Computer-aided prediction of polyp histology on white light colonoscopy using surface pattern analysis

Cristina Sánchez-Montes; Francisco Javier Sánchez; Jorge Bernal; Henry Córdova; María López-Cerón; Miriam Cuatrecasas; Cristina Rodríguez de Miguel; Ana García-Rodríguez; Rodrigo Garcés-Durán; María Pellisé; Josep Llach; Glòria Fernández-Esparrach

doi:10.1055/a-0732-5250

Endoscopy, Table of Contents

Endoscopy 2019; 51(03): 261-265
DOI: 10.1055/a-0732-5250

Innovations and brief communications

Computer-aided prediction of polyp histology on white light colonoscopy using surface pattern analysis

Cristina Sánchez-Montes

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

Francisco Javier Sánchez

²Computer Science Department, Universitat Autònoma de Barcelona and Computer Vision Center, Barcelona, Spain

,

Jorge Bernal

²Computer Science Department, Universitat Autònoma de Barcelona and Computer Vision Center, Barcelona, Spain

,

Henry Córdova

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

María López-Cerón

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

Miriam Cuatrecasas

³Pathology Department, Centre de Diagnòstic Biomèdic, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

⁴Banc de Tumors-Biobanc Clínic, IDIBAPS-XBTC, Barcelona, Spain

,

Cristina Rodríguez de Miguel

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

Ana García-Rodríguez

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

Rodrigo Garcés-Durán

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

María Pellisé

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

Josep Llach

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

,

Glòria Fernández-Esparrach

¹Endoscopy Unit, Gastroenterology Department, Hospital Clínic, IDIBAPS, CIBEREHD, University of Barcelona, Barcelona, Spain

› Author Affiliations

Abstract

Background This study aimed to evaluate a new computational histology prediction system based on colorectal polyp textural surface patterns using high definition white light images.

Methods Textural elements (textons) were characterized according to their contrast with respect to the surface, shape, and number of bifurcations, assuming that dysplastic polyps are associated with highly contrasted, large tubular patterns with some degree of bifurcation. Computer-aided diagnosis (CAD) was compared with pathological diagnosis and the diagnosis made by endoscopists using Kudo and Narrow-Band Imaging International Colorectal Endoscopic classifications.

Results Images of 225 polyps were evaluated (142 dysplastic and 83 nondysplastic). The CAD system correctly classified 205 polyps (91.1 %): 131/142 dysplastic (92.3 %) and 74/83 (89.2 %) nondysplastic. For the subgroup of 100 diminutive polyps (≤ 5 mm), CAD correctly classified 87 polyps (87.0 %): 43/50 (86.0 %) dysplastic and 44/50 (88.0 %) nondysplastic. There were no statistically significant differences in polyp histology prediction between the CAD system and endoscopist assessment.

Conclusion A computer vision system based on the characterization of the polyp surface in white light accurately predicted colorectal polyp histology.

Full Text

References

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