MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA.
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA.
Neuroimage. 2011 Jul 1;57(1):182-189. doi: 10.1016/j.neuroimage.2011.03.060. Epub 2011 Apr 8.
If local arterial input function (AIF) could be identified, we present a theoretical approach to generate a correction factor based on local AIF for the estimation of relative cerebral blood flow (rCBF) under the framework of early time points perfusion imaging (ET). If C(t), the contrast agent bolus concentration signal time course, is used for rCBF estimation in ET, the correction factor for C(t) is the integral of its local AIF. The recipe to apply the correction factor is to divide C(t) by the integral of its local AIF to obtain the correct rCBF. By similar analysis, the correction factor for the maximum derivative (MD1) of C(t) is the maximum signal of AIF and the correction factor for the maximum second derivative (MD2) of C(t) is the maximum derivative of AIF. In the specific case of using normalized gamma-variate function as a model for AIF, the correction factor for C(t) (but not for MD1) at the time to reach the maximum derivative is relatively insensitive to the shape of the local AIF.
如果能确定局部动脉输入函数 (AIF)，我们提出了一种理论方法，以便在早期时间点灌注成像 (ET) 的框架下，基于局部 AIF 生成相对脑血流 (rCBF) 的校正因子。如果在 ET 中使用对比剂浓度信号时间曲线 C(t) 来估计 rCBF，则 C(t) 的校正因子是其局部 AIF 的积分。应用校正因子的方法是将 C(t) 除以其局部 AIF 的积分，以获得正确的 rCBF。类似地，C(t) 的最大导数 (MD1) 的校正因子是 AIF 的最大信号，C(t) 的最大二阶导数 (MD2) 的校正因子是 AIF 的最大导数。在使用归一化伽马变量函数作为 AIF 模型的具体情况下，在达到最大导数的时间，C(t) 的校正因子（而不是 MD1 的校正因子）对局部 AIF 的形状相对不敏感。
