Evidence map›Paper›PMID 30421015›Full record

ArticleEuropean radiology2019

Ultrasound-based radiomics score: a potential biomarker for the prediction of microvascular invasion in hepatocellular carcinoma.

Hang-Tong Hu, Zhu Wang, Xiao-Wen Huang, Shu-Ling Chen, Xin Zheng, Si-Min Ruan, Xiao-Yan Xie, Ming-de Lu, Jie Yu, Jie Tian and 3 more

Abstract read
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In one paragraph

Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed, 5 pooled it
–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

117 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  13. Clinical Applications of Advanced Ultrasound Imaging.Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer · 2026
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57 more citing papers are in PubMed but not listed here.

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

13 authors.

Hang-Tong HuDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China.
Zhu WangDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China.
Xiao-Wen HuangDepartment of Ultrasonography, Zhongshan Hospital of Traditional Chinese Medicine, Affiliated to Guangzhou University of Chinese Medicine, Zhongshan, People's Republic of China.
Shu-Ling ChenDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China.
Xin ZhengDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China.
Si-Min RuanDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China.
Xiao-Yan XieDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China.
Ming-de LuDivision of Interventional Ultrasound and Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China.
Jie YuDepartment of interventional Ultrasound, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Jie TianKey Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People's Republic of China.
Ping LiangDepartment of interventional Ultrasound, Chinese PLA General Hospital, Beijing, 100853, People's Republic of China.
Wei WangDepartment of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People's Republic of China. wangw73@mail.sysu.edu.cn.
Ming KuangDivision of Interventional Ultrasound and Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People's Republic of China. kuangm@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-7397-5779

Funding

Guangdong Natural Science Foundation 2017A030313661Guangdong Science and Technology Foundation 2017A020215195National Nature Science Foundation of China 81701701Training Project for Young Teacher of Sun Yat-sen University 16YKPY37
6 · The paper itself

Abstract

purposeTo develop an ultrasound (US)-based radiomics score for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

methodsBetween January 1, 2012, and October 31, 2017, a total of 482 HCC patients who underwent contrast-enhanced ultrasound (CEUS) were retrospectively reviewed. The study population was divided into a training cohort (n = 341) and a validation cohort (n = 141) based on a cutoff time of January 1, 2016. Radiomics features were extracted from the grayscale US images of HCC. After features selection, a radiomics score was developed from the training cohort. The incremental value of the radiomics score to the clinic-pathological factors for MVI prediction was assessed in the validation cohort with respect to discrimination, calibration, and clinical usefulness.

resultsThe US-based radiomics score consisted of six selected features. Multivariate logistic regression analysis showed that the radiomics score, alpha-fetoprotein (AFP), and tumor size were independent predictors of MVI. The radiomics nomogram (based on the three factors) showed better performance for MVI detection (area under the curve [AUC] 0.731[0.647, 0.815] than the clinical nomogram (based on AFP and tumor size) (0.634 [0.543, 0.724]) (p = 0.015). Both nomograms showed good calibration. Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the clinical nomogram.

conclusionThe US-based radiomics score was an independent predictor of MVI in HCC. Combining the radiomics score with clinical factors improved the prediction efficacy. KEY POINTS: • Radiomics can be applied in US images. • US-based radiomics score was an independent predictor of MVI. • Radiomics nomogram incorporated with the radiomics score showed good performance for MVI prediction.

Indexed as

AgedCarcinoma, HepatocellularFemaleHumansLiver NeoplasmsMaleMicrovesselsMiddle AgedNeoplasm InvasivenessPortal VeinPredictive Value of TestsRetrospective StudiesUltrasonographyNomogramRadiomicsUltrasonography

Identifiers

PMID30421015

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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.