Evidence map›Paper›PMID 41353520›Full record

ArticleSkeletal radiology2026

Development and evaluation of multimodal ultrasound radiomics models for predicting active inflammation in rheumatoid arthritis.

Haiyan Tian, Jie Liu, Shigang Li, Tianzi Yang

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Article in Skeletal radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Haiyan TianDepartment of Ultrasound, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China.
Jie LiuDepartment of Ultrasound, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, No. 2 Jiefang Road, Xiling District, Yichang, Hubei, China. 54414749@qq.com.ORCID http://orcid.org/0000-0002-3102-9565
Shigang LiCollege of Basic Medical Sciences, China Three Gorges University, No. 8, University Road, Yichang City, Hubei, China.
Tianzi YangRenmin Hospital of Wuhan University, No. 6, Gaoxin Road, Jiangxia District, Wuhan City, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a multimodal ultrasound radiomics model integrating power Doppler (PD) and superb microvascular imaging (SMI) data, combined with clinical baseline characteristics, and to evaluate its predictive performance for active inflammation in rheumatoid arthritis (RA).

methodsA total of 2,503 PD and 2,503 SMI ultrasound images of metacarpophalangeal and proximal interphalangeal joints were collected from RA patients with active inflammation and non-active controls between December 2022 and March 2024. Single-modality (PD/SMI), multimodal (SMI_PD), and clinical-integrated models were developed. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

resultsThe area under the curve (AUC) values for PD, SMI, multimodal SMI_PD, and clinical-integrated models were 0.76, 0.75, 0.82, and 0.83, respectively.

conclusionThe multimodal radiomics model demonstrated superior diagnostic performance for RA active inflammation. SMI shows potential as a tool for subclinical inflammation monitoring, while the integration of multimodal ultrasound radiomics with clinical data further enhances clinical utility.

Indexed as

Arthritis, RheumatoidInflammationMultimodal ImagingUltrasonography, DopplerAdultAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsRadiomicsUltrasonographyActive inflammationMultimodal ultrasoundRheumatoid arthritisUltrasound radiomics

Identifiers

PMID41353520

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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.