Evidence map›Paper›PMID 39402235›Full record

ReviewAbdominal radiology (New York)2025

Multisystem diseases in the abdomen and pelvis: imaging manifestations and diagnostic roles of cross-sectional imaging.

Mi Hye Yu, Young Jun Kim, Sungeun Park, Hee Sun Park, Sung Il Jung

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 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

5 authors.

Mi Hye YuDepartment of Radiology, Konkuk University Medical Center, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, Republic of Korea.
Young Jun KimDepartment of Radiology, Konkuk University Medical Center, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, Republic of Korea. yjkim@kuh.ac.kr.
Sungeun ParkDepartment of Radiology, Konkuk University Medical Center, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, Republic of Korea.
Hee Sun ParkDepartment of Radiology, Konkuk University Medical Center, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, Republic of Korea.
Sung Il JungDepartment of Radiology, Konkuk University Medical Center, Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic diseases, such as IgG4-related disease, sarcoidosis, and amyloidosis, usually involve multiple systems or organs simultaneously or sequentially. The gastrointestinal tract, hepatobiliary system, and genitourinary tract are commonly involved in many multisystem diseases and can also be the first sites with disease involvement. Cross-sectional imaging, such as CT and MR, plays an important role in the diagnosis and management of multisystem diseases by aiding in the evaluation of multiorgan involvement. Here, common imaging features of frequently affected organs are reviewed in multisystem diseases that we often encounter in the abdomen and pelvis, and the diagnostic roles of cross-sectional imaging for these diseases are also discussed.

Indexed as

Magnetic Resonance ImagingTomography, X-Ray ComputedAbdomenAmyloidosisDigestive System DiseasesGastrointestinal DiseasesHumansImmunoglobulin G4-Related DiseasePelvisSarcoidosisAmyloidosisIgG4-related diseaseSarcoidosisSystemic diseaseSystemic lupus erythematosusTuberculosisTuberous sclerosis complexVon Hippel–Lindau disease

Identifiers

What OpenQuestion holds

Textmetadata
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.