Evidence map›Paper›PMID 41062762›Full record

ArticleSurgical endoscopy2026

Computer-aided diagnosis system for predicting deeply invasive colorectal cancer: a comparison with a prospective study using magnifying chromoendoscopy.

Tomoaki Matsumura, Mai Fujie, Yukihiro Nomura, Kenichiro Okimoto, Mamoru Tokunaga, Tsubasa Ishikawa, Naoki Akizue, Keisuke Matsusaka, Takuto Suzuki, Yoshiyasu Kitagawa and 3 more

Abstract readComparative StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Tomoaki MatsumuraDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chiba, 260-8670, Japan. matsumura@chiba-u.jp.ORCID 0000-0001-5314-9325
Mai FujieDepartment of Clinical Engineering Center, Chiba University Hospital, Chiba, Japan.
Yukihiro NomuraCenter for Frontier Medical Engineering, Chiba University, Chiba, Japan.
Kenichiro OkimotoDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chiba, 260-8670, Japan.
Mamoru TokunagaEndoscopy Division, Chiba Cancer Center, Chiba, Japan.
Tsubasa IshikawaDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chiba, 260-8670, Japan.
Naoki AkizueDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chiba, 260-8670, Japan.
Keisuke MatsusakaDepartment of Diagnostic Pathology, Graduate School of Medicine, Chiba University, Chiba, Japan.
Takuto SuzukiEndoscopy Division, Chiba Cancer Center, Chiba, Japan.
Yoshiyasu KitagawaEndoscopy Division, Chiba Cancer Center, Chiba, Japan.
Kengo NagashimaBiostatistics Unit, Clinical and Translational Research Center, Keio University Hospital, Tokyo, Japan.
Toshiya NakaguchiCenter for Frontier Medical Engineering, Chiba University, Chiba, Japan.
Jun KatoDepartment of Gastroenterology, Graduate School of Medicine, Chiba University, Inohana 1-8-1, Chiba, 260-8670, Japan.

Funding

JSPS KAKENHI 21K07885
6 · The paper itself

Abstract

backgroundComputer-aided diagnosis (CAD) systems for predicting deeply invasive colorectal cancer (CRC) have been developed, but their clinical utility remains uncertain. This study aimed to compare the diagnostic accuracy of a CAD system with that of endoscopists using magnifying narrow-band imaging (M-NBI) and magnifying chromoendoscopy (MCE).

methodsA total of 303 lesions obtained from a prospective multicenter study were analyzed. CAD diagnoses were classified as high- or low-confidence. The diagnostic accuracy of CAD was compared with that of M-NBI and MCE.

resultsThe diagnostic accuracy of the CAD system was 61.3%; sensitivity: 92.3%; specificity: 47.5%; positive predictive value (PPV): 95.4%; negative predictive value (NPV), and 89.1% overall accuracy. Among the 303 lesions, 193 (63.7%) were diagnosed with high confidence, with accuracy rates of 95.3% for high-confidence cases and 78.2% for low-confidence cases. For M-NBI, the sensitivity, specificity, PPV, NPV, and accuracy were 74.2%, 96.3%, 69.7%, 97.0%, and 94.1%, respectively. For MCE, the values were 83.9%, 95.2%, 66.7%, 98.1%, and 94.1%, respectively. The overall accuracy of the CAD system was lesser than that of M-NBI (p = 0.011) and MCE (p = 0.014). However, in high-confidence cases, the diagnostic performance of the CAD system was comparable to that of M-NBI and MCE.

conclusionsIn high-confidence cases, the diagnostic accuracy rates of the CAD system were comparable to those of M-NBI and MCE. However, in low-confidence cases, the accuracy of the CAD system was insufficient, and further evaluations using M-NBI and MCE are necessary.

Indexed as

ColonoscopyColorectal NeoplasmsDiagnosis, Computer-AssistedNarrow Band ImagingAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedNeoplasm InvasivenessPredictive Value of TestsProspective StudiesSensitivity and SpecificityChromoendoscopyColorectal cancerColorectal polypComputer-aided diagnosisNarrow-band imaging

Identifiers

PMID41062762
PMCPMC12823740

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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.