Evidence map›Paper›PMID 41356987›Full record

ReviewCureus2025

Advanced Imaging Modalities in Gastrointestinal Endoscopy: A Systematic Review of Diagnostic Accuracy and Clinical Impact.

Anas E Ahmed, Ali M Abudash, Abdul Rah Man K Al Am Er, Ibrahim N Almuhaihi, Abdulkarim M Alghaithi, Abdullah A Alammar, Maryam K Magfouri, Nasser A Alnasser, Maryam M Abdulaal, Khalid S Altamimi

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Anas E AhmedDepartment of Community Medicine, Jazan University, Jazan, SAU.
Ali M AbudashDepartment of Emergency Medicine, Sabya General Hospital, Jazan, SAU.
Abdul Rah Man K Al Am ErCollege of Medicine, King Faisal University, Al-Ahsa, SAU.
Ibrahim N AlmuhaihiCollege of Medicine, University of Hail, Hail, SAU.
Abdulkarim M AlghaithiCollege of Medicine, University of Hail, Hail, SAU.
Abdullah A AlammarCollege of Medicine, University of Hail, Hail, SAU.
Maryam K MagfouriCollege of Medicine, Jazan University, Jazan, SAU.
Nasser A AlnasserCollege of Medicine, King Saud University, Riyadh, SAU.
Maryam M AbdulaalCollege of Medicine, Taibah University, Madinah, SAU.
Khalid S AltamimiCollege of Medicine, University of Hail, Hail, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional white light endoscopy (WLE) has limited sensitivity for detecting subtle gastrointestinal lesions, leading to missed diagnoses and interval cancers. Advanced imaging modalities, including narrow band imaging (NBI), linked color imaging (LCI), blue laser imaging (BLI), autofluorescence imaging (AFI), and artificial intelligence (AI)-based systems, have been developed to enhance lesion detection, characterization, and diagnostic confidence. This systematic review, conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, evaluated the diagnostic accuracy and clinical impact of these technologies compared with WLE and other standard approaches. Comprehensive searches of PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Scopus, and Web of Science (from inception to September 2025) identified 14,288 records, of which 10,590 unique studies were screened, and 21 met the inclusion criteria. NBI demonstrated moderate-to-high diagnostic accuracy but offered limited improvement over high-definition WLE in adenoma detection. LCI improved sensitivity and lesion visibility across gastric, esophageal, and inflammatory disorders, showing strong performance in early gastric cancer and reflux esophagitis. BLI and BLI-bright enhanced real-time gastric cancer detection and supported colorectal optical diagnosis comparable to NBI. AFI showed inferior performance to dye-based chromoendoscopy in ulcerative colitis surveillance but effectively distinguished reflux phenotypes with high accuracy. AI-based systems consistently increased adenoma detection rate (ADR) and adenomas per colonoscopy (APC) through computer-aided detection (CADe) and achieved clinically actionable accuracy for optical diagnosis in selected settings using computer-aided diagnosis (CADx). Overall, advanced imaging modalities improve lesion detection and diagnostic precision compared with WLE, each offering distinct advantages. LCI and BLI are most effective for early gastric cancer and inflammatory conditions, NBI remains a validated tool for targeted diagnosis, and AI-based systems provide the greatest gains in adenoma yield while showing promise for reliable real-time optical diagnosis. Standardization, multicenter validation, and integration into clinical practice guidelines are essential to optimize their impact on patient outcomes.

Indexed as

adenoma detection rateadvanced imagingartificial intelligenceautofluorescence imagingblue laser imagingcomputer-aided detectioncomputer-aided diagnosisgastrointestinal endoscopylinked color imagingnarrow band imaging

Identifiers

PMID41356987
PMCPMC12680370

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Registered trials

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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.