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基于intravoxel不连贯运动扩散权重成像的基因图谱分析,用于确定直肠癌的围神经入侵状态

Rong He¹, Gesheng Song¹, Junyi Fu¹

¹Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, China.

Quantitative imaging in medicine and surgery

|August 15, 2024

概括

在直肠癌 (RC) 中,输内素不连贯运动扩散加权成像 (IVIM-DWI) 基因组图分析显示在评估周围神经侵入 (PNI) 方面具有前途. 结合IVIM-DWI特征和直肠壁周长侵入的组合模型显著改善了PNI状态评估.

科学领域:

放射学和成像学放射学和成像学
在瘤学瘤学.
医学物理医学物理

背景情况:

形态磁共振成像 (MRI) 在确定直肠癌 (RC) 中围神经侵入 (PNI) 状态方面存在局限性.
输入素不连贯的运动扩散权重成像 (IVIM-DWI) 提供了超出标准MRI的高级功能信息.
对IVIM-DWI数据的组图分析可以量化内异质性.

研究的目的:

评估IVIM-DWI的组图分析对评估直肠癌中PNI状态的有用性.
为了比较IVIM-DWI组图特征的诊断性能与传统的临床放射学因素.
使用IVIM-DWI开发和验证RC中PNI状态的预测模型.

主要方法:

175名直肠癌患者的回顾性分析,这些患者接受了手术前的直肠MRI,使用IVIM-DWI.
使用开源软件从IVIM-DWI中提取整个瘤体积直方图的特征.
统计分析包括单变量,多变量逻辑回归和接收器操作特征 (ROC) 曲线分析.

主要成果:

对于IVIM-DWI直方图的特征,观察者之间达成良好或优异的共识.
几种组图特征 (例如,D*_energy,D*_skewness,f_minimum) 和直肠壁周长侵入 (PCI) 的百分比是PNI状态的重要预测因素.
整合了三个直方图特征和PCI的综合模型显示,PNI评估的曲线下面面积高 (0.807),表现优于单个参数.

结论:

IVIM-DWI 组图分析为评估直肠癌中的 PNI 提供了有价值的定量信息.
结合IVIM-DWI直方图特征和PCI的组合模型为PNI状态提供了更好的诊断性能.
这种方法可能有助于术前风险分层和直肠癌患者的治疗计划.

关键词:

这是直肠癌 (RC).在intravoxel不连贯的运动扩散权重成像 (IVIM-DWI) 中.围神经入侵 (PNI) 是一种疾病.

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