用连续随机步行MR扩散模型评估乳腺癌恶性病变,预后因素和分子亚型
Huan Chang1, Dawei Wang2, Yuting Li3
1Department of Radiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, Shandong, China.
European journal of radiology
|July 28, 2023
概括
连续时间随机步行 (CTRW) 模型显示了使用MRI评估乳腺病变的前景. 结合扩散权重成像,CTRW参数可以帮助区分恶性和良性乳腺瘤,并预测癌症亚型.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 在瘤学瘤学.
背景情况:
- 乳腺癌的诊断严重依赖于成像技术.
- 扩散权重成像 (DWI) 提供了关于组织微观结构的功能信息.
- 连续时间随机步行 (CTRW) 模型为分析扩散数据提供了一种新的方法.
研究的目的:
- 评估CTRW模型在区分良性和恶性乳腺病变方面的诊断效用.
- 调查CTRW模型参数与乳腺癌病理和分子因素之间的关系.
- 评估CTRW参数作为非侵入性成像生物标志物的潜力.
主要方法:
- 追溯分析85名乳腺病变患者接受3.0TMRI.
- 获取DWI数据,用于CTRW模型的16个b值.
- 病变类型之间的CTRW参数 (Dm,α,β) 和明显扩散系数 (ADC) 的比较以及与预后因素的相关性.
主要成果:
- 与良性病变相比,CTRW参数 (Dm,α,β) 和ADC在恶性病变中明显较低.
- 综合的CTRW参数实现了0.833的AUC,用于区分恶性状态.
- CTRW参数与雌激素受体,孕受体和Ki-67表达相关,有助于分子亚型诊断.
结论:
- CTRW模型参数显示乳腺病变具有显著的诊断价值.
- 这些参数可以作为乳腺癌评估的非侵入性定量成像标记.
- CTRW分析具有改善乳腺癌特征和亚型预测的潜力.
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