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

  • Abdominal Radiology
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

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, I2 = 83.5%) and 0.75 (95% CI 0.67–0.82, I2 = 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.

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Author notes

  1. Jing Wen and Wei Liu have contributed equally to this work.

Authors and Affiliations

  1. Department of Medical Imaging, Jiangsu Vocational College of Medicine, Yancheng, China

    Jing Wen, Yilan Zhang & Xiaocui Shen

  2. Department of Radiology, Yancheng Tinghu District People’s Hospital, Yancheng, China

    Wei Liu

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Correspondence to Jing Wen.

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Wen, J., Liu, W., Zhang, Y. et al. MRI-based radiomics for prediction of extraprostatic extension of prostate cancer: a systematic review and meta-analysis. Radiol med 129, 702–711 (2024). https://doi.org/10.1007/s11547-024-01810-1

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