Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video) - 21/01/19
Abstract |
Background and Aims |
In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbation and dysplasia. However, identification of persistent histologic inflammation is extremely difficult using conventional endoscopy. Furthermore, the reproducibility of endoscopic disease activity is poor. We developed and evaluated a computer-aided diagnosis (CAD) system to predict persistent histologic inflammation using endocytoscopy (EC; 520-fold ultra-magnifying endoscope).
Methods |
We evaluated the accuracy of the CAD system using test image sets. First, we retrospectively reviewed the data of 187 patients with UC from whom biopsy samples were obtained after endocytoscopic observation. EC images and biopsy samples of each patient were collected from 6 colorectal segments: cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. All EC images were tagged with reference to the biopsy sample’s histologic activity. For validation samples, 525 validation sets of 525 independent segments were collected from 100 patients, and 12,900 EC images from the remaining 87 patients were used for machine learning to construct CAD. The primary outcome measure was the diagnostic ability of CAD to predict persistent histologic inflammation. Its reproducibility for all test images was also assessed.
Results |
CAD provided diagnostic sensitivity, specificity, and accuracy as follows: 74% (95% confidence interval, 65%-81%), 97% (95% confidence interval, 95%-99%), and 91% (95% confidence interval, 83%-95%), respectively. Its reproducibility was perfect (κ = 1).
Conclusions |
Our CAD system potentially allows fully automated identification of persistent histologic inflammation associated with UC.
Le texte complet de cet article est disponible en PDF.Graphical abstract |
Abbreviations : CAD, EC, MES, NBI, NPV, PPV, UC, WLE
Plan
| DISCLOSURE: The following authors disclosed financial relationships relevant to this publication: S. Kudo, Y. Mori, M. Misawa: Speaker for Olympus; patent-holders and premium recipients for “Image-processing instrument and 47 method” (No. 6059271 in Japan). K. Mori: Research support recipient from Cybernet Corp. All other authors disclosed no financial relationships relevant to this publication. Research support for this study was provided by JSPS KAKENHI (grant no. JP17K15973). |
Vol 89 - N° 2
P. 408-415 - février 2019 Retour au numéro
Article précédent
- EUS-guided antegrade intervention for benign biliary diseases in patients with surgically altered anatomy (with videos)
- Shuntaro Mukai, Takao Itoi, Atsushi Sofuni, Takayoshi Tsuchiya, Reina Tanaka, Ryosuke Tonozuka, Mitsuyoshi Honjo, Mitsuru Fujita, Kenjiro Yamamoto, Yuichi Nagakawa
- Novel computer-assisted diagnosis system for endoscopic disease activity in patients with ulcerative colitis
- Tsuyoshi Ozawa, Soichiro Ishihara, Mitsuhiro Fujishiro, Hiroaki Saito, Youichi Kumagai, Satoki Shichijo, Kazuharu Aoyama, Tomohiro Tada
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