Evidence map›Paper›PMID 41832724›Full record

ArticleCurrent medical imaging2026

Muscle MR Radiomics for Evaluation of Idiopathic Inflammatory Myopathies

Wenyan Zhang, Qin Li, Gang Wu

Abstract read
In one paragraph

Article in Current medical imaging, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Wenyan ZhangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0001-8252-4796
Qin LiDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0002-7090-4502
Gang WuDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to establish a prediction model for Idiopathic Inflammatory Myopathies (IIM) based on the radiomics of vastus intermedius.

methods43 IIM patients and 48 control cases were analyzed in the retrospective study. By using the 3D slicer software, 107 radiomics features were obtained for each case. The selection of variables was performed using a two-sample t-test or the Mann-Whitney U test, followed by maximum correlation minimum redundancy (mRMR). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for dimension reduction. To assess the model performance, the receiver operating characteristic (ROC) curve was plotted.

resultsThe results showed that 67 features were varying between the IIM cases and control groups (p < 0.05). With the mRMR and LASSO methods, seven features were finally determined. Regarding the radiomics model's performance, it achieved an AUC of 0.983 in the validation data. DISCUSSION: This study investigated microstructural differences in a specific muscle (varasimus intermedias) between Idiopathic Inflammatory Myopathy (IIM) patients and normal controls using radiomics. It identified 67 distinguishing radiomics features and successfully established a high-performance prediction model (AUC >0.9) using LASSO and mRMR for feature selection. These features likely reflect IIM-induced microstructural changes, such as inflammation and necrosis, typically visible on MRI as signal abnormalities. Radiomics thus offers a potential non-invasive alternative to muscle biopsy for assessing these changes.

conclusionMuscle MR radiomics is feasible for identifying idiopathic inflammatory myopathy and has the potential to serve as a non-invasive alternative to muscle biopsy.

Indexed as

Magnetic Resonance ImagingMyositisAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedRadiomicsRetrospective StudiesROC CurveCase-control study.Idiopathic inflammatory myopathies (IIM)Least absolute shrinkage and selection operator (LASSO) regressionMuscle MR radiomicsPredication model

Identifiers

PMID41832724
PMCPMC13445545

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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.