The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Amit Rastogi - One of the best experts on this subject based on the ideXlab platform.
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didactic training vs computer based self learning in the prediction of diminutive Colon Polyp histology by trainees a randomized controlled study
Endoscopy, 2017Co-Authors: Taimur Khan, Neil Gupta, Ajay Bansal, Sachin Wani, Birtukan Cinnor, Lindsay Hosford, Mojtaba Olyaee, Amit RastogiAbstract:Background and study aim Experts can accurately predict diminutive Polyp histology, but the ideal method to train nonexperts is not known. The aim of the study was to compare accuracy in diminutive Polyp histology characterization using narrow-band imaging (NBI) between participants undergoing classroom didactic training vs. computer-based self-learning. Participants and methods Trainees at two institutions were randomized to classroom didactic training or computer-based self-learning. In didactic training, experienced endoscopists reviewed a presentation on NBI patterns for adenomatous and hyperplastic Polyps and 40 NBI videos, along with interactive discussion. The self-learning group reviewed the same presentation of 40 teaching videos independently, without interactive discussion. A total of 40 testing videos of diminutive Polyps under NBI were then evaluated by both groups. Performance characteristics were calculated by comparing predicted and actual histology. Fisher’s exact test was used and P Results A total of 17 trainees participated (8 didactic training and 9 self-learning). A larger proportion of Polyps were diagnosed with high confidence in the classroom group (66.5 % vs. 50.8 %; P Conclusion The self-learning group showed results on a par with or, for high-confidence predictions, even slightly superior to classroom didactic training for predicting diminutive Polyp histology. This approach can help in widespread training and clinical implementation of real-time Polyp histology characterization.
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community gastroenterologists can learn diminutive Colon Polyp histology characterization with narrow band imaging by a computer based teaching module
Digestive Endoscopy, 2015Co-Authors: Preetika Sinh, Neil Gupta, Ajay Bansal, Prateek Sharma, Sachin Wani, John I Allen, Scott R Ketover, Amit RastogiAbstract:Background and Aim The aim of the present study was to evaluate the impact of a computer-based teaching module on the performance of community gastroenterologists for characterization of diminutive Polyps (≤5 mm) using narrow band imaging video clips. Methods Eighty videos were distributed in pre- and post-test DVD along with a 20-min audiovisual teaching presentation detailing endoscopic features differentiating adenomas from hyperplastic Polyps using narrow band imaging. Each participant first reviewed pretest video clips and entered their responses for Polyp histology and their confidence in diagnosis: high: ≥90% or low: <90%. Following this, they reviewed the teaching module and assessed the post-test videos. Performance characteristics were calculated for pre- and post-test videos by comparing predicted histology with actual histology. Fisher's exact test was used for analysis and the kappa statistic was calculated for interobserver agreement. Results Fifteen gastroenterologists in community practice completed the study. Sensitivity, specificity, accuracy and negative predictive value in characterization of Polyp histology improved significantly post-test compared to pretest. In post-test, accuracy was 92% for high-confidence diagnoses and the proportion of these increased with training from 46% (pretest) to 64% (post-test); P < 0.001. Interobserver agreement for diagnosis improved from fair (kappa = 0.23) in pretest to moderate (kappa = 0.56) in post-test. Conclusions A teaching module using video clips can be used to teach community gastroenterologists Polyp histology characterization by narrow band imaging. Whether this translates into real-time high accuracy in Polyp detection needs to be further evaluated.
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tu1739 in vivo optical diagnosis of Colon Polyp histology using high definition white light endoscopy hd wle can the asge preservation of innovative endoscopic innovation pivi targets be met
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:ERCPs, 15.9% compared to 10.4% (p 0.09; OR 1.54; 95% CI 0.93, 2.54). Procedure duration was similar between groups, 38.5 minutes compared to 38.4 minutes (p 0.97) for morning and afternoon procedures, respectively. In multivariate analysis, the OR for AEs in the afternoon was 1.69 (95% CI (0.93, 3.04)), and the OR procedural success in the afternoon was 0.36 (CI (0.13, 0.91)). Additional data are presented in Table 1. Conclusions: Afternoon ERCPs appear to have a lower procedural success rate, even after adjusting for potential confounders. Afternoon ERCPs also showed a trend toward higher AE rate. Further research is needed to determine the impact of time of day on outcomes of ERCP.
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accuracy of in vivo optical diagnosis of Colon Polyp histology by narrow band imaging in predicting Colonoscopy surveillance intervals
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:Background The American Society for Gastrointestinal Endoscopy (ASGE) recently developed thresholds for the performance characteristics of technologies for real-time assessment of histology of diminutive (≤5 mm) Colon Polyps. Narrow-band imaging (NBI) has been shown to predict Polyp histology with moderate to high accuracy in several studies. Objective To determine whether in vivo optical diagnosis of Polyp histology by using NBI can reach the 2 benchmarks set forth by the ASGE. Design Retrospective analysis of data from 3 prospective clinical trials. Setting Two tertiary referral centers. Patients Subjects undergoing screening or surveillance Colonoscopy. Interventions In vivo optical diagnosis of Polyp histology by using NBI. Main Outcome Measurement Accuracy in predicting Colonoscopy surveillance intervals, negative predictive value (NPV) for diagnosing adenomatous histology in the rectosigmoid. Results A total of 410 patients met the inclusion/exclusion criteria and had at least 1 Polyp seen and resected during Colonoscopy. Using in vivo optical diagnosis instead of histopathology for all diminutive Polyps predicted the correct Colonoscopy surveillance interval in 86% to 94% patients. When optical diagnosis was limited to diminutive Polyps in the rectosigmoid only, the NPV for diagnosing adenomatous histology with NBI was 95%. Limitations Retrospective analysis from tertiary referral centers. Conclusions The threshold NPV for diagnosing adenomatous histology in diminutive rectosigmoid Polyps recently set forth by the ASGE can be achieved by using NBI. The threshold accuracy rate for predicting surveillance interval recommendations can be reached by using NBI, but only if patients with 1 to 2 small adenomas without advanced features have a repeat Colonoscopy in 10 years.
Neil Gupta - One of the best experts on this subject based on the ideXlab platform.
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Validation of Probe-based Confocal Laser Endomicroscopy (pCLE) Criteria for Diagnosing Colon Polyp Histology
Journal of Clinical Gastroenterology, 2017Co-Authors: Sreekar Vennelaganti, Prashanth Vennalaganti, Sharad C. Mathur, Satish K. Singh, M. Mazen Jamal, Vijay Kanakadandi, Matt Hall, Neil Gupta, Venkat NutalapatiAbstract:Validated probe-based confocal endomicroscopy (pCLE) criteria for distinguishing hyperplastic Polyps (HPs) and tubular adenomas (TA) have not yet been developed. To develop pCLE criteria for distinguishing HP from TA and evaluate its performance characteristics among experts. pCLE criteria for Colon Polyp histology were developed and tested in 2 phases prospectively. Phase I: 8 preliminary criteria were developed and tested internally. Criteria achieving an accuracy of >75% (epithelial surface: regular vs. irregular; goblet cells: increased vs. decreased; gland axis: horizontal vs. vertical; gland shape: slit/stellate vs. villiform; image scale: gray vs. dark) were evaluated in Phase II of study wherein external assessors evaluated these criteria in a separate set of pCLE videos. Accuracy and interobserver agreement (95% confidence intervals) were determined for Colon histology prediction. Phase I (criteria development/internal testing): 8 criteria were assessed by 4 pCLE experts using 28 videos (14 HP/14 TA). Five of 8 pCLE criteria met selection for phase II (accuracy >75%). Phase II (external validation): 36 pCLE Colon Polyp videos (HP 16/TA 20) were evaluated by 8 external assessors. Overall accuracy in diagnosis of Colon Polyp histology was 84.9% (95% confidence interval, 81.7-87.7). Of predictions made with high confidence (75%), histology was predicted with an accuracy of 91%, sensitivity 83%, specificity 100%, negative predictive value 87% and positive predictive value 98%. Interobserver agreement was substantial (κ=0.73). We demonstrate the development and validation of pCLE criteria for prediction of Colon Polyp histology. Using these criteria, overall accuracy in differentiating TA from HP was high with substantial interobserver agreement.
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didactic training vs computer based self learning in the prediction of diminutive Colon Polyp histology by trainees a randomized controlled study
Endoscopy, 2017Co-Authors: Taimur Khan, Neil Gupta, Ajay Bansal, Sachin Wani, Birtukan Cinnor, Lindsay Hosford, Mojtaba Olyaee, Amit RastogiAbstract:Background and study aim Experts can accurately predict diminutive Polyp histology, but the ideal method to train nonexperts is not known. The aim of the study was to compare accuracy in diminutive Polyp histology characterization using narrow-band imaging (NBI) between participants undergoing classroom didactic training vs. computer-based self-learning. Participants and methods Trainees at two institutions were randomized to classroom didactic training or computer-based self-learning. In didactic training, experienced endoscopists reviewed a presentation on NBI patterns for adenomatous and hyperplastic Polyps and 40 NBI videos, along with interactive discussion. The self-learning group reviewed the same presentation of 40 teaching videos independently, without interactive discussion. A total of 40 testing videos of diminutive Polyps under NBI were then evaluated by both groups. Performance characteristics were calculated by comparing predicted and actual histology. Fisher’s exact test was used and P Results A total of 17 trainees participated (8 didactic training and 9 self-learning). A larger proportion of Polyps were diagnosed with high confidence in the classroom group (66.5 % vs. 50.8 %; P Conclusion The self-learning group showed results on a par with or, for high-confidence predictions, even slightly superior to classroom didactic training for predicting diminutive Polyp histology. This approach can help in widespread training and clinical implementation of real-time Polyp histology characterization.
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community gastroenterologists can learn diminutive Colon Polyp histology characterization with narrow band imaging by a computer based teaching module
Digestive Endoscopy, 2015Co-Authors: Preetika Sinh, Neil Gupta, Ajay Bansal, Prateek Sharma, Sachin Wani, John I Allen, Scott R Ketover, Amit RastogiAbstract:Background and Aim The aim of the present study was to evaluate the impact of a computer-based teaching module on the performance of community gastroenterologists for characterization of diminutive Polyps (≤5 mm) using narrow band imaging video clips. Methods Eighty videos were distributed in pre- and post-test DVD along with a 20-min audiovisual teaching presentation detailing endoscopic features differentiating adenomas from hyperplastic Polyps using narrow band imaging. Each participant first reviewed pretest video clips and entered their responses for Polyp histology and their confidence in diagnosis: high: ≥90% or low: <90%. Following this, they reviewed the teaching module and assessed the post-test videos. Performance characteristics were calculated for pre- and post-test videos by comparing predicted histology with actual histology. Fisher's exact test was used for analysis and the kappa statistic was calculated for interobserver agreement. Results Fifteen gastroenterologists in community practice completed the study. Sensitivity, specificity, accuracy and negative predictive value in characterization of Polyp histology improved significantly post-test compared to pretest. In post-test, accuracy was 92% for high-confidence diagnoses and the proportion of these increased with training from 46% (pretest) to 64% (post-test); P < 0.001. Interobserver agreement for diagnosis improved from fair (kappa = 0.23) in pretest to moderate (kappa = 0.56) in post-test. Conclusions A teaching module using video clips can be used to teach community gastroenterologists Polyp histology characterization by narrow band imaging. Whether this translates into real-time high accuracy in Polyp detection needs to be further evaluated.
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tu1739 in vivo optical diagnosis of Colon Polyp histology using high definition white light endoscopy hd wle can the asge preservation of innovative endoscopic innovation pivi targets be met
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:ERCPs, 15.9% compared to 10.4% (p 0.09; OR 1.54; 95% CI 0.93, 2.54). Procedure duration was similar between groups, 38.5 minutes compared to 38.4 minutes (p 0.97) for morning and afternoon procedures, respectively. In multivariate analysis, the OR for AEs in the afternoon was 1.69 (95% CI (0.93, 3.04)), and the OR procedural success in the afternoon was 0.36 (CI (0.13, 0.91)). Additional data are presented in Table 1. Conclusions: Afternoon ERCPs appear to have a lower procedural success rate, even after adjusting for potential confounders. Afternoon ERCPs also showed a trend toward higher AE rate. Further research is needed to determine the impact of time of day on outcomes of ERCP.
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accuracy of in vivo optical diagnosis of Colon Polyp histology by narrow band imaging in predicting Colonoscopy surveillance intervals
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:Background The American Society for Gastrointestinal Endoscopy (ASGE) recently developed thresholds for the performance characteristics of technologies for real-time assessment of histology of diminutive (≤5 mm) Colon Polyps. Narrow-band imaging (NBI) has been shown to predict Polyp histology with moderate to high accuracy in several studies. Objective To determine whether in vivo optical diagnosis of Polyp histology by using NBI can reach the 2 benchmarks set forth by the ASGE. Design Retrospective analysis of data from 3 prospective clinical trials. Setting Two tertiary referral centers. Patients Subjects undergoing screening or surveillance Colonoscopy. Interventions In vivo optical diagnosis of Polyp histology by using NBI. Main Outcome Measurement Accuracy in predicting Colonoscopy surveillance intervals, negative predictive value (NPV) for diagnosing adenomatous histology in the rectosigmoid. Results A total of 410 patients met the inclusion/exclusion criteria and had at least 1 Polyp seen and resected during Colonoscopy. Using in vivo optical diagnosis instead of histopathology for all diminutive Polyps predicted the correct Colonoscopy surveillance interval in 86% to 94% patients. When optical diagnosis was limited to diminutive Polyps in the rectosigmoid only, the NPV for diagnosing adenomatous histology with NBI was 95%. Limitations Retrospective analysis from tertiary referral centers. Conclusions The threshold NPV for diagnosing adenomatous histology in diminutive rectosigmoid Polyps recently set forth by the ASGE can be achieved by using NBI. The threshold accuracy rate for predicting surveillance interval recommendations can be reached by using NBI, but only if patients with 1 to 2 small adenomas without advanced features have a repeat Colonoscopy in 10 years.
Ajay Bansal - One of the best experts on this subject based on the ideXlab platform.
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didactic training vs computer based self learning in the prediction of diminutive Colon Polyp histology by trainees a randomized controlled study
Endoscopy, 2017Co-Authors: Taimur Khan, Neil Gupta, Ajay Bansal, Sachin Wani, Birtukan Cinnor, Lindsay Hosford, Mojtaba Olyaee, Amit RastogiAbstract:Background and study aim Experts can accurately predict diminutive Polyp histology, but the ideal method to train nonexperts is not known. The aim of the study was to compare accuracy in diminutive Polyp histology characterization using narrow-band imaging (NBI) between participants undergoing classroom didactic training vs. computer-based self-learning. Participants and methods Trainees at two institutions were randomized to classroom didactic training or computer-based self-learning. In didactic training, experienced endoscopists reviewed a presentation on NBI patterns for adenomatous and hyperplastic Polyps and 40 NBI videos, along with interactive discussion. The self-learning group reviewed the same presentation of 40 teaching videos independently, without interactive discussion. A total of 40 testing videos of diminutive Polyps under NBI were then evaluated by both groups. Performance characteristics were calculated by comparing predicted and actual histology. Fisher’s exact test was used and P Results A total of 17 trainees participated (8 didactic training and 9 self-learning). A larger proportion of Polyps were diagnosed with high confidence in the classroom group (66.5 % vs. 50.8 %; P Conclusion The self-learning group showed results on a par with or, for high-confidence predictions, even slightly superior to classroom didactic training for predicting diminutive Polyp histology. This approach can help in widespread training and clinical implementation of real-time Polyp histology characterization.
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community gastroenterologists can learn diminutive Colon Polyp histology characterization with narrow band imaging by a computer based teaching module
Digestive Endoscopy, 2015Co-Authors: Preetika Sinh, Neil Gupta, Ajay Bansal, Prateek Sharma, Sachin Wani, John I Allen, Scott R Ketover, Amit RastogiAbstract:Background and Aim The aim of the present study was to evaluate the impact of a computer-based teaching module on the performance of community gastroenterologists for characterization of diminutive Polyps (≤5 mm) using narrow band imaging video clips. Methods Eighty videos were distributed in pre- and post-test DVD along with a 20-min audiovisual teaching presentation detailing endoscopic features differentiating adenomas from hyperplastic Polyps using narrow band imaging. Each participant first reviewed pretest video clips and entered their responses for Polyp histology and their confidence in diagnosis: high: ≥90% or low: <90%. Following this, they reviewed the teaching module and assessed the post-test videos. Performance characteristics were calculated for pre- and post-test videos by comparing predicted histology with actual histology. Fisher's exact test was used for analysis and the kappa statistic was calculated for interobserver agreement. Results Fifteen gastroenterologists in community practice completed the study. Sensitivity, specificity, accuracy and negative predictive value in characterization of Polyp histology improved significantly post-test compared to pretest. In post-test, accuracy was 92% for high-confidence diagnoses and the proportion of these increased with training from 46% (pretest) to 64% (post-test); P < 0.001. Interobserver agreement for diagnosis improved from fair (kappa = 0.23) in pretest to moderate (kappa = 0.56) in post-test. Conclusions A teaching module using video clips can be used to teach community gastroenterologists Polyp histology characterization by narrow band imaging. Whether this translates into real-time high accuracy in Polyp detection needs to be further evaluated.
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tu1739 in vivo optical diagnosis of Colon Polyp histology using high definition white light endoscopy hd wle can the asge preservation of innovative endoscopic innovation pivi targets be met
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:ERCPs, 15.9% compared to 10.4% (p 0.09; OR 1.54; 95% CI 0.93, 2.54). Procedure duration was similar between groups, 38.5 minutes compared to 38.4 minutes (p 0.97) for morning and afternoon procedures, respectively. In multivariate analysis, the OR for AEs in the afternoon was 1.69 (95% CI (0.93, 3.04)), and the OR procedural success in the afternoon was 0.36 (CI (0.13, 0.91)). Additional data are presented in Table 1. Conclusions: Afternoon ERCPs appear to have a lower procedural success rate, even after adjusting for potential confounders. Afternoon ERCPs also showed a trend toward higher AE rate. Further research is needed to determine the impact of time of day on outcomes of ERCP.
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accuracy of in vivo optical diagnosis of Colon Polyp histology by narrow band imaging in predicting Colonoscopy surveillance intervals
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:Background The American Society for Gastrointestinal Endoscopy (ASGE) recently developed thresholds for the performance characteristics of technologies for real-time assessment of histology of diminutive (≤5 mm) Colon Polyps. Narrow-band imaging (NBI) has been shown to predict Polyp histology with moderate to high accuracy in several studies. Objective To determine whether in vivo optical diagnosis of Polyp histology by using NBI can reach the 2 benchmarks set forth by the ASGE. Design Retrospective analysis of data from 3 prospective clinical trials. Setting Two tertiary referral centers. Patients Subjects undergoing screening or surveillance Colonoscopy. Interventions In vivo optical diagnosis of Polyp histology by using NBI. Main Outcome Measurement Accuracy in predicting Colonoscopy surveillance intervals, negative predictive value (NPV) for diagnosing adenomatous histology in the rectosigmoid. Results A total of 410 patients met the inclusion/exclusion criteria and had at least 1 Polyp seen and resected during Colonoscopy. Using in vivo optical diagnosis instead of histopathology for all diminutive Polyps predicted the correct Colonoscopy surveillance interval in 86% to 94% patients. When optical diagnosis was limited to diminutive Polyps in the rectosigmoid only, the NPV for diagnosing adenomatous histology with NBI was 95%. Limitations Retrospective analysis from tertiary referral centers. Conclusions The threshold NPV for diagnosing adenomatous histology in diminutive rectosigmoid Polyps recently set forth by the ASGE can be achieved by using NBI. The threshold accuracy rate for predicting surveillance interval recommendations can be reached by using NBI, but only if patients with 1 to 2 small adenomas without advanced features have a repeat Colonoscopy in 10 years.
Ilangko Balasingham - One of the best experts on this subject based on the ideXlab platform.
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A Framework With a Fully Convolutional Neural Network for Semi-Automatic Colon Polyp Annotation
IEEE Access, 2019Co-Authors: Hemin Ali Qadir, Lars Aabakken, Jacob Bergsland, Johannes Solhusvik, Ilangko BalasinghamAbstract:Deep learning has delivered promising results for automatic Polyp detection and segmentation. However, deep learning is known for being data-hungry, and its performance is correlated with the amount of available training data. The lack of large labeled Polyp training images is one of the major obstacles in performance improvement of automatic Polyp detection and segmentation. Labeling is typically performed by an endoscopist, who performs pixel-level annotation of Polyps. Manual Polyp labeling of a video sequence is difficult and time-consuming. We propose a semi-automatic annotation framework powered by a convolutional neural network (CNN) to speed up Polyp annotation in video-based datasets. Our CNN network requires only ground-truth (manually annotated masks) of a few frames in a video for training and annotating the rest of the frames in a semi-supervised manner. To generate masks similar to the ground-truth masks, we use some pre and post-processing steps such as different data augmentation strategies, morphological operations, Fourier descriptors, and a second stage fine-tuning. We use Fourier coefficients of the ground-truth masks to select similar generated output masks. The results show that it is possible to 1) produce ~ 96% of Dice similarity score between the Polyp masks provided by clinicians and the masks generated by our framework, and 2) save clinicians time as they need to manually annotate only a few frames instead of annotating the entire video, frame-by-frame.
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Abnormal Colon Polyp Image Synthesis Using Conditional Adversarial Networks for Improved Detection Performance
IEEE Access, 2018Co-Authors: Younghak Shin, Hemin Ali Qadir, Ilangko BalasinghamAbstract:One of the major obstacles in automatic Polyp detection during Colonoscopy is the lack of labeled Polyp training images. In this paper, we propose a framework of conditional adversarial networks to increase the number of training samples by generating synthetic Polyp images. Using a normal binary form of Polyp mask which represents only the Polyp position as an input conditioned image, realistic Polyp image generation is a difficult task in a generative adversarial networks approach. We propose an edge filtering-based combined input conditioned image to train our proposed networks. This enables realistic Polyp image generations while maintaining the original structures of the Colonoscopy image frames. More importantly, our proposed framework generates synthetic Polyp images from normal Colonoscopy images which have the advantage of being relatively easy to obtain. The network architecture is based on the use of multiple dilated convolutions in each encoding part of our generator network to consider large receptive fields and avoid much contractions of a feature map size. An image resizing with convolution for upsampling in the decoding layers is considered to prevent artifacts on generated images. We show that the generated Polyp images are not only qualitatively realistic, but also help to improve Polyp detection performance.
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Automatic Colon Polyp Detection Using Region Based Deep CNN and Post Learning Approaches
IEEE Access, 2018Co-Authors: Younghak Shin, Hemin Ali Qadir, Lars Aabakken, Jacob Bergsland, Ilangko BalasinghamAbstract:Automatic image detection of Colonic Polyps is still an unsolved problem due to the large variation of Polyps in terms of shape, texture, size, and color, and the existence of various Polyp-like mimics during Colonoscopy. In this paper, we apply a recent region-based convolutional neural network (CNN) approach for the automatic detection of Polyps in the images and videos obtained from Colonoscopy examinations. We use a deep-CNN model (Inception Resnet) as a transfer learning scheme in the detection system. To overcome the Polyp detection obstacles and the small number of Polyp images, we examine image augmentation strategies for training deep networks. We further propose two efficient post-learning methods, such as automatic false positive learning and offline learning, both of which can be incorporated with the region-based detection system for reliable Polyp detection. Using the large size of Colonoscopy databases, experimental results demonstrate that the suggested detection systems show better performance than other systems in the literature. Furthermore, we show improved detection performance using the proposed post-learning schemes for Colonoscopy videos.
Prateek Sharma - One of the best experts on this subject based on the ideXlab platform.
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community gastroenterologists can learn diminutive Colon Polyp histology characterization with narrow band imaging by a computer based teaching module
Digestive Endoscopy, 2015Co-Authors: Preetika Sinh, Neil Gupta, Ajay Bansal, Prateek Sharma, Sachin Wani, John I Allen, Scott R Ketover, Amit RastogiAbstract:Background and Aim The aim of the present study was to evaluate the impact of a computer-based teaching module on the performance of community gastroenterologists for characterization of diminutive Polyps (≤5 mm) using narrow band imaging video clips. Methods Eighty videos were distributed in pre- and post-test DVD along with a 20-min audiovisual teaching presentation detailing endoscopic features differentiating adenomas from hyperplastic Polyps using narrow band imaging. Each participant first reviewed pretest video clips and entered their responses for Polyp histology and their confidence in diagnosis: high: ≥90% or low: <90%. Following this, they reviewed the teaching module and assessed the post-test videos. Performance characteristics were calculated for pre- and post-test videos by comparing predicted histology with actual histology. Fisher's exact test was used for analysis and the kappa statistic was calculated for interobserver agreement. Results Fifteen gastroenterologists in community practice completed the study. Sensitivity, specificity, accuracy and negative predictive value in characterization of Polyp histology improved significantly post-test compared to pretest. In post-test, accuracy was 92% for high-confidence diagnoses and the proportion of these increased with training from 46% (pretest) to 64% (post-test); P < 0.001. Interobserver agreement for diagnosis improved from fair (kappa = 0.23) in pretest to moderate (kappa = 0.56) in post-test. Conclusions A teaching module using video clips can be used to teach community gastroenterologists Polyp histology characterization by narrow band imaging. Whether this translates into real-time high accuracy in Polyp detection needs to be further evaluated.
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tu1739 in vivo optical diagnosis of Colon Polyp histology using high definition white light endoscopy hd wle can the asge preservation of innovative endoscopic innovation pivi targets be met
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:ERCPs, 15.9% compared to 10.4% (p 0.09; OR 1.54; 95% CI 0.93, 2.54). Procedure duration was similar between groups, 38.5 minutes compared to 38.4 minutes (p 0.97) for morning and afternoon procedures, respectively. In multivariate analysis, the OR for AEs in the afternoon was 1.69 (95% CI (0.93, 3.04)), and the OR procedural success in the afternoon was 0.36 (CI (0.13, 0.91)). Additional data are presented in Table 1. Conclusions: Afternoon ERCPs appear to have a lower procedural success rate, even after adjusting for potential confounders. Afternoon ERCPs also showed a trend toward higher AE rate. Further research is needed to determine the impact of time of day on outcomes of ERCP.
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accuracy of in vivo optical diagnosis of Colon Polyp histology by narrow band imaging in predicting Colonoscopy surveillance intervals
Gastrointestinal Endoscopy, 2012Co-Authors: Neil Gupta, Sreenivasa S Jonnalagadda, Ajay Bansal, Dayna S Early, Steven A Edmundowicz, Prateek Sharma, Amit RastogiAbstract:Background The American Society for Gastrointestinal Endoscopy (ASGE) recently developed thresholds for the performance characteristics of technologies for real-time assessment of histology of diminutive (≤5 mm) Colon Polyps. Narrow-band imaging (NBI) has been shown to predict Polyp histology with moderate to high accuracy in several studies. Objective To determine whether in vivo optical diagnosis of Polyp histology by using NBI can reach the 2 benchmarks set forth by the ASGE. Design Retrospective analysis of data from 3 prospective clinical trials. Setting Two tertiary referral centers. Patients Subjects undergoing screening or surveillance Colonoscopy. Interventions In vivo optical diagnosis of Polyp histology by using NBI. Main Outcome Measurement Accuracy in predicting Colonoscopy surveillance intervals, negative predictive value (NPV) for diagnosing adenomatous histology in the rectosigmoid. Results A total of 410 patients met the inclusion/exclusion criteria and had at least 1 Polyp seen and resected during Colonoscopy. Using in vivo optical diagnosis instead of histopathology for all diminutive Polyps predicted the correct Colonoscopy surveillance interval in 86% to 94% patients. When optical diagnosis was limited to diminutive Polyps in the rectosigmoid only, the NPV for diagnosing adenomatous histology with NBI was 95%. Limitations Retrospective analysis from tertiary referral centers. Conclusions The threshold NPV for diagnosing adenomatous histology in diminutive rectosigmoid Polyps recently set forth by the ASGE can be achieved by using NBI. The threshold accuracy rate for predicting surveillance interval recommendations can be reached by using NBI, but only if patients with 1 to 2 small adenomas without advanced features have a repeat Colonoscopy in 10 years.