通过分布匹配实现脑结构连接的协调

IF 3.5 2区 医学 Q1 NEUROIMAGING
Zhen Zhou, Bruce Fischl, Iman Aganj, for the Alzheimer's Disease Neuroimaging Initiative
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引用次数: 0

摘要

多位点弥散加权磁共振成像(dMRI)研究的日益普及,有可能为研究大脑结构提供增强的统计能力。然而,由于扫描仪硬件和采集协议的变化,这些研究面临挑战。虽然存在几种dMRI数据协调方法,但很少有专门针对大脑结构连接的方法。我们介绍了一种新的分布匹配方法来协调不同部位和扫描仪之间的大脑结构连接。我们使用来自三个不同数据集(OASIS-3、ADNI-2和prevention - ad)的大脑结构连接数据来评估我们的方法,并将其性能与广泛使用的ComBat方法和最近的CovBat方法进行比较。我们研究了协调对大脑连通性与最小精神状态检查分数和年龄的相关性的影响。我们的研究结果表明,我们的分布匹配技术有效地协调了大脑结构连接,同时保持了连接值的非负性,并产生了与其他方法竞争的相关强度和显著性水平。定性评估说明了跨数据集的期望分布一致性,而定量评估确认了竞争表现。这项工作有助于dMRI协调领域的发展,有可能提高结构连接研究的可靠性和可比性,这些研究结合了神经科学和临床研究中不同来源的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Harmonization of Structural Brain Connectivity Through Distribution Matching

Harmonization of Structural Brain Connectivity Through Distribution Matching

The increasing prevalence of multi-site diffusion-weighted magnetic resonance imaging (dMRI) studies potentially offers enhanced statistical power to investigate brain structure. However, these studies face challenges due to variations in scanner hardware and acquisition protocols. While several methods for dMRI data harmonization exist, few specifically address structural brain connectivity. We introduce a new distribution-matching approach to harmonizing structural brain connectivity across different sites and scanners. We evaluate our method using structural brain connectivity data from three distinct datasets (OASIS-3, ADNI-2, and PREVENT-AD), comparing its performance to the widely used ComBat method and the more recent CovBat approach. We examine the impact of harmonization on the correlation of brain connectivity with the Mini-Mental State Examination score and age. Our results demonstrate that our distribution-matching technique effectively harmonizes structural brain connectivity while maintaining non-negativity of the connectivity values and produces correlation strengths and significance levels competitive with alternative approaches. Qualitative assessments illustrate the desired distributional alignment across datasets, while quantitative evaluations confirm competitive performance. This work contributes to the growing field of dMRI harmonization, potentially improving the reliability and comparability of structural connectivity studies that combine data from different sources in neuroscientific and clinical research.

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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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