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使用磁共振成像技术预测乳腺癌亚型基于自动细分的放射学

Wen-Yi Yue, Hong-Tao Zhang¹, Shen Gao¹

¹From the Fifth Medical Center of Chinese PLA General Hospital.

Journal of computer assisted tomography

|September 14, 2023

概括

使用自动细分的放射学准确地从MRI扫描中预测乳腺癌分子亚型. 这种非侵入性方法显示了在乳腺癌亚型化中大规模临床应用的潜力.

科学领域:

医疗成像医学成像
在瘤学瘤学.
人工智能的人工智能

背景情况:

准确的乳腺癌分子亚型是指导治疗决策的关键.
目前用于分类的方法可能是侵入性的或耗时的.
需要使用非侵入性,高效的方法来预测分子亚型.

研究的目的:

评估放射学的可行性,利用自动细分,用于预测乳腺癌分子亚型.
评估放射学模型在分类不同分子亚型方面的性能.

主要方法:

对516名乳腺癌患者进行了回顾性研究.
基于3D UNet的自动卷积神经网络被用于兴趣区域细分.
提取了1316个放射性特征,并采用了18种放射性方法来进行模型选择和性能评估,使用AUC,精度,灵敏度和特异性.

主要成果:

自动细分实现了0.89.9的Dice平均相似系数.
放射学模型成功预测了4种分子亚型,平均AUC为0.8623.3.
在特定亚型预测方面观察到高性能,包括三阴性乳腺癌 (AUC = 0.9335).

结论:

基于自动MRI细分的放射学为预测乳腺癌分子亚型提供了一种非侵入性的方法.
这种方法显示了在大型患者队伍中改善乳腺癌管理的应用潜力.

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相关概念视频

Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...