CT morphometrics and AI show promise for complex ventral hernia repair but lack robust validation

CT morphometrics (loss of domain, muscle quality) and AI (automated segmentation, radiomics) show promise for predicting outcomes in ventral hernia repair, but evidence is limited to small retrospective studies without external validation.

• CT morphometrics including volumetric assessment, loss of domain, muscle morphology, sarcopenia, and adipose distribution correlate with fascial closure and surgical-site outcomes.
• AI tools such as automated segmentation, radiomics, and machine learning models have shown promising performance for risk prediction but lack standardization and external validation.
• Predominantly retrospective single-centre studies with small datasets limit clinical implementation.

Automated summary

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