Kleinschmidt A, Hänicke W, Requardt M, Merboldt K D, Frahm J
Biomedizinische NMR Forschungs GmbH, Max-Planck-Institut für biophysikalische Chemie, Göttingen.
Radiologe. 1995 Apr;35(4):242-51.
The sensitivity of gradient-echo magnetic resonance imaging (MRI) to changes in cerebral blood oxygenation has been introduced for mapping functional brain activation. To benefit from the high spatial and temporal resolution of the respective dynamic MRI data sets, their analysis requires algorithms that are capable of both precisely delineating task-related activation patterns and demonstrating functional connectivity of interacting areas. Here, we present various strategies for data evaluation by means of correlational analyses that surpass the quality of subtraction-based activation maps by improving both sensitivity and robustness. On a pixel-by-pixel basis the approach correlates signal time courses with a reference function, reflecting the temporal sequence of activated and control states. Extended versions employ the calculation of auto- or cross-correlation functions that increase sensitivity, but require periodic stimulations. Following individual correction for non-specific but correlated signal fluctuations, mapping of task-related coherent activation can be improved using neighborhood principles. Such refined strategies are expected to enhance the usefulness of oxygenation-sensitive MRI for studying the functional anatomy of the human brain under both physiological and pathological conditions.
梯度回波磁共振成像（MRI）对脑血氧变化的敏感性已被用于绘制功能性脑激活图。为了从各自动态MRI数据集的高空间和时间分辨率中受益，对其进行分析需要能够精确描绘与任务相关的激活模式并展示相互作用区域功能连接性的算法。在此，我们通过相关分析展示了各种数据评估策略，这些策略通过提高敏感性和稳健性超越了基于减法的激活图的质量。该方法在逐个像素的基础上，将信号时间历程与一个参考函数相关联，该参考函数反映了激活状态和对照状态的时间序列。扩展版本采用自相关或互相关函数的计算，这增加了敏感性，但需要周期性刺激。在对非特异性但相关的信号波动进行个体校正之后，可以使用邻域原理改善与任务相关的相干激活的映射。预计这种精细的策略将提高血氧敏感MRI在生理和病理条件下研究人类脑功能解剖学的有用性。
