Abstract
The FiTT analysis procedure was as follows: First, the TEC of the arterial input function (AIF) was fitted to the gamma distribution function. Next, we defined the residual functions (<em>R(t)</em>s) that assume various perfusion states of brain tissue, and theoretical brain TECs were calculated by convolution of the AIF and <em>R(t)</em>s. Finally, we determined a theoretical TEC with the least error from the observed brain tissue TEC, using the theoretical TEC's perfusion parameters as the estimations for the observation point.
Highlights
Knowing the size of the ischemic core and penumbra helps determine the appropriate endovascular treatment for acute stroke [1,2]
Parametric map findings: For the academic analyzer, Tmax was affected by mean transit time (MTT); for the commercial analyzer, MTT was modulated by delay; for FiTT, cerebral blood volume (CBV) was slightly affected by MTT
The global characteristics and effect of the R(t) shape: The academic analyzer underestimated MTT, and tracer delay varied; the commercial analyzer had a positive bias for cerebral blood volume (CBV); and for FiTT, CBV and tracer delay estimated close to ground truth, cerebral blood flow (CBF) and MTT were affected by the R(t) shape
Summary
Knowing the size of the ischemic core and penumbra helps determine the appropriate endovascular treatment for acute stroke [1,2]. Int J Radiol Imaging Technol 2021, 7:077 Page 1 of 13 . Because the solution oscillates with image noise, this method requires regularization. Several methods have been proposed for determining the regularization parameters, which are constant or case-specific values for each analyzer [4,5,6]. When the size of the ischemic core or penumbra is to be measured, a threshold value must be set for each analyzer [7,8,9]. Various studies have been conducted to reduce source image noise and stabilize deconvolution [10,11,12,13,14]
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