Evidence map›Paper›PMID 41425560›Full record

SynthesisFrontiers in immunology2025

Clinical characteristics and multimodal imaging insights of coronary involvement in immunoglobulin G4-related disease.

Guan Wang, Yaqi Du, Yun Bai, Yimo Zhou, Shuang Ding, Xinrui Wang, Yibin Xie, Hsin-Jung Yang, Debiao Li, Zhaoyang Fan and 4 more

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

14 authors.

Guan Wang *Department of Radiology, The First Hospital of China Medical University, Shenyang, China.
Yaqi Du *Department of Radiology, The First Hospital of China Medical University, Shenyang, China.
Yun Bai *Department of Radiology, The First Hospital of China Medical University, Shenyang, China.
Yimo Zhou *Department of Radiology, The First Hospital of China Medical University, Shenyang, China.
Shuang DingDepartment of Rheumatology and Immunology, The First Hospital of China Medical University, Shenyang, China.
Xinrui WangDepartment of Radiology, The First Hospital of China Medical University, Shenyang, China.
Yibin XieBiomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA, United States.
Hsin-Jung YangBiomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA, United States.
Debiao LiBiomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA, United States.
Zhaoyang FanRadiology and Radiation Oncology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
Guoguang FanDepartment of Radiology, The First Hospital of China Medical University, Shenyang, China.
Zhe Lou *Department of Echocardiography, The First Hospital of China Medical University, Shenyang, China.
Jiayi Wei *Key Laboratory of Cell Biology and Key Laboratory of Medical Cell Biology, Department of Developmental Cell Biology, China Medical University, Shenyang, China.
Yingxian Sun *Department of Cardiovascular Medicine, The First Hospital of China Medical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Coronary involvement in immunoglobulin G4-related disease (IgG4-RD) has remained underexplored despite its risk posed in terms of major adverse cardiovascular events (MACEs). The study provides a comprehensive review, particularly focusing on multimodal imaging characteristics and clinical applicability. Methods: A systematic review was conducted on IgG4-related coronary involvement, supplemented by serial cases from our center included. We analyzed clinical features and multimodal imaging, focusing on the presence or absence of cardiovascular symptoms. Results: A total of 134 IgG4-RD patients with coronary involvement were included and analyzed, including 118 from the literature and 16 from our center. Seven (5%) patients died from secondary myocardial ischemia/infarction. Coronary anomalies commonly affected the left anterior descending artery (LAD) (79%) and presented as diffuse wall thickening or periarterial soft tissue encasement (85%). Stenosis was frequent (47%) and often secondary. Symptoms, primarily induced by myocardial ischemia or infarction (84%), were largely due to stenosis (68%). Chest computed tomography (CT) and coronary computed tomography angiography (CTA) were the primary imaging modalities (81%), particularly in symptomatic cases (88%). Positron emission tomography-computed tomography (PET-CT) was applied in 55 patients (41%) and often in asymptomatic cases (51%). CMR, though less adopted (23%), demonstrated potential in detecting coronary lesions (77%). Glucocorticoid therapy is the most common (76%), with the best response of periarterial encasement (66%). Surgery was less common (32%), primarily being applied to aneurysms (63%). Conclusion: Coronary involvement in IgG4-RD presents four phenotypes, sometimes with an insidious onset and as the sole affected site, poses a potential risk for MACEs. Multimodal imaging is essential for early diagnosis and effective monitoring, with coronary CMR showing promise for early detection without the risk of radiation-induced inflammation and fibrosis.

Indexed as

Coronary Artery DiseaseCoronary VesselsImmunoglobulin GImmunoglobulin G4-Related DiseaseMultimodal ImagingAgedFemaleHumansMaleMiddle AgedPositron Emission Tomography Computed TomographyImmunoglobulin GcardiovascularIgG4-related coronary arteritisIgG4-related diseaseimagingprognosis

Identifiers

PMID41425560
PMCPMC12711756

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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.