Evidence map›Paper›PMID 38263209›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2024

Dual-modal radiomics nomogram based on contrast-enhanced ultrasound to improve differential diagnostic accuracy and reduce unnecessary biopsy rate in ACR TI-RADS 4-5 thyroid nodules.

Jia-Yu Ren, Wen-Zhi Lv, Liang Wang, Wei Zhang, Ying-Ying Ma, Yong-Zhen Huang, Yue-Xiang Peng, Jian-Jun Lin, Xin-Wu Cui

Open access · goldAbstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
5.7field-weighted citation impact, top 3% of its field
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

12 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Radiomics in thyroid nodule assessment.BMC medical imaging · 2026
    Review
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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 at 3 institutions in 1 country.

Jia-Yu RenDepartment of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Wen-Zhi LvDepartment of Artificial Intelligence, Julei Technology Company, Wuhan, China.
Liang WangCenter of Computer, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Wei ZhangDepartment of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ying-Ying MaDepartment of Medical Ultrasound, The First People's Hospital of Qinzhou, Qinzhou, China.
Yong-Zhen HuangDepartment of Medical Ultrasound, The First People's Hospital of Qinzhou, Qinzhou, China.
Yue-Xiang PengDepartment of Medical Ultrasound, Wuhan Third Hospital, Tongren Hospital of Wuhan University, Wuhan, China.
Jian-Jun LinDepartment of Medical Ultrasound, The First People's Hospital of Qinzhou, Qinzhou, China. 2819825313@qq.com.
Xin-Wu CuiDepartment of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. cuixinwu@live.cn.ORCID http://orcid.org/0000-0003-3890-6660
Tongji Hospital · CNBeibu Gulf University · CNTongren Hospital · CN

Funding

Health Commission of Hubei Province 2022SCZ044Wuhan Tongji Hospital 2020YBKY021
6 · The paper itself

Abstract

backgroundAmerican College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS, TR) 4 and 5 thyroid nodules (TNs) demonstrate much more complicated and overlapping risk characteristics than TR1-3 and have a rather wide range of malignancy possibilities (> 5%), which may cause overdiagnosis or misdiagnosis. This study was designed to establish and validate a dual-modal ultrasound (US) radiomics nomogram integrating B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) imaging to improve differential diagnostic accuracy and reduce unnecessary fine needle aspiration biopsy (FNAB) rates in TR 4-5 TNs.

methodsA retrospective dataset of 312 pathologically confirmed TR4-5 TNs from 269 patients was collected for our study. Data were randomly divided into a training dataset of 219 TNs and a validation dataset of 93 TNs. Radiomics characteristics were derived from the BMUS and CEUS images. After feature reduction, the BMUS and CEUS radiomics scores (Rad-score) were built. A multivariate logistic regression analysis was conducted incorporating both Rad-scores and clinical/US data, and a radiomics nomogram was subsequently developed. The performance of the radiomics nomogram was evaluated using calibration, discrimination, and clinical usefulness, and the unnecessary FNAB rate was also calculated.

resultsBMUS Rad-score, CEUS Rad-score, age, shape, margin, and enhancement direction were significant independent predictors associated with malignant TR4-5 TNs. The radiomics nomogram involving the six variables exhibited excellent calibration and discrimination in the training and validation cohorts, with an AUC of 0.873 (95% CI, 0.821-0.925) and 0.851 (95% CI, 0.764-0.938), respectively. The marked improvements in the net reclassification index and integrated discriminatory improvement suggested that the BMUS and CEUS Rad-scores could be valuable indicators for distinguishing benign from malignant TR4-5 TNs. Decision curve analysis demonstrated that our developed radiomics nomogram was an instrumental tool for clinical decision-making. Using the radiomics nomogram, the unnecessary FNAB rate decreased from 35.3 to 14.5% in the training cohort and from 41.5 to 17.7% in the validation cohorts compared with ACR TI-RADS.

conclusionThe dual-modal US radiomics nomogram revealed superior discrimination accuracy and considerably decreased unnecessary FNAB rates in benign and malignant TR4-5 TNs. It could guide further examination or treatment options.

Indexed as

RadiomicsThyroid NoduleBiopsyHumansNomogramsRetrospective StudiesACR TI-RADS 4–5Contrast-enhanced ultrasoundNomogramRadiomicsThyroid nodules

Identifiers

PMID38263209
PMCPMC10807093
OpenAlexW4391132472

What OpenQuestion holds

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LicenceCC BY
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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.