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跨站点定量MRI协调:对健康和疾病中的年龄建模的影响

Xinjie Chen^1,2,3,4,5, Mario Ocampo-Pineda^1,2,3, Po-Jui Lu^1,2,3

¹Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland.

Imaging neuroscience (Cambridge, Mass.)

|February 27, 2026

概括

定量MRI (qMRI) 协调有效地减少了跨多地点研究的地点变异性,保持了规范性的年龄建模和多发性硬化症等疾病的临床见解.

科学领域:

神经成像是一种神经成像.
生物医学工程生物医学工程
放射学放射学是一门学科.

背景情况:

跨站点定量MRI (qMRI) 研究面临着与站点相关的变化和不同的采集协议带来的挑战.
在qMRI数据中的批量效应可以掩盖生物信号,影响规范年龄建模和临床解释.
整合多站点队列需要强大的协调策略来确保数据的一致性.

研究的目的:

为了比较多个策略在多个站点的QMRI队列的协调性能.
量化协调对规范年龄建模的影响.
检查协调后临床相关偏差的保留情况.

主要方法:

利用了健康对照组 (n=530) 和多发性硬化症患者 (pwMS,n=98) 的qMRI数据.
使用类内相关系数 (ICC) 和ANOVA评估批量效应.
应用基于实证贝叶斯的通用增量模型 (GAM) 和层次贝叶斯回归 (HBR) 进行协调.

主要成果:

无论是GAM还是HBR,都显著减少了与地点相关的差异 (协调后的ICC<0.001, η2 <0.01).
协调导致了估计的峰值年龄的小,取决于组织的差异,但在整个组织中减少了根平均平方误差 (RMSE).
协调Z-分数保留了pwMS中与疾病相关的偏差,并显示了与临床残疾 (EDSS分数) 的相关性.

结论:

在多站点的QMRI数据中,GAM和B-spline模型有效地减少了位点效应.
协调保持了规范年龄建模的一致性,并保留了生物学上有意义的偏差.
跨站点的qMRI协调对于规范性年龄建模和疾病环境中的临床应用都很有价值.

关键词:

这就是为什么Combat ComBat.大脑衰老老龄化层次化的贝叶斯回归.多发性硬化症多发性硬化症规范性建模规范性建模

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