Clinical Endoscopy

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Response to Artificial intelligence-based colorectal polyp histology prediction using narrow-band image-magnifying colonoscopy: a stepping stone for clinical practice: Istvan Racz, Andras Horvath, Zoltán Horvath; Clin Endosc 2022;55(5):701-702. Published online September 27, 2022; DOI: https://doi.org/10.5946/ce.2022.123.1

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Original Article

Artificial Intelligence-Based Colorectal Polyp Histology Prediction by Using Narrow-Band Image-Magnifying Colonoscopy: Istvan Racz, Andras Horvath, Noemi Kranitz, Gyongyi Kiss, Henriett Regoczi, Zoltan Horvath; Clin Endosc 2022;55(1):113-121. Published online September 23, 2021; DOI: https://doi.org/10.5946/ce.2021.149

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Background
/Aims: We have been developing artificial intelligence based polyp histology prediction (AIPHP) method to classify Narrow Band Imaging (NBI) magnifying colonoscopy images to predict the hyperplastic or neoplastic histology of polyps. Our aim was to analyze the accuracy of AIPHP and narrow-band imaging international colorectal endoscopic (NICE) classification based histology predictions and also to compare the results of the two methods.
Methods
We studied 373 colorectal polyp samples taken by polypectomy from 279 patients. The documented NBI still images were analyzed by the AIPHP method and by the NICE classification parallel. The AIPHP software was created by machine learning method. The software measures five geometrical and color features on the endoscopic image.
Results
The accuracy of AIPHP was 86.6% (323/373) in total of polyps. We compared the AIPHP accuracy results for diminutive and non-diminutive polyps (82.1% vs. 92.2%; p=0.0032). The accuracy of the hyperplastic histology prediction was significantly better by NICE compared to AIPHP method both in the diminutive polyps (n=207) (95.2% vs. 82.1%) (p<0.001) and also in all evaluated polyps (n=373) (97.1% vs. 86.6%) (p<0.001)
Conclusions
Our artificial intelligence based polyp histology prediction software could predict histology with high accuracy only in the large size polyp subgroup.

Citations

Citations to this article as recorded by

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Response to Artificial intelligence-based colorectal polyp histology prediction using narrow-band image-magnifying colonoscopy: a stepping stone for clinical practice
Istvan Racz, Andras Horvath, Zoltán Horvath
Clinical Endoscopy.2022; 55(5): 701. CrossRef

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