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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

European Radiology

Early Access. Jan. 2025.
Top Journal

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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