Computed Tomography Image Analysis in Abdominal Wall Reconstruction: A Systematic Review.

Area of Science:

• Radiology
• Surgical Outcomes
• Medical Imaging Analysis

Background:

• Ventral hernias pose a significant healthcare burden.
• Routine preoperative imaging is common but its quantitative data is underutilized.
• Anatomic features from imaging are seldomly integrated into patient selection and surgical planning.

Purpose of the Study:

• To examine the application of computed tomography (CT) features in predicting surgical outcomes for ventral hernias.
• To assess the current state of CT feature quantification in preoperative risk stratification and planning.

Main Methods:

• A systematic review adhering to PRISMA guidelines was performed.
• Databases searched included PubMed, MEDLINE, and Embase (2000-2020).
• Search terms combined "computed tomography imaging" and "abdominal hernia".

Main Results:

• Twelve studies met inclusion criteria from 1922 initial records.
• Frequently quantified CT features included hernia volume, subcutaneous fat volume, and defect size.
• The hernia neck ratio > 2.5 demonstrated the highest predictive value (AUC 0.903).

Conclusions:

• CT feature selection enables quantification of morphologic tissue features for preoperative decision-making in hernia surgery.
• This approach aids in identifying high-risk patients and optimizing surgical planning.
• Future integration of 3D volumetric analysis and AI models promises improved patient care.