Work

Deep learning analysis of capillary refill dynamics in ischemic colitis: differentiating reversible vs. gangrenous mucosa

Year: 2026

Type: article

Abstract: Ischemic colitis remains a diagnostic challenge, as endoscopic grading of mucosal ischemia is subjective and insensitive for transmural infarction. While the majority of non-gangrenous cases are resolved conservatively, gangrenous mucosa necessitates immediate resection. The current reliance on visual signals, such as color and bleeding, results in misclassification and variability. We propose a novel deep learning approach to quantify micro-capillary refill dynamics from colonoscopy video. The technology produces objective perfusion measures and real-time viability classification by examining frame-by-frame color recovery following temporary mucosal blanching. This approach makes use of recent developments in AI-assisted colonoscopy, annotated datasets, and endoscopic hardware. By incorporating capillary refill analysis, operational decision-making might be improved, interobserver variability could be decreased, and unnecessary colectomy and delayed gangrene treatment could be avoided. Pilot studies are warranted to validate this concept and establish its role in guiding therapy for ischemic colitis.

Source: Frontiers in Gastroenterology

DOI: 10.3389/fgstr.2026.1782255

Authors: Zarqa Yasin, Hamza Sajid, Noor ul Ain Saleem, Ursula Abu Nahla

Institutions: Henry Ford Hospital, Allama Iqbal Medical College, FMH College of Medicine & Dentistry, Fatima Memorial Hospital, Hebron University

Language: English

Topic: Abdominal vascular conditions and treatments

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,353