Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis
Background and study aims With the advent of deep neural networks (DNN) learning, the field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials (RCT) have investigated the influence of integrating AI in colonoscopy and its impact on adenoma detection rates (ADRs)...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Georg Thieme Verlag KG
2021-03-01
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| Series: | Endoscopy International Open |
| Online Access: | http://www.thieme-connect.de/DOI/DOI?10.1055/a-1341-0457 |
| _version_ | 1819163386077773824 |
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| author | Munish Ashat Jagpal Singh Klair Dhruv Singh Arvind Rangarajan Murali Rajesh Krishnamoorthi |
| author_facet | Munish Ashat Jagpal Singh Klair Dhruv Singh Arvind Rangarajan Murali Rajesh Krishnamoorthi |
| author_sort | Munish Ashat |
| collection | DOAJ |
| description | Background and study aims With the advent of deep neural networks (DNN) learning, the field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials (RCT) have investigated the influence of integrating AI in colonoscopy and its impact on adenoma detection rates (ADRs) and polyp detection rates (PDRs). We performed a systematic review and meta-analysis to reliably assess if the impact is statistically significant enough to warrant the adoption of AI -assisted colonoscopy (AIAC) in clinical practice.
Methods We conducted a comprehensive search of multiple electronic databases and conference proceedings to identify RCTs that compared outcomes between AIAC and conventional colonoscopy (CC). The primary outcome was ADR. The secondary outcomes were PDR and total withdrawal time (WT).
Results Six RCTs (comparing AIAC vs CC) with 5058 individuals undergoing average-risk screening colonoscopy were included in the meta-analysis. ADR was significantly higher with AIAC compared to CC (33.7 % versus 22.9 %; odds ratio (OR) 1.76, 95 % confidence interval (CI) 1.55–2.00; I2 = 28 %). Similarly, PDR was significantly higher with AIAC (45.6 % versus 30.6 %; OR 1.90, 95 %CI, 1.68–2.15, I2 = 0 %). The overall WT was higher for AIAC compared to CC (mean difference [MD] 0.46 (0.00–0.92) minutes, I2 = 94 %).
Conclusions There is an increase in adenoma and polyp detection with the utilization of AIAC. |
| first_indexed | 2024-12-22T17:43:18Z |
| format | Article |
| id | doaj.art-37b242d64b3942648d60f3fdde511ba7 |
| institution | Directory Open Access Journal |
| issn | 2364-3722 2196-9736 |
| language | English |
| last_indexed | 2024-12-22T17:43:18Z |
| publishDate | 2021-03-01 |
| publisher | Georg Thieme Verlag KG |
| record_format | Article |
| series | Endoscopy International Open |
| spelling | doaj.art-37b242d64b3942648d60f3fdde511ba72022-12-21T18:18:21ZengGeorg Thieme Verlag KGEndoscopy International Open2364-37222196-97362021-03-010904E513E52110.1055/a-1341-0457Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysisMunish Ashat0Jagpal Singh Klair1Dhruv Singh2Arvind Rangarajan Murali3Rajesh Krishnamoorthi4Department of Gastroenterology and Hepatology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, United StatesDigestive Disease Institute, Virginia Mason Medical Center, Seattle, Washington, United StatesDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, New York, United StatesDepartment of Gastroenterology and Hepatology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, United StatesDigestive Disease Institute, Virginia Mason Medical Center, Seattle, Washington, United StatesBackground and study aims With the advent of deep neural networks (DNN) learning, the field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials (RCT) have investigated the influence of integrating AI in colonoscopy and its impact on adenoma detection rates (ADRs) and polyp detection rates (PDRs). We performed a systematic review and meta-analysis to reliably assess if the impact is statistically significant enough to warrant the adoption of AI -assisted colonoscopy (AIAC) in clinical practice. Methods We conducted a comprehensive search of multiple electronic databases and conference proceedings to identify RCTs that compared outcomes between AIAC and conventional colonoscopy (CC). The primary outcome was ADR. The secondary outcomes were PDR and total withdrawal time (WT). Results Six RCTs (comparing AIAC vs CC) with 5058 individuals undergoing average-risk screening colonoscopy were included in the meta-analysis. ADR was significantly higher with AIAC compared to CC (33.7 % versus 22.9 %; odds ratio (OR) 1.76, 95 % confidence interval (CI) 1.55–2.00; I2 = 28 %). Similarly, PDR was significantly higher with AIAC (45.6 % versus 30.6 %; OR 1.90, 95 %CI, 1.68–2.15, I2 = 0 %). The overall WT was higher for AIAC compared to CC (mean difference [MD] 0.46 (0.00–0.92) minutes, I2 = 94 %). Conclusions There is an increase in adenoma and polyp detection with the utilization of AIAC.http://www.thieme-connect.de/DOI/DOI?10.1055/a-1341-0457 |
| spellingShingle | Munish Ashat Jagpal Singh Klair Dhruv Singh Arvind Rangarajan Murali Rajesh Krishnamoorthi Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis Endoscopy International Open |
| title | Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis |
| title_full | Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis |
| title_fullStr | Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis |
| title_full_unstemmed | Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis |
| title_short | Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis |
| title_sort | impact of real time use of artificial intelligence in improving adenoma detection during colonoscopy a systematic review and meta analysis |
| url | http://www.thieme-connect.de/DOI/DOI?10.1055/a-1341-0457 |
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