Evidence map›Paper›PMID 40256005›Full record

ArticleNagoya journal of medical science2025

Added value of diffusion-weighted magnetic resonance imaging in the diagnosis of recurrent cholangiocarcinoma.

Keiichiro Yamada, Yasuo Takehara, Satoko Ishigaki, Hiroshi Ogawa, Ayumi Nishida, Keita Kato, Tomoki Ebata, Takashi Mizuno, Shinji Naganawa

Abstract read
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In one paragraph

Article in Nagoya journal of medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

9 authors.

Keiichiro YamadaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yasuo TakeharaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Satoko IshigakiDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Hiroshi OgawaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Ayumi NishidaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Keita KatoDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Tomoki EbataDepartment of Surgical Oncology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Takashi MizunoDepartment of Surgical Oncology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shinji NaganawaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distinguishing recurrent cholangiocarcinoma lesions from postoperative fibrosis or biliojejunostomy lesions using contrast-enhanced computed tomography (CECT) alone is challenging. This study examined the value of adding diffusion-weighted magnetic resonance imaging (DWI) to CECT for the detection of cholangiocarcinoma recurrence. This single-institution retrospective analysis included 33 patients who underwent cholangiocarcinoma resection between January 2016 and December 2020. Of the patients, 20 were in the recurrence group and 13 were in the non-recurrence group. Two observers independently reviewed the CECT images and subsequently reviewed the combined CECT and DWI images (b-value, 1000 s/mm

Indexed as

Bile Duct NeoplasmsCholangiocarcinomaDiffusion Magnetic Resonance ImagingNeoplasm Recurrence, LocalAdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesROC CurveTomography, X-Ray Computedbile ductscholangiocarcinomacomputed tomographydiffusion-weighted imagingmagnetic resonance imaging

Identifiers

PMID40256005
PMCPMC12003994

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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.