Reference-based Cbf Index of Maximum Upslope without Using Arterial Input Function in Dynamic Susceptibility Contrast Mri: Comparison with Deconvolution Method

Introduction Accurate measurements of arterial input function (AIF) are indispensable for quantification of perfusion parameters such as MTT, CBV and CBF based on the indicator dilution theory in perfusion imaging using vascular contrast materials. Quantification of cerebral perfusion using deconvolution methods with DSC-MRI has been reported on [1-2]. However, accurately measuring AIF in DSC-MRI is difficult due to non-linearity and the limited dynamic range between ΔR2* and the concentration of contrast media. Relative perfusion parameters without measuring AIF have been widely employed [3]. We have presented that the reference–based CBF, named CBFratio, using maximum upslope (US) of tissue time-intensity curve [4] without AIF was practical because errors were insignificant compared to the other non-AIF based CBF indexes [5,6], and transit delay time errors could be neglected even in the stroke patients [5]. The purpose of this study was to assess errors in the CBFratios obtained using US and block-circulant SVD (cSVD) [7], by using numerical simulation with adding noise, and to assess clinical results. Methods The ideal quantification of DSC-MRI data is analyzed based on the following Indicator dilution theory: (1) where Ca(t) and C(t) are respectively AIF and time intensity curve for tissue, Ka is a scaling factor depending on hematocrit difference between capillaries and large vessels, AIF is an arterial input function, and R(t) is a residue function R(t). Almost the same simulation design as Wu’s study [7] was used. AIF was modeled by a gamma-variate function: otherwise t b t k t C a a : 0 , 0 : ] / exp[ ) ( = ≥ − = (2) of a=3 and b=1.5 (peak time=4.5 s). C(t) was