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Effect of Artificial Intelligence-Aided Differentiation of Adenomatous and Non-Adenomatous Colorectal Polyps at CT Colonography on Radiologists’ Therapy Management

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Michael Ingrisch

Prof. Dr.

Principal Investigator

Clinical Data Science in Radiology

Abstract

Objectives: Adenomatous colorectal polyps require endoscopic resection, as opposed to non-adenomatous hyperplastic colorectal polyps. This study aims to evaluate the effect of artificial intelligence (AI)-assisted differentiation of adenomatous and non-adenomatous colorectal polyps at CT colonography on radiologists’ therapy management.<br>Materials and methods: Five board-certified radiologists evaluated CT colonography images with colorectal polyps of all sizes and morphologies retrospectively and decided whether the depicted polyps required endoscopic resection. After a primary unassisted reading based on current guidelines, a second reading with access to the classification of a radiomics-based random-forest AI-model labelling each polyp as 'non-adenomatous' or 'adenomatous' was performed. Performance was evaluated using polyp histopathology as the reference standard.<br>Results: 77 polyps in 59 patients comprising 118 polyp image series (47% supine position, 53% prone position) were evaluated unassisted and AI-assisted by five independent board-certified radiologists, resulting in a total of 1180 readings (subsequent polypectomy: yes or no). AI-assisted readings had higher accuracy (76% +/− 1% vs. 84% +/− 1%), sensitivity (78% +/− 6% vs. 85% +/− 1%), and specificity (73% +/− 8% vs. 82% +/− 2%) in selecting polyps eligible for polypectomy (p < 0.001). Inter-reader agreement was improved in the AI-assisted readings (Fleiss’ kappa 0.69 vs. 0.92).<br>Conclusion: AI-based characterisation of colorectal polyps at CT colonography as a second reader might enable a more precise selection of polyps eligible for subsequent endoscopic resection. However, further studies are needed to confirm this finding and histopathologic polyp evaluation is still mandatory.

article GFW+25

European Radiology

Early Access. Jan. 2025.
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Authors

S. Grosu • M. P. Fabritius • M. Winkelmann • D. Puhr-Westerheide • M. Ingenerf • S. Maurus • A. Graser • C. Schulz • T. Knösel • C. C. Cyran • J. Ricke • P. M. Kazmierczak • M. Ingrisch • P. Wesp

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DOI

Research Area

 C1 | Medicine

BibTeXKey: GFW+25

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