Colonoscopy is often recommended after an episode of acute diverticulitis, particularly complicated diverticulitis, and when no colonoscopy was performed the previous year. Colonoscopy in prior diverticulitis can be difficult, as excellent bowel preparation may be harder to achieve with an angulated and narrowed sigmoid, and barotrauma risk is increased in diseased sigmoids.
Artificial intelligence (AI) programs are increasingly used to enhance radiographic diagnosis. This study evaluated whether an AI program could improve differentiation of acute diverticulitis from colon cancer.
Cases were acquired from a prospectively curated database. More than half were excluded for imperfect CT quality. Of the 585 included cases, 318 had cancer, 435 were used for training, 90 for validation, and 60 for testing.
For the test set, the AI system had cancer sensitivity of 83.3% and specificity of 86.6%. Board-certified radiologists had a sensitivity of 85.5%, which increased to 90.0% with AI.
Ziegelmayer S, Reischl S, Havrda H, et al. Development and validation of a deep learning algorithm to differentiate colon carcinoma from acute diverticulitis in computed tomography images. JAMA Netw Open
2023 Jan 27. (https://doi.org/10.1001/jamanetworkopen.2022.53370