Evidence map›Paper›PMID 36175457›Full record

Trial reportScientific reports2022

Artificial intelligence-enhanced volumetric laser endomicroscopy improves dysplasia detection in Barrett's esophagus in a randomized cross-over study.

Allon Kahn, Matthew J McKinley, Molly Stewart, Kenneth K Wang, Prasad G Iyer, Cadman L Leggett, Arvind J Trindade

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.4field-weighted citation impact, top 11% of its field
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

3 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
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

7 authors at 4 institutions in 1 country.

Allon KahnDivision of Gastroenterology and Hepatology, Mayo Clinic Arizona, Scottsdale, AZ, USA.
Matthew J McKinleyDivision of Gastroenterology, Zucker School of Medicine at Hofstra/Northwell, Long Island Jewish Medical Center, 270-05 76th Avenue, New Hyde Park, NY, 11040, USA.
Molly StewartDivision of Gastroenterology, Zucker School of Medicine at Hofstra/Northwell, Long Island Jewish Medical Center, 270-05 76th Avenue, New Hyde Park, NY, 11040, USA.
Kenneth K WangDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.
Prasad G IyerDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.
Cadman L LeggettDivision of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA.
Arvind J TrindadeDivision of Gastroenterology, Zucker School of Medicine at Hofstra/Northwell, Long Island Jewish Medical Center, 270-05 76th Avenue, New Hyde Park, NY, 11040, USA. arvind.trindade@gmail.com.
Mayo Clinic in Arizona · USFeinstein Institute for Medical Research · USHealth Innovations (United States) · USLong Island Jewish Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Volumetric laser endomicroscopy (VLE) is an advanced endoscopic imaging tool that can improve dysplasia detection in Barrett's esophagus (BE). However, VLE scans generate 1200 cross-sectional images that can make interpretation difficult. The impact of a new VLE artificial intelligence algorithm called Intelligent Real-time Image Segmentation (IRIS) is not well-characterized. This is a randomized prospective cross-over study of BE patients undergoing endoscopy who were randomized to IRIS-enhanced or unenhanced VLE first followed by the other (IRIS-VLE vs. VLE-IRIS, respectively) at expert BE centers. The primary outcome was image interpretation time, which served as a surrogate measure for ease of interpretation. The secondary outcome was diagnostic yield of dysplasia for each imaging modality. 133 patients were enrolled. 67 patients were randomized to VLE-IRIS and 66 to IRIS-VLE. Total interpretation time did not differ significantly between groups (7.8 min VLE-IRIS vs. 7 min IRIS-VLE, P = 0.1), however unenhanced VLE interpretation time was significantly shorter in the IRIS-VLE group (2.4 min vs. 3.8 min, P < 0.01). When IRIS was used first, 100% of dysplastic areas were identified, compared with 76.9% when VLE was the first interpretation modality (P = 0.06). IRIS-enhanced VLE reduced the time of subsequent unenhanced VLE interpretation, suggesting heightened efficiency and improved dysplasia detection. It was also able to identify all endoscopically non-visible dysplastic areas.

Indexed as

Barrett EsophagusArtificial IntelligenceCross-Over StudiesHumansHyperplasiaLasersProspective Studies

Identifiers

PMID36175457
PMCPMC9523020
OpenAlexW4297996609

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.