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通过多模态融合成像直接估计诱发的血红蛋白变化。

Direct estimation of evoked hemoglobin changes by multimodality fusion imaging.

作者信息

Huppert Theodore J, Diamond Solomon G, Boas David A

机构信息

The Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129, USA.

出版信息

J Biomed Opt. 2008 Sep-Oct;13(5):054031. doi: 10.1117/1.2976432.

Abstract

In the last two decades, both diffuse optical tomography (DOT) and blood oxygen level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) methods have been developed as noninvasive tools for imaging evoked cerebral hemodynamic changes in studies of brain activity. Although these two technologies measure functional contrast from similar physiological sources, i.e., changes in hemoglobin levels, these two modalities are based on distinct physical and biophysical principles leading to both limitations and strengths to each method. In this work, we describe a unified linear model to combine the complimentary spatial, temporal, and spectroscopic resolutions of concurrently measured optical tomography and fMRI signals. Using numerical simulations, we demonstrate that concurrent optical and BOLD measurements can be used to create cross-calibrated estimates of absolute micromolar deoxyhemoglobin changes. We apply this new analysis tool to experimental data acquired simultaneously with both DOT and BOLD imaging during a motor task, demonstrate the ability to more robustly estimate hemoglobin changes in comparison to DOT alone, and show how this approach can provide cross-calibrated estimates of hemoglobin changes. Using this multimodal method, we estimate the calibration of the 3 tesla BOLD signal to be -0.55%+/-0.40% signal change per micromolar change of deoxyhemoglobin.

摘要

在过去二十年中,扩散光学层析成像(DOT)和基于血氧水平依赖(BOLD)的功能磁共振成像(fMRI)方法均已被开发出来,作为在脑活动研究中对诱发的脑血流动力学变化进行成像的非侵入性工具。尽管这两种技术从相似的生理来源测量功能对比度,即血红蛋白水平的变化,但这两种模态基于不同的物理和生物物理原理,导致每种方法都有其局限性和优势。在这项工作中,我们描述了一个统一的线性模型,以结合同时测量的光学层析成像和fMRI信号的互补空间、时间和光谱分辨率。通过数值模拟,我们证明了同时进行光学和BOLD测量可用于创建绝对微摩尔脱氧血红蛋白变化的交叉校准估计。我们将这种新的分析工具应用于在运动任务期间同时通过DOT和BOLD成像获取的实验数据,证明与单独使用DOT相比,能够更稳健地估计血红蛋白变化,并展示这种方法如何能够提供血红蛋白变化的交叉校准估计。使用这种多模态方法,我们估计3特斯拉BOLD信号的校准为每微摩尔脱氧血红蛋白变化产生-0.55%±0.40%的信号变化。

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