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基于双序MRI的放射性诺米克图,用于评估乳腺癌中的Ki-67表达

Li Zhang¹, Mengyi Shen¹, Dingyi Zhang¹

¹Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.

Journal of magnetic resonance imaging : JMRI

|December 13, 2023

概括

这项研究开发了一种使用双序MRI放射学和临床数据来预测乳腺癌中Ki-67表达的nomogram. 组合模型显示了Ki-67水平的优异预测准确性.

科学领域:

在瘤学瘤学.
放射学放射学是一门学科.
医疗成像医学成像

背景情况:

放射学用于预测乳腺癌 (BC) 中的Ki-67,但通常依赖于单个MRI序列.
不同的MRI序列对于Ki-67预测具有不同的灵敏度和特异性.

研究的目的:

为评估BC中的Ki-67表达开发一个名图.
诺米图集成了双序MRI放射性特征和临床特征.

主要方法:

对227名患有233个BC病变的女性患者进行了回顾性分析.
从显微扩散系数 (ADC) 和动态对比增强MRI (DCE-MRI) 序列中提取了放射性特征.
后勤回归和LASSO被用来构建ADC,DCE-MRI和双序MRI (dsMRI) 模型,其次是包含临床因素的诺姆图构造.

主要成果:

在试验组中,dSMRI模型显示出比ADC (AUC=0.797) 和DCE-MRI (AUC=0.755) 模型更高的预测效率 (AUC=0.862).
纳米图,结合雌激素受体 (ER) 和带淋巴结 (ALN) 转移,实现了0.876.6的AUC.
诺米图表的表现优于临床模型 (AUC=0.787) 和放射学模型.

结论:

综合dsMRI放射性特征和临床特征的nomogram可以有效地评估乳腺癌中的Ki-67表达.
与单个序列放射学或仅仅临床模型相比,这种方法提供了更好的预测准确性.

关键词:

这就是 Ki-67 的特点.乳腺癌乳腺癌乳腺癌这个名字是名ogramogram.无线电学 (radiomics) 是一种无线电学.

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