Computer-aided system for predicting the histology of colorectal tumors by using narrow-band imaging magnifying colonoscopy (with video)

Gastrointest Endosc. 2012 Jan;75(1):179-85. doi: 10.1016/j.gie.2011.08.051.


Background: Narrow-band imaging (NBI) classification of colorectal lesions is clinically useful in determining treatment options for colorectal tumors. There is a learning curve, however. Accurate NBI-based diagnosis requires training and experience. In addition, objective diagnosis is necessary. Thus, we developed a computerized system to automatically classify NBI magnifying colonoscopic images.

Objective: To evaluate the utility and limitations of our automated NBI classification system.

Design: Retrospective study.

Setting: Department of endoscopy, university hospital.

Main outcome measurements: Performance of our computer-based system for classification of NBI magnifying colonoscopy images in comparison to classification by two experienced endoscopists and to histologic findings.

Results: For the 371 colorectal lesions depicted on validation images, the computer-aided classification system yielded a detection accuracy of 97.8% (363/371); sensitivity and specificity of types B-C3 lesions for a diagnosis of neoplastic lesion were 97.8% (317/324) and 97.9% (46/47), respectively. Diagnostic concordance between the computer-aided classification system and the two experienced endoscopists was 98.7% (366/371), with no significant difference between methods.

Limitations: Retrospective, single-center in this initial report.

Conclusion: Our new computer-aided system is reliable for predicting the histology of colorectal tumors by using NBI magnifying colonoscopy.

Publication types

  • Video-Audio Media

MeSH terms

  • Adenoma / classification
  • Adenoma / pathology*
  • Carcinoma / classification
  • Carcinoma / pathology*
  • Colonoscopy / methods*
  • Colorectal Neoplasms / classification
  • Colorectal Neoplasms / pathology*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted*
  • Inflammation / pathology
  • Intestinal Mucosa / pathology
  • Neoplasm Invasiveness
  • Predictive Value of Tests
  • Retrospective Studies