Evidence map›Paper›PMID 42458314›Full record

Observational studyBMC gastroenterology2026

Diagnostic utility of endoscopic ultrasound features in pancreatic tumors: a retrospective observational study focusing on tumor size and imaging characteristics.

Ming-Sheng Chien, Ting-Chung Wo, Jian-Han Lai

Abstract readObservational Study
In one paragraph

Observational study in BMC gastroenterology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Ming-Sheng ChienDepartment of Internal Medicine, Division of Gastroenterology, Mackay Memorial Hospital, Taipei, Taiwan.
Ting-Chung WoDepartment of Internal Medicine, Division of Gastroenterology, Mackay Memorial Hospital, Taipei, Taiwan.
Jian-Han LaiDepartment of Internal Medicine, Division of Gastroenterology, Mackay Memorial Hospital, No.92, Sec. 2, Chung-Shan, North Road, Taipei, 10449, Taiwan. jiannhann@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEndoscopic ultrasound (EUS) is a highly sensitive imaging modality for detecting pancreatic tumors, particularly small lesions. However, its ability to distinguish malignant from benign lesions remains a diagnostic challenge. This study aimed to evaluate the imaging characteristics observed via EUS in differentiating malignancy and to assess the influence of tumor size on diagnostic accuracy.

methodsThis retrospective study included 315 patients who underwent EUS evaluation for pancreatic tumors between January 2019 and July 2024. The final diagnosis was established based on surgical pathology, EUS-FNB results, or clinical follow-up ≥ 6 months. Key imaging features assessed included echogenicity, lesion margins, pancreatic duct dilatation, and distal pancreatic atrophy. Tumors were categorized by size (< 2 cm or > 2 cm), and statistical analyses were conducted to identify predictive factors of malignancy.

resultsOf the 315 tumors, 205 (65.1%) were malignant. Five EUS imaging features-hypoechoic pattern, heterogeneous echotexture, irregular margins, pancreatic duct dilatation, and distal pancreatic atrophy-were identified as predictive of malignancy. The ROC-derived cutoff of 3.5 corresponds clinically to ≥ 4 features. AUC was 0.807 (95% CI: 0.759-0.849). Using a ≥ 4-feature threshold, sensitivity was 87.8%, specificity 54.5%, PPV 78.6%, and NPV 69.4%. Subgroup multivariable analysis revealed that heterogeneous echotexture and pancreatic duct dilatation were significant predictors of malignancy in tumors < 2 cm. However, in tumors > 2 cm, no individual feature significantly distinguished malignancy.

conclusionAmong pancreatic tumors, those exhibiting four or more of the five EUS features should be prioritized for malignancy evaluation. In small tumors, heterogeneous echotexture and pancreatic duct dilatation offer valuable diagnostic insight. Conversely, larger tumors present greater diagnostic challenges due to overlapping features on B-mode imaging alone.

Indexed as

EndosonographyPancreatic NeoplasmsAdultAgedAged, 80 and overAtrophyDiagnosis, DifferentialFemaleHumansMaleMiddle AgedPancreatic DuctsRetrospective StudiesROC CurveSensitivity and SpecificityTumor BurdenEndoscopic ultrasound (EUS)Fine-needle biopsy (FNB)Pancreatic ductal adenocarcinoma (PDAC)

Identifiers

PMID42458314
PMCPMC13656625

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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.