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ArticleDigestive diseases and sciences2025

Prospective Comparison of Pathology and Computer-Aided Optical Diagnosis for Polyp Characterization Using Expert Consensus.

Felix Huang, Thea Iulia Dimbu, Douglas K Rex, Heiko Pohl, Cesare Hassan, Roupen Djinbachian, Victoire Michal, Dong Hyun Danny Kim, Bilal Amani, Nahlah Haddouch and 2 more

Abstract readComparative Study
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Article in Digestive diseases and sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Felix HuangFaculty of Medicine, University of Montreal, Montreal, QC, Canada.
Thea Iulia DimbuFaculty of Medicine, University of Montreal, Montreal, QC, Canada.
Douglas K RexDivision of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, IN, USA.
Heiko PohlDepartment of Veterans Affairs Medical Center, White River Junction, VT, USA.
Cesare HassanDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Roupen DjinbachianDivision of Gastroenterology, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada.
Victoire MichalUniversity of Montreal Hospital Research Center (CRCHUM), Montreal, QC, Canada.
Dong Hyun Danny KimDepartment of Internal Medicine, McGill University, Montreal, QC, Canada.
Bilal AmaniFaculty of Medicine, University of Montreal, Montreal, QC, Canada.
Nahlah HaddouchFaculty of Medicine, University of Montreal, Montreal, QC, Canada.
Sofie FournierFaculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada.
Daniel von RentelnDivision of Gastroenterology, University of Montreal Hospital Center (CHUM), Montreal, QC, Canada. danielrenteln@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHistopathology is the accepted gold standard for classifying colorectal polyps. However, the complex pathway from initial polyp detection and resection to final histological diagnosis involves multiple steps (retrieval, embedding, sectioning, interpretation), each potentially introducing diagnostic errors. We aimed to investigate the diagnostic accuracy of autonomous computer-aided optical polyp diagnosis (CADx) versus histopathology, using expert consensus as the reference standard.

methodsIn this prospective study, three internationally recognized expert endoscopists independently reviewed colonoscopy images and videos of diminutive (≤ 5 mm) polyps assessed by autonomous CADx. Unanimous, high-confidence expert agreement was defined as the reference standard ('ground truth'), assumed superior due to absence of resection or specimen-management related artifacts. The primary outcome was the proportion of specimens with potential incorrect histopathology diagnosis. Secondary outcomes included comparative accuracy, sensitivity, and specificity of autonomous CADx and histopathology against the expert-defined reference standard.

resultsAmong 510 patients, experts provided unanimous, high-confidence diagnoses for 226 diminutive (≤ 5 mm) colorectal polyps, serving as the reference standard. The proportion of potentially incorrect pathology diagnoses was 23% (95% CI: (17.8,29.2)). Autonomous CADx achieved a higher accuracy of 91.2% (95% CI: 86.5-94.4%), compared with pathology at 77.0% (95% CI: 70.8-82.2%; p < 0.001).

conclusionThese findings highlight that histopathological diagnosis after polyp resection is not infallible and can introduce diagnostic errors in a relevant proportion of cases. CADx diagnosis, obtained during the procedure and unaffected by specimen handling artifacts, may prevent some of these errors, suggesting it could offer superior accuracy for polyp characterization in certain cases.

Indexed as

Colonic PolypsColonoscopyDiagnosis, Computer-AssistedAdultAgedConsensus Statements as TopicFemaleHumansMaleMiddle AgedProspective StudiesSensitivity and SpecificityColonoscopyComputer-aided diagnostic systemHistopathology

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