ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps
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In vivo real-time assessment of the histology of diminutive (≤5 mm) colorectal polyps detected at colonoscopy can be achieved by means of an "optical biopsy" by using currently available endoscopic technologies. This systematic review and meta-analysis was performed by the American Society for Gastrointestinal Endoscopy (ASGE) Technology Committee to specifically assess whether acceptable performance thresholds outlined by an ASGE Preservation and Incorporation of Valuable endoscopic Innovations (PIVI) document for clinical adoption of these technologies have been met. We conducted direct meta-analyses calculating the pooled negative predictive value (NPV) for narrow-band imaging (NBI), i-SCAN, and Fujinon Intelligent Color Enhancement (FICE)-assisted optical biopsy for predicting adenomatous polyp histology of small/diminutive colorectal polyps. We also calculated the pooled percentage agreement with histopathology when assigning postpolypectomy surveillance intervals based on combining real-time optical biopsy of colorectal polyps 5 mm or smaller with histopathologic assessment of polyps larger than 5 mm. Random-effects meta-analysis models were used. Statistical heterogeneity was evaluated by means of I(2) statistics. Our meta-analyses indicate that optical biopsy with NBI, exceeds the NPV threshold for adenomatous polyp histology, supporting a "diagnose-and-leave" strategy for diminutive predicted nonneoplastic polyps in the rectosigmoid colon. The pooled NPV of NBI for adenomatous polyp histology by using the random-effects model was 91% (95% confidence interval [CI], 88-94). This finding was associated with a high degree of heterogeneity (I(2) = 89%). Subgroup analysis indicated that the pooled NPV was greater than 90% for academic medical centers (91.8%; 95% CI, 89-94), for experts (93%; 95% CI, 91-96), and when the optical biopsy assessment was made with high confidence (93%; 95% CI, 90-96). Our meta-analyses also indicate that the agreement in assignment of postpolypectomy surveillance intervals based on optical biopsy with NBI of diminutive colorectal polyps is 90% or greater in academic settings (91%; 95% CI, 86-95), with experienced endoscopists (92%; 95% CI, 88-96) and when optical biopsy assessments are made with high confidence (91%; 95% CI, 88-95). Our systematic review and meta-analysis confirms that the thresholds established by the ASGE PIVI for real-time endoscopic assessment of the histology of diminutive polyps have been met, at least with NBI optical biopsy, with endoscopists who are expert in using this advanced imaging technology and when assessments are made with high confidence.
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Previous studies on CADx systems for colonoscopy focused on assessing the performances of AI against the accuracy of physicians or against criteria established by gastroenterology societies for implementing the technology in a clinical setting.
“Previous studies on cadx systems for colonoscopy focused on assessing the performances of ai against the accuracy of physicians19,20,27–30, or against the criteria established by gastroenterology societies for implementing the technology in a clinical setting31–34.”
From Experimental evidence of effective human–AI collaboration in medical decision-making (2022) · cites this paper as [31]
The Discussion states that ASGE PIVI established performance thresholds for adopting real-time optical assessment of diminutive colorectal polyps, and this review assesses imaging technologies against those thresholds. It does not establish that previous AI-based CADx studies evaluated their performance against those criteria; the technologies analyzed here are endoscopic imaging methods such as NBI, i-SCAN, and FICE. (LLM, conf=0.86)
Experimental — accuracy not yet measuredComputer-aided diagnosis (CADx) systems based on artificial intelligence (AI) can help endoscopists in the optical diagnosis of colorectal polyps by predicting the histopathology.
“Computer-aided diagnosis (CADx) systems based on artificial intelligence (AI) can help endoscopists in the optical diagnosis of colorectal polyps by predicting the histopathology.”
From Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction (2024) · cites this paper as [2]
The Introduction (page unavailable) says endoscopic imaging technologies allow real-time characterization of diminutive colorectal polyps, and the References list software for automated classification of confocal endomicroscopy videos. The paper does not establish that AI-based CADx systems help endoscopists predict polyp histopathology; its discussion of performance concerns imaging technologies and endoscopists’ interpretation of them. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe stand-alone performance of CADx systems and comparisons of CADx performances with thresholds for clinical implementation have been evaluated and show promising results.
“The stand-alone performance of CADx systems and comparisons of CADx performances with thresholds for clinical implementation have been evaluated and show promising results.[1][2][3][4][5][6][7]”
From Appropriate trust in artificial intelligence for the optical diagnosis of colorectal polyps: the role of human/artificial intelligence interaction (2024) · cites this paper as [2]
The Discussion (page unavailable in our copy) reports promising results for real-time optical biopsy using NBI, i-SCAN and FICE against ASGE PIVI thresholds, particularly with expert operators. But the paper evaluates endoscopist assessments with imaging technologies, not the stand-alone performance of CADx systems; that part of the claim is unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measured
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- Authors
- Abu Dayyeh, B. K., Thosani, N., Konda, V., Wallace, M. B., Rex, D. K., Chauhan, S. S., Hwang, J. H., Komanduri, S., Manfredi, M., Maple, J. T., Murad, F. M., Siddiqui, U. D., & Banerjee, S.
- ORCID
- Venue
- Gastrointestinal Endoscopy
- Publisher
- Elsevier BV
- Published
- 2015-03
- Volume
- 81
- Issue
- 3
- Pages
- 502.e1-502.e16
- ISSN
- 0016-5107 (ISSN-L)
- OpenAlex
- W2055082612
- Cited by
- 389
- References
- 61
- Citations by year
- 2026: 15 · 2025: 23 · 2024: 30 · 2023: 39 · 2022: 38 · 2021: 42 · 2020: 44 · 2019: 42 · 2018: 35 · 2017: 40 · 2016: 24 · 2015: 16 · 2014: 1
- FWCI
- 4.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Gastrointestinal Endoscopy (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Colorectal Cancer Screening and Detection
- Health Sciences › Medicine › Pathology and Forensic Medicine › Genetic factors in colorectal cancer
- Health Sciences › Medicine › Oncology › Colorectal Cancer Surgical Treatments
- Keywords
- diminutive colorectal polyps, optical biopsy, narrow-band imaging, i-scan, negative predictive value, rectosigmoid colon, polypectomy, histopathological correlation
- MeSH terms
- Biopsy, Colon, Colonoscopy, Humans, Intestinal Polyps, Predictive Value of Tests, Rectum, United States, Colorectal Neoplasms, Models, Statistical, Practice Guidelines as Topic, Adenomatous Polyps, Narrow Band Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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