Chai Yuhui, Morgan A Tyler, Handwerker Daniel A, Li Linqing, Huber Laurentius, Sutton Bradley P, Bandettini Peter A
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States.
Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, United States.
Imaging Neurosci (Camb). 2024 Aug 1;2. doi: 10.1162/imag_a_00249. eCollection 2024.
Functional MRI (fMRI) time series are inherently susceptible to the influence of respiratory variations. While many studies treat respiration as a source of noise in fMRI, this study employs natural respiratory variations during high resolution (0.8 mm) fMRI at 7T to formulate a respiration effect related map and then use this map to reduce macrovascular bias for a more laminar-specific fMRI measurement. Our results indicate that respiratory-related signal changes are modulated by breath phase (breathing in/out or in the transition between breath in and out) during fMRI acquisition, with distinct patterns across various brain regions. We demonstrate that respiration maps generated from normal fMRI runs, such as task-oriented sessions, closely resemble those from deep-breath and breath-hold experiments. These maps show a significant correlation with the macro-vasculature automatically segmented based on susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM) images. Most crucially, by removing voxels most responsive to respiratory variations, we can refine high-resolution fMRI measurements to be more layer-specific, improving the accuracy of laminar fMRI analysis.
功能磁共振成像（fMRI）时间序列本质上易受呼吸变化的影响。虽然许多研究将呼吸视为fMRI中的噪声源，但本研究在7T高分辨率（0.8毫米）fMRI期间利用自然呼吸变化来制定与呼吸效应相关的图谱，然后使用该图谱来减少大血管偏差，以进行更具层特异性的fMRI测量。我们的结果表明，在fMRI采集期间，与呼吸相关的信号变化受呼吸阶段（吸气/呼气或在吸气和呼气之间的过渡阶段）调制，不同脑区有不同模式。我们证明，从正常fMRI运行（如任务导向型会话）生成的呼吸图谱与深呼吸和屏气实验生成的图谱非常相似。这些图谱与基于磁敏感加权成像（SWI）和定量磁敏感图谱（QSM）图像自动分割的大血管有显著相关性。最关键的是，通过去除对呼吸变化最敏感的体素，我们可以将高分辨率fMRI测量细化为更具层特异性，提高层特异性fMRI分析的准确性。
