATION A total of 103 patients (63 had csPCA) with a mean age of 66.83 (± 7.22) years were included. FIELD STRENGTH/SEQUENCE A 1.5-T; T1- and T2-weighted turbo spin-echo imaging (T1WI and T2WI), echo-planar diffusion-weighted images, and dynamic contrast-enhanced T1W imaging. ASSESSMENT Three readers independently evaluated the fpMRI and mpMRI images in different sessions blinded to all patient information. Diagnostic performances of fpMRI and mpMRI were evaluated. Kappa coefficient (κ) was used to determine the interreader and intrareader agreement. A detailed cost analysis was performed for each protocol. STATISTICAL TESTS Receiver operating characteristics analysis, area under the curve (AUC), and κ test were used. Diagnostic performance parameters were also calculated. RESULTS Of the 63 malignant index lesions (csPCA), 53/63 of those (84.1%) originated from the peripheral zone and 10/63 lesions (15.9%) originated from the transition zone. The AUC values for fpMRI were 0.878 for reader 1, 0.937 for reader 2, and 0.855 for reader 3. For mpMRI, the AUC values were 0.893 for reader 1, 0.94 for reader 2, and 0.862 for reader 3. Inter and intrareader agreements were moderate to substantial (κ range, 0.5-0.79). The total cost per examination was calculated as €12.39 and €30.10 for fpMRI and mpMRI, respectively. DATA CONCLUSIONS Fast MRI protocol has similar diagnostic performance with mpMRI in detecting csPCA, and fpMRI can be considered an alternative protocol that could create a lower financial burden on health-care systems. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY STAGE: 6.
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Affiliation(s)
- Kadir Han Alver
- Department of Radiology, School of Medicine, University of Pamukkale, Denizli, Turkey
| | - Ahmet Baki Yagci
- Department of Radiology, School of Medicine, University of Pamukkale, Denizli, Turkey
| | - Ayse Ruksan Utebey
- Department of Radiology, School of Medicine, University of Pamukkale, Denizli, Turkey
| | - Nilay Sen Turk
- Department of Pathology, School of Medicine, University of Pamukkale, Denizli, Turkey
| | - Furkan Ufuk
- Department of Radiology, School of Medicine, University of Pamukkale, Denizli, Turkey
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Anderson MA, Mercaldo S, Chung R, Ulrich E, Jones RW, Harisinghani M. Improving Prostate Cancer Detection With MRI: A Multi-Reader, Multi-Case Study Using Computer-Aided Detection (CAD). Acad Radiol 2022:S1076-6332(22)00500-1. [DOI: 10.1016/j.acra.2022.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/06/2022] [Accepted: 09/12/2022] [Indexed: 11/01/2022]
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Zhu L, Gao G, Zhu Y, Han C, Liu X, Li D, Liu W, Wang X, Zhang J, Zhang X, Wang X. Fully automated detection and localization of clinically significant prostate cancer on MR images using a cascaded convolutional neural network. Front Oncol 2022; 12:958065. [PMID: 36249048 PMCID: PMC9558117 DOI: 10.3389/fonc.2022.958065] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose To develop a cascaded deep learning model trained with apparent diffusion coefficient (ADC) and T2-weighted imaging (T2WI) for fully automated detection and localization of clinically significant prostate cancer (csPCa). Methods This retrospective study included 347 consecutive patients (235 csPCa, 112 non-csPCa) with high-quality prostate MRI data, which were randomly selected for training, validation, and testing. The ground truth was obtained using manual csPCa lesion segmentation, according to pathological results. The proposed cascaded model based on Res-UNet takes prostate MR images (T2WI+ADC or only ADC) as inputs and automatically segments the whole prostate gland, the anatomic zones, and the csPCa region step by step. The performance of the models was evaluated and compared with PI-RADS (version 2.1) assessment using sensitivity, specificity, accuracy, and Dice similarity coefficient (DSC) in the held-out test set. Results In the test set, the per-lesion sensitivity of the biparametric (ADC + T2WI) model, ADC model, and PI-RADS assessment were 95.5% (84/88), 94.3% (83/88), and 94.3% (83/88) respectively (all p > 0.05). Additionally, the mean DSC based on the csPCa lesions were 0.64 ± 0.24 and 0.66 ± 0.23 for the biparametric model and ADC model, respectively. The sensitivity, specificity, and accuracy of the biparametric model were 95.6% (108/113), 91.5% (665/727), and 92.0% (773/840) based on sextant, and were 98.6% (68/69), 64.8% (46/71), and 81.4% (114/140) based on patients. The biparametric model had a similar performance to PI-RADS assessment (p > 0.05) and had higher specificity than the ADC model (86.8% [631/727], p< 0.001) based on sextant. Conclusion The cascaded deep learning model trained with ADC and T2WI achieves good performance for automated csPCa detection and localization.
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Affiliation(s)
- Lina Zhu
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ge Gao
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Yi Zhu
- Department of Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Chao Han
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Xiang Liu
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Derun Li
- Department of Urology, Peking University First Hospital, Beijing, China
| | - Weipeng Liu
- Department of Development and Research, Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China
| | - Xiangpeng Wang
- Department of Development and Research, Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China
| | - Jingyuan Zhang
- Department of Development and Research, Beijing Smart Tree Medical Technology Co. Ltd., Beijing, China
| | - Xiaodong Zhang
- Department of Radiology, Peking University First Hospital, Beijing, China
| | - Xiaoying Wang
- Department of Radiology, Peking University First Hospital, Beijing, China
- *Correspondence: Xiaoying Wang,
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Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review. Cancers (Basel) 2022; 14:cancers14194747. [PMID: 36230670 PMCID: PMC9562712 DOI: 10.3390/cancers14194747] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 11/18/2022] Open
Abstract
Simple Summary Magnetic resonance imaging (MRI) has allowed the early detection of PCa to evolve towards clinically significant PCa (csPCa), decreasing unnecessary prostate biopsies and overdetection of insignificant tumours. MRI identifies suspicious lesions of csPCa, predicting the semi-quantitative risk through the prostate imaging report and data system (PI-RADS), and enables guided biopsies, increasing the sensitivity of csPCa. Predictive models that individualise the risk of csPCa have also evolved adding PI-RADS score (MRI-PMs), improving the selection of candidates for prostate biopsy beyond the PI-RADS category. During the last five years, many MRI-PMs have been developed. Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness through a systematic review. We have found high heterogeneity between MRI technique, PI-RADS versions, biopsy schemes and approaches, and csPCa definitions. MRI-PMs outperform the selection of candidates for prostate biopsy beyond MRI alone and PMs based on clinical predictors. However, few developed MRI-PMs are externally validated or have available risk calculators (RCs), which constitute the appropriate requirements used in routine clinical practice. Abstract MRI can identify suspicious lesions, providing the semi-quantitative risk of csPCa through the Prostate Imaging-Report and Data System (PI-RADS). Predictive models of clinical variables that individualise the risk of csPCa have been developed by adding PI-RADS score (MRI-PMs). Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness. A systematic review was performed after a literature search performed by two independent investigators in PubMed, Cochrane, and Web of Science databases, with the Medical Subjects Headings (MESH): predictive model, nomogram, risk model, magnetic resonance imaging, PI-RADS, prostate cancer, and prostate biopsy. This review was made following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria and studied eligibility based on the Participants, Intervention, Comparator, and Outcomes (PICO) strategy. Among 723 initial identified registers, 18 studies were finally selected. Warp analysis of selected studies was performed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Clinical predictors in addition to the PI-RADS score in developed MRI-PMs were age, PCa family history, digital rectal examination, biopsy status (initial vs. repeat), ethnicity, serum PSA, prostate volume measured by MRI, or calculated PSA density. All MRI-PMs improved the prediction of csPCa made by clinical predictors or imaging alone and achieved most areas under the curve between 0.78 and 0.92. Among 18 developed MRI-PMs, 7 had any external validation, and two RCs were available. The updated PI-RADS version 2 was exclusively used in 11 MRI-PMs. The performance of MRI-PMs according to PI-RADS was only analysed in a single study. We conclude that MRI-PMs improve the selection of candidates for prostate biopsy beyond the PI-RADS category. However, few developed MRI-PMs meet the appropriate requirements in routine clinical practice.
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Thaiss WM, Moser S, Hepp T, Kruck S, Rausch S, Scharpf M, Nikolaou K, Stenzl A, Bedke J, Kaufmann S. Head-to-head comparison of biparametric versus multiparametric MRI of the prostate before robot-assisted transperineal fusion prostate biopsy. World J Urol 2022; 40:2431-2438. [PMID: 35922717 PMCID: PMC9512861 DOI: 10.1007/s00345-022-04120-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 07/23/2022] [Indexed: 11/30/2022] Open
Abstract
Purpose Prostate biparametric magnetic resonance imaging (bpMRI) including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) might be an alternative to multiparametric MRI (mpMRI, including dynamic contrast imaging, DCE) to detect and guide targeted biopsy in patients with suspected prostate cancer (PCa). However, there is no upgrading peripheral zone PI-RADS 3 to PI-RADS 4 without DCE in bpMRI. The aim of this study was to evaluate bpMRI against mpMRI in biopsy-naïve men with elevated prostate-specific antigen (PSA) scheduled for robot-assisted-transperineal fusion-prostate biopsy (RA-TB). Methods Retrospective single-center-study of 563 biopsy-naïve men (from 01/2015 to 09/2018, mean PSA 9.7 ± 6.5 ng/mL) with PI-RADSv2.1 conform mpMRI at 3 T before RA-TB. Clinically significant prostate cancer (csPCa) was defined as ISUP grade ≥ 2 in any core. Two experienced readers independently evaluated images according to PI-RADSv2.1 criteria (separate readings for bpMRI and mpMRI sequences, 6-month interval). Reference standard was histology from RA-TB. Results PI-RADS 2 was scored in 5.1% of cases (3.4% cancer/3.4% csPCa), PI-RADS 3 in 16.9% (32.6%/3.2%), PI-RADS 4 in 57.6% (66.1%/58.3%) and PI-RADS 5 in 20.4% of cases (79.1%/74.8%). For mpMRI/bpMRI test comparison, sensitivity was 99.0%/97.1% (p < 0.001), specificity 47.5%/61.2% (p < 0.001), PPV 69.5%/75.1% (p < 0.001) and NPV 97.6%/94.6% (n.s.). csPCa was considered gold standard. 35 cases without cancer were upgraded to PI-RADS 4 (mpMRI) and six PI-RADS 3 cases with csPCa were not upgraded (bpMRI). Conclusion In patients planned for RA-TB with elevated PSA and clinical suspicion for PCa, specificity was higher in bpMRI vs. mpMRI, which could solve constrains regarding time and contrast agent.
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Affiliation(s)
- Wolfgang M Thaiss
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
- Department of Nuclear Medicine, University Hospital Ulm, Albert-Einstein-Allee 23, 89081, Ulm, Germany
| | - Simone Moser
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
| | - Tobias Hepp
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
| | - Stephan Kruck
- Department of Urology, Siloah St. Trudpert Klinikum, Wilferdinger Str. 67, 75179, Pforzheim, Germany
| | - Steffen Rausch
- Department of Urology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
| | - Marcus Scharpf
- Department of Pathology and Neuropathology, Eberhard-Karls-University, Liebermeisterstr. 8, 72076, Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
| | - Arnulf Stenzl
- Department of Urology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
| | - Jens Bedke
- Department of Urology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany.
| | - Sascha Kaufmann
- Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076, Tübingen, Germany
- Diagnostic and Interventional Radiology, Siloah St. Trudpert Klinikum, Pforzheim, Germany
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Comparison between biparametric and multiparametric MRI diagnosis strategy for prostate cancer in the peripheral zone using PI-RADS version 2.1. ABDOMINAL RADIOLOGY (NEW YORK) 2022; 47:2905-2916. [PMID: 35622121 DOI: 10.1007/s00261-022-03553-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 01/18/2023]
Abstract
PURPOSE To compare and analyse the diagnostic value of PI-RADS v2.1 when used with biparametric MRI (bpMRI) versus multiparametric MRI (mpMRI), DWI versus T2WI to detect peripheral-zone prostate cancer (pzPCa) and clinically significant peripheral-zone prostate cancer (cs-pzPCa). METHODS The diagnostic efficiencies of mpMRI and bpMRI as well as DWI and T2WI in pzPCa and cs-pzPCa were compared using a PI-RADS score of ≥ 4 as the positive threshold and prostate biopsy and radical prostatectomy as the reference standards. RESULTS A total of 307 prostate cases were included in the study, including 142 in the non-pzPCa group, 165 in the pzPCa group, and 130 in the cs-pzPCa group. The AUCs of mpMRI and bpMRI were 0.717 and 0.733 (P = 0.317), respectively, for the diagnosis of pzPCa (sensitivities: 89.1% and 81.8%; specificities: 54.2% and 64.8%, both P < 0.001) and 0.594 and 0.602 (P = 0.756), respectively, for the diagnosis of cs-pzPCa (sensitivities: 93.1% and 86.2%, P = 0.004; specificities: 25.7% and 34.3%, P = 0.250). The AUCs of DWI and T2WI were 0.733 and 0.749 (P = 0.308), respectively, for the diagnosis of pzPCa (sensitivities: 81.8% and 84.2%; specificities: 64.8% and 66.2%, both P > 0.05) and 0.602 and 0.581 (P = 0.371), respectively, for the diagnosis of cs-pzPCa (sensitivities: 86.2% and 87.7%; specificities: 34.3% and 28.6%, both P > 0.05). CONCLUSION mpMRI and bpMRI as well as DWI and T2WI using PI-RADS v2.1 exhibited similar diagnostic efficiency in pzPCa and cs-pzPCa.
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