REVIEW article
Front. Oncol.
Sec. Cancer Imaging and Image-directed Interventions
This article is part of the Research TopicArtificial Intelligence and Advanced Imaging Techniques for Early and Precision Detection of Breast CancerView all articles
Ultrasound-based Radiomics for the Evaluation of Breast Cancer
Provisionally accepted
- 1Central Hospital of Dalian University of Technology, Dalian, China
- 2Huazhong University of Science and Technology Tongji Medical College Tongji Hospital, Wuhan, China
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Breast cancer is the most common cancer among women all over the world. Ultrasound examination is instrumental in breast lesion screening, diagnosis and prognosis assessment, relying on non-radiation, inexpensiveness and real-time operation. However, it still has some limitations in diagnostic sensitivity and specificity. Radiomics aims at extracting high-throughput quantitative features from medical images, so as to deeply mine image information and further discover tumor features that cannot be discerned by naked eyes. Ultrasound radiomics models are gradually applied in evaluating breast cancer diagnosis and therapy, aiming to help with the precise diagnosis, prediction and treatment. This review summarizes the recent research progress of ultrasound radiomics in diagnosing benign and malignant breast lesion, predicting molecular subtype, lymph node status, neoadjuvant chemotherapy response and disease prognosis. Besides, the review also discusses the challenges and future research perspectives regarding ultrasound-based radiomics for the evaluation of breast cancer.
Keywords: artificial intelligence, breast cancer, Evaluation, Radiomics, ultrasound
Received: 22 Sep 2025; Accepted: 11 Dec 2025.
Copyright: © 2025 Sun, Meng, Liu, Cao, Fu, Meng, Cui and Pan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xin-Wu Cui
Xiao-Fang Pan
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