Systematic review and meta-analysis of deep learning for MSI-H in colorectal cancer whole slide images.

ABSTRACT: This meta-analysis evaluated diagnostic performance of deep learning (DL) algorithms using whole slide images (WSIs) for detecting microsatellite instability-high (MSI-H) in colorectal cancer (CRC). PubMed, Embase, and Web of Science were searched until January 2025. Nineteen studies comprising 33,383 samples were included. Bivariate random-effects models calculated pooled sensitivity/specificity with 95% CIs. The revised QUADAS-2 tool was used for quality assessment. Pooled patient-based internal validation showed a sensitivity of 0.88 and specificity of 0.86, while external validation revealed higher sensitivity of 0.93 but lower specificity of 0.71. Image-based analysis showed similar accuracy. Meta-regression identified center, reference standard, and tile size as major sources of hete

SUBMITTER: Li H 

PROVIDER: S-EPMC12274608 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature