A Prospective Cohort Study for Machine Learning-Based Prediction of Anal Fistula Formation After Perianal Abscess Drainage Based on Drainage Setting, Provider Experience, and MRI Interpretation (PRISM)

Perianal abscess drainage is a common surgical procedure. However, subsequent fistula formation remains a significant complication. This study aims to determine whether the procedure setting (operating room, emergency department, or outpatient clinic) and the experience level of the performing clinician affect fistula development rates.

Furthermore, the study evaluates the use of AI-assisted analysis of selected MR images to identify early signs of fistula formation. Selected image slices will be labeled based on radiological reports, and a machine learning model will be trained to predict fistula risk. The study will also compare AI-generated interpretations with expert radiologist assessments to validate performance.

The ultimate goal is to create a risk stratification tool to support clinical decision-making in surgical management of perianal abscesses.