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Garcia-Becerra CA, Arias-Gallardo MI, Soltero-Molinar V, Juarez-Garcia JE, Rivera-Rocha MI, Parra-Camaño LF, Garcia-Becerra N, Garcia-Gutierrez CM. Is biparametric MRI a feasible option for detecting clinically significant prostate cancer?: A systematic review and meta-analysis. Urol Oncol 2025; 43:396.e9-396.e17. [PMID: 39753482 DOI: 10.1016/j.urolonc.2024.12.262] [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: 09/08/2024] [Revised: 09/09/2024] [Accepted: 12/10/2024] [Indexed: 05/19/2025]
Abstract
BACKGROUND Multiparametric MRI (Mp-MRI) is a key tool to screen for Prostate Cancer (Pca) and Clinically Significant Prostate Cancer (CsPca). It primarily includes T2-Weighted imaging (T2w), diffusion-weighted imaging (DWI), and Dynamic Contrast-Enhanced imaging (DCE). Despite its improvements in CsPca screening, concerns about the cost-effectiveness of DCE persist due to its associated side effects, increased cost, longer acquisition time, and limitations in patients with poor kidney function. Recent studies have explored Biparametric MRI (Bp-MRI) as an alternative that excludes DCE. OBJECTIVES The main objective of this study is to compile and evaluate updated results of Bp-MRI as a diagnostic alternative to detect CsPca. METHODS A systematic review was conducted using PubMed, Central Cochrane, and ClinicalTrialls.gov registry. Inclusion criteria was focused on observational and experimental studies that assessed a direct comparison of Bp-MRI and Mp-MRI for CsPca detection. The primary outcomes included were necessary to create a contingency 2×2 table and CsPca prevalence from each study. The secondary outcomes included were demographic data and imaging protocol features. The statistical analysis used a Bivariate Random-Effect model to estimate the pooled sensitivity, specificity, and area under the curve (AUC). An univariate random-effect model was conducted to estimate the positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies -2 tool. RESULTS From 534 articles initially identified, 19 studies met the inclusion criteria with a total of 5075 patients. The pooled sensitivity estimated was 0.89, pooled specificity was 0.73, and AUC was 0.90; these results showed a slight increase compared to previous studies. CONCLUSION The results obtained showed that Bp-MRI is a feasible alternative to detect CsPca, which demonstrates high diagnostic accuracy and avoids the drawbacks associated with DCE. REGISTRY This is a sub-analysis of the protocol registered at PROSPERO (CRD42024552125).
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Affiliation(s)
| | | | - Veronica Soltero-Molinar
- Basic Science Institute, School of Medicine, Autonomous University of Guadalajara, Guadalajara, México
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Syer T, Carmo B, Sanmugalingam N, Lawson B, Chishaya W, Shepherd C, Barrett T, Caglic I. On-table monitoring of prostate MRI could enable tailored utilisation of gadolinium contrast. Eur Radiol 2025:10.1007/s00330-025-11479-3. [PMID: 40088286 DOI: 10.1007/s00330-025-11479-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2024] [Revised: 01/10/2025] [Accepted: 02/10/2025] [Indexed: 03/17/2025]
Abstract
OBJECTIVES To compare the impact of on-table monitoring vs standard-of-care multiparametric MRI (mpMRI) for the utilisation of gadolinium contrast use in prostate MRI. MATERIALS AND METHODS This retrospective observation study of prospectively acquired data was conducted at a single institution over an 18-month period. A cohort of patients undergoing MRI for suspected prostate cancer (PCa) underwent on-table monitoring where their T2 and DWI images were reviewed by a supervising radiologist during the scan to decide whether to acquire dynamic contrast-enhanced (DCE) sequences. MRI scans were reported using PI-RADS v2.1, patients were followed up with biopsy for at least 12 months. The rate of gadolinium administration, biopsy rates, and diagnostic accuracy were compared to that of a standard-of-care control group undergoing mpMRI during the same period using propensity score matching. Estimates of cost savings were also calculated. RESULTS 1410 patients were identified and after propensity score matching 598 patients were analysed, with 178 undergoing on-table monitoring. Seventy-five and eight tenths (135/178) of patients did not receive gadolinium. Contrast was used mainly for indeterminate lesions (27/43) and significant artefacts on bpMRI (14/43). When comparing the monitored cohort to a non-monitored control group, there was a comparable number of biopsies performed (52.2% vs 49.5%, p = 0.54), PI-RADS 3/5 scoring rates (10.1% vs 7.4%, p = 0.27), sensitivity (98.3% vs 99.2%, p = 0.56), and specificity (63.9% vs 70.7%, p = 0.18) for detection of clinically-significant PCa. When acquired, DCE was deemed helpful in 67.4% (29/43) of cases and improved both PI-QUALv2 and reader confidence scores. There was an estimated saving of £56,677 over the 18-month study. CONCLUSION On-table monitoring significantly reduced the need for gadolinium contrast without compromising diagnostic accuracy and biopsy rates. KEY POINTS Question Default use of gadolinium contrast in prostate MRI is not always of clinical benefit and has associated side effects and healthcare costs. Findings On-table monitoring avoided the use of gadolinium in 75.8% of patients, reducing associated costs whilst maintaining clinically significant cancer detection, and diagnostic accuracy and improving reader confidence. Clinical relevance On-table monitoring offers personalised patient protocolling with a significant reduction in the use of gadolinium and its associated side effects and costs, potentially maximising the advantages of both multiparametric and biparametric prostate MRI.
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Affiliation(s)
- Tom Syer
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Bruno Carmo
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Nimalam Sanmugalingam
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Brooke Lawson
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Wellington Chishaya
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Christopher Shepherd
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
- Department of Radiology, University of Cambridge, Cambridge, UK.
| | - Iztok Caglic
- Department of Radiology, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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Dong Y, Wang P, Geng H, Liu Y, Wang E. Ultrasound and advanced imaging techniques in prostate cancer diagnosis: A comparative study of mpMRI, TRUS, and PET/CT. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2025; 33:436-447. [PMID: 39973788 DOI: 10.1177/08953996241304988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
ObjectiveThis study aims to assess and compare the diagnostic performance of three advanced imaging modalities-multiparametric magnetic resonance imaging (mpMRI), transrectal ultrasound (TRUS), and positron emission tomography/computed tomography (PET/CT)-in detecting prostate cancer in patients with elevated PSA levels and abnormal DRE findings.MethodsA retrospective analysis was conducted on 150 male patients aged 50-75 years with elevated PSA and abnormal DRE. The diagnostic accuracy of each modality was assessed through sensitivity, specificity, and the area under the curve (AUC) to compare performance in detecting clinically significant prostate cancer (Gleason score ≥ 7).ResultsMpMRI demonstrated the highest diagnostic performance, with a sensitivity of 90%, specificity of 85%, and AUC of 0.92, outperforming both TRUS (sensitivity 76%, specificity 78%, AUC 0.77) and PET/CT (sensitivity 82%, specificity 80%, AUC 0.81). MpMRI detected clinically significant tumors in 80% of cases. Although TRUS and PET/CT had similar detection rates for significant tumors, their overall accuracy was lower. Minor adverse events occurred in 5% of patients undergoing TRUS, while no significant complications were associated with mpMRI or PET/CT.ConclusionThese findings suggest that mpMRI is the most reliable imaging modality for early detection of clinically significant prostate cancer. It reduces the need for unnecessary biopsies and optimizes patient management.
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Affiliation(s)
- Ying Dong
- Department of Radiology, Beijing Renhe Hospital, Beijing, China
| | - Peng Wang
- Department of Imaging Diagnostic, Binzhou Hospital of Traditional Chinese Medicine, Binzhou City, China
| | - Hua Geng
- Department of Oncology, Binzhou Hospital of Traditional Chinese Medicine, Binzhou City, China
| | - Yankun Liu
- Department of Medical Imaging Center, Central Hospital Afffliated to Shandong First Medical University, Jinan City, China
| | - Enguo Wang
- Department of Medical Imaging Center, Central Hospital Afffliated to Shandong First Medical University, Jinan City, China
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Pickersgill NA, Alkazemi MH, Ostergar A, Joseph K, Vetter JM, Barashi NS, Kim EH, Andriole GL, Sivaraman A. Correlation of Prostate High-Resolution Microultrasound With Multiparametric Magnetic Resonance Imaging. Urology 2025; 197:33-39. [PMID: 39615700 DOI: 10.1016/j.urology.2024.11.048] [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: 08/11/2024] [Revised: 10/15/2024] [Accepted: 11/22/2024] [Indexed: 12/16/2024]
Abstract
OBJECTIVE To assess the correlation between high-resolution microultrasound (microUS) and multiparametric magnetic resonance imaging (MP-MRI) in clinically significant prostate cancer (csPCa) lesion identification. METHODS We reviewed our prospectively maintained database of 267 consecutive patients who underwent MP-MRI and transperineal microUS-guided biopsy between February 2021 and April 2023. The Prostate Risk Identification using MicroUS (PRI-MUS) protocol was utilized to risk stratify prostate lesions, with PRI-MUS 3-5 defined as positive. MRI lesions were classified according to the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Clinicopathologic outcomes were analyzed. Spearman correlation testing was computed to assess the relationship between PRI-MUS and PI-RADS. RESULTS A total of 161 patients met inclusion criteria. Mean±standard deviation age was 65.6±1.5years and prostate-specific antigen was 7.6±0.6ng/mL. Ninety-two patients were found to have PIRADS 3-5 lesions. Spearman correlation analysis revealed a moderate positive correlation between PRI-MUS and PI-RADS (r=0.40, P<.001). MicroUS-targeted cores detected higher grade disease than systematic and MRI-targeted cores in 8/161 (5.0%) patients. CsPCa would have been missed in 4/161 (2.5%) patients without microUS-targeted sampling. CONCLUSION MicroUS/PRI-MUS demonstrates moderate positive correlation with MP-MRI/PI-RADS and offers improved csPCa detection compared to MRI-targeted biopsy alone. MicroUS may be useful in conjunction with MP-MRI or as an alternative imaging modality in MRI-ineligible patients.
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Affiliation(s)
- Nicholas A Pickersgill
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO; Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY.
| | - Muhammad Hassan Alkazemi
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO; Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Adam Ostergar
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO; Department of Urology, Mayo Clinic, Phoenix, AZ
| | - Karan Joseph
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO
| | - Joel M Vetter
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO
| | - Nimrod S Barashi
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO
| | - Eric H Kim
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO
| | - Gerald L Andriole
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO
| | - Arjun Sivaraman
- Department of Surgery, Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO; Department of Urology, Medical College of Wisconsin, Milwaukee, WI
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Twilt JJ, Saha A, Bosma JS, van Ginneken B, Bjartell A, Padhani AR, Bonekamp D, Villeirs G, Salomon G, Giannarini G, Kalpathy-Cramer J, Barentsz J, Maier-Hein KH, Rusu M, Rouvière O, van den Bergh R, Panebianco V, Kasivisvanathan V, Obuchowski NA, Yakar D, Elschot M, Veltman J, Fütterer JJ, Huisman H, de Rooij M. Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study. Eur Urol 2025; 87:240-250. [PMID: 39438187 PMCID: PMC11769734 DOI: 10.1016/j.eururo.2024.09.035] [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: 05/06/2024] [Revised: 09/05/2024] [Accepted: 09/28/2024] [Indexed: 10/25/2024]
Abstract
BACKGROUND AND OBJECTIVE Biparametric magnetic resonance imaging (bpMRI), excluding dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), is a potential replacement for multiparametric MRI (mpMRI) in diagnosing clinically significant prostate cancer (csPCa). An extensive international multireader multicase observer study was conducted to assess the noninferiority of bpMRI to mpMRI in csPCa diagnosis. METHODS An observer study was conducted with 400 mpMRI examinations from four European centers, excluding examinations with prior prostate treatment or csPCa (Gleason grade [GG] ≥2) findings. Readers assessed bpMRI and mpMRI sequentially, assigning lesion-specific Prostate Imaging Reporting and Data System (PI-RADS) scores (3-5) and a patient-level suspicion score (0-100). The noninferiority of patient-level bpMRI versus mpMRI csPCa diagnosis was evaluated using the area under the receiver operating curve (AUROC) alongside the sensitivity and specificity at PI-RADS ≥3 with a 5% margin. The secondary outcomes included insignificant prostate cancer (GG1) diagnosis, diagnostic evaluations at alternative risk thresholds, decision curve analyses (DCAs), and subgroup analyses considering reader expertise. Histopathology and ≥3 yr of follow-up were used for the reference standard. KEY FINDINGS AND LIMITATIONS Sixty-two readers (45 centers and 20 countries) participated. The prevalence of csPCa was 33% (133/400); bpMRI and mpMRI showed similar AUROC values of 0.853 (95% confidence interval [CI], 0.819-0.887) and 0.859 (95% CI, 0.826-0.893), respectively, with a noninferior difference of -0.6% (95% CI, -1.2% to 0.1%, p < 0.001). At PI-RADS ≥3, bpMRI and mpMRI had sensitivities of 88.6% (95% CI, 84.8-92.3%) and 89.4% (95% CI, 85.8-93.1%), respectively, with a noninferior difference of -0.9% (95% CI, -1.7% to 0.0%, p < 0.001), and specificities of 58.6% (95% CI, 52.3-63.1%) and 57.7% (95% CI, 52.3-63.1%), respectively, with a noninferior difference of 0.9% (95% CI, 0.0-1.8%, p < 0.001). At alternative risk thresholds, mpMRI increased sensitivity at the expense of reduced specificity. DCA demonstrated the highest net benefit for an mpMRI pathway in cancer-averse scenarios, whereas a bpMRI pathway showed greater benefit for biopsy-averse scenarios. A subgroup analysis indicated limited additional benefit of DCE MRI for nonexperts. Limitations included that biopsies were conducted based on mpMRI imaging, and reading was performed in a sequential order. CONCLUSIONS AND CLINICAL IMPLICATIONS It has been found that bpMRI is noninferior to mpMRI in csPCa diagnosis at AUROC, along with the sensitivity and specificity at PI-RADS ≥3, showing its value in individuals without prior csPCa findings and prostate treatment. Additional randomized prospective studies are required to investigate the generalizability of outcomes.
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Affiliation(s)
- Jasper J Twilt
- Minimally Invasive Image-Guided Intervention Center, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
| | - Anindo Saha
- Minimally Invasive Image-Guided Intervention Center, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands; Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joeran S Bosma
- Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Bram van Ginneken
- Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anders Bjartell
- Department of Urology, Skåne University Hospital, Lund, Sweden; Division of Translational Cancer Research, Lund University Cancer Centre, Lund, Sweden
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, UK
| | - David Bonekamp
- Division of Radiology, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - Geert Villeirs
- Department of Diagnostic Sciences, Ghent University Hospital, Ghent, Belgium
| | - Georg Salomon
- Martini Clinic, Prostate Cancer Center, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Gianluca Giannarini
- Urology Unit, Santa Maria della Misericordia University Hospital, Udine, Italy
| | - Jayashree Kalpathy-Cramer
- Division of Artificial Medical Intelligence in Ophthalmology, University of Colorado, Boulder, CO, USA
| | - Jelle Barentsz
- Department of Medical Imaging, Andros Clinics, Amsterdam, The Netherlands
| | - Klaus H Maier-Hein
- Division of Medical Image Computing, Deutsches Krebsforschungszentrum, Heidelberg, Germany; Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Mirabela Rusu
- Departments of Radiology, Urology and Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Olivier Rouvière
- Department of Urinary and Vascular Imaging, Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France; Faculté de Médecine Lyon-Est, Université Lyon 1, Université de Lyon, Lyon, France
| | | | - Valeria Panebianco
- Department of Radiological Sciences, Oncology and Pathology, Sapienza University of Rome, Rome, Italy
| | - Veeru Kasivisvanathan
- Division of Surgery and Interventional Sciences, University College London and University College London Hospital, London, UK
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Diagnostic Radiology, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Derya Yakar
- Department of Radiology, University Medical Center Groningen, Groningen, The Netherlands; Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Mattijs Elschot
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Jeroen Veltman
- Department of Radiology, Ziekenhuisgroep Twente, Almelo, The Netherland; Department of Multi-Modality Medical Imaging, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Jurgen J Fütterer
- Minimally Invasive Image-Guided Intervention Center, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Henkjan Huisman
- Diagnostic Image Analysis Group, Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Maarten de Rooij
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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Baxter MT, Conlin CC, Bagrodia A, Barrett T, Bartsch H, Brau A, Cooperberg M, Dale AM, Guidon A, Hahn ME, Harisinghani MG, Javier-DesLoges JF, Kamran SC, Kane CJ, Kuperman JM, Margolis DJ, Murphy PM, Nakrour N, Ohliger MA, Rakow-Penner R, Shabaik A, Simko JP, Tempany CM, Wehrli N, Woolen SA, Zou J, Seibert TM. Advanced Restriction Imaging and Reconstruction Technology for Prostate Magnetic Resonance Imaging (ART-Pro): A Study Protocol for a Multicenter, Multinational Trial Evaluating Biparametric Magnetic Resonance Imaging and Advanced, Quantitative Diffusion Magnetic Resonance Imaging for the Detection of Prostate Cancer. EUR UROL SUPPL 2025; 71:132-143. [PMID: 39811103 PMCID: PMC11730575 DOI: 10.1016/j.euros.2024.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2024] [Indexed: 01/16/2025] Open
Abstract
Multiparametric magnetic resonance imaging (mpMRI) is strongly recommended by current clinical guidelines for improved detection of clinically significant prostate cancer (csPCa). However, the major limitations are the need for intravenous (IV) contrast and dependence on reader expertise. Efforts to address these issues include use of biparametric magnetic resonance imaging (bpMRI) and advanced, quantitative magnetic resonance imaging (MRI) techniques. One such advanced technique is the Restriction Spectrum Imaging restriction score (RSIrs), an imaging biomarker that has been shown to improve quantitative accuracy of patient-level csPCa detection. Advanced Restriction imaging and reconstruction Technology for Prostate MRI (ART-Pro) is a multisite, multinational trial that aims to evaluate whether IV contrast can be avoided in the setting of standardized, state-of-the-art image acquisition, with or without addition of RSIrs. Additionally, RSIrs will be evaluated as a stand-alone, quantitative, objective biomarker. ART-Pro will be conducted in two stages and will include a total of 500 patients referred for multiparametric prostate MRI with a clinical suspicion of prostate cancer at the participating sites. ART-Pro-1 will evaluate bpMRI, mpMRI, and RSIrs on the accuracy of expert radiologists' detection of csPCa and will evaluate RSIrs as a stand-alone, quantitative, objective biomarker. ART-Pro-2 will evaluate the same MRI techniques on the accuracy of nonexpert radiologists' detection of csPCa, and findings will be evaluated against the expertly created dataset from ART-Pro-1. The primary endpoint is to evaluate whether bpMRI is noninferior to mpMRI among expert (ART-Pro-1) and nonexpert (ART-Pro-2) radiologists for the detection of grade group ≥2 csPCa. This trial is registered in the US National Library of Medicine Trial Registry (NCT number: NCT06579417) at ClinicalTrials.gov. Patient accrual at the first site (UC San Diego) began in December 2023. Initial results are anticipated by the end of 2026.
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Affiliation(s)
- Madison T. Baxter
- Department of Radiation Medicine and Applied Sciences, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Christopher C. Conlin
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Aditya Bagrodia
- Department of Urology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Tristan Barrett
- Department of Radiology, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Hauke Bartsch
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | | | - Matthew Cooperberg
- Department of Urology, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Anders M. Dale
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego School of Medicine, La Jolla, CA, USA
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
| | | | - Michael E. Hahn
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | | | - Juan F. Javier-DesLoges
- Department of Urology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Sophia C. Kamran
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA
| | - Christopher J. Kane
- Department of Urology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Joshua M. Kuperman
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | | | - Paul M. Murphy
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Nabih Nakrour
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Michael A. Ohliger
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Rebecca Rakow-Penner
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
| | - Ahmed Shabaik
- Department of Pathology, UC San Diego School of Medicine, La Jolla, CA, USA
| | - Jeffry P. Simko
- Department of Urology, University of California San Francisco, San Francisco, CA, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, USA
| | - Clare M. Tempany
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Natasha Wehrli
- Department of Radiology, Weill Cornell Medical College, New York, NY, USA
| | - Sean A. Woolen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jingjing Zou
- Department of Biostatistics, Herbert Wertheim School of Public Health & Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Tyler M. Seibert
- Department of Radiation Medicine and Applied Sciences, University of California San Diego School of Medicine, La Jolla, CA, USA
- Department of Radiology, University of California San Diego School of Medicine, La Jolla, CA, USA
- Department of Urology, University of California San Diego School of Medicine, La Jolla, CA, USA
- Department of Bioengineering, University of California San Diego Jacobs School of Engineering, La Jolla, CA, USA
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7
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Huang H, Mo J, Ding Z, Peng X, Liu R, Zhuang D, Zhang Y, Hu G, Huang B, Qiu Y. Deep Learning to Simulate Contrast-Enhanced MRI for Evaluating Suspected Prostate Cancer. Radiology 2025; 314:e240238. [PMID: 39807983 DOI: 10.1148/radiol.240238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2025]
Abstract
Background Multiparametric MRI, including contrast-enhanced sequences, is recommended for evaluating suspected prostate cancer, but concerns have been raised regarding potential contrast agent accumulation and toxicity. Purpose To evaluate the feasibility of generating simulated contrast-enhanced MRI from noncontrast MRI sequences using deep learning and to explore their potential value for assessing clinically significant prostate cancer using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Materials and Methods Male patients with suspected prostate cancer who underwent multiparametric MRI were retrospectively included from three centers from April 2020 to April 2023. A deep learning model (pix2pix algorithm) was trained to synthesize contrast-enhanced MRI scans from four noncontrast MRI sequences (T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, and apparent diffusion coefficient maps) and then tested on an internal and two external datasets. The reference standard for model training was the second postcontrast phase of the dynamic contrast-enhanced sequence. Similarity between simulated and acquired contrast-enhanced images was evaluated using the multiscale structural similarity index. Three radiologists independently scored T2-weighted and diffusion-weighted MRI with either simulated or acquired contrast-enhanced images using PI-RADS, version 2.1; agreement was assessed with Cohen κ. Results A total of 567 male patients (mean age, 66 years ± 11 [SD]) were divided into a training test set (n = 244), internal test set (n = 104), external test set 1 (n = 143), and external test set 2 (n = 76). Simulated and acquired contrast-enhanced images demonstrated high similarity (multiscale structural similarity index: 0.82, 0.71, and 0.69 for internal test set, external test set 1, and external test set 2, respectively) with excellent reader agreement of PI-RADS scores (Cohen κ, 0.96; 95% CI: 0.94, 0.98). When simulated contrast-enhanced imaging was added to biparametric MRI, 34 of 323 (10.5%) patients were upgraded to PI-RADS 4 from PI-RADS 3. Conclusion It was feasible to generate simulated contrast-enhanced prostate MRI using deep learning. The simulated and acquired contrast-enhanced MRI scans exhibited high similarity and demonstrated excellent agreement in assessing clinically significant prostate cancer based on PI-RADS, version 2.1. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Neji and Goh in this issue.
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Affiliation(s)
- Hongyan Huang
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Junyang Mo
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Zhiguang Ding
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Xuehua Peng
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Ruihao Liu
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Danping Zhuang
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Yuzhong Zhang
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Genwen Hu
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Bingsheng Huang
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
| | - Yingwei Qiu
- From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.)
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Yang L, Zhang T, Liu S, Ding H, Li Z, Zhang Z. Diagnostic Performance of Multiparametric MRI for the Detection of suspected Prostate Cancer in Biopsy-Naive Patients: A Systematic Review and Meta-analysis. Acad Radiol 2025; 32:260-274. [PMID: 39227219 DOI: 10.1016/j.acra.2024.08.027] [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: 06/29/2024] [Revised: 08/03/2024] [Accepted: 08/14/2024] [Indexed: 09/05/2024]
Abstract
RATIONALE AND OBJECTIVES This meta-analysis aimed to assess the diagnostic accuracy of multiparametric MRI (mpMRI) in detecting suspected prostate cancer (PCa) in biopsy-naive men. MATERIALS AND METHODS PubMed, Scopus, and the Cochrane Library databases were systematically searched for studies published from January 2013 to April 2024. Sixteen studies comprising 4973 patients met the inclusion criteria. Data were extracted to construct 2×2 contingency tables for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). A random-effects model was used for pooled estimation, and subgroup analyses were conducted. Summary receiver operating characteristic (SROC) curves were generated to summarize overall diagnostic performance. RESULTS The overall detection rate of PCa across studies was 57.3%. For detecting any PCa, mpMRI showed pooled sensitivity of 82% (95% CI, 80-83%) and specificity of 62% (95% CI, 60-64%), with positive likelihood ratio (LR) of 1.97 (95% CI, 1.71-2.26), negative LR of 0.28 (95% CI, 0.24-0.34), and diagnostic odds ratio (DOR) of 7.34 (95% CI, 5.60-9.63), and an area under the SROC curve of 0.81. For clinically significant PCa (csPCa), mpMRI had pooled sensitivity of 88% (95% CI, 87-90%) and specificity of 64% (95% CI, 63-66%), with positive LR of 2.49 (95% CI, 2.03-3.05), negative LR of 0.20 (95% CI, 0.16-0.25), DOR of 13.83 (95% CI, 9.14-20.9), and area under the curve of 0.90. CONCLUSION This meta-analysis suggests that mpMRI is effective in detecting PCa in biopsy-naive patients, particularly for csPCa. It can help reduce unnecessary biopsies and lower the risk of missing clinically significant cases, thereby guiding informed biopsy decisions.
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Affiliation(s)
- Lei Yang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China; Department of Radiology, Qingdao Women and Children's Hospital, Qingdao, China
| | - Taijuan Zhang
- Department of Radiology, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Traditional Chinese Medicine Hospital), Qingdao, China
| | - Shunli Liu
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hui Ding
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhiming Li
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zaixian Zhang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
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9
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Zhang H, Yang J, Wu K, Hou Z, Du J, Yan J, Zhao Y. Comparison of tracer kinetic models in differentiating malignant from normal prostate tissue using dynamic contrast-enhanced MRI. Front Oncol 2024; 14:1450388. [PMID: 39711955 PMCID: PMC11659129 DOI: 10.3389/fonc.2024.1450388] [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: 06/17/2024] [Accepted: 11/15/2024] [Indexed: 12/24/2024] Open
Abstract
Purpose The aim of this study was to evaluate the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived kinetic parameters with high spatiotemporal resolution in discriminating malignant from normal prostate tissues. Methods Fifty patients with suspicious of malignant diseases in prostate were included in this study. Regions of interest (ROI) were manually delineated by experienced radiologists. Voxel-wise kinetic parameters were produced with the following tracer kinetic models (TKMs): Tofts model, extended Tofts model (ETM), Brix's conventional two-compartment model (Brix), adiabatic tissue homogeneity model (ATH), and distributed parameter model (DP). The initial area under the signal-time curve (IAUC) with an uptake integral approach was also included. Mann-Whitney U test and receiver operating characteristic (ROC) curves were used to evaluate the capability of distinguishing tumor lesions from normal tissues. A p-value of 0.05 or less is considered statistically significant. ROI based parameters correlation analysis between DP and ETM were performed. Results 624 lesions and 269 normal tissue ROIs were obtained. Thirty parameters were derived from the six kinetic models. Except for PS from Brix, statistically significant differences between lesions and normal tissues (P<0.05) were observed in other parameters.Ve from DP, ATH and Brix and PS from ATH have AUC values less than 0.6 in the ROC analysis. MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, IAUC parameters and F from Brix have AUC values larger than 0.8. Ve and Vp from DP and ETM are correlated (r> 0.65). The correlation coefficient between Ktrans from ETM and PS from DP is 0.751. Conclusion MTT, Vp and PS from DP, Ktrans from ETM and Tofts, E and PS from ATH, F from Brix and IAUC parameters can be used to differentiate malignant lesions from normal tissues in the prostate.
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Affiliation(s)
- Hongjiang Zhang
- Department of Magnetic Resonance Imaging (MRI), The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Jing Yang
- Department of Magnetic Resonance Imaging (MRI), The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Kunhua Wu
- Department of Magnetic Resonance Imaging (MRI), The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Zujun Hou
- Department of Radiology, FISCA Laboratory for Advanced Imaging, Nanjing, China
| | - Ji Du
- Department of Magnetic Resonance Imaging (MRI), The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Jianhua Yan
- Department of Nuclear Medicine, The First Affiliated Hospital of University of Science and Technology of China, Hefei, Anhui, China
| | - Ying Zhao
- Department of Magnetic Resonance Imaging (MRI), The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
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10
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Kim DH, Choi MH, Lee YJ, Rha SE, Nickel MD, Lee HS, Han D. Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment. Sci Rep 2024; 14:29249. [PMID: 39587164 PMCID: PMC11589747 DOI: 10.1038/s41598-024-79348-5] [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: 03/01/2024] [Accepted: 11/08/2024] [Indexed: 11/27/2024] Open
Abstract
This bicenter retrospective analysis included 162 patients who had undergone prostate biopsy following prebiopsy MRI, excluding those with PCa identified only in the peripheral zone (PZ). DLR T2WI achieved a 69% reduction in scan time relative to TSE T2WI. The intermethod agreement between the two T2WI sets in terms of the Prostate Imaging Reporting and Data System (PI-RADS) classification and extraprostatic extension (EPE) grade was measured using the intraclass correlation coefficient (ICC) and diagnostic performance was assessed with the area under the receiver operating characteristic curve (AUC). Clinically significant PCa (csPCa) was found in 74 (45.7%) patients. Both T2WI methods showed high intermethod agreement for the overall PI-RADS classification (ICC: 0.907-0.949), EPE assessment (ICC: 0.925-0.957) and lesion size measurement (ICC: 0.980-0.996). DLR T2WI and TSE T2WI showed similar AUCs (0.666-0.814 versus 0.684-0.832) for predicting EPE. The AUCs for detecting csPCa with DLR T2WI (0.834-0.935) and TSE T2WI (0.891-0.935) were comparable in 139 patients with TZ lesions with no significant differences (P > 0.05). The findings suggest that DLR T2WI is an efficient alternative for TZ lesion assessment, offering reduced scan times without compromising diagnostic accuracy.
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Affiliation(s)
- Dong Hwan Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Moon Hyung Choi
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 1021, Tongil-ro, Eunpyeong-gu, Seoul, 03312, Republic of Korea.
| | - Young Joon Lee
- Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 1021, Tongil-ro, Eunpyeong-gu, Seoul, 03312, Republic of Korea
| | - Sung Eun Rha
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | | | - Hyun-Soo Lee
- Siemens Healthineers Ltd, Seoul, Republic of Korea
| | - Dongyeob Han
- Siemens Healthineers Ltd, Seoul, Republic of Korea
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11
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Kohjimoto Y, Uemura H, Yoshida M, Hinotsu S, Takahashi S, Takeuchi T, Suzuki K, Shinmoto H, Tamada T, Inoue T, Sugimoto M, Takenaka A, Habuchi T, Ishikawa H, Mizowaki T, Saito S, Miyake H, Matsubara N, Nonomura N, Sakai H, Ito A, Ukimura O, Matsuyama H, Hara I. Japanese clinical practice guidelines for prostate cancer 2023. Int J Urol 2024; 31:1180-1222. [PMID: 39078210 DOI: 10.1111/iju.15545] [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: 06/24/2024] [Accepted: 07/09/2024] [Indexed: 07/31/2024]
Abstract
This fourth edition of the Japanese Clinical Practice Guidelines for Prostate Cancer 2023 is compiled. It was revised under the leadership of the Japanese Urological Association, with members selected from multiple academic societies and related organizations (Japan Radiological Society, Japanese Society for Radiation Oncology, the Department of EBM and guidelines, Japan Council for Quality Health Care (Minds), Japanese Society of Pathology, and the patient group (NPO Prostate Cancer Patients Association)), in accordance with the Minds Manual for Guideline Development (2020 ver. 3.0). The most important feature of this revision is the adoption of systematic reviews (SRs) in determining recommendations for 14 clinical questions (CQs). Qualitative SRs for these questions were conducted, and the final recommendations were made based on the results through the votes of 24 members of the guideline development group. Five algorithms based on these results were also created. Contents not covered by the SRs, which are considered textbook material, have been described in the general statement. In the general statement, a literature search for 14 areas was conducted; then, based on the general statement and CQs of the Japanese Clinical Practice Guidelines for Prostate Cancer 2016, the findings revealed after the 2016 guidelines were mainly described. This article provides an overview of these guidelines.
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Affiliation(s)
- Yasuo Kohjimoto
- Department of Urology, Wakayama Medical University, Wakayama, Japan
| | - Hiroji Uemura
- Department of Urology and Renal Transplantation, Yokohama City University Medical Center, Yokohama, Kanagawa, Japan
| | - Masahiro Yoshida
- Department of Hepato-Biliary-Pancreatic and Gastrointestinal Surgery, School of Medicine, International University of Health and Welfare, Narita, Chiba, Japan
- Department of EBM and Guidelines, Japan Council for Quality Health Care (Minds), Tokyo, Japan
| | - Shiro Hinotsu
- Department of Biostatistics and Data Management, Sapporo Medical University School of Medicine, Sapporo, Japan
| | - Satoru Takahashi
- Department of Urology, Nihon University School of Medicine, Tokyo, Japan
| | - Tsutomu Takeuchi
- NPO Prostate Cancer Patients Association, Takarazuka, Hyogo, Japan
| | - Kazuhiro Suzuki
- Department of Urology, Gunma University Graduate School of Medicine, Maebashi, Gunma, Japan
| | - Hiroshi Shinmoto
- Department of Radiology, National Defense Medical College, Tokorozawa, Tochigi, Japan
| | - Tsutomu Tamada
- Department of Radiology, Kawasaki Medical School, Kurashiki, Okayama, Japan
| | - Takahiro Inoue
- Department of Nephro-Urologic Surgery and Andrology, Mie University Graduate School of Medicine, Tsu, Mie, Japan
| | - Mikio Sugimoto
- Department of Urology, Faculty of Medicine, Kagawa University, Takamatsu, Kagawa, Japan
| | - Atsushi Takenaka
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, Yonago, Tottori, Japan
| | - Tomonori Habuchi
- Department of Urology, Akita University Graduate School of Medicine, Akita, Japan
| | - Hitoshi Ishikawa
- QST Hospital, National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Takashi Mizowaki
- Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Shiro Saito
- Department of Urology, Prostate Cancer Center Ofuna Chuo Hospital, Kamakura, Kanagawa, Japan
| | - Hideaki Miyake
- Division of Urology, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan
| | - Nobuaki Matsubara
- Department of Medical Oncology, National Cancer Center Hospital East, Kashiwa, Chiba, Japan
| | - Norio Nonomura
- Department of Urology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hideki Sakai
- Department of Urology, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
- Nagasaki Rosai Hospital, Sasebo, Nagasaki, Japan
| | - Akihiro Ito
- Department of Urology, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Osamu Ukimura
- Department of Urology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Hideyasu Matsuyama
- Department of Urology, Graduate School of Medicine, Yamaguchi University, Ube, Yamaguchi, Japan
- Department of Urology, JA Yamaguchi Kouseiren Nagato General Hospital, Yamaguchi, Japan
| | - Isao Hara
- Department of Urology, Wakayama Medical University, Wakayama, Japan
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Park SH, Choi MH, Lee YJ, Jung SE. Rationale for adopting a combination of monoparametric MRI with the prostate-specific antigen in detecting clinically significant prostate cancer: comparison with standard biparametric and multiparametric MRI. Br J Radiol 2024; 97:1775-1781. [PMID: 39212614 DOI: 10.1093/bjr/tqae134] [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: 05/21/2024] [Revised: 07/23/2024] [Accepted: 07/27/2024] [Indexed: 09/04/2024] Open
Abstract
OBJECTIVES To compare prostate monoparametric MRI (monoMRI), which uses only diffusion-weighted imaging (DWI), with biparametric (bpMRI) and multiparametric MRI (mpMRI) in detecting clinically significant cancer (CSC) and to evaluate the effect of the combination of monoMRI results and prostate-specific antigen (PSA) level. METHODS In this study, 193 patients (average age 70.5 years; average PSA 7.9 ng/mL) underwent prebiopsy MRI and subsequent prostate biopsy from January 2020 to February 2022. Two radiologists independently reviewed the 3 MRI protocols using the Prostate Imaging Reporting and Data System (PI-RADS). Interreader agreement was assessed using the intraclass correlation coefficient (ICC), and diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. The Youden index was used to determine the new cutoff value of PSA for detecting CSCs in patients with negative monoMRI results. RESULTS CSC was confirmed in 109 patients (56.5%). The interreader agreement on monoMRI (ICC = 0.798) was comparable to that on bpMRI and mpMRI (ICC = 0.751 and 0.714, respectively). ROC curve analysis of the 3 protocols revealed no difference in detecting CSCs (P > 0.05). Applying a new PSA cutoff value (9.5 and 7.4 ng/mL, respectively) in monoMRI-negative patients improved the sensitivity of monoMRI from 89.9% to 96.3% for Reader 1, and from 95.4% to 99.1% for Reader 2. CONCLUSIONS MonoMRI based solely on DWI demonstrated similar diagnostic performance to bpMRI and mpMRI in detecting CSCs, and the combination of PSA level with monoMRI has the potential to effectively triage patients with a high likelihood of CSCs. ADVANCES IN KNOWLEDGE Monoparametric MRI conducted only with diffusion-weighted imaging (DWI), may show comparable performance to biparametric and multiparametric MRI in detecting clinically significant prostate cancer. In patients with negative monoparametric MRI results, implementing a new PSA cutoff value to determine the need for a biopsy could decrease the number of missed prostate cancer.
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Affiliation(s)
- Seung Hyun Park
- Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea
| | - 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
| | - Seung Eun Jung
- Department of Radiology, Eunpyeong St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Republic of Korea
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13
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Khalid MJ, Parker P, Smith S, Byass OR, Cast JEI. Prevalence of clinically significant prostate carcinoma in Prostate Imaging Reporting and Data System (PIRADS) 3 lesions detected in the peripheral zone on biparametric magnetic resonance imaging (MRI)-a local experience. Clin Radiol 2024; 79:773-780. [PMID: 39129105 DOI: 10.1016/j.crad.2024.07.014] [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: 02/19/2024] [Revised: 06/14/2024] [Accepted: 07/16/2024] [Indexed: 08/13/2024]
Abstract
AIM The aim of this study was to determine whether biparametric magnetic resonance imaging (MRI) is effective in the diagnosis of clinically significant prostate cancer in prostate peripheral zone Prostate Imaging Reporting and Data System (PIRADS) 3 lesions without the use of dynamic contrast enhancement. MATERIALS AND METHODS Patients who underwent biparametric MRI over a 12-month period from January 2022 to December 2022 and were diagnosed with PIRADS 3 lesion in the peripheral zone were included in the study. No patient received dynamic contrast enhancement. Histological analysis was done after performing local anesthetic transperineal biopsy to determine detection rate of clinically significant prostate cancer. Prostate-specific antigen density (PSAD) and biopsy complication rates were also reviewed. RESULTS Sixty-one out of 688 MRIs (8.8%) performed over the study period had a PIRADS 3 lesion in the peripheral zone where contrast is supposed to add value. Fifty-eight of the 61 went ahead to biopsy, and csPCa (Gleason score: ≥3 + 4, with a max core length of ≥6 mm and above) was diagnosed in 17%. Among those diagnosed with csPCa, 80% had a PSAD of >0.15 ng/ml/cc. No postbiopsy complications were reported. CONCLUSION Biparametric MRI without contrast offers a reliable alternative to multiparametric MRI with minimum or neglible impact on clinically significant prostate cancer (csPCa) diagnosis in peripheral zone PIRADS 3 lesions, especially when used in conjunction with other factors such as PSAD. There is potential to address health economics and patient burden in prostate cancer investigation.
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Affiliation(s)
- M J Khalid
- Department of Radiology, Hull University Teaching Hospitals NHS Trust, Kingston-upon-Hull, UK.
| | - P Parker
- Department of Radiology, Hull University Teaching Hospitals NHS Trust, Kingston-upon-Hull, UK
| | - S Smith
- Department of Radiology, Hull University Teaching Hospitals NHS Trust, Kingston-upon-Hull, UK
| | - O R Byass
- Department of Radiology, Hull University Teaching Hospitals NHS Trust, Kingston-upon-Hull, UK
| | - J E I Cast
- Department of Radiology, Hull University Teaching Hospitals NHS Trust, Kingston-upon-Hull, UK
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14
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Caglic I, Sushentsev N, Syer T, Lee KL, Barrett T. Biparametric MRI in prostate cancer during active surveillance: is it safe? Eur Radiol 2024; 34:6217-6226. [PMID: 38656709 PMCID: PMC11399179 DOI: 10.1007/s00330-024-10770-z] [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: 02/02/2024] [Revised: 03/13/2024] [Accepted: 03/22/2024] [Indexed: 04/26/2024]
Abstract
Active surveillance (AS) is the preferred option for patients presenting with low-intermediate-risk prostate cancer. MRI now plays a crucial role for baseline assessment and ongoing monitoring of AS. The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations aid radiological assessment of progression; however, current guidelines do not advise on MRI protocols nor on frequency. Biparametric (bp) imaging without contrast administration offers advantages such as reduced costs and increased throughput, with similar outcomes to multiparametric (mp) MRI shown in the biopsy naïve setting. In AS follow-up, the paradigm shifts from MRI lesion detection to assessment of progression, and patients have the further safety net of continuing clinical surveillance. As such, bpMRI may be appropriate in clinically stable patients on routine AS follow-up pathways; however, there is currently limited published evidence for this approach. It should be noted that mpMRI may be mandated in certain patients and potentially offers additional advantages, including improving image quality, new lesion detection, and staging accuracy. Recently developed AI solutions have enabled higher quality and faster scanning protocols, which may help mitigate against disadvantages of bpMRI. In this article, we explore the current role of MRI in AS and address the need for contrast-enhanced sequences. CLINICAL RELEVANCE STATEMENT: Active surveillance is the preferred plan for patients with lower-risk prostate cancer, and MRI plays a crucial role in patient selection and monitoring; however, current guidelines do not currently recommend how or when to perform MRI in follow-up. KEY POINTS: Noncontrast biparametric MRI has reduced costs and increased throughput and may be appropriate for monitoring stable patients. Multiparametric MRI may be mandated in certain patients, and contrast potentially offers additional advantages. AI solutions enable higher quality, faster scanning protocols, and could mitigate the disadvantages of biparametric imaging.
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Affiliation(s)
- Iztok Caglic
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Nikita Sushentsev
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Tom Syer
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Kang-Lung Lee
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tristan Barrett
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, United Kingdom.
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom.
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15
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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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16
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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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17
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Zawaideh JP, Caglic I, Sushentsev N, Priest AN, Warren AY, Carmisciano L, Barrett T. MRI assessment of seminal vesicle involvement by prostate cancer using T2 signal intensity and volume. Abdom Radiol (NY) 2024; 49:2534-2539. [PMID: 38734785 DOI: 10.1007/s00261-024-04349-x] [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: 03/13/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 05/13/2024]
Abstract
BACKGROUND Seminal vesicle involvement (SVI) in patients with newly diagnosed prostate cancer is associated with high rates of treatment failure and tumor recurrence; correct identification of SVI allows for effective management decisions and surgical planning. METHODS This single-center retrospective study analyzed MR images of the seminal vesicles from patients undergoing radical prostatectomy with confirmed T3b disease, comparing them to a control group without SVI matched for age and Gleason grade with a final stage of T2 or T3a. Seminal vesicles were segmented by an experienced uroradiologist, "raw" and bladder-normalized T2 signal intensity, as well as SV volume, were obtained. RESULTS Among the 82 patients with SVI, 34 (41.6%) had unilateral invasion, and 48 (58.4%) had bilateral disease. There was no statistically significant difference in the degree of distension between normal and involved seminal vesicles (P = 0.08). Similarly, no statistically significant difference was identified in the raw SV T2 signal intensity (P = 0.09) between the groups. In the 159 patients analyzed, SVI was prospectively suspected in 10 of 82 patients (specificity, 100%; sensitivity, 12.2%). In all these cases, lesions macroscopically invaded the seminal vesicle, and the raw T2 signal intensity was significantly lower than that in the SVI and control groups (P = 0.02 and 0.01). CONCLUSION While signal intensity measurements in T2-weighted images may provide insight into T3b disease, our findings suggest that this data alone is insufficient to reliably predict SVI, indicating the need for further investigation and complementary diagnostic approaches.
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Affiliation(s)
- Jeries P Zawaideh
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
- Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
| | - Iztok Caglic
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Andrew N Priest
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Anne Y Warren
- Department of Pathology, Addenbrooke's Hospital, Cambridge, UK
| | - Luca Carmisciano
- Department of Health Sciences (DISSAL), Biostatistics Section, University of Genoa, Genoa, Italy
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
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18
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Gulati R, Jiao B, Al-Faouri R, Sharma V, Kaul S, Fleishman A, Wymer K, Boorjian SA, Olumi AF, Etzioni R, Gershman B. Lifetime Health and Economic Outcomes of Biparametric Magnetic Resonance Imaging as First-Line Screening for Prostate Cancer : A Decision Model Analysis. Ann Intern Med 2024; 177:871-881. [PMID: 38830219 PMCID: PMC11250625 DOI: 10.7326/m23-1504] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND Contemporary prostate cancer (PCa) screening uses first-line prostate-specific antigen (PSA) testing, possibly followed by multiparametric magnetic resonance imaging (mpMRI) for men with elevated PSA levels. First-line biparametric MRI (bpMRI) screening has been proposed as an alternative. OBJECTIVE To evaluate the comparative effectiveness and cost-effectiveness of first-line bpMRI versus PSA-based screening. DESIGN Decision analysis using a microsimulation model. DATA SOURCES Surveillance, Epidemiology, and End Results database; randomized trials. TARGET POPULATION U.S. men aged 55 years with no prior screening or PCa diagnosis. TIME HORIZON Lifetime. PERSPECTIVE U.S. health care system. INTERVENTION Biennial screening to age 69 years using first-line PSA testing (test-positive threshold, 4 µg/L) with or without second-line mpMRI or first-line bpMRI (test-positive threshold, PI-RADS [Prostate Imaging Reporting and Data System] 3 to 5 or 4 to 5), followed by biopsy guided by MRI or MRI plus transrectal ultrasonography. OUTCOME MEASURES Screening tests, biopsies, diagnoses, overdiagnoses, treatments, PCa deaths, quality-adjusted and unadjusted life-years saved, and costs. RESULTS OF BASE-CASE ANALYSIS For 1000 men, first-line bpMRI versus first-line PSA testing prevented 2 to 3 PCa deaths and added 10 to 30 life-years (4 to 11 days per person) but increased the number of biopsies by 1506 to 4174 and the number of overdiagnoses by 38 to 124 depending on the biopsy imaging scheme. At conventional cost-effectiveness thresholds, first-line PSA testing with mpMRI followed by either biopsy approach for PI-RADS 4 to 5 produced the greatest net monetary benefits. RESULTS OF SENSITIVITY ANALYSIS First-line PSA testing remained more cost-effective even if bpMRI was free, all men with low-risk PCa underwent surveillance, or screening was quadrennial. LIMITATION Performance of first-line bpMRI was based on second-line mpMRI data. CONCLUSION Decision analysis suggests that comparative effectiveness and cost-effectiveness of PCa screening are driven by false-positive results and overdiagnoses, favoring first-line PSA testing with mpMRI over first-line bpMRI. PRIMARY FUNDING SOURCE National Cancer Institute.
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Affiliation(s)
- Roman Gulati
- Fred Hutchinson Cancer Center, Seattle, Washington
| | - Boshen Jiao
- Fred Hutchinson Cancer Center, Seattle, Washington
- The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle, Washington
| | - Ra’ad Al-Faouri
- Division of Urologic Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | - Sumedh Kaul
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Aaron Fleishman
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | | | | | - Aria F. Olumi
- Division of Urologic Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Ruth Etzioni
- Fred Hutchinson Cancer Center, Seattle, Washington
| | - Boris Gershman
- Division of Urologic Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts
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19
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Martini F, Pigati M, Mattiauda M, Ponzano M, Piol N, Pigozzi S, Spina B, Cittadini G, Giasotto V, Zawaideh JP. Extra-prostatic extension grading system: correlation with MRI features and integration of capsular enhancement sign for "enhanced" detection of T3a lesions. Br J Radiol 2024; 97:971-979. [PMID: 38544291 PMCID: PMC11075987 DOI: 10.1093/bjr/tqae065] [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: 02/20/2024] [Revised: 03/15/2024] [Accepted: 03/21/2024] [Indexed: 05/09/2024] Open
Abstract
PURPOSE This study aims to confirm the diagnostic accuracy of extra-prostatic extension (EPE) grading system and to explore the predictive capabilities of the prostate MRI while considering various MRI features such as lesion location, apparent diffusion coefficient (ADC) values and capsular enhancement sign (CES). METHODS Our monocentric study is based on a retrospective analysis of 99 patients who underwent radical prostatectomy from January 2021 to January 2023. The observers reviewed for each lesion, including location (transitional or peripheral zone, anterior or posterior location), capsular contact length, irregular bulging of the capsule, asymmetry of the neurovascular bundle, obliteration of the recto-prostatic angle, macroscopic EPE, ADC value, and CES. RESULTS Among 99 patients, 31 patients had EPE. Lesions with EPE have broadercapsule contact (24 mm vs 12 mm) with contact ≥14 mm being the optimal cut-off for EPE discrimination. Among the morphological MRI criteria used to determine the EPE, the one with major sensitivity was shown to be bulging (sen 81%), while macroscopic extension had highest specificity (100%). Univariate analysis showed as significative risk factors for EPE: capsular contact ≥14 mm (P < .001), International Society of Urological Pathology score ≥3 (P = .005), CES (P < .001), bulging (P = .001), neurovascular bundle asymmetry (P < .001) and EPE score ≥2 (P < .001), and in multivariate analysis CES (P = .001) and EPE score ≥2 (P = .004) were significant. The AUC of the EPE score was 0.76, raised to 0.83 when combining it with CES (P = .11). CONCLUSION CES in the setting of multiparametric MRI can increase diagnostic accuracy for the prediction of extracapsular disease. ADVANCES IN KNOWLEDGE This study highlights the potential of contrast media in prostate cancer local staging.
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Affiliation(s)
- Federica Martini
- Department of Health Sciences (DISSAL), Radiology section, University of Genoa, Genova 16132, Italy
| | - Maria Pigati
- Department of Health Sciences (DISSAL), Radiology section, University of Genoa, Genova 16132, Italy
| | - Matilde Mattiauda
- Department of Health Sciences (DISSAL), Radiology section, University of Genoa, Genova 16132, Italy
| | - Marta Ponzano
- Department of Health Sciences, Section of Biostatistics, University of Genoa, Genova 16132, Italy
| | - Nataniele Piol
- Anatomia Patologica Universitaria Unit, IRCCS Ospedale Policlinico San Martino, Genova 16132, Italy
| | - Simona Pigozzi
- Anatomia Patologica Universitaria Unit, IRCCS Ospedale Policlinico San Martino, Genova 16132, Italy
- Department of Surgical and Diagnostic Sciences (DISC), Urology Section, University of Genova, Genova 16132, Italy
| | - Bruno Spina
- Pathology Unit, IRCCS Ospedale Policlinico San Martino, Genova 16132, Italy
| | - Giuseppe Cittadini
- Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genova 16132, Italy
| | - Veronica Giasotto
- Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genova 16132, Italy
| | - Jeries P Zawaideh
- Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genova 16132, Italy
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20
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Shimizu R, Morizane S, Yamamoto A, Yamane H, Nishikawa R, Kimura Y, Yamaguchi N, Hikita K, Honda M, Takenaka A. Assessment of the accuracy of biparametric MRI/TRUS fusion-guided biopsy for index tumor evaluation using postoperative pathology specimens. BMC Urol 2024; 24:79. [PMID: 38575912 PMCID: PMC10996083 DOI: 10.1186/s12894-024-01473-0] [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: 07/15/2023] [Accepted: 04/01/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Multiparametric MRI (mpMRI) is widely used for the diagnosis, surveillance, and staging of prostate cancer. However, it has several limitations, including higher costs, longer examination times, and the use of gadolinium-based contrast agents. This study aimed to investigate the accuracy of preoperatively assessed index tumors (ITs) using biparametric MRI (bpMRI)/transrectal ultrasound (TRUS) fusion biopsy compared with radical prostatectomy (RP) specimens. METHODS We included 113 patients diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsies of lesions with a Prostate Imaging Reporting and Data System (PI-RADS) category ≥ 3. These patients underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution between July 2017 and March 2023. We examined the localization of preoperative and postoperative ITs, the highest Gleason score (GS), and tumor diameter in these patients. RESULTS The preoperative cT stage matched the postoperative pT stage in 53 cases (47%), while 31 cases (27%) were upstaged, and 29 cases (26%) were downstaged (Weighted Kappa = 0.21). The preoperative and postoperative IT localizations were consistent in 97 cases (86%). The concordance rate between Gleason groups in targeted biopsies and RP specimens was 51%, with an upgrade in 25 cases (23%) and a downgrade in 27 cases (25%) (Weighted Kappa = 0.42). The maximum diameter of the IT and the maximum cancer core length on biopsy were correlated with the RP tumor's maximum diameter (p < 0.001 for both). CONCLUSION The diagnostic accuracy of bpMRI/TRUS fusion biopsy is comparable to mpMRI, suggesting that it can be a cost-effective and time-saving alternative.
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Affiliation(s)
- Ryutaro Shimizu
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Shuichi Morizane
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan.
| | - Atsushi Yamamoto
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Hiroshi Yamane
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Ryoma Nishikawa
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Yusuke Kimura
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Noriya Yamaguchi
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Katsuya Hikita
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Masashi Honda
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
| | - Atsushi Takenaka
- Division of Urology, Department of Surgery, Faculty of Medicine, Tottori University, 36-1, Nishi-cho, Yonago, 683-8504, Japan
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21
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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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22
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Rajendran I, Lee KL, Thavaraja L, Barrett T. Risk stratification of prostate cancer with MRI and prostate-specific antigen density-based tool for personalized decision making. Br J Radiol 2024; 97:113-119. [PMID: 38263825 PMCID: PMC11027333 DOI: 10.1093/bjr/tqad027] [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: 07/04/2023] [Revised: 09/22/2023] [Accepted: 10/03/2023] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVES MRI is now established for initial prostate cancer diagnosis; however, there is no standardized pathway to avoid unnecessary biopsy in low-risk patients. Our study aimed to test previously proposed MRI-focussed and risk-adapted biopsy decision models on a real-world dataset. METHODS Single-centre retrospective study performed on 2055 biopsy naïve patients undergoing MRI. Diagnostic pathways included "biopsy all", "MRI-focussed" and two risk-based MRI-directed pathways. Risk thresholds were based on prostate-specific antigen (PSA) density as low (<0.10 ng mL-2), intermediate (0.10-0.15 ng mL-2), high (0.15-0.20 ng mL-2), or very high-risk (>0.20 ng mL-2). The outcome measures included rates of biopsy avoidance, detection of clinically significant prostate cancer (csPCa), missed csPCa, and overdiagnosis of insignificant prostate cancer (iPCa). RESULTS Overall cancer rate was 39.9% (819/2055), with csPCa (Grade-Group ≥2) detection of 30.3% (623/2055). In men with a negative MRI (Prostate Imaging-Reporting and Data System, PI-RADS 1-2), the risk of cancer was 1.2%, 2.6%, 9.0%, and 12.9% in the low, intermediate, high, and very high groups, respectively; for PI-RADS score 3 lesions, the rates were 10.5%, 14.3%, 25.0%, and 33.3%, respectively. MRI-guided pathway and risk-based pathway with a low threshold missed only 1.6% csPCa with a biopsy-avoidance rate of 54.4%, and the risk-based pathway with a higher threshold avoided 62.9% (1292/2055) of biopsies with 2.9% (61/2055) missed csPCa detection. Decision curve analysis found that the "risk-based low threshold" pathway has the highest net benefit for probability thresholds between 3.6% and 13.9%. CONCLUSION Combined MRI and PSA-density risk-based pathways can be a helpful decision-making tool enabling high csPCa detection rates with the benefit of biopsy avoidance and reduced iPCa detection. ADVANCES IN KNOWLEDGE This real-world dataset from a large UK-based cohort confirms that combining MRI scoring with PSA density for risk stratification enables safe biopsy avoidance and limits the over-diagnosis of insignificant cancers.
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Affiliation(s)
- Ishwariya Rajendran
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge CB2 0QQ, United Kingdom
| | - Kang-Lung Lee
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge CB2 0QQ, United Kingdom
- Department of Radiology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Liness Thavaraja
- School of Medicine, Addenbrooke’s Hospital, Cambridge CB2 0SP, United Kingdom
| | - Tristan Barrett
- Department of Radiology, Addenbrooke’s Hospital and University of Cambridge, Cambridge CB2 0QQ, United Kingdom
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23
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Ringe KI, Wang J, Deng Y, Pi S, Geahchan A, Taouli B, Bashir MR. Abbreviated MRI Protocols in the Abdomen and Pelvis. J Magn Reson Imaging 2024; 59:58-69. [PMID: 37144673 DOI: 10.1002/jmri.28764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 05/06/2023] Open
Abstract
Abbreviated MRI (AMRI) protocols rely on the acquisition of a limited number of sequences tailored to a specific question. The main objective of AMRI protocols is to reduce exam duration and costs, while maintaining an acceptable diagnostic performance. AMRI is of increasing interest in the radiology community; however, challenges limiting clinical adoption remain. In this review, we will address main abdominal and pelvic applications of AMRI in the liver, pancreas, kidney, and prostate, including diagnostic performance, pitfalls, limitations, and cost effectiveness will also be discussed. Level of Evidence: 3 Technical Efficacy Stage: 3.
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Affiliation(s)
- Kristina I Ringe
- Department of Diagnostic and Interventional Radiology, Hannover Medical School, Hannover, Germany
| | - Jin Wang
- Department of Radiology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Ying Deng
- Department of Radiology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Shan Pi
- Department of Radiology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Amine Geahchan
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mustafa R Bashir
- Department of Radiology, Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, North Carolina, USA
- Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA
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24
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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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25
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Barrett T, Lee KL, de Rooij M, Giganti F. Update on Optimization of Prostate MR Imaging Technique and Image Quality. Radiol Clin North Am 2024; 62:1-15. [PMID: 37973236 DOI: 10.1016/j.rcl.2023.06.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Prostate MR imaging quality has improved dramatically over recent times, driven by advances in hardware, software, and improved functional imaging techniques. MRI now plays a key role in prostate cancer diagnostic work-up, but outcomes of the MRI-directed pathway are heavily dependent on image quality and optimization. MR sequences can be affected by patient-related degradations relating to motion and susceptibility artifacts which may enable only partial mitigation. In this Review, we explore issues relating to prostate MRI acquisition and interpretation, mitigation strategies at a patient and scanner level, PI-QUAL reporting, and future directions in image quality, including artificial intelligence solutions.
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Affiliation(s)
- Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
| | - Kang-Lung Lee
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK; Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Maarten de Rooij
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK; Division of Surgery and Interventional Science, University College London, London, UK
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26
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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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27
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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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28
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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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Sanmugalingam N, Sushentsev N, Lee KL, Caglic I, Englman C, Moore CM, Giganti F, Barrett T. The PRECISE Recommendations for Prostate MRI in Patients on Active Surveillance for Prostate Cancer: A Critical Review. AJR Am J Roentgenol 2023; 221:649-660. [PMID: 37341180 DOI: 10.2214/ajr.23.29518] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations were published in 2016 to standardize the reporting of MRI examinations performed to assess for disease progression in patients on active surveillance for prostate cancer. Although a limited number of studies have reported outcomes from use of PRECISE in clinical practice, the available studies have demonstrated PRECISE to have high pooled NPV but low pooled PPV for predicting progression. Our experience in using PRECISE in clinical practice at two teaching hospitals has highlighted issues with its application and areas requiring clarification. This Clinical Perspective critically appraises PRECISE on the basis of this experience, focusing on the system's key advantages and disadvantages and exploring potential changes to improve the system's utility. These changes include consideration of image quality when applying PRECISE scoring, incorporation of quantitative thresholds for disease progression, adoption of a PRECISE 3F sub-category for progression not qualifying as substantial, and comparisons with both the baseline and most recent prior examinations. Items requiring clarification include derivation of a patient-level score in patients with multiple lesions, intended application of PRECISE score 5 (i.e., if requiring development of disease that is no longer organ-confined), and categorization of new lesions in patients with prior MRI-invisible disease.
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Affiliation(s)
- Nimalan Sanmugalingam
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
| | - Kang-Lung Lee
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
- Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Iztok Caglic
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
| | - Cameron Englman
- Division of Surgery & Interventional Science, University College London, London, UK
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Caroline M Moore
- Division of Surgery & Interventional Science, University College London, London, UK
- Department of Urology, University College London Hospital NHS Foundation Trust, London, UK
| | - Francesco Giganti
- Division of Surgery & Interventional Science, University College London, London, UK
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Box 218, Cambridge Biomedical Campus, CB2 0QQ, Cambridge, UK
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30
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Mayer R, Turkbey B, Choyke PL, Simone CB. Relationship between Eccentricity and Volume Determined by Spectral Algorithms Applied to Spatially Registered Bi-Parametric MRI and Prostate Tumor Aggressiveness: A Pilot Study. Diagnostics (Basel) 2023; 13:3238. [PMID: 37892059 PMCID: PMC10605733 DOI: 10.3390/diagnostics13203238] [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: 09/22/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: Non-invasive prostate cancer assessments using multi-parametric MRI are essential to the reliable detection of lesions and proper management of patients. While current guidelines call for the administration of Gadolinium-containing intravenous contrast injections, eliminating such injections would simplify scanning and reduce patient risk and costs. However, augmented image analysis is necessary to extract important diagnostic information from MRIs. Purpose: This study aims to extend previous work on the signal to clutter ratio and test whether prostate tumor eccentricity and volume are indicators of tumor aggressiveness using bi-parametric (BP)-MRI. (2) Methods: This study retrospectively processed 42 consecutive prostate cancer patients from the PI-CAI data collection. BP-MRIs (apparent diffusion coefficient, high b-value, and T2 images) were resized, translated, cropped, and stitched to form spatially registered BP-MRIs. The International Society of Urological Pathology (ISUP) grade was used to judge cases of prostate cancer as either clinically significant prostate cancer (CsPCa) (ISUP ≥ 2) or clinically insignificant prostate cancer (CiPCa) (ISUP < 2). The Adaptive Cosine Estimator (ACE) algorithm was applied to the BP-MRIs, followed by thresholding, and then eccentricity and volume computations, from the labeled and blobbed detection maps. Then, univariate and multivariate linear regression fittings of eccentricity and volume were applied to the ISUP grade. The fits were quantitatively evaluated by computing correlation coefficients (R) and p-values. Area under the curve (AUC) and receiver operator characteristic (ROC) curve scores were used to assess the logistic fitting to CsPCa/CiPCa. (3) Results: Modest correlation coefficients (R) (>0.35) and AUC scores (0.70) for the linear and/or logistic fits from the processed prostate tumor eccentricity and volume computations for the spatially registered BP-MRIs exceeded fits using the parameters of prostate serum antigen, prostate volume, and patient age (R~0.17). (4) Conclusions: This is the first study that applied spectral approaches to BP-MRIs to generate tumor eccentricity and volume metrics to assess tumor aggressiveness. This study found significant values of R and AUC (albeit below those from multi-parametric MRI) to fit and relate the metrics to the ISUP grade and CsPCA/CiPCA, respectively.
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Affiliation(s)
- Rulon Mayer
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Oncoscore, Garrett Park, MD 20896, USA
| | - Baris Turkbey
- National Institutes of Health, Bethesda, MD 20892, USA; (B.T.); (P.L.C.)
| | - Peter L. Choyke
- National Institutes of Health, Bethesda, MD 20892, USA; (B.T.); (P.L.C.)
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31
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Nicola R, Bittencourt LK. PI-RADS 3 lesions: a critical review and discussion of how to improve management. Abdom Radiol (NY) 2023; 48:2401-2405. [PMID: 37160472 DOI: 10.1007/s00261-023-03929-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 05/11/2023]
Abstract
Since the publication of PI-RADS v1 in 2012, the debate regarding the question of how to manage PI-RADS 3 lesions has been mostly unsolved. However, based on our review of the current literature we discuss possible solutions and improvements to the original classification, factors such as PSAD (Prostate Specific Antigen Density), age, and tumor volume, in the decision of whether to proceed with a biopsy or not.
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Affiliation(s)
- Refky Nicola
- Division of Abdominal Radiology, SUNY-Upstate Medical University, 750 East Adams St, Syracuse, NY, 13210, USA.
| | - Leonardo Kayat Bittencourt
- School of Medicine, Abdominal Imaging, Case Western University, 11100 Euclid Ave, Cleveland, OH, 44106, USA
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32
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Wu M, Zheng X, Wang W, Chang J, Xue M, Zhang Y, Song J, Zhao J. Primary seminal vesicle Burkitt lymphoma in a patient living with HIV undergoing radical prostate and seminal vesicle resection: a rare missed case report. Infect Agent Cancer 2023; 18:32. [PMID: 37226239 DOI: 10.1186/s13027-023-00509-8] [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: 09/11/2022] [Accepted: 05/03/2023] [Indexed: 05/26/2023] Open
Abstract
Primary seminal vesicle Burkitt lymphoma (PSBL) is rare that is not frequently reported. Burkitt lymphoma is often associated with extranodal organs. The diagnosis of carcinoma in seminal vesical can be difficult. In this report, we present a missed case of PSBL in a male patient who underwent radical prostate and seminal vesicle resection. We retrospectively analyzed the clinical data to explore the diagnosis, pathological features, treatment, and prognosis of this rare disease. The patient visited our hospital for dysuria, and the serum prostate-specific antigen (PSA) was moderately elevated. Pelvic magnetic resonance imaging (MRI) and computed tomography (CT) scans suggested a notable enlargement of the seminal vesicle. The patient then underwent radical surgery and the pathology diagnosis revealed Burkitt lymphoma. The diagnosis of PSBL is difficult, and the prognosis is generally poorer than that of other types of lymphoma. However, earlier diagnosis and treatment may help to improve the survival rate among patients with Burkitt lymphoma.
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Affiliation(s)
- Menghua Wu
- Department of Urology, Beijing Youan Hospital, Capital Medical University, Beijing, China
- Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xin Zheng
- Department of Urology, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Wei Wang
- Department of Radiology, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Jing Chang
- Department of Clinical Pathology, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Meng Xue
- Department of Medical Record, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Yu Zhang
- Department of Urology, Beijing Youan Hospital, Capital Medical University, Beijing, China.
| | - Jian Song
- Department of Urology, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Jimao Zhao
- Department of Urology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
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Nematollahi H, Moslehi M, Aminolroayaei F, Maleki M, Shahbazi-Gahrouei D. Diagnostic Performance Evaluation of Multiparametric Magnetic Resonance Imaging in the Detection of Prostate Cancer with Supervised Machine Learning Methods. Diagnostics (Basel) 2023; 13:diagnostics13040806. [PMID: 36832294 PMCID: PMC9956028 DOI: 10.3390/diagnostics13040806] [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: 01/10/2023] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
Prostate cancer is the second leading cause of cancer-related death in men. Its early and correct diagnosis is of particular importance to controlling and preventing the disease from spreading to other tissues. Artificial intelligence and machine learning have effectively detected and graded several cancers, in particular prostate cancer. The purpose of this review is to show the diagnostic performance (accuracy and area under the curve) of supervised machine learning algorithms in detecting prostate cancer using multiparametric MRI. A comparison was made between the performances of different supervised machine-learning methods. This review study was performed on the recent literature sourced from scientific citation websites such as Google Scholar, PubMed, Scopus, and Web of Science up to the end of January 2023. The findings of this review reveal that supervised machine learning techniques have good performance with high accuracy and area under the curve for prostate cancer diagnosis and prediction using multiparametric MR imaging. Among supervised machine learning methods, deep learning, random forest, and logistic regression algorithms appear to have the best performance.
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Barrett T, de Rooij M, Giganti F, Allen C, Barentsz JO, Padhani AR. Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway. Nat Rev Urol 2023; 20:9-22. [PMID: 36168056 DOI: 10.1038/s41585-022-00648-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/11/2022] [Indexed: 01/11/2023]
Abstract
Multiparametric MRI of the prostate is now recommended as the initial diagnostic test for men presenting with suspected prostate cancer, with a negative MRI enabling safe avoidance of biopsy and a positive result enabling MRI-directed sampling of lesions. The diagnostic pathway consists of several steps, from initial patient presentation and preparation to performing and interpreting MRI, communicating the imaging findings, outlining the prostate and intra-prostatic target lesions, performing the biopsy and assessing the cores. Each component of this pathway requires experienced clinicians, optimized equipment, good inter-disciplinary communication between specialists, and standardized workflows in order to achieve the expected outcomes. Assessment of quality and mitigation measures are essential for the success of the MRI-directed prostate cancer diagnostic pathway. Quality assurance processes including Prostate Imaging-Reporting and Data System, template biopsy, and pathology guidelines help to minimize variation and ensure optimization of the diagnostic pathway. Quality control systems including the Prostate Imaging Quality scoring system, patient-level outcomes (such as Prostate Imaging-Reporting and Data System MRI score assignment and cancer detection rates), multidisciplinary meeting review and audits might also be used to provide consistency of outcomes and ensure that all the benefits of the MRI-directed pathway are achieved.
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Affiliation(s)
- Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.
| | - Maarten de Rooij
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Francesco Giganti
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
- Division of Surgery and Interventional Science, University College London, London, UK
| | - Clare Allen
- Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK
| | - Jelle O Barentsz
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, Middlesex, UK
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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: 1.7] [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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Adams LC, Makowski MR, Engel G, Rattunde M, Busch F, Asbach P, Niehues SM, Vinayahalingam S, van Ginneken B, Litjens G, Bressem KK. Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection. Comput Biol Med 2022; 148:105817. [PMID: 35841780 DOI: 10.1016/j.compbiomed.2022.105817] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 06/12/2022] [Accepted: 07/03/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND The development of deep learning (DL) models for prostate segmentation on magnetic resonance imaging (MRI) depends on expert-annotated data and reliable baselines, which are often not publicly available. This limits both reproducibility and comparability. METHODS Prostate158 consists of 158 expert annotated biparametric 3T prostate MRIs comprising T2w sequences and diffusion-weighted sequences with apparent diffusion coefficient maps. Two U-ResNets trained for segmentation of anatomy (central gland, peripheral zone) and suspicious lesions for prostate cancer (PCa) with a PI-RADS score of ≥4 served as baseline algorithms. Segmentation performance was evaluated using the Dice similarity coefficient (DSC), the Hausdorff distance (HD), and the average surface distance (ASD). The Wilcoxon test with Bonferroni correction was used to evaluate differences in performance. The generalizability of the baseline model was assessed using the open datasets Medical Segmentation Decathlon and PROSTATEx. RESULTS Compared to Reader 1, the models achieved a DSC/HD/ASD of 0.88/18.3/2.2 for the central gland, 0.75/22.8/1.9 for the peripheral zone, and 0.45/36.7/17.4 for PCa. Compared with Reader 2, the DSC/HD/ASD were 0.88/17.5/2.6 for the central gland, 0.73/33.2/1.9 for the peripheral zone, and 0.4/39.5/19.1 for PCa. Interrater agreement measured in DSC/HD/ASD was 0.87/11.1/1.0 for the central gland, 0.75/15.8/0.74 for the peripheral zone, and 0.6/18.8/5.5 for PCa. Segmentation performances on the Medical Segmentation Decathlon and PROSTATEx were 0.82/22.5/3.4; 0.86/18.6/2.5 for the central gland, and 0.64/29.2/4.7; 0.71/26.3/2.2 for the peripheral zone. CONCLUSIONS We provide an openly accessible, expert-annotated 3T dataset of prostate MRI and a reproducible benchmark to foster the development of prostate segmentation algorithms.
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Affiliation(s)
- Lisa C Adams
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| | - Marcus R Makowski
- Technical University of Munich, Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Ismaninger Str. 22, 81675, Munich, Germany
| | - Günther Engel
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany; Institute for Diagnostic and Interventional Radiology, Georg-August University, Göttingen, Germany
| | - Maximilian Rattunde
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Felix Busch
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Patrick Asbach
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Stefan M Niehues
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Shankeeth Vinayahalingam
- Department of Oral and Maxillofacial Surgery, Radboud University Medical Center, Nijmegen, GA, the Netherlands
| | | | - Geert Litjens
- Radboud University Medical Center, Nijmegen, GA, the Netherlands
| | - Keno K Bressem
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute for Radiology, Luisenstraße 7, 10117, Hindenburgdamm 30, 12203, Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
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Belue MJ, Yilmaz EC, Daryanani A, Turkbey B. Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis. Life (Basel) 2022; 12:804. [PMID: 35743835 PMCID: PMC9224842 DOI: 10.3390/life12060804] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 05/23/2022] [Accepted: 05/23/2022] [Indexed: 12/19/2022] Open
Abstract
The role of multiparametric MRI (mpMRI) in the detection of prostate cancer is well-established. Based on the limited role of dynamic contrast enhancement (DCE) in PI-RADS v2.1, the risk of potential side effects, and the increased cost and time, there has been an increase in studies advocating for the omission of DCE from MRI assessments. Per PI-RADS v2.1, DCE is indicated in the assessment of PI-RADS 3 lesions in the peripheral zone, with its most pronounced effect when T2WI and DWI are of insufficient quality. The aim of this study was to evaluate the methodology and reporting in the literature from the past 5 years regarding the use of DCE in prostate MRI, especially with respect to the indications for DCE as stated in PI-RADS v2.1, and to describe the different approaches used across the studies. We searched for studies investigating the use of bpMRI and/or mpMRI in the detection of clinically significant prostate cancer between January 2017 and April 2022 in the PubMed, Web of Science, and Google Scholar databases. Through the search process, a total of 269 studies were gathered and 41 remained after abstract and full-text screening. The following information was extracted from the eligible studies: general clinical and technical characteristics of the studies, the number of PI-RADS 3 lesions, different definitions of clinically significant prostate cancer (csPCa), biopsy thresholds, reference standard methods, and number and experience of readers. Forty-one studies were included in the study. Only 51% (21/41) of studies reported the prevalence of csPCa in their equivocal lesion (PI-RADS category 3 lesions) subgroups. Of the included studies, none (0/41) performed a stratified sub-analysis of the DCE benefit versus MRI quality and 46% (19/41) made explicit statements about removing MRI scans based on a range of factors including motion, noise, and image artifacts. Furthermore, the number of studies investigating the role of DCE using readers with varying experience was relatively low. This review demonstrates that a high proportion of the studies investigating whether bpMRI can replace mpMRI did not transparently report information inherent to their study design concerning the key indications of DCE, such as the number of clinically insignificant/significant PI-RADS 3 lesions, nor did they provide any sub-analyses to test image quality, with some removing bad quality MRI scans altogether, or reader-experience-dependency indications for DCE. For the studies that reported on most of the DCE indications, their conclusions about the utility of DCE were heavily definition-dependent (with varying definitions of csPCa and of the PI-RADS category biopsy significance threshold). Reporting the information inherent to the study design and related to the specific indications for DCE as stated in PI-RADS v2.1 is needed to determine whether DCE is helpful or not. With most of the recent literature being retrospective and not including the data related to DCE indications in particular, the ongoing dispute between bpMRI and mpMRI is likely to linger.
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Affiliation(s)
| | | | | | - Baris Turkbey
- Molecular Imaging Branch, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892-9760, USA; (M.J.B.); (E.C.Y.); (A.D.)
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Kortenbach KC, Løgager V, Thomsen HS, Boesen L. Early experience in avoiding biopsies for biopsy-naïve men with clinical suspicion of prostate cancer but non-suspicious biparametric magnetic resonance imaging results and prostate-specific antigen density < 0.15 ng/mL 2: A 2-year follow-up study. Acta Radiol Open 2022; 11:20584601221094825. [PMID: 35464293 PMCID: PMC9024082 DOI: 10.1177/20584601221094825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background Only limited data have been published on the diagnostic accuracy of combining biparametric (bp) magnetic resonance imaging (MRI) and prostate-specific antigen density (PSAd) to rule out biopsies. Purpose The purpose is to assess the 2-year risk of being diagnosed with sPCa following the strategy of avoiding immediate biopsies in men with non-suspicious bp MRIs and a PSAd <0.15 ng/mL2. Material and Methods Two hundred biopsy-naïve men with clinical suspicion of PCa underwent a pre-biopsy bp MRI from March to July 2019. Of these, 109 men had a Prostate Imaging Reporting and Data System (PI-RADS) score of 1–3 including 77 men with calculated PSAd <0.15 ng/mL2. As a result, no biopsies were performed in these 77 men, who were clinically followed up for at least 2 years and re-examined in case of rising suspicion of sPCa. The remaining 32 men with a calculated PSAd ≥0.15 ng/mL2 underwent systematic biopsies and targeted biopsies of any PI-RADS 3 lesion. Results One of the 77 men (1.3%) had an sPCa diagnosed within 2 years of follow-up. All men were referred back to their general practitioner within 1 year and 9% (7/77) were re-referred to the urology department during follow-up. Among these men, 43% (3/7) continued to have PSA levels that were above their individual thresholds at confirmatory testing and underwent secondary MRI scans. Conclusions No biopsies for men with bpMRI results exhibiting maximum PI-RADS 3 and with a PSAd <0.15 ng/mL2 resulted in a 2-year risk of being diagnosed with sPCa of 1.3%.
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Affiliation(s)
| | - Vibeke Løgager
- Department of Radiology, Herlev Gentofte University Hospital, Herlev, Denmark
| | - Henrik S Thomsen
- Department of Radiology, Herlev Gentofte University Hospital, Herlev, Denmark
| | - Lars Boesen
- Department of Urological Research, Herlev Gentofte University Hospital, Herlev, Denmark
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Ippoliti S, Fletcher P, Orecchia L, Miano R, Kastner C, Barrett T. Optimal biopsy approach for detection of clinically significant prostate cancer. Br J Radiol 2022; 95:20210413. [PMID: 34357796 PMCID: PMC8978235 DOI: 10.1259/bjr.20210413] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/14/2021] [Accepted: 07/18/2021] [Indexed: 11/05/2022] Open
Abstract
Prostate cancer (PCa) diagnostic and therapeutic work-up has evolved significantly in the last decade, with pre-biopsy multiparametric MRI now widely endorsed within international guidelines. There is potential to move away from the widespread use of systematic biopsy cores and towards an individualised risk-stratified approach. However, the evidence on the optimal biopsy approach remains heterogeneous, and the aim of this review is to highlight the most relevant features following a critical assessment of the literature. The commonest biopsy approaches are via the transperineal (TP) or transrectal (TR) routes. The former is considered more advantageous due to its negligible risk of post-procedural sepsis and reduced need for antimicrobial prophylaxis; the more recent development of local anaesthetic (LA) methods now makes this approach feasible in the clinic. Beyond this, several techniques are available, including cognitive registration, MRI-Ultrasound fusion imaging and direct MRI in-bore guided biopsy. Evidence shows that performing targeted biopsies reduces the number of cores required and can achieve acceptable rates of detection whilst helping to minimise complications and reducing pathologist workloads and costs to health-care facilities. Pre-biopsy MRI has revolutionised the diagnostic pathway for PCa, and optimising the biopsy process is now a focus. Combining MR imaging, TP biopsy and a more widespread use of LA in an outpatient setting seems a reasonable solution to balance health-care costs and benefits, however, local choices are likely to depend on the expertise and experience of clinicians and on the technology available.
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Affiliation(s)
- Simona Ippoliti
- Urology Department, The Queen Elizabeth Hospital NHS Foundation Trust, King’s Lynn, Norfolk, UK
| | - Peter Fletcher
- Urology Department, Cambridge University Hospitals, Cambridge, UK
| | | | | | - Christof Kastner
- Urology Department, Cambridge University Hospitals, Cambridge, UK
| | - Tristan Barrett
- Radiology Department, Cambridge University Hospitals, Cambridge, UK
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Caglic I, Sushentsev N, Shah N, Warren AY, Lamb BW, Barrett T. Integration of Prostate Biopsy Results with Pre-Biopsy Multiparametric Magnetic Resonance Imaging Findings Improves Local Staging of Prostate Cancer. Can Assoc Radiol J 2022; 73:515-523. [PMID: 35199583 DOI: 10.1177/08465371211073158] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
PURPOSE To assess the added value of histological information for local staging of prostate cancer (PCa) by comparing the accuracy of multiparametric MRI alone (mpMRI) and mpMRI with biopsy Gleason grade (mpMRI+Bx). METHODS 133 consecutive patients who underwent preoperative 3T-MRI and subsequent radical prostatectomy for PCa were included in this single-centre retrospective study. mpMRI imaging was reviewed independently by two uroradiologists for the presence of extracapsular extension (ECE) and seminal vesicle invasion (SVI) on a 5-point Likert scale. For second reads, the radiologists received results of targeted fused MR/US biopsy (mpMRI+Bx) prior to re-staging. RESULTS The median patient age was 63 years (interquartile range (IQR) 58-67 years) and median PSA was 6.5 ng/mL (IQR 5.0-10.0 ng/mL). Extracapsular extension was present in 85/133 (63.9%) patients and SVI was present in 22/133 (16.5%) patients. For ECE prediction, mpMRI showed sensitivity and specificity of 63.5% and 81.3%, respectively, compared to 77.7% and 81.3% achieved by mpMRI+Bx. At an optimal cut-off value of Likert score ≥ 3, areas under the curves (AUCs) was .85 for mpMRI+Bx and .78 for mpMRI, P < .01. For SVI prediction, AUC was .95 for mpMRI+Bx compared to .92 for mpMRI; P = .20. Inter-reader agreement for ECE and SVI prediction was substantial for mpMRI (k range, .78-.79) and mpMRI+Bx (k range, .74-.79). CONCLUSIONS MpMRI+Bx showed superior diagnostic performance with an increased sensitivity for ECE prediction but no significant difference for SVI prediction. Inter-reader agreement was substantial for both protocols. Integration of biopsy information adds value when staging prostate mpMRI.
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Affiliation(s)
- Iztok Caglic
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Radiology, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Faculty of Medicine, University of Ljubljana, Slovenia
| | - Nikita Sushentsev
- Department of Radiology, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Nimish Shah
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Urology, 573020Addenbrooke's Hospital, Cambridge, UK
| | - Anne Y Warren
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Pathology, 573020Addenbrooke's Hospital, Cambridge, UK
| | - Benjamin W Lamb
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Urology, 573020Addenbrooke's Hospital, Cambridge, UK
| | - Tristan Barrett
- CamPARI Prostate Cancer Group, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
- Department of Radiology, 573020Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
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Pellicer-Valero OJ, Marenco Jiménez JL, Gonzalez-Perez V, Casanova Ramón-Borja JL, Martín García I, Barrios Benito M, Pelechano Gómez P, Rubio-Briones J, Rupérez MJ, Martín-Guerrero JD. Deep learning for fully automatic detection, segmentation, and Gleason grade estimation of prostate cancer in multiparametric magnetic resonance images. Sci Rep 2022; 12:2975. [PMID: 35194056 PMCID: PMC8864013 DOI: 10.1038/s41598-022-06730-6] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 02/03/2022] [Indexed: 02/07/2023] Open
Abstract
Although the emergence of multi-parametric magnetic resonance imaging (mpMRI) has had a profound impact on the diagnosis of prostate cancers (PCa), analyzing these images remains still complex even for experts. This paper proposes a fully automatic system based on Deep Learning that performs localization, segmentation and Gleason grade group (GGG) estimation of PCa lesions from prostate mpMRIs. It uses 490 mpMRIs for training/validation and 75 for testing from two different datasets: ProstateX and Valencian Oncology Institute Foundation. In the test set, it achieves an excellent lesion-level AUC/sensitivity/specificity for the GGG[Formula: see text]2 significance criterion of 0.96/1.00/0.79 for the ProstateX dataset, and 0.95/1.00/0.80 for the IVO dataset. At a patient level, the results are 0.87/1.00/0.375 in ProstateX, and 0.91/1.00/0.762 in IVO. Furthermore, on the online ProstateX grand challenge, the model obtained an AUC of 0.85 (0.87 when trained only on the ProstateX data, tying up with the original winner of the challenge). For expert comparison, IVO radiologist's PI-RADS 4 sensitivity/specificity were 0.88/0.56 at a lesion level, and 0.85/0.58 at a patient level. The full code for the ProstateX-trained model is openly available at https://github.com/OscarPellicer/prostate_lesion_detection . We hope that this will represent a landmark for future research to use, compare and improve upon.
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Affiliation(s)
- Oscar J Pellicer-Valero
- Intelligent Data Analysis Laboratory, Department of Electronic Engineering, ETSE (Engineering School), Universitat de València (UV), Av. Universitat, sn, 46100, Bujassot, Valencia, Spain.
| | - José L Marenco Jiménez
- Department of Urology, Fundación Instituto Valenciano de Oncología (FIVO), Beltrán Báguena, 8, 46009, Valencia, Spain
| | - Victor Gonzalez-Perez
- Department of Medical Physics, Fundación Instituto, Valenciano de Oncología (FIVO), Beltrán Báguena, 8, 46009, Valencia, Spain
| | | | - Isabel Martín García
- Department of Radiodiagnosis, Fundación Instituto, Valenciano de Oncología (FIVO), Beltrán Báguena, 8, 46009, Valencia, Spain
| | - María Barrios Benito
- Department of Radiodiagnosis, Fundación Instituto, Valenciano de Oncología (FIVO), Beltrán Báguena, 8, 46009, Valencia, Spain
| | - Paula Pelechano Gómez
- Department of Radiodiagnosis, Fundación Instituto, Valenciano de Oncología (FIVO), Beltrán Báguena, 8, 46009, Valencia, Spain
| | - José Rubio-Briones
- Department of Urology, Fundación Instituto Valenciano de Oncología (FIVO), Beltrán Báguena, 8, 46009, Valencia, Spain
| | - María José Rupérez
- Instituto de Ingeniería Mecánica y Biomecánica, Universitat Politècnica de València (UPV), Camino de Vera, sn, 46022, Valencia, Spain
| | - José D Martín-Guerrero
- Intelligent Data Analysis Laboratory, Department of Electronic Engineering, ETSE (Engineering School), Universitat de València (UV), Av. Universitat, sn, 46100, Bujassot, Valencia, Spain
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43
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Li D, Han X, Gao J, Zhang Q, Yang H, Liao S, Guo H, Zhang B. Deep Learning in Prostate Cancer Diagnosis Using Multiparametric Magnetic Resonance Imaging With Whole-Mount Histopathology Referenced Delineations. Front Med (Lausanne) 2022; 8:810995. [PMID: 35096899 PMCID: PMC8793798 DOI: 10.3389/fmed.2021.810995] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Multiparametric magnetic resonance imaging (mpMRI) plays an important role in the diagnosis of prostate cancer (PCa) in the current clinical setting. However, the performance of mpMRI usually varies based on the experience of the radiologists at different levels; thus, the demand for MRI interpretation warrants further analysis. In this study, we developed a deep learning (DL) model to improve PCa diagnostic ability using mpMRI and whole-mount histopathology data. Methods: A total of 739 patients, including 466 with PCa and 273 without PCa, were enrolled from January 2017 to December 2019. The mpMRI (T2 weighted imaging, diffusion weighted imaging, and apparent diffusion coefficient sequences) data were randomly divided into training (n = 659) and validation datasets (n = 80). According to the whole-mount histopathology, a DL model, including independent segmentation and classification networks, was developed to extract the gland and PCa area for PCa diagnosis. The area under the curve (AUC) were used to evaluate the performance of the prostate classification networks. The proposed DL model was subsequently used in clinical practice (independent test dataset; n = 200), and the PCa detective/diagnostic performance between the DL model and different level radiologists was evaluated based on the sensitivity, specificity, precision, and accuracy. Results: The AUC of the prostate classification network was 0.871 in the validation dataset, and it reached 0.797 using the DL model in the test dataset. Furthermore, the sensitivity, specificity, precision, and accuracy of the DL model for diagnosing PCa in the test dataset were 0.710, 0.690, 0.696, and 0.700, respectively. For the junior radiologist without and with DL model assistance, these values were 0.590, 0.700, 0.663, and 0.645 versus 0.790, 0.720, 0.738, and 0.755, respectively. For the senior radiologist, the values were 0.690, 0.770, 0.750, and 0.730 vs. 0.810, 0.840, 0.835, and 0.825, respectively. The diagnosis made with DL model assistance for radiologists were significantly higher than those without assistance (P < 0.05). Conclusion: The diagnostic performance of DL model is higher than that of junior radiologists and can improve PCa diagnostic accuracy in both junior and senior radiologists.
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Affiliation(s)
- Danyan Li
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China.,Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Xiaowei Han
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Jie Gao
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Qing Zhang
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Haibo Yang
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Shu Liao
- Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
| | - Hongqian Guo
- Department of Urology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China.,Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
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44
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Diagnostic Accuracy of Abbreviated Bi-Parametric MRI (a-bpMRI) for Prostate Cancer Detection and Screening: A Multi-Reader Study. Diagnostics (Basel) 2022; 12:diagnostics12020231. [PMID: 35204322 PMCID: PMC8871361 DOI: 10.3390/diagnostics12020231] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/07/2022] [Accepted: 01/12/2022] [Indexed: 11/25/2022] Open
Abstract
(1) Background: There is currently limited evidence on the diagnostic accuracy of abbreviated biparametric MRI (a-bpMRI) protocols for prostate cancer (PCa) detection and screening. In the present study, we aim to investigate the performance of a-bpMRI among multiple readers and its potential application to an imaging-based screening setting. (2) Methods: A total of 151 men who underwent 3T multiparametric MRI (mpMRI) of the prostate and transperineal template prostate mapping biopsies were retrospectively selected. Corresponding bpMRI (multiplanar T2WI, DWI, ADC maps) and a-bpMRI (axial T2WI and b 2000 s/mm2 DWI only) dataset were derived from mpMRI. Three experienced radiologists scored a-bpMRI, standard biparametric MRI (bpMRI) and mpMRI in separate sessions. Diagnostic accuracy and interreader agreement of a-bpMRI was tested for different positivity thresholds and compared to bpMRI and mpMRI. Predictive values of a-bpMRI were computed for lower levels of PCa prevalence to simulate a screening setting. The primary definition of clinically significant PCa (csPCa) was Gleason ≥ 4 + 3, or cancer core length ≥ 6 mm. (3) Results: The median age was 62 years, the median PSA was 6.8 ng/mL, and the csPCa prevalence was 40%. Using a cut off of MRI score ≥ 3, the sensitivity and specificity of a-bpMRI were 92% and 48%, respectively. There was no significant difference in sensitivity compared to bpMRI and mpMRI. Interreader agreement of a-bpMRI was moderate (AC1 0.58). For a low prevalence of csPCa (e.g., <10%), higher cut offs (MRI score ≥ 4) yield a more favourable balance between the predictive values and positivity rate of MRI. (4) Conclusion: Abbreviated bpMRI protocols could match the diagnostic accuracy of bpMRI and mpMRI for the detection of csPCa. If a-bpMRI is used in low-prevalence settings, higher cut-offs for MRI positivity should be prioritised.
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45
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Kortenbach KC, Boesen L, Løgager V, Thomsen HS. Outcome of 5-year follow-up in men with negative findings on initial biparametric MRI. Heliyon 2021; 7:e08325. [PMID: 34820539 PMCID: PMC8601994 DOI: 10.1016/j.heliyon.2021.e08325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 08/23/2021] [Accepted: 11/02/2021] [Indexed: 11/26/2022] Open
Abstract
Background We assessed the 5-year risk of being diagnosed with significant prostate cancer following a low-suspicion biparametric magnetic resonance imaging result. Methods The study population was derived from a prospective database used to assess the diagnostic accuracy of biparametric magnetic resonance imaging for significant prostate cancer detection in 1020 biopsy-naïve men. Significant prostate cancer was defined as any core with Gleason grade group ≥3 or a maximum cancerous core length greater than 50% of Gleason grade group 2. A secondary definition of significant prostate cancer was also included: any core with prostate cancer Gleason grade group ≥2. Of the 1020 men, 305 had a low-suspicion biparametric magnetic resonance imaging result (Prostate Imaging Reporting and Data System score of 1 or 2) but four men were excluded from follow-up. Thus, the final study population consisted of 301 men, who were clinically followed-up from inclusion (November 2015 to June 2017) until 1 June 2021. Findings Overall, 1·7% (5/301) of the study population had significant prostate cancer diagnosed within 5 years (median 1480 days, Interquartile Range (1587-1382)) of their low-suspicion result and corresponding set of biopsies. When the secondary definition of significant prostate cancer was applied, this increased to 5% (15/301) of the study population. Interpretation The 5-year risk of being diagnosed with significant prostate cancer after a prebiopsy low-suspicion prebiopsy biparametric magnetic resonance imaging result was 1·7%.
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Affiliation(s)
- Karen-Cecilie Kortenbach
- Herlev Gentofte University Hospital, Department of Radiology, Borgmester Ib Juuls vej 17, DK-2730 Herlev, Denmark
| | - Lars Boesen
- Herlev Gentofte University Hospital, Department of Radiology, Borgmester Ib Juuls vej 17, DK-2730 Herlev, Denmark
| | - Vibeke Løgager
- Herlev Gentofte University Hospital, Department of Radiology, Borgmester Ib Juuls vej 17, DK-2730 Herlev, Denmark
| | - Henrik S Thomsen
- Herlev Gentofte University Hospital, Department of Radiology, Borgmester Ib Juuls vej 17, DK-2730 Herlev, Denmark
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46
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Schick F, Pieper CC, Kupczyk P, Almansour H, Keller G, Springer F, Mürtz P, Endler C, Sprinkart AM, Kaufmann S, Herrmann J, Attenberger UI. 1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 1. Invest Radiol 2021; 56:680-691. [PMID: 34324464 DOI: 10.1097/rli.0000000000000812] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
ABSTRACT Whole-body magnetic resonance imaging (MRI) systems with a field strength of 3 T have been offered by all leading manufacturers for approximately 2 decades and are increasingly used in clinical diagnostics despite higher costs. Technologically, MRI systems operating at 3 T have reached a high standard in recent years, as well as the 1.5-T devices that have been in use for a longer time. For modern MRI systems with 3 T, more complexity is required, especially for the magnet and the radiofrequency (RF) system (with multichannel transmission). Many clinical applications benefit greatly from the higher field strength due to the higher signal yield (eg, imaging of the brain or extremities), but there are also applications where the disadvantages of 3 T might outweigh the advantages (eg, lung imaging or examinations in the presence of implants). This review describes some technical features of modern 1.5-T and 3-T whole-body MRI systems, and reports on the experience of using both types of devices in different clinical settings, with all sections written by specialist radiologists in the respective fields.This first part of the review includes an overview of the general physicotechnical aspects of both field strengths and elaborates the special conditions of diffusion imaging. Many relevant aspects in the application areas of musculoskeletal imaging, abdominal imaging, and prostate diagnostics are discussed.
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Affiliation(s)
- Fritz Schick
- From the Section of Experimental Radiology, Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen
| | | | - Patrick Kupczyk
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Haidara Almansour
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Gabriel Keller
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Fabian Springer
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Petra Mürtz
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Christoph Endler
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Alois M Sprinkart
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Sascha Kaufmann
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Judith Herrmann
- Department of Radiology, Diagnostic, and Interventional Radiology, University of Tübingen, Tübingen, Germany
| | - Ulrike I Attenberger
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
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Bass EJ, Pantovic A, Connor M, Gabe R, Padhani AR, Rockall A, Sokhi H, Tam H, Winkler M, Ahmed HU. A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk. Prostate Cancer Prostatic Dis 2021; 24:596-611. [PMID: 33219368 DOI: 10.1038/s41391-020-00298-w] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 10/14/2020] [Accepted: 10/19/2020] [Indexed: 02/01/2023]
Abstract
INTRODUCTION Multiparametric magnetic resonance imaging (mpMRI), the use of three multiple imaging sequences, typically T2-weighted, diffusion weighted (DWI) and dynamic contrast enhanced (DCE) images, has a high sensitivity and specificity for detecting significant cancer. Current guidance now recommends its use prior to biopsy. However, the impact of DCE is currently under debate regarding test accuracy. Biparametric MRI (bpMRI), using only T2 and DWI has been proposed as a viable alternative. We conducted a contemporary systematic review and meta-analysis to further examine the diagnostic performance of bpMRI in the diagnosis of any and clinically significant prostate cancer. METHODS A systematic review of the literature from 01/01/2017 to 06/07/2019 was performed by two independent reviewers using predefined search criteria. The index test was biparametric MRI and the reference standard whole-mount prostatectomy or prostate biopsy. Quality of included studies was assessed by the QUADAS-2 tool. Statistical analysis included pooled diagnostic performance (sensitivity; specificity; AUC), meta-regression of possible covariates and head-to-head comparisons of bpMRI and mpMRI where both were performed in the same study. RESULTS Forty-four articles were included in the analysis. The pooled sensitivity for any cancer detection was 0.84 (95% CI, 0.80-0.88), specificity 0.75 (95% CI, 0.68-0.81) for bpMRI. The summary ROC curve yielded a high AUC value (AUC = 0.86). The pooled sensitivity for clinically significant prostate cancer was 0.87 (95% CI, 0.78-0.93), specificity 0.72 (95% CI, 0.56-0.84) and the AUC value was 0.87. Meta-regression analysis revealed no difference in the pooled diagnostic estimates between bpMRI and mpMRI. CONCLUSIONS This meta-analysis on contemporary studies shows that bpMRI offers comparable test accuracies to mpMRI in detecting prostate cancer. These data are broadly supportive of the bpMRI approach but heterogeneity does not allow definitive recommendations to be made. There is a need for prospective multicentre studies of bpMRI in biopsy naïve men.
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Affiliation(s)
- E J Bass
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK. .,Imperial Urology, Division of Cancer, Cardiovascular Medicine and Surgery, Imperial College Healthcare NHS Trust, London, UK.
| | - A Pantovic
- Centre of Research Excellence in Nutrition and Metabolism, Institute for Medical Research, Belgrade, Serbia
| | - M Connor
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.,Imperial Urology, Division of Cancer, Cardiovascular Medicine and Surgery, Imperial College Healthcare NHS Trust, London, UK
| | - R Gabe
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - A R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, London, UK
| | - A Rockall
- Division of Cancer, Department of Surgery and Cancer,Faculty of Medicine, Imperial College London, London, UK
| | - H Sokhi
- Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, London, UK.,Department of Radiology, Hillingdon Hospitals NHS Foundation Trust, London, UK
| | - H Tam
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.,Department of Radiology, Imperial College Healthcare NHS Trust, London, UK
| | - M Winkler
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.,Imperial Urology, Division of Cancer, Cardiovascular Medicine and Surgery, Imperial College Healthcare NHS Trust, London, UK
| | - H U Ahmed
- Imperial Prostate, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.,Imperial Urology, Division of Cancer, Cardiovascular Medicine and Surgery, Imperial College Healthcare NHS Trust, London, UK
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48
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Czyzewska D, Sushentsev N, Latoch E, Slough RA, Barrett T. T2-PROPELLER Compared to T2-FRFSE for Image Quality and Lesion Detection at Prostate MRI. Can Assoc Radiol J 2021; 73:355-361. [PMID: 34423672 DOI: 10.1177/08465371211030206] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
PURPOSE The primary objective was to compare T2-FRFSE and T2-PROPELLER sequences for image quality. The secondary objective was to compare the ability to detect prostate lesions at MRI in the presence and absence of motion artefact using the 2 sequences. METHODS 99 patients underwent 3 T MRI examination of the prostate, including T2-FRFSE and T2-PROPELLER sequences. All patients underwent prostate biopsy. Two independent readers rated overall image quality, presence of motion artefact, and blurring for both sequences using a 5-point Likert scale. Scores were compared for the whole group and for subgroups with and without significant motion artefact. Outcome for lesion detection at an MRI threshold of PI-RADS score ≥3 was compared between T2-FRFSE and T2-PROPELLER. RESULTS The overall image quality was not significantly different between T2-FRFSE and T2-PROPELLER sequences (3.74 vs. 3.93, p = 0.275). T2-PROPELLER recorded a lesser degree of motion artefact (score 4.53 vs. 3.78, p <0.0001), but demonstrated greater image blurring (score 3.29 vs. 3.73, p <0.001). However, in a subgroup of patients with significant motion artefact on T2-FRFSE, the T2-PROPELLER sequence demonstrated significantly higher image quality (3.46 vs. 2.49, p <0.001). T2-FRFSE and T2-PROPELLER showed comparable positive predictive values for lesion detection at 93.2% and 97.7%, respectively. CONCLUSIONS T2-PROPELLER provides higher quality imaging in the presence of motion artefact, but T2-FRFSE is preferred in the absence of motion. T2-PROPELLER is therefore recommended as a secondary T2 sequence when imaging requires repeat acquisition due to motion artefact.
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Affiliation(s)
- Dorota Czyzewska
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen, Denmark
| | - Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Eryk Latoch
- Department of Pediatric Oncology and Hematology, Medical University of Bialystok, Poland
| | - Rhys A Slough
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge, UK.,CamPARI Prostate Cancer Group, Addenbrooke's Hospital and University of Cambridge, Cambridge, United Kingdom
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49
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Hötker AM, Da Mutten R, Tiessen A, Konukoglu E, Donati OF. Improving workflow in prostate MRI: AI-based decision-making on biparametric or multiparametric MRI. Insights Imaging 2021; 12:112. [PMID: 34370164 PMCID: PMC8353049 DOI: 10.1186/s13244-021-01058-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 07/13/2021] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVES To develop and validate an artificial intelligence algorithm to decide on the necessity of dynamic contrast-enhanced sequences (DCE) in prostate MRI. METHODS This study was approved by the institutional review board and requirement for study-specific informed consent was waived. A convolutional neural network (CNN) was developed on 300 prostate MRI examinations. Consensus of two expert readers on the necessity of DCE acted as reference standard. The CNN was validated in a separate cohort of 100 prostate MRI examinations from the same vendor and 31 examinations from a different vendor. Sensitivity/specificity were calculated using ROC curve analysis and results were compared to decisions made by a radiology technician. RESULTS The CNN reached a sensitivity of 94.4% and specificity of 68.8% (AUC: 0.88) for the necessity of DCE, correctly assigning 44%/34% of patients to a biparametric/multiparametric protocol. In 2% of all patients, the CNN incorrectly decided on omitting DCE. With a technician reaching a sensitivity of 63.9% and specificity of 89.1%, the use of the CNN would allow for an increase in sensitivity of 30.5%. The CNN achieved an AUC of 0.73 in a set of examinations from a different vendor. CONCLUSIONS The CNN would have correctly assigned 78% of patients to a biparametric or multiparametric protocol, with only 2% of all patients requiring re-examination to add DCE sequences. Integrating this CNN in clinical routine could render the requirement for on-table monitoring obsolete by performing contrast-enhanced MRI only when needed.
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Affiliation(s)
- 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
| | - Anja Tiessen
- 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
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50
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Sushentsev N, Rundo L, Blyuss O, Gnanapragasam VJ, Sala E, Barrett T. MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance. Sci Rep 2021; 11:12917. [PMID: 34155265 PMCID: PMC8217549 DOI: 10.1038/s41598-021-92341-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 06/03/2021] [Indexed: 02/05/2023] Open
Abstract
Nearly half of patients with prostate cancer (PCa) harbour low- or intermediate-risk disease considered suitable for active surveillance (AS). However, up to 44% of patients discontinue AS within the first five years, highlighting the unmet clinical need for robust baseline risk-stratification tools that enable timely and accurate prediction of tumour progression. In this proof-of-concept study, we sought to investigate the added value of MRI-derived radiomic features to standard-of-care clinical parameters for improving baseline prediction of PCa progression in AS patients. Tumour T2-weighted imaging (T2WI) and apparent diffusion coefficient radiomic features were extracted, with rigorous calibration and pre-processing methods applied to select the most robust features for predictive modelling. Following leave-one-out cross-validation, the addition of T2WI-derived radiomic features to clinical variables alone improved the area under the ROC curve for predicting progression from 0.61 (95% confidence interval [CI] 0.481-0.743) to 0.75 (95% CI 0.64-0.86). These exploratory findings demonstrate the potential benefit of MRI-derived radiomics to add incremental benefit to clinical data only models in the baseline prediction of PCa progression on AS, paving the way for future multicentre studies validating the proposed model and evaluating its impact on clinical outcomes.
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Affiliation(s)
- Nikita Sushentsev
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK.
| | - Leonardo Rundo
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Oleg Blyuss
- School of Physics, Engineering & Computer Science, University of Hertfordshire, Hatfield, UK
- Department of Paediatrics and Paediatric Infectious Diseases, Sechenov First Moscow State Medical University, Moscow, Russia
- Department of Applied Mathematics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
| | - Vincent J Gnanapragasam
- Division of Urology, Department of Surgery, University of Cambridge, Cambridge, UK
- Cambridge Urology Translational Research and Clinical Trials Office, University of Cambridge, Cambridge, UK
| | - Evis Sala
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, UK
| | - Tristan Barrett
- Department of Radiology, Addenbrooke's Hospital, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Box 218, Cambridge, CB2 0QQ, UK
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