Dataset Information

Accuracy of i-Scan for Optical Diagnosis of Colonic Polyps: A Meta-Analysis.

ABSTRACT:

Background

i-Scan is a novel virtual chromoendoscopy system designed to enhance surface and vascular patterns to improve optical diagnostic performance. Numerous prospective studies have been done to evaluate the accuracy of i-Scan in differentiating colonic neoplasms from non-neoplasms. i-Scan could be an effective endoscopic technique for optical diagnosis of colonic polyps.

Objective

Our aim of this study was to perform a meta-analysis of published data to establish the diagnostic accuracy of i-Scan for optical diagnosis of colonic polyps.

Methods

We searched PubMed, Medline, Elsevier ScienceDirect and Cochrane Library databases. We used a bivariate meta-analysis following a random effects model to summarize the data and plotted hierarchical summary receiver-operating characteristic (HSROC) curves. The area under the HSROC curve (AUC) serves as an indicator of the diagnostic accuracy.

Results

The meta-analysis included a total of 925 patients and 2312 polyps. For the overall studies, the area under the HSROC curve was 0.96. The summary sensitivity was 90.4% (95%CI 85%-94.1%) and specificity was 90.9% (95%CI 84.3%-94.9%). In 11 studies predicting polyps histology in real-time, the summary sensitivity and specificity was 91.5% (95%CI 85.7%-95.1%) and 92.1% (95%CI 84.5%-96.1%), respectively, with the AUC of 0.97. For three different diagnostic criteria (Kudo, NICE, others), the sensitivity was 86.3%, 93.0%, 85.0%, respectively and specificity was 84.8%, 94.4%, 91.8%, respectively.

Conclusions

Endoscopic diagnosis with i-Scan has accurate optical diagnostic performance to differentiate neoplastic from non-neoplastic polyps with an area under the HSROC curve exceeding 0.90. Both the sensitivity and specificity for diagnosing colonic polyps are over 90%.

SUBMITTER: Guo CG

PROVIDER: S-EPMC4433272 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Accuracy of i-Scan for Optical Diagnosis of Colonic Polyps: A Meta-Analysis.

Guo Chuan-Guo CG Ji Rui R Li Yan-Qing YQ

PloS one 20150515 5

<h4>Background</h4>i-Scan is a novel virtual chromoendoscopy system designed to enhance surface and vascular patterns to improve optical diagnostic performance. Numerous prospective studies have been done to evaluate the accuracy of i-Scan in differentiating colonic neoplasms from non-neoplasms. i-Scan could be an effective endoscopic technique for optical diagnosis of colonic polyps.<h4>Objective</h4>Our aim of this study was to perform a meta-analysis of published data to establish the diagnos ...[more]

PMID: 25978459

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Project description:Adenomas and hyperplastic polyps are polypoid lesion and may occur at any location in the colon. At the present moment, all polyps should be resected endoscopically, although only adenomas, but not hyperplastic polyps have the potential to develop colorectal cancer. This approach enables the conduction of microscopic investigations of the lesions. By today, only the pathological diagnosis can distinguish exactly between adenomas and hyperplastic polyps. Some studies have investigated the value of the socalled optical biopsy method. Optical biopsy means the visual assessment of the polyp and the determination of a diagnosis solely on behalf of optical criteria. This method is conducted in real time during colonoscopy. If it can be shown, that endoscopist using optical biopsy are able to predict histopathological diagnoses of colonic polyps sufficiently this would possibly lead to simplification of diagnostic procedures. For instance, it would be conceivable to resect hyperplastic polyps and small adenomas and discard them without further assessment by a pathologist. Gastroenterological societies demand for a 90 percent accordance between diagnoses set by endoscopists and pathologists as a prerequisite for the implementation of the optical biopsy method. In this study we want to proof that the use of a new narrow-band imaging (NBI) tool (Exera III, Olmpus) is capable to rise accuracy of optically ascertained diagnoses of colonic polyps. NBI is a light filter tool which can be activated by pressing a button at the endoscope. NBI function leads to an endoscopic picture which appears blue and enables endoscopists to better assess surface structures and vascular patterns. In a prospective randomised multicenter setting we plan to conduct colonoscopy in 380 patients. Half of the patients will be examined without use of NBI (control arm). In these cases colonoscopists will assess optical diagnosis of polyps without turning on the NBI tool. If polyps are detected in patients belonging to the intervention arm NBI will be used and optical diagnosis will be determined using the NICE (NBI International Colorectal Endoscopic) classification. All polyps will be resected and send to pathology for further microscopic assessment. After completing the trial we aim to compare accuracy of the optical diagnosis in both groups. Our hypothesis is, that by using the new NBI tool accuracy (accordance between optical and histopathological diagnosis) can be increased from 78% to 90%.

Project description:Background and study aims Correct optical diagnosis of colorectal polyps is crucial to implement a resect and discard strategy. Training methods have been proposed to reach recommended optical diagnosis thresholds. The aim of our study was to present a systematic review and meta-analysis on optical diagnosis training. Methods PubMed/Medline and Cochrane databases were searched between 1980 and October 2019 for studies reporting outcomes on optical diagnosis training of colorectal polyps. The primary outcome was optical diagnosis accuracy compared to histological analysis pre-training and post-training intervention. Subgroup analyses of experienced/trainee endoscopists, training methods, and small/diminutive polyps were included. Results Overall, 16 studies met inclusion criteria, analyzing the impact of training on 179 endoscopists. Pre-training accuracy was 70.3 % (6416/9131 correct diagnoses) whereas post-training accuracy was 81.6 % (7416/9213 correct diagnoses) (risk ratio [RR] 1.17; 95 % confidence interval [CI]: 1.09-1.24, P < 0.001). In experienced endoscopists, accuracy improved from 69.8 % (3771/5403 correct diagnoses) to 82.4 % (4521/5485 correct diagnoses) (RR 1.20; 95 % CI: 1.11-1.29, P < 0.001). Among trainees, accuracy improved from 69.6 % (2645/3803 correct diagnoses) to 78.8 % (2995/3803 correct diagnoses) (RR 1.14; 95 % CI 1.06-1.24, P < 0.001). In the small/diminutive polyp subgroup, accuracy improved from 68.1 % (3549/5214 correct diagnoses) to 77.1 % (4022/5214 correct diagnoses) in (RR 1.16 95 % CI 1.08-1.24 P < 0.001). On meta-regression analysis, the improvement in accuracy did not differ between computerized vs. didactic training approaches for experienced ( P = 0.792) and trainee endoscopists ( P = 0.312). Conclusions Optical diagnosis training is effective in improving accuracy of histology prediction in colorectal polyps. Didactic and computer-based training show comparable effectiveness in improving diagnostic accuracy.

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Project description:Importance:The recent advances in the field of machine learning have raised expectations that computer-aided diagnosis will become the standard for the diagnosis of melanoma. Objective:To critically review the current literature and compare the diagnostic accuracy of computer-aided diagnosis with that of human experts. Data Sources:The MEDLINE, arXiv, and PubMed Central databases were searched to identify eligible studies published between January 1, 2002, and December 31, 2018. Study Selection:Studies that reported on the accuracy of automated systems for melanoma were selected. Search terms included melanoma, diagnosis, detection, computer aided, and artificial intelligence. Data Extraction and Synthesis:Evaluation of the risk of bias was performed using the QUADAS-2 tool, and quality assessment was based on predefined criteria. Data were analyzed from February 1 to March 10, 2019. Main Outcomes and Measures:Summary estimates of sensitivity and specificity and summary receiver operating characteristic curves were the primary outcomes. Results:The literature search yielded 1694 potentially eligible studies, of which 132 were included and 70 offered sufficient information for a quantitative analysis. Most studies came from the field of computer science. Prospective clinical studies were rare. Combining the results for automated systems gave a melanoma sensitivity of 0.74 (95% CI, 0.66-0.80) and a specificity of 0.84 (95% CI, 0.79-0.88). Sensitivity was lower in studies that used independent test sets than in those that did not (0.51; 95% CI, 0.34-0.69 vs 0.82; 95% CI, 0.77-0.86; P?<?.001); however, the specificity was similar (0.83; 95% CI, 0.71-0.91 vs 0.85; 95% CI, 0.80-0.88; P?=?.67). In comparison with dermatologists' diagnosis, computer-aided diagnosis showed similar sensitivities and a 10 percentage points lower specificity, but the difference was not statistically significant. Studies were heterogeneous and substantial risk of bias was found in all but 4 of the 70 studies included in the quantitative analysis. Conclusions and Relevance:Although the accuracy of computer-aided diagnosis for melanoma detection is comparable to that of experts, the real-world applicability of these systems is unknown and potentially limited owing to overfitting and the risk of bias of the studies at hand.

Dataset Information

Accuracy of i-Scan for Optical Diagnosis of Colonic Polyps: A Meta-Analysis.

Background

Objective

Methods

Results

Conclusions

Publications

Accuracy of i-Scan for Optical Diagnosis of Colonic Polyps: A Meta-Analysis.

Similar Datasets

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