Objective Assessment of the Utility of Chromoendoscopy with a Support Vector Machine

Ryo Ogawa,Yurika Koto,Yoshihiko Hamamoto,Isao Sakaida,Takeshi Okamoto,Madoka Unno,Atsushi Goto,Eizaburo Hideura,Ryo Kawasato,Jun Nishikawa,Yuko Yamaoka,Shinichi Hashimoto,Shunsuke Ito,Hiroyuki Ogihara

doi:10.1007/s12029-018-0083-6

Abstract

PurposeThe utility of chromoendoscopy for early gastric cancer (GC) was determined by machine learning using data of color differences.MethodsEighteen histopathologically confirmed early GC lesions were examined. We prepared images from white light endoscopy (WL), indigo carmine (Indigo), and acetic acid-indigo carmine chromoendoscopy (AIM). A border between cancerous and non-cancerous areas on endoscopic images was established from post-treatment pathological findings, and 2000 pixels with equivalent luminance values were randomly extracted from each image of cancerous and non-cancerous areas. Each pixel was represented as a three-dimensional vector with RGB values and defined as a sample. We evaluated the Mahalanobis distance using RGB values, indicative of color differences between cancerous and non-cancerous areas. We then conducted diagnosis test using a support vector machine (SVM) for each image. SVM was trained using the 100 training samples per class and determined which area each of 1900 test samples per class came from.ResultsThe means of the Mahalanobis distances for WL, Indigo, and AIM were 1.52, 1.32, and 2.53, respectively and there were no significant differences in the three modalities. Diagnosability per endoscopy technique was assessed using the F1 measure. The means of F1 measures for WL, Indigo, and AIM were 0.636, 0.618, and 0.687, respectively. AIM images were better than WL and Indigo images for the diagnosis of GC.ConclusionObjective assessment by SVM found AIM to be suitable for diagnosis of early GC based on color differences.

Highlights

The detectability of early gastric cancers has improved with the use of high-resolution video endoscopy and chromoendoscopy [1,2,3]
Images tend to be superior in color difference to white light endoscopy (WL) and indigo carmine (Indigo) images
When we compared each diagnosability by using support vector machine (SVM), the means of the F1 measures with WL, Indigo, and acid-indigo carmine chromoendoscopy (AIM) were 0.636, 0.618, and 0.687, respectively

Summary

Introduction

The detectability of early gastric cancers has improved with the use of high-resolution video endoscopy and chromoendoscopy [1,2,3]. Magnifying endoscopy combined with image-enhanced endoscopy such as narrow-band imaging has been reported to improve the qualitative diagnosability of gastric cancers [4,5,6]. Previous assessment of the diagnosability of early gastric cancer using endoscopy was based on the endoscopist’s subjective judgment and thereby included some problems in its objectivity [7, 8]. We used the three-dimensional vectors with RGB value, indicative of color differences between cancerous and non-cancerous areas. Objective assessment of the diagnosability per endoscopy technique was conducted by its discriminator generated following training of a support vector machine (SVM) [9].

Methods

Results

Conclusion