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MidRISH:扩散信号旋转不变谐波的无偏协调

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

作者信息

Newlin Nancy R, Kim Michael E, Kanakaraj Praitayini, Yao Tianyuan, Hohman Timothy, Pechman Kimberly R, Beason-Held Lori L, Resnick Susan M, Archer Derek, Jefferson Angela, Landman Bennett A, Moyer Daniel

机构信息

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

VMAC, VUMC, Nashville, TN, USA and Vanderbilt University, Nashville, TN, USA.

出版信息

bioRxiv. 2023 Aug 15:2023.08.12.553099. doi: 10.1101/2023.08.12.553099.

Abstract

OBJECTIVE

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.

METHODS

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.

CONCLUSION

MidRISH reduces bias of reference selection while preserving harmonization efficacy of LinearRISH.

SIGNIFICANCE

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

目的

在多中心扩散图像分析中,数据协调对于消除混杂效应是必要的。一种这样的协调方法,即线性旋转不变球谐函数(LinearRISH),将一个站点(“目标”)的旋转不变球谐函数(RISH)特征缩放到第二个站点(“参考”),以减少混杂的扫描仪效应。然而,参考站点和目标站点的指定并非随意的,并且由此产生的扩散指标(分数各向异性、平均扩散率)会受到这种选择的影响而产生偏差。在这项工作中,我们提出了中间旋转不变球谐函数(MidRISH):我们不是将参考RISH特征缩放到目标RISH特征,而是将两个站点投影到一个中间空间。

方法

我们通过以下实验验证MidRISH:协调37名无认知障碍的匹配患者的扫描仪差异,以及协调117名无认知障碍的匹配患者的采集和研究差异。

结论

MidRISH在保持LinearRISH协调效果的同时,减少了参考选择的偏差。

意义

在进行LinearRISH协调时,用户应谨慎。选择一个参考站点就是选择扩散指标的效应大小。我们提出的方法消除了导致偏差的站点选择步骤。

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