Evidence map›Paper›PMID 41385057›Full record

ArticleThe international journal of cardiovascular imaging2026

Dual-modal ultrasound radiomics model enhances identification of symptomatic carotid plaque: a multicenter retrospective study.

Tingting Wang, Ying Zhang, Jifan Chen, Lingling Chen, Xiaoming Ding, Yuhan Fu, Jianting Yao, Qingbiao Wu, Pintong Huang

Abstract readMulticenter StudyComparative StudyValidation Study
PubMed Publisher
In one paragraph

Article in The international journal of cardiovascular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Tingting WangDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, No. 88 Jiefang Road, Shangcheng District, Hangzhou, 310009, Zhejiang, People's Republic of China.
Ying ZhangDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, No. 88 Jiefang Road, Shangcheng District, Hangzhou, 310009, Zhejiang, People's Republic of China.
Jifan ChenDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, No. 88 Jiefang Road, Shangcheng District, Hangzhou, 310009, Zhejiang, People's Republic of China.
Lingling ChenDepartment of Ultrasound in Medicine, The Cixi Integrated Traditional Chinese and Western Medicine Medical and Health Group Cixi Red Cross Hospital, Cixi, 315301, People's Republic of China.
Xiaoming DingDepartment of Ultrasound in Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, 317000, People's Republic of China.
Yuhan FuDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, No. 88 Jiefang Road, Shangcheng District, Hangzhou, 310009, Zhejiang, People's Republic of China.
Jianting YaoDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, No. 88 Jiefang Road, Shangcheng District, Hangzhou, 310009, Zhejiang, People's Republic of China.
Qingbiao WuDepartment of Mathematics, Zhejiang University, Hangzhou, 310027, Zhejiang, People's Republic of China. qbwu@zju.edu.cn.
Pintong HuangDepartment of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, No. 88 Jiefang Road, Shangcheng District, Hangzhou, 310009, Zhejiang, People's Republic of China. huangpintong@zju.edu.cn.ORCID http://orcid.org/0000-0003-0747-5765

Funding

National Natural Science Foundation of China 82102052Science and Technology Plan Project of Taizhou 22ywb03
6 · The paper itself

Abstract

We aimed to identify the most valuable variables in multi-modal ultrasound technologies and compare the performance of radiomics models in detecting symptomatic carotid plaques. From August 2013 to April 2021, we retrospectively enrolled 112 carotid plaque patients and randomly divided them into training and validation cohorts at a 3:1 ratio. Additionally, 42 patients from two other centers were enrolled as an independent test cohort. A traditional model (T model) was built using independently significant variables from multivariate analysis of clinical and multi-modal ultrasound characteristics. Radiomics models based on B-mode ultrasound, contrast-enhanced ultrasound (CEUS), and a combined approach (USR, CEUSR, and US-CEUSR models) were then developed. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and decision curve analysis. Only intraplaque contrast enhancement from CEUS modality was independently associated with clinical symptoms [odds ratio = 3.328; 95% confidence interval (CI), 1.230-9.003; p = 0.018] and was used to construct the T model, which achieved an AUC of 0.658 (95% CI, 0.502-0.815) in the external test cohort. The radiomics model showed good and repeatable diagnostic performance for identifying symptomatic plaques, particularly the US-CEUSR model, which had an AUC of 0.775 (95% CI, 0.607-0.915) in external test cohort. This model also provided high clinical benefits in detecting symptomatic plaques. Intraplaque contrast enhancement, a qualitative variable by CEUS, is an independent risk factor for symptomatic carotid plaques, and radiomics features from B-mode ultrasound and CEUS can effectively identify symptomatic carotid plaques.

Indexed as

Carotid ArteriesCarotid Artery DiseasesCarotid StenosisImage Interpretation, Computer-AssistedPlaque, AtheroscleroticAgedContrast MediaFemaleHumansMaleMiddle AgedPredictive Value of TestsRadiomicsReproducibility of ResultsRetrospective StudiesRisk FactorsContrast MediaCarotid plaqueContrast agentRadiomicsStrokeUltrasound

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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.