Evidence map›Paper›PMID 36530981›Full record

ArticleFrontiers in oncology2022

Development and validation of an ultrasound-based radiomics nomogram for predicting the luminal from non-luminal type in patients with breast carcinoma.

Jiangfeng Wu, Lifang Ge, Yun Jin, Yunlai Wang, Liyan Hu, Dong Xu, Zhengping Wang

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Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
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12citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Jiangfeng WuDepartment of Ultrasound, Dongyang People's Hospital, Dongyang, Zhejiang, China.
Lifang GeDepartment of Ultrasound, Dongyang People's Hospital, Dongyang, Zhejiang, China.
Yun JinDepartment of Ultrasound, Dongyang People's Hospital, Dongyang, Zhejiang, China.
Yunlai WangDepartment of Ultrasound, Dongyang People's Hospital, Dongyang, Zhejiang, China.
Liyan HuDepartment of Ultrasound, Dongyang People's Hospital, Dongyang, Zhejiang, China.
Dong XuDepartment of Diagnostic Ultrasound Imaging and Interventional Therapy, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
Zhengping WangDepartment of Ultrasound, Dongyang People's Hospital, Dongyang, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The molecular subtype plays a significant role in breast carcinoma (BC), which is the main indicator to guide treatment and is closely associated with prognosis. The aim of this study was to investigate the feasibility and efficacy of an ultrasound-based radiomics nomogram in preoperatively discriminating the luminal from non-luminal type in patients with BC. Methods: A total of 264 BC patients who underwent routine ultrasound examination were enrolled in this study, of which 184 patients belonged to the training set and 80 patients to the test set. Breast tumors were delineated manually on the ultrasound images and then radiomics features were extracted. In the training set, the T test and least absolute shrinkage and selection operator (LASSO) were used for selecting features, and the radiomics score (Rad-score) for each patient was calculated. Based on the clinical risk features, Rad-score, and combined clinical risk features and Rad-score, three models were established, respectively. The performances of the models were validated with receiver operator characteristic (ROC) curve and decision curve analysis. Results: In all, 788 radiomics features per case were obtained from the ultrasound images. Through radiomics feature selection, 11 features were selected to constitute the Rad-score. The area under the ROC curve (AUC) of the Rad-score for predicting the luminal type was 0.828 in the training set and 0.786 in the test set. The nomogram comprising the Rad-score and US-reported tumor size showed AUCs of the training and test sets were 0.832 and 0.767, respectively, which were significantly higher than the AUCs of the clinical model in the training and test sets (0.691 and 0.526, respectively). However, there was no significant difference in predictive performance between the Rad-score and nomogram. Conclusion: Both the Rad-score and nomogram can be applied as useful, noninvasive tools for preoperatively discriminating the luminal from non-luminal type in patients with BC. Furthermore, this study might provide a novel technique to evaluate molecular subtypes of BC.

Indexed as

breast carcinomaluminal typenon-luminal typeradiomicsultrasound

Identifiers

PMID36530981
PMCPMC9749858

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