Zhong SY, Deng XR, Han BC, Yang LQ, Ye ST, Niu XK. Diagnostic performance of magnetic resonance imaging-based radiomics for detecting prostate cancer: A systematic review and meta-analysis. World J Radiol 2026; 18(3): 116826 [DOI: 10.4329/wjr.v18.i3.116826]
Corresponding Author of This Article
Xiang-Ke Niu, Department of Interventional Radiology, Affiliated Hospital of Chengdu University, No. 82 2nd N Section of Second Ring Road, Chengdu 610081, Sichuan Province, China. niu19850519@163.com
Research Domain of This Article
Urology & Nephrology
Article-Type of This Article
Meta-Analysis
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Mar 28, 2026 (publication date) through Mar 26, 2026
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Journal Information of This Article
Publication Name
World Journal of Radiology
ISSN
1949-8470
Publisher of This Article
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Zhong SY, Deng XR, Han BC, Yang LQ, Ye ST, Niu XK. Diagnostic performance of magnetic resonance imaging-based radiomics for detecting prostate cancer: A systematic review and meta-analysis. World J Radiol 2026; 18(3): 116826 [DOI: 10.4329/wjr.v18.i3.116826]
Shi-Yu Zhong, Xiang-Rong Deng, Department of Radiology, Chongzhou Traditional Chinese Medicine Hospital, Chengdu 611200, Sichuan Province, China
Bang-Cai Han, Department of Radiology, Suzhou BOE Hospital, Suzhou 130021, Jiangsu Province, China
Liu-Qing Yang, Department of Ultrasound, The First Hospital of Jilin University, Changchun 130021, Jilin Province, China
Su-Ting Ye, Department of Function Inspection, Sichuan Integrative Medicine Hospital, Chengdu 610041, Sichuan Province, China
Xiang-Ke Niu, Department of Interventional Radiology, Affiliated Hospital of Chengdu University, Chengdu 610081, Sichuan Province, China
Author contributions: Zhong SY and Niu XK designed the research study; Deng XR and Han BC performed data extraction and analysis; Yang LQ and Ye ST conducted literature screening and quality assessment; Niu XK supervised the study and revised the manuscript. All authors read and approved the final manuscript.
Supported by Natural Science Foundation of Sichuan Province, China, No. 2024NSFSC0657; Sichuan Medical Association Tumor (Hengrui-a Line) Special Scientific Research Project, China, No. 2024HR123; and Innovation Team Foundation of the Affiliated Hospital of Chengdu University, China, No. CDFYCX202204.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Corresponding author: Xiang-Ke Niu, Department of Interventional Radiology, Affiliated Hospital of Chengdu University, No. 82 2nd N Section of Second Ring Road, Chengdu 610081, Sichuan Province, China. niu19850519@163.com
Received: November 24, 2025 Revised: December 8, 2025 Accepted: January 26, 2026 Published online: March 28, 2026 Processing time: 125 Days and 15.4 Hours
Abstract
BACKGROUND
Prostate cancer (PCa) is the second most common malignancy and the fifth leading cause of cancer death among men worldwide. Magnetic resonance imaging (MRI)-based radiomics has emerged as a promising tool for diagnosing PCa, but its true potential remains a subject of ongoing debate.
AIM
To evaluate the diagnostic performance of MRI-based radiomics for PCa detection and compare it with the Prostate Imaging Reporting and Data System (PI-RADS) score.
METHODS
A systematic search of EMBASE, Web of Science, and PubMed was conducted up to August 18, 2025. Pooled sensitivity, specificity, and area under the curve were calculated. Subgroup analyses were performed to evaluate heterogeneity. Additionally, the diagnostic accuracy of MRI-based radiomics was compared with that of the PI-RADS score. Methodological quality was evaluated via the Radiomics Quality Score.
RESULTS
This meta-analysis included 49 studies encompassing 10512 patients. MRI-based radiomics demonstrated a pooled sensitivity of 0.84 [95% confidence interval (CI): 0.80-0.87], specificity of 0.78 (95%CI: 0.72-0.84), and area under the curve of 0.88 (95%CI: 0.85-0.91). Deek’s funnel plot asymmetry test indicated no publication bias. Subgroup analyses revealed that multiparametric MRI-based radiomics is more effective in diagnosing clinically significant PCa and that 3D-based radiomics outperforms 2D approaches. In a head-to-head comparison, the MRI-radiomics model yielded a numerically greater pooled diagnostic value (0.85; 95%CI: 0.82-0.88) than did the PI-RADS score (0.71; 95%CI: 0.63-0.77) (P = 0.07). The mean Radiomics Quality Score was 18.2 (50.6% of the maximum score). All studies reported performing cut-off analyses, 22 studies (44.9%) addressed biological correlates, and all claimed code or data accessibility.
CONCLUSION
MRI-based radiomics is a reliable tool for detecting PCa, with 3D radiomic models showing greater effectiveness than 2D approaches in terms of sensitivity (0.85 vs 0.79). Radiomics also offers superior diagnostic accuracy for clinically significant PCa compared with the PI-RADS score, underscoring its potential in improving PCa diagnostics.
Core Tip: This meta-analysis demonstrates that magnetic resonance imaging-based radiomics is a reliable tool for detecting prostate cancer, with 3D radiomic models offering higher sensitivity than 2D models. Compared to the Prostate Imaging Reporting and Data System score, radiomics shows superior diagnostic accuracy for clinically significant prostate cancer, highlighting its potential to optimize diagnostic workflows and reduce unnecessary biopsies.
