Computer-aided prediction of polyp histology on white light colonoscopy using surface pattern analysis
submitted 23. November 2017
accepted after revision 13. August 2018
25. Oktober 2018 (eFirst)
Background This study aimed to evaluate a new computational histology prediction system based on colorectal polyp textural surface patterns using high definition white light images.
Methods Textural elements (textons) were characterized according to their contrast with respect to the surface, shape, and number of bifurcations, assuming that dysplastic polyps are associated with highly contrasted, large tubular patterns with some degree of bifurcation. Computer-aided diagnosis (CAD) was compared with pathological diagnosis and the diagnosis made by endoscopists using Kudo and Narrow-Band Imaging International Colorectal Endoscopic classifications.
Results Images of 225 polyps were evaluated (142 dysplastic and 83 nondysplastic). The CAD system correctly classified 205 polyps (91.1 %): 131/142 dysplastic (92.3 %) and 74/83 (89.2 %) nondysplastic. For the subgroup of 100 diminutive polyps (≤ 5 mm), CAD correctly classified 87 polyps (87.0 %): 43/50 (86.0 %) dysplastic and 44/50 (88.0 %) nondysplastic. There were no statistically significant differences in polyp histology prediction between the CAD system and endoscopist assessment.
Conclusion A computer vision system based on the characterization of the polyp surface in white light accurately predicted colorectal polyp histology.
- 1 Quintero E, Castells A, Bujanda L. et al. COLONPREV Study Investigators. Colonoscopy versus fecal immunochemical testing in colorectal-cancer screening. N Engl J Med 2012; 366: 697-706
- 2 Corley DA, Jensen CD, Marks AR. et al. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med 2014; 370: 1298-1306
- 3 Rees CJ, Rajasekhar PT, Wilson A. et al. Narrow band imaging optical diagnosis of small colorectal polyps in routine clinical practice: the Detect Inspect Characterise Resect and Discard 2 (DISCARD 2) study. Gut 2017; 66: 887-895
- 4 Ignjatovic A, East JE, Suzuki N. et al. Optical diagnosis of small colorectal polyps at routine colonoscopy (Detect InSpect ChAracterise Resect and Discard; DISCARD trial): a prospective cohort study. Lancet Oncol 2009; 10: 1171-1178
- 5 Kudo S, Tamura S, Nakajima T. et al. Diagnosis of colorectal tumorous lesions by magnifying endoscopy. Gastrointest Endosc 1996; 44: 8-14
- 6 Hayashi N, Tanaka S, Hewett DG. et al. Endoscopic prediction of deep submucosal invasive carcinoma: validation of the narrow-band imaging international colorectal endoscopic (NICE) classification. Gastrointest Endosc 2013; 78: 625-632
- 7 Mori Y, Kudo S, Berzin TM. et al. Computer-aided diagnosis for colonoscopy. Endoscopy 2017; 49: 813-819
- 8 Chen P-J, Lin M-C, Lai M-J. et al. Accurate classification of diminutive colorectal polyps using computer-aided analysis. Gastroenterology 2018; 154: 568-575
- 9 East JE, Vieth M, Rex DK. Serrated lesions in colorectal cancer screening: detection, resection, pathology and surveillance. Gut 2015; 64: 991-1000
- 10 Sánchez FJ, Bernal J, Sánchez-Montes C. et al. Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos. Mach Vis Appl 2017; 28: 917-936
- 11 Cortes C, Vapnik V. Support-vector networks. Mach Learn 1995; 20: 273-297
- 12 Rogart JN, Jain D, Siddiqui UD. et al. Narrow-band imaging without high magnification to differentiate polyps during real-time colonoscopy: improvement with experience. Gastrointest Endosc 2008; 68: 1136-1145
- 13 Takemura Y, Yoshida S, Tanaka S. et al. Computer-aided system for predicting the histology of colorectal tumors by using narrow-band imaging magnifying colonoscopy (with video). Gastrointest Endosc 2012; 75: 179-185
- 14 Cohen J, Bosworth BP, Chak A. et al. Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) on the use of endoscopy simulators for training and assessing skill. Gastrointest Endosc 2012; 76: 471-475
- 15 Carballal S, Rodríguez-Alcalde D, Moreira L. et al. Colorectal cancer risk factors in patients with serrated polyposis syndrome: a large multicenter study. Gut 2016; 65: 1829-1837