Kazan Samira M, Huber Laurentius, Flandin Guillaume, Ivanov Dimo, Bandettini Peter, Weiskopf Nikolaus
Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, U.K.
Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA.
Magn Reson Med. 2017 Sep;78(3):1168-1173. doi: 10.1002/mrm.26494. Epub 2016 Nov 9.
The statistical power of functional MRI (fMRI) group studies is significantly hampered by high intersubject spatial and magnitude variance. We recently presented a vascular autocalibration method (VasA) to account for vascularization differences between subjects and hence improve the sensitivity in group studies. Here, we validate the novel calibration method by means of direct comparisons of VasA with more established measures of baseline venous blood volume (and indirectly vascular reactivity), the M-value.
Seven healthy volunteers participated in two 7 T (T) fMRI experiments to compare M-values with VasA estimates: (i) a hypercapnia experiment to estimate voxelwise M-value maps, and (ii) an fMRI experiment using visual stimulation to estimate voxelwise VasA maps.
We show that VasA and M-value calibration maps show the same spatial profile, providing strong evidence that VasA is driven by local variations in vascular reactivity as reflected in the M-value.
The agreement of vascular reactivity maps obtained with VasA when compared with M-value maps confirms empirically the hypothesis that the VasA method is an adequate tool to account for variations in fMRI response amplitudes caused by vascular reactivity differences in healthy volunteers. VasA can therefore directly account for them and increase the statistical power of group studies. The VasA toolbox is available as a statistical parametric mapping (SPM) toolbox, facilitating its general application. Magn Reson Med, 2016. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
功能磁共振成像(fMRI)组研究的统计功效受到受试者间高空间和幅度差异的显著阻碍。我们最近提出了一种血管自动校准方法(VasA),以考虑受试者之间的血管化差异,从而提高组研究的敏感性。在此,我们通过将VasA与更成熟的基线静脉血容量测量方法(以及间接的血管反应性)即M值进行直接比较,来验证这种新的校准方法。
7名健康志愿者参与了两项7T fMRI实验,以比较M值与VasA估计值:(i)一项高碳酸血症实验,用于估计体素水平的M值图;(ii)一项使用视觉刺激的fMRI实验,用于估计体素水平的VasA图。
我们表明,VasA和M值校准图显示出相同的空间分布,有力地证明了VasA是由M值所反映的血管反应性局部变化驱动的。
与M值图相比,用VasA获得的血管反应性图的一致性从经验上证实了以下假设:VasA方法是一种合适的工具,可用于解释健康志愿者中由血管反应性差异引起的fMRI反应幅度变化。因此,VasA可以直接解释这些变化,并提高组研究的统计功效。VasA工具箱可作为一种统计参数映射(SPM)工具箱使用,便于其广泛应用。《磁共振医学》,2016年。©2016作者。《磁共振医学》由威利期刊公司代表国际磁共振医学学会出版。