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Classification of nuclear morphology in endocytoscopy of colorectal neoplasms.

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BACKGROUND AND AIMS We investigated endocytoscopy (EC) findings that were considered risk factors for colorectal neoplasms and determined whether they could be used as new indices to identify carcinomas with… Click to show full abstract

BACKGROUND AND AIMS We investigated endocytoscopy (EC) findings that were considered risk factors for colorectal neoplasms and determined whether they could be used as new indices to identify carcinomas with massive submucosal invasion (SM-m) or worse outcomes. METHODS We performed a multivariate analysis of 8 factors on EC images to determine whether they were associated with SM-m or worse. Based on the results, we divided the EC3a category of the EC classification into low grade or high grade and investigated the diagnostic accuracy of this subclassification. In addition, we compared the diagnostic ability of EC for SM-m with that of other modalities (narrow-band imaging and pit pattern). RESULTS The multivariate analysis indicated that unclear glandular lumens (ULs), high degree of nuclear enlargement (HNE), and multilayered nuclei (MNs) were the most useful factors for the diagnosis of SM-m or worse. The odds ratios for these factors were 12.47, 12.29, and 10.48, respectively (P < .001). The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and positive likelihood ratio for the diagnostic accuracy of the EC3a subclassification were 88.9%, 91.3%, 75.0%, 96.6%, 90.8%, and 10.2, respectively (P < .001). The sensitivity, negative predictive value, and accuracy of EC were significantly higher than those of narrow-band imaging and pit pattern. CONCLUSIONS From the EC findings, the presence of ULs, HNE, and MNs are important risk factors for SM-m or worse outcomes. Furthermore, the EC3a subclassification taking these findings into consideration could be effective for the diagnosis of SM-m or worse. (Clinical trial registration number: UMIN 000014906.).

Keywords: classification; accuracy; classification nuclear; predictive value; nuclear morphology; colorectal neoplasms

Journal Title: Gastrointestinal endoscopy
Year Published: 2017

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