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MidRISH:对扩散信号的旋转不变谐波进行无偏协调。

MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal.

机构信息

Department of Computer Science, Vanderbilt University, Nashville, TN, USA.

Department of Computer Science, Vanderbilt University, Nashville, TN, USA.

出版信息

Magn Reson Imaging. 2024 Sep;111:113-119. doi: 10.1016/j.mri.2024.03.033. Epub 2024 Mar 26.

Abstract

Data harmonization is necessary for removing confounding effects in multi-site diffusion image analysis. One such harmonization method, LinearRISH, scales rotationally invariant spherical harmonic (RISH) features from one site ("target") to the second ("reference") to reduce confounding scanner effects. However, reference and target site designations are not arbitrary and resultant diffusion metrics (fractional anisotropy, mean diffusivity) are biased by this choice. In this work we propose MidRISH: rather than scaling reference RISH features to target RISH features, we project both sites to a mid-space. We validate MidRISH with the following experiments: harmonizing scanner differences from 37 matched patients free of cognitive impairment, and harmonizing acquisition and study differences on 117 matched patients free of cognitive impairment. We find that MidRISH reduces bias of reference selection while preserving harmonization efficacy of LinearRISH. Users should be cautious when performing LinearRISH harmonization. To select a reference site is to choose diffusion metric effect-size. Our proposed method eliminates the bias-inducing site selection step.

摘要

数据协调对于去除多部位扩散成像分析中的混杂效应是必要的。线性 RISH 是一种协调方法,它将旋转不变的球谐(RISH)特征从一个部位(“目标”)缩放为第二个部位(“参考”),以减少混杂的扫描仪效应。然而,参考和目标部位的指定并非随意的,并且由此产生的扩散指标(各向异性分数、平均扩散系数)会受到这种选择的影响。在这项工作中,我们提出了 MidRISH:我们不是将参考 RISH 特征缩放为目标 RISH 特征,而是将两个部位投影到中间空间。我们通过以下实验验证了 MidRISH:协调来自 37 名无认知障碍的匹配患者的扫描仪差异,以及协调来自 117 名无认知障碍的匹配患者的采集和研究差异。我们发现,MidRISH 减少了参考选择的偏差,同时保持了 LinearRISH 的协调效果。在执行 LinearRISH 协调时,用户应谨慎。选择参考部位就是选择扩散指标的效应大小。我们提出的方法消除了引起偏差的部位选择步骤。

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