Key result
A computer-aided diagnosis system using endoscopic optical coherence tomography achieved an accuracy of 84% for classifying non-dysplastic versus dysplastic tissue in Barrett's esophagus.
Why the study?
Does a computer-aided diagnosis system using endoscopic optical coherence tomography accurately classify dysplasia in Barrett's esophagus?
Observational (n=96)
No
Does a computer-aided diagnosis system using endoscopic optical coherence tomography accurately classify dysplasia in Barrett's esophagus?
Effect estimate: 84% accuracy
A computer-aided diagnosis system using endoscopic optical coherence tomography achieved 84% accuracy in differentiating non-dysplastic from dysplastic Barrett's esophagus tissue.
May support CAD-OCT for Barrett's dysplasia detection; hypothesis-generating and requires prospective validation before practice change.
Barrett's esophagus (BE) and associated adenocarcinoma have emerged as a major health care problem. Endoscopic optical coherence tomography is a microscopic sub-surface imaging technology that has been shown to differentiate tissue layers of the gastrointestinal wall and identify dysplasia in the mucosa, and is proposed as a surveillance tool to aid in management of BE. In this work a computer-aided diagnosis (CAD) system has been demonstrated for classification of dysplasia in Barrett's esophagus using EOCT. The system is composed of four modules: region of interest segmentation, dysplasia-related image feature extraction, feature selection, and site classification and validation. Multiple feature extraction and classification methods were evaluated and the process of developing the CAD system is described in detail. Use of multiple EOCT images to classify a single site was also investigated. A total of 96 EOCT image-biopsy pairs (63 non-dysplastic, 26 low-grade and 7 high-grade dysplastic biopsy sites) from a previously described clinical study were analyzed using the CAD system, yielding an accuracy of 84% for classification of non-dysplastic vs. dysplastic BE tissue. The results motivate continued development of CAD to potentially enable EOCT surveillance of large surface areas of Barrett's mucosa to identify dysplasia.
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Qi et al. (2010) conducted an observational in Barrett's esophagus (n=96). Computer-aided diagnosis (CAD) system using EOCT vs. Histopathological diagnosis was evaluated on Accuracy for classification of non-dysplastic vs. dysplastic BE tissue (84% accuracy). A computer-aided diagnosis system using endoscopic optical coherence tomography achieved an accuracy of 84% for classifying non-dysplastic versus dysplastic tissue in Barrett's esophagus.
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