Abstract
BACKGROUND: Accurate interpretation of computed tomography (CT) prior to ventral hernia repair (VHR) is critical for operative planning, particularly in recurrent cases where prior mesh type and placement influence surgical approach. While radiologists possess specialized expertise in imaging interpretation, their performance in identifying post-VHR mesh characteristics remains unstudied. This study assesses the diagnostic performance of radiologists in identifying mesh plane and type on CT following VHR. METHODS: Forty body radiologists from 16 centers evaluated 18 de-identified CT scans, including 12 post-VHR cases and 6 controls. After receiving standardized training on mesh characteristics and surgical planes, radiologists were tasked with identifying both the VHR mesh plane and the mesh type. The study assessed correct identification rates, interrater reliability, and repeatability. RESULTS: Radiologists demonstrated overall accuracy rates of 39.2% for mesh plane identification and 43.5% for mesh type identification. Accuracy was highest for intraperitoneal approaches (53.8%) and heavy-weight mesh (52.5%), with significantly lower accuracy (16.9-22.5%) for other surgical planes and mesh types (30.6%). Interrater reliability was poor (Gwet's AC1 = 0.127), with significant between-radiologist variability. Self-reported confidence levels correlated positively with accuracy rates, with high-confidence radiologists showing significantly better performance (OR 4.55, p < 0.001). Years of clinical experience did not predict diagnostic accuracy. CONCLUSIONS: Radiologists demonstrated limited ability to accurately interpret post-VHR CT scans, even after targeted instruction. These diagnostic challenges mirror findings among abdominal wall reconstruction surgeons, suggesting inherent limitations in CT-based assessment rather than discipline-specific deficits. Multidisciplinary collaboration, standardized operative documentation, and dedicated abdominal wall imaging protocol and training are essential to improve diagnostic accuracy and optimize surgical planning.