ArticleInternal medicine (Tokyo, Japan)2021
The Differential Diagnosis of Colorectal Polyps Using Colon Capsule Endoscopy.
Article in Internal medicine (Tokyo, Japan), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- Flexible spectral imaging color enhancement in colon capsule endoscopy: Scoping review of evidence for lesion detection and characterization.Endoscopy international open · 2026Review
- Expected Values of Artificial Intelligence in Colon Capsule Endoscopy: Artificial Intelligence in Capsule Endoscopy Consortium Position Statement.Endoscopy international open · 2026Article
- Explainable AI in Digestive Healthcare and Gastrointestinal Endoscopy.Journal of clinical medicine · 2025Review
- Polyp Matching in Colon Capsule Endoscopy: Pioneering CCE-Colonoscopy Integration Towards an AI-Driven Future.Journal of clinical medicine · 2024Review
- Rationalizing polyp matching criteria in colon capsule endoscopy: an international expert consensus through RAND (modified DELPHI) process.Therapeutic advances in gastroenterology · 2024Article
- Smart Endoscopy Is Greener Endoscopy: Leveraging Artificial Intelligence and Blockchain Technologies to Drive Sustainability in Digestive Health Care.Diagnostics (Basel, Switzerland) · 2023Review
- Colon Capsule Endoscopy in the Diagnosis of Colon Polyps: Who Needs a Colonoscopy?Diagnostics (Basel, Switzerland) · 2022Review
- Virtual Chromoendoscopy in Capsule Endoscopy: A Narrative Review.Diagnostics (Basel, Switzerland) · 2022Review
- Performance of a Deep Learning System for Automatic Diagnosis of Protruding Lesions in Colon Capsule Endoscopy.Diagnostics (Basel, Switzerland) · 2022Article
- Comment on "Artificial intelligence in gastroenterology: A state-of-the-art review".World journal of gastroenterology · 2022Article
- Image-Enhanced Capsule Endoscopy Improves the Identification of Small Intestinal Lesions.Diagnostics (Basel, Switzerland) · 2021Review
- Scoring Systems for Clinical Colon Capsule Endoscopy-All You Need to Know.Journal of clinical medicine · 2021Review
- Artificial intelligence for the detection of polyps or cancer with colon capsule endoscopy.Therapeutic advances in gastrointestinal endoscopyReview
Corrections and comments
- Commented on by
Authors and funding
18 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective Although colorectal polyps (CPs) can be observed with colon capsule endoscopy (CCE), it is difficult to determine the type of polyp using CCE. The objective of this study was to differentiate adenomatous polyps (APs) from hyperplastic polyps (HPs) with CCE. Methods In this single-center retrospective study, an analysis was conducted on the same CPs with both CCE and colonoscopy (CS) and histopathologically diagnosed as AP or HP. The color difference (ΔE) between the polyp surface and the surrounding mucosa was calculated using the CIE1976 L*a*b* color space method on white light (WL), flexible spectral imaging color enhancement (FICE), and blue mode (BM) CP images. We investigated the ability of the ratio of the color differences (ΔE') to differentiate between APs and HPs. Results The size of all 51 polyps (34 APs, 17 HPs) was 7.5±4.6 mm with CCE and 7.3±4.2 mm with CS, and this difference was not significant (p=0.28). The FICEΔE' of APs was 3.3±1.8, which was significantly higher than the FICEΔE' of HPs (1.3±0.6; p<0.001). A receiver operating characteristic analysis showed that FICEΔE' was useful for differentiating between APs and HPs, with an area under the curve of 0.928 (95% confidence interval, 0.843-1). The sensitivity was 91.2%, and the specificity was 88.2% with a cut-off value of 1.758. Conclusion Using FICE on CCE images of CPs and applying the CIELAB color space method, we were able to differentiate between APs and HPs with high accuracy. This method has the potential to reduce unnecessary CS procedures.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.