Evidence map›Paper›PMID 34472242›Full record

ArticleJournal of biomedical optics2021

Virtual scale function of gastrointestinal endoscopy for accurate polyp size estimation in real-time: a preliminary study.

Masato Yoshioka, Yuichi Sakaguchi, Daisuke Utsunomiya, Shinichiro Sonoda, Takeichi Tatsuta, Satoshi Ozawa, Yuichi Teramura, Keita Harada, Hideaki Kinugasa, Hiroyuki Okada

Open access · goldAbstract read
In one paragraph

Article in Journal of biomedical optics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 32 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Masato YoshiokaFUJIFILM Corp., Japan.
Yuichi SakaguchiFUJIFILM Corp., Japan.
Daisuke UtsunomiyaFUJIFILM Corp., Japan.
Shinichiro SonodaFUJIFILM Corp., Japan.
Takeichi TatsutaFUJIFILM Corp., Japan.
Satoshi OzawaFUJIFILM Corp., Japan.
Yuichi TeramuraFUJIFILM Corp., Japan.
Keita HaradaOkayama Univ., Japan.
Hideaki KinugasaOkayama Univ., Japan.
Hiroyuki OkadaOkayama Univ., Japan.
Fujifilm (Japan) · JPOkayama University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

significancePolyp size is important for selecting the surveillance interval or treatment policy. Nevertheless, it is challenging to accurately estimate the polyp size during endoscopy. An easy and cost-effective function to assist in polyp size estimation is required.

aimTo propose a virtual scale function for endoscopy and evaluate its performance and expected accuracy. APPROACH: An adaptive virtual scale behavior was demonstrated. The measurement error of the virtual scale along the distance between the tip of the endoscope and the object plane was evaluated using graph paper. The accuracy of polyp size estimation by an expert endoscopist was compared with the accuracy of the biopsy forceps method using phantom images.

resultsThe measurement errors of the virtual scale were   ≤  0.7  mm when the distance to the graph paper, which faced the tip of the endoscope, varied from 4 to 30 mm. The accuracy with the virtual scale was significantly higher than that obtained with biopsy forceps (5.3  ±  5.5  %   versus 11.9  ±  9.4  %  , P  <  0.001).

conclusionsThe virtual scale function, which operates in real-time without any additional device, can be used to estimate polyp sizes easily and accurately with endoscopy.

Indexed as

AlgorithmsEndoscopesBiopsyEndoscopy, GastrointestinalPhantoms, Imagingendoscopyimage processinglaser applicationsreal-time imagingsize estimationvirtual scale

Identifiers

PMID34472242
PMCPMC8408764
OpenAlexW3197714691

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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.