Misdiagnosis of Idiopathic Mesenteric Phlebosclerosis: The Role of AI-Assisted Computed Tomography Pattern Recognition

Abstract

Idiopathic mesenteric phlebosclerosis (IMP) is a rare form of chronic ischemic colitis that is frequently misdiagnosed due to its nonspecific clinical presentation and overlap with more common gastrointestinal conditions such as inflammatory bowel disease and ischemic colitis. Despite the presence of characteristic computed tomography (CT) findings, including serpiginous mesenteric venous calcifications and colonic wall thickening, delayed or incorrect diagnosis remains common, particularly in non-endemic regions and low-volume centers. This commentary builds upon a recently published case report to highlight the limitations of conventional diagnostic pathways and the downstream consequences of misdiagnosis, including inappropriate immunosuppressive therapy and delayed definitive management. We propose that artificial intelligence–assisted CT pattern recognition may serve as a valuable adjunct in the early identification of IMP by enhancing detection of subtle, disease-specific imaging patterns that may be overlooked during routine interpretation. Integration of AI-based decision support tools into radiologic workflows has the potential to improve diagnostic accuracy, reduce unnecessary interventions, and support preventive strategies by enabling earlier disease recognition. Further multicenter studies are warranted to evaluate the clinical utility and generalizability of AI-assisted imaging approaches in rare vascular gastrointestinal diseases.