Study on the Differentiation of Infiltrating Breast Cancer Molecular Subtypes Based on Ultrasound Radiomics.

IF 2.9 3区医学 Q2 ONCOLOGY

Clinical breast cancer Pub Date : 2025-01-16 DOI:10.1016/j.clbc.2025.01.005

Hanqin Liu, Han Xia, Xiaoxiao Yin, Aiping Qin, Wen Zhang, Shuang Feng, Jing Jin

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引用次数: 0

Abstract

Objective: To establish and validate a 2-dimensional ultrasound (US) radiomics model for the noninvasive preoperative differentiation of various molecular subtypes of infiltrating breast cancer (IBC).

Methods: A retrospective analysis of 210 female patients diagnosed with IBC through surgical operation or needle biopsy pathology at our hospital between May 2019 and February 2024 was conducted. Relevant data were collected to establish predictive models for different molecular subtypes of IBC.

Results: Based on 5936 US radiomics features, 39, 25 and 19 optimal features were identified for the differentiation of luminal versus nonluminal types, luminal A versus luminal B types and human epidermal growth factor receptor 2 (HER2) overexpression versus triple-negative (TN) IBC subgroups, respectively. The corresponding areas under the curve for the training and validation sets were 0.901 and 0.752 (luminal vs. nonluminal), 0.931 and 0.773 (luminal A vs. luminal B) and 0.962 and 0.842 (HER2 overexpression vs. TN), respectively, indicating robust discriminatory performance of these models for different pathological molecular subtypes of IBC.

Conclusion: A radiomics model based on US images is capable of effectively differentiating between various molecular subtypes of IBC prior to surgery, holding promise in assisting medical professionals in crafting tailored diagnostic and therapeutic strategies.

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目的建立并验证二维超声（US）放射组学模型，用于术前无创分化浸润性乳腺癌（IBC）的各种分子亚型：对我院2019年5月至2024年2月期间通过外科手术或针刺活检病理确诊为IBC的210例女性患者进行回顾性分析。收集相关数据以建立 IBC 不同分子亚型的预测模型：基于5936个美国放射组学特征，分别确定了39、25和19个最佳特征，用于区分管腔型与非管腔型、管腔A型与管腔B型以及人表皮生长因子受体2（HER2）过表达与三阴性（TN）IBC亚组。训练集和验证集的相应曲线下面积分别为 0.901 和 0.752（管腔型 vs. 非管腔型）、0.931 和 0.773（管腔型 A vs. 管腔型 B）以及 0.962 和 0.842（HER2 过度表达 vs. TN），表明这些模型对不同病理分子亚型的 IBC 具有强大的判别性能：结论：基于 US 图像的放射组学模型能够在手术前有效区分 IBC 的各种分子亚型，有望帮助医务人员制定量身定制的诊断和治疗策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical breast cancer 医学-肿瘤学

CiteScore

5.40

自引率

3.20%

发文量

174

审稿时长

48 days

期刊介绍： Clinical Breast Cancer is a peer-reviewed bimonthly journal that publishes original articles describing various aspects of clinical and translational research of breast cancer. Clinical Breast Cancer is devoted to articles on detection, diagnosis, prevention, and treatment of breast cancer. The main emphasis is on recent scientific developments in all areas related to breast cancer. Specific areas of interest include clinical research reports from various therapeutic modalities, cancer genetics, drug sensitivity and resistance, novel imaging, tumor genomics, biomarkers, and chemoprevention strategies.