人类表皮生长因子受体2 (HER2) 低表达和HER2过度表达乳腺癌之间的歧视:对四个MRI扩散模型的比较研究
Chunping Mao1,2, Lanxin Hu1,2, Wei Jiang1,2
1Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.
European radiology
|September 6, 2023
概括
连续随机步行 (CTRW) 扩散MRI模型,特别是alpha (α) CTRW参数,有效地区分HER2-低和HER2-过度表达的乳腺癌. 将αCTRW与临床病理特征相结合,进一步提高了歧视准确度.
科学领域:
- 放射学和成像学 放射学和成像学
- 在瘤学瘤学.
- 生物物理学的生物物理.
背景情况:
- 准确地确定人体表皮生长因子受体2 (HER2) 状态对于乳腺癌 (BC) 治疗选择至关重要.
- 区分HER2-低和HER2-过度表达BC对于优化HER2-向疗法至关重要.
研究的目的:
- 评估扩散加权成像 (DWI) 模型的有效性,包括连续时间随机步行 (CTRW),分数顺序计算 (FROC) 和伸展指数模型 (SEM),在乳腺癌中区分HER2状态.
- 为了确定最佳的扩散参数来分类HER2表达水平.
主要方法:
- 一项前性研究,涉及158名乳腺癌妇女,按HER2状态分类 (HER2-零,HER2-低,HER2-过度表达).
- 使用CTRW,FROC和SEM模型从DWI获得的九个扩散参数的分析.
- 后勤回归和接收器操作特征 (ROC) 曲线分析,以评估扩散指标和临床病理特征的辨别能力.
主要成果:
- 在HER2-低和HER2-过度表达组之间观察到雌激素受体 (ER),孕激素受体 (PR) 状态和瘤大小的显著差异.
- 在HER2-低BC中发现了αCTRW,DCTRW,βFROC,DFROC,μFROC,αSEM和DDCSEM的较低值,与HER2-过度表达BC相比.
- 与ADC (AUC = 0.610) 相比,αCTRW参数显示了最高的区分能力 (AUC = 0.802).
- 将αCTRW与ER状态,PR状态和瘤大小相结合,使AUC提高到0.877.
结论:
- 来自CTRW扩散MRI的αCTRW参数是区分HER2-低和HER2-过度表达的乳腺癌的一个有价值的工具.
- 像CTRW这样的高级扩散MRI模型为预测HER2状态提供了有希望的方法,可能为乳腺癌患者的治疗决策提供指导.
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