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Mo1527 A Computer-Based System for Quantitative Diagnosis of Early Gastric Cancer Under Blue LASER Imaging-Magnifying Endoscopy
Abstracts
found no significant difference between two groups. Nine studies have assessed the effect of MEI on ancillary maneuvers and found no significant difference between two groups. Conclusion: Cecal intubation rate was found to be higher in MEI group compared to standard colonoscopy group among both experienced and inexperienced endoscopists. MEI had no effect on abdominal pain scores, dose of sedation used or use of ancillary maneuvers.
Mo1527 A Computer-Based System for Quantitative Diagnosis of Early Gastric Cancer Under Blue LASER Imaging-Magnifying Endoscopy Shigeto Yoshida*1,4, Rie Miyaki2, Yoko Kominami2, Yoji Sanomura1, Taiji Matsuo1, Shiro Oka1, Shinji Tanaka1, Bisser Raytchev3, Toru Tamaki3, Kazufumi Kaneda3, Tsubasa Mishima4, Satoshi Shigemi4, Anh-Tuan Hoang4, Tetsushi Koide4, Kazuaki Chayama2 1 Department of Endoscopy, Hiroshima University, Hiroshima, Japan; 2 Department of Gastroenterology and Metabolism, Hiroshima University, Hiroshima, Japan; 3Department of Information Engineering, Hiroshima University, Hiroshima, Japan; 4Research Institute for Nanodevice and Bio Systems, Hiroshima University, Hiroshima, Japan Introduction: A blue laser imaging (BLI) system has been devised by Fujifilm Medical Co. Ltd. as an alternative to conventional xenon lamp illumination systems for imageenhanced endoscopy. The new narrow-band imaging system uses two laser light sources (410 nm and 450 nm) and a phosphor white light source. Magnifying endoscopy with BLI is clinically useful in diagnosing gastric cancer and determining treatment options. There is a learning curve, however. Accurate BLI-based diagnosis requires training and experience. Aims&Methods: We devised a computer-based analysis system to be used with the new endoscopy system and evaluated the utility of the system for quantitatively identifying gastric cancer on images obtained by magnifying endoscopy with BLI. The system incorporates bag-of- features representation of local features and support vector machine (SVM) classification. We first developed a custom software program that can represent features and classify regions according to corresponding features on training images. Dense scale-invariant feature transform (SIFT) descriptors were used for local features. An SVM with a linear kernel was used as the classifier. We then produced a set of images from 90 early gastric cancers (67 differentiated-type and 23 undifferentiated-type), 40 flat or slightly depressed, small, reddened lesions, and 90 surrounding tissues examined by BLI magnification at Hiroshima University Hospital. No biopsy specimen of a reddened lesion and surrounding tissues showed evidence of malignancy. The lesion was obtained by BLI in BLI-bright mode at five-sevenths maximum magnification (100 magnification). Thereafter, images were digitized (1280 1024 pixels) and stored. On each BLI-derived magnified image, a region of interest (ROI) was selected manually. All lesions were diagnosed histopathologically. Then we applied our custom software to identify gastric cancer, reddened lesions, and surrounding tissue quantitatively. We calculated the SVM output values for the tissue types on the images. Results: The average SVM output value was 0.840.23 for cancerous lesions, 0.380.35 for reddened lesions, and 0.230.29 for surrounding tissue, with the SVM output value for cancerous lesions being significantly greater than that for reddened lesions or surrounding tissue. The average SVM output value for differentiated-type cancer was 0.840.21 and for undifferentiated-type cancer was 0.850.27. Conclusion: Although further development is needed, we conclude that our computer-based analysis system used with BLI magnifying endoscopy images will accurately differentiate gastric lesions quantitatively, facilitating clinical diagnosis of gastric cancer as well as treatment decisions.
AB364 GASTROINTESTINAL ENDOSCOPY Volume 79, No. 5S : 2014
Mo1528 Volumetric LASER Endomicroscopy Signal Heterogeneity: New Criteria for Detection of Dyplasia in Barrett’s Esophagus Cadman L. Leggett*, Emmanuel C. Gorospe, Daniel Chan, Marlys Anderson, Lori S. Lutzke, Kenneth K. Wang Mayo Clinic, Rochester, Rochester, MN Background: Volumetric laser endomicroscopy (VLE) is a second generation optical coherence tomography device capable of generating cross-sectional images of the esophageal mucosa. The irregular architecture associated with dysplasia in Barrett’s esophagus (BE) is thought to enhance backscattering of light and produce a stronger and perhaps more heterogeneous VLE signal. The relationship between VLE signal heterogeneity and dysplasia has not been established. Aim: To determine the relationship between VLE signal heterogeneity and dysplasia in BE. Methods: Patients enrolled in a BE surveillance program at a large tertiary referral center who underwent endoscopic mucosal resection (EMR) were included in the study. EMR specimens were imaged using VLE immediately after resection and submitted for histological evaluation by two expert pathologists. EMRs were dichotomized into [1] non-dysplastic, if they contained low-grade dysplasia or no evidence of dysplasia and [2] dysplastic, if they contained high-grade dysplasia or intramucosal adenocarcinoma extending to the lateral margins. Three-dimensional rendering of VLE scans was performed and a transverse 2-D image plane was obtained at the level of the mucosa for each EMR. Histogram analysis was performed for each 2-D image to determine degree of signal heterogeneity measured in arbitrary units (au). Wilcoxon-signed rank test between dysplastic and nondysplastic groups was performed Results: A total of 32 EMR specimens were imaged using VLE (13 dysplastic and 12 non-dysplastic). Non-dysplastic EMRs had a statistically significant higher degree of signal intensity heterogeneity (median) at the level of the mucosa compared to dysplastic EMRs: 16.3 (12.4-18.7) versus 13.5 (11.6-16.6) au, pZ0.007 (Figure 1). VLE scans were reviewed to determine what accounted for the observed difference. A total of 10 (83%) non-dysplastic scans were noted to have partial effacement of layering traditionally associated with squamous epithelium while all (100%) dysplastic EMRs scans showed complete effacement. Conclusion: Non-dysplastic BE is associated with a higher degree of VLE signal heterogeneity at the level of the mucosa compared to dysplastic BE. We are the first to observe that this difference is due to partial effacement of layering in non-dysplastic BE. Prospective validation of this new criteria is needed to determine its diagnostic accuracy for dysplasia in BE.
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found no significant difference between two groups. Nine studies have assessed the effect of MEI on ancillary maneuvers and found no significant difference between two groups. Conclusion: Cecal intubation rate was found to be higher in MEI group compared to standard colonoscopy group among both experienced and inexperienced endoscopists. MEI had no effect on abdominal pain scores, dose of sedation used or use of ancillary maneuvers.
Mo1527 A Computer-Based System for Quantitative Diagnosis of Early Gastric Cancer Under Blue LASER Imaging-Magnifying Endoscopy Shigeto Yoshida*1,4, Rie Miyaki2, Yoko Kominami2, Yoji Sanomura1, Taiji Matsuo1, Shiro Oka1, Shinji Tanaka1, Bisser Raytchev3, Toru Tamaki3, Kazufumi Kaneda3, Tsubasa Mishima4, Satoshi Shigemi4, Anh-Tuan Hoang4, Tetsushi Koide4, Kazuaki Chayama2 1 Department of Endoscopy, Hiroshima University, Hiroshima, Japan; 2 Department of Gastroenterology and Metabolism, Hiroshima University, Hiroshima, Japan; 3Department of Information Engineering, Hiroshima University, Hiroshima, Japan; 4Research Institute for Nanodevice and Bio Systems, Hiroshima University, Hiroshima, Japan Introduction: A blue laser imaging (BLI) system has been devised by Fujifilm Medical Co. Ltd. as an alternative to conventional xenon lamp illumination systems for imageenhanced endoscopy. The new narrow-band imaging system uses two laser light sources (410 nm and 450 nm) and a phosphor white light source. Magnifying endoscopy with BLI is clinically useful in diagnosing gastric cancer and determining treatment options. There is a learning curve, however. Accurate BLI-based diagnosis requires training and experience. Aims&Methods: We devised a computer-based analysis system to be used with the new endoscopy system and evaluated the utility of the system for quantitatively identifying gastric cancer on images obtained by magnifying endoscopy with BLI. The system incorporates bag-of- features representation of local features and support vector machine (SVM) classification. We first developed a custom software program that can represent features and classify regions according to corresponding features on training images. Dense scale-invariant feature transform (SIFT) descriptors were used for local features. An SVM with a linear kernel was used as the classifier. We then produced a set of images from 90 early gastric cancers (67 differentiated-type and 23 undifferentiated-type), 40 flat or slightly depressed, small, reddened lesions, and 90 surrounding tissues examined by BLI magnification at Hiroshima University Hospital. No biopsy specimen of a reddened lesion and surrounding tissues showed evidence of malignancy. The lesion was obtained by BLI in BLI-bright mode at five-sevenths maximum magnification (100 magnification). Thereafter, images were digitized (1280 1024 pixels) and stored. On each BLI-derived magnified image, a region of interest (ROI) was selected manually. All lesions were diagnosed histopathologically. Then we applied our custom software to identify gastric cancer, reddened lesions, and surrounding tissue quantitatively. We calculated the SVM output values for the tissue types on the images. Results: The average SVM output value was 0.840.23 for cancerous lesions, 0.380.35 for reddened lesions, and 0.230.29 for surrounding tissue, with the SVM output value for cancerous lesions being significantly greater than that for reddened lesions or surrounding tissue. The average SVM output value for differentiated-type cancer was 0.840.21 and for undifferentiated-type cancer was 0.850.27. Conclusion: Although further development is needed, we conclude that our computer-based analysis system used with BLI magnifying endoscopy images will accurately differentiate gastric lesions quantitatively, facilitating clinical diagnosis of gastric cancer as well as treatment decisions.
AB364 GASTROINTESTINAL ENDOSCOPY Volume 79, No. 5S : 2014
Mo1528 Volumetric LASER Endomicroscopy Signal Heterogeneity: New Criteria for Detection of Dyplasia in Barrett’s Esophagus Cadman L. Leggett*, Emmanuel C. Gorospe, Daniel Chan, Marlys Anderson, Lori S. Lutzke, Kenneth K. Wang Mayo Clinic, Rochester, Rochester, MN Background: Volumetric laser endomicroscopy (VLE) is a second generation optical coherence tomography device capable of generating cross-sectional images of the esophageal mucosa. The irregular architecture associated with dysplasia in Barrett’s esophagus (BE) is thought to enhance backscattering of light and produce a stronger and perhaps more heterogeneous VLE signal. The relationship between VLE signal heterogeneity and dysplasia has not been established. Aim: To determine the relationship between VLE signal heterogeneity and dysplasia in BE. Methods: Patients enrolled in a BE surveillance program at a large tertiary referral center who underwent endoscopic mucosal resection (EMR) were included in the study. EMR specimens were imaged using VLE immediately after resection and submitted for histological evaluation by two expert pathologists. EMRs were dichotomized into [1] non-dysplastic, if they contained low-grade dysplasia or no evidence of dysplasia and [2] dysplastic, if they contained high-grade dysplasia or intramucosal adenocarcinoma extending to the lateral margins. Three-dimensional rendering of VLE scans was performed and a transverse 2-D image plane was obtained at the level of the mucosa for each EMR. Histogram analysis was performed for each 2-D image to determine degree of signal heterogeneity measured in arbitrary units (au). Wilcoxon-signed rank test between dysplastic and nondysplastic groups was performed Results: A total of 32 EMR specimens were imaged using VLE (13 dysplastic and 12 non-dysplastic). Non-dysplastic EMRs had a statistically significant higher degree of signal intensity heterogeneity (median) at the level of the mucosa compared to dysplastic EMRs: 16.3 (12.4-18.7) versus 13.5 (11.6-16.6) au, pZ0.007 (Figure 1). VLE scans were reviewed to determine what accounted for the observed difference. A total of 10 (83%) non-dysplastic scans were noted to have partial effacement of layering traditionally associated with squamous epithelium while all (100%) dysplastic EMRs scans showed complete effacement. Conclusion: Non-dysplastic BE is associated with a higher degree of VLE signal heterogeneity at the level of the mucosa compared to dysplastic BE. We are the first to observe that this difference is due to partial effacement of layering in non-dysplastic BE. Prospective validation of this new criteria is needed to determine its diagnostic accuracy for dysplasia in BE.
www.giejournal.org