BACKGROUND: Endocytoscopy enables in vivo observation of nuclei at 450× magnification during GI endoscopy, thus allowing precise prediction of lesion pathology. However, because it requires training and experience, it may be beneficial only when performed by expert endoscopists. OBJECTIVE: To develop and evaluate a novel computer-aided diagnosis system for endocytoscopic imaging (EC-CAD) of colorectal lesions. DESIGN: Pilot study. SETTING: University hospital. PATIENTS: One hundred fifty-two patients with small colorectal polyps (≤10 mm) who had undergone endocytoscopy. INTERVENTION: Test sets of white-light endoscopic images and endocytoscopic images from 176 small colorectal polyps (137 neoplastic and 39 non-neoplastic polyps) were assessed by EC-CAD, 2 expert endoscopists, and 2 trainee endoscopists. MAIN OUTCOME MEASUREMENT: Sensitivity, specificity, and accuracy in predicting neoplastic change by EC-CAD comparing expert and trainee endoscopists. RESULTS: EC-CAD had a sensitivity of 92.0% and an accuracy of 89.2%; these were comparable to those achieved by expert endoscopists (92.7% and 92.3%; P = .868 and .256, respectively) and significantly higher than those achieved by trainee endoscopists (81.8% and 80.4%; P < .001 and .002, respectively). EC-CAD achieved a specificity of 79.5%; this did not differ significantly from that achieved by the experts and trainees. EC-CAD also enabled instant diagnosis, taking only 0.3 seconds for each lesion with perfect reproducibility. LIMITATIONS: No sample size calculation. CONCLUSIONS: EC-CAD provides fully automated instant classification of colorectal polyps with excellent sensitivity, accuracy, and objectivity. Thus, it can be a powerful tool for facilitating decision making during routine colonoscopy.
BACKGROUND: Endocytoscopy enables in vivo observation of nuclei at 450× magnification during GI endoscopy, thus allowing precise prediction of lesion pathology. However, because it requires training and experience, it may be beneficial only when performed by expert endoscopists. OBJECTIVE: To develop and evaluate a novel computer-aided diagnosis system for endocytoscopic imaging (EC-CAD) of colorectal lesions. DESIGN: Pilot study. SETTING: University hospital. PATIENTS: One hundred fifty-two patients with small colorectal polyps (≤10 mm) who had undergone endocytoscopy. INTERVENTION: Test sets of white-light endoscopic images and endocytoscopic images from 176 small colorectal polyps (137 neoplastic and 39 non-neoplastic polyps) were assessed by EC-CAD, 2 expert endoscopists, and 2 trainee endoscopists. MAIN OUTCOME MEASUREMENT: Sensitivity, specificity, and accuracy in predicting neoplastic change by EC-CAD comparing expert and trainee endoscopists. RESULTS: EC-CAD had a sensitivity of 92.0% and an accuracy of 89.2%; these were comparable to those achieved by expert endoscopists (92.7% and 92.3%; P = .868 and .256, respectively) and significantly higher than those achieved by trainee endoscopists (81.8% and 80.4%; P < .001 and .002, respectively). EC-CAD achieved a specificity of 79.5%; this did not differ significantly from that achieved by the experts and trainees. EC-CAD also enabled instant diagnosis, taking only 0.3 seconds for each lesion with perfect reproducibility. LIMITATIONS: No sample size calculation. CONCLUSIONS: EC-CAD provides fully automated instant classification of colorectal polyps with excellent sensitivity, accuracy, and objectivity. Thus, it can be a powerful tool for facilitating decision making during routine colonoscopy.