Evidence map›Paper›PMID 39948651›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2025

Predicting lymph node metastasis in papillary thyroid carcinoma: radiomics using two types of ultrasound elastography.

Xian-Ya Zhang, Di Zhang, Wang Zhou, Zhi-Yuan Wang, Chao-Xue Zhang, Jin Li, Liang Wang, Xin-Wu Cui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2025. 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
–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

12 citing papers in PubMed.

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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

8 authors.

Xian-Ya ZhangDepartment of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, Hubei Province, 430030, China.
Di ZhangDepartment of Medical Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
Wang ZhouDepartment of Medical Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
Zhi-Yuan WangDepartment of Medical Ultrasound, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410031, China.
Chao-Xue ZhangDepartment of Medical Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, China.
Jin LiComputer Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, Hubei Province, 430030, China.
Liang Wang *Computer Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, Hubei Province, 430030, China. nywl@tjh.tjmu.edu.cn.
Xin-Wu Cui *Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan, Hubei Province, 430030, China. cuixinwu@live.cn.

Funding

High-end Foreign Experts Recruitment Plan of China G2022154032LNational Natural Science Foundation of China 82371992
6 · The paper itself

Abstract

backgroundTo develop a model based on intra- and peritumoral radiomics features derived from B-mode ultrasound (BMUS), strain elastography (SE), and shear wave elastography (SWE) for cervical lymph node metastasis (LNM) prediction in papillary thyroid cancer (PTC) and to determine the optimal peritumoral size.

methodsPTC Patients were enrolled from two medical centers. Radiomics features were extracted from intratumoral and four peritumoral regions with widths of 0.5-2.0 mm on tri-modality ultrasound (US) images. Boruta algorithm and XGBoost classifier were used for features selection and radiomics signature (RS) construction, respectively. A hybrid model combining the optimal RS with the highest AUC and clinical characteristics as well as a clinical model were built via multivariate logistic regression analysis. The performance of the established models was evaluated by discrimination, calibration, and clinical utility. DeLong's test was used for performance comparison. The diagnostic augmentation of two radiologists with hybrid model's assistance was also evaluated.

resultsA total of 660 patients (mean age, 41 years ± 12 [SD]; 506 women) were divided into training, internal test and external test cohorts. The multi-modality RS

conclusionsThe intra-peritumoral radiomics model based on tri-modality US imaging holds promise for improving risk stratification and guiding treatment strategies in PTC.

trial registrationRetrospectively registered.

Indexed as

Elasticity Imaging TechniquesLymphatic MetastasisThyroid Cancer, PapillaryThyroid NeoplasmsAdultFemaleHumansLymph NodesMaleMiddle AgedRadiomicsRetrospective StudiesLymph node metastasisPapillary thyroid carcinomaPeritumoral regionRadiomicsUltrasound elastography

Identifiers

PMID39948651
PMCPMC11827213

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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.