MRI-based radiomics for prediction of extraprostatic extension of prostate cancer: a systematic review and meta-analysis

• Published in: Radiologia medica Vol. 129; no. 5; pp. 702 - 711
• Main Authors: Wen, Jing, Liu, Wei, Zhang, Yilan, Shen, Xiaocui
• Format: Journal Article
• Language: English
• Published: Milan Springer Milan 01.05.2024; Springer Nature B.V
• Subjects: Abdominal Radiology; Diagnostic Radiology; Heterogeneity; Humans; Imaging; Interventional Radiology; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medicine; Medicine & Public Health; Neuroradiology; Performance evaluation; Predictive Value of Tests; Prostate cancer; Prostatic Neoplasms - diagnostic imaging; Prostatic Neoplasms - pathology; Quality assessment; Radiology; Radiomics; Regression analysis; Sensitivity; Sensitivity and Specificity; Subgroups; Ultrasound; Multiparametric magnetic resonance imaging; Prostatic neoplasms; Diagnosis; Radiomics; Meta-analysis
• ISSN: 1826-6983; 0033-8362; 1826-6983
• DOI: 10.1007/s11547-024-01810-1

Purpose We to systematically evaluate the diagnostic performance of MRI radiomics in detecting extracapsular extension (EPE) of prostate cancer (PCa). Methods A literature search of online databases of PubMed, EMBASE, Cochrane Library, Web of Science, and Google Scholar online scientific publication databases was performed to identify studies published up to July 2023. The summary estimates were pooled with the hierarchical summary receiver-operating characteristic (HSROC) model. This study was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, the quality of included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies–2 tool (QUADAS-2) and the radiomics quality score (RQS). Meta-regression and subgroup analyses were performed to explore the impact of varying clinical settings. Results A total of ten studies met the inclusion criteria. The pooled sensitivity and specificity were 0.77 (95% CI 0.68–0.84, I 2  = 83.5%) and 0.75 (95% CI 0.67–0.82, I 2  = 83.5%), respectively, with an area under the HSROC curve of 0.88 (95% CI 0.85–0.91). Study quality was not high while assessing with the RQS. Substantial heterogeneity was observed between studies; however, meta-regression analysis did not reveal any significant contributing factors. Conclusions MRI radiomics demonstrated moderate sensitivity and specificity, offering similar diagnostic performance with previous risk stratifications and models that primarily based on radiologists’ subjective experience. However, all studies included were retrospective, thus the performance of radiomics needs to validate in prospective, multicenter studies.