High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results

Abstract

This report evaluates several methods to map relative cerebral blood flow (rCBF) by applying both parametric and nonparametric techniques to deconvolve high resolution dynamic MRI measurements of paramagnetic bolus passages with noninvasively determined arterial inputs. We found a nonparametric (singular value decomposition (SVD)) deconvolution technique produced the most robust results, giving mean gray:white flow ratio of 2.7 +/- 0.5 (SEM) in six normal volunteers, in excellent agreement with recent PET literature values for age-matched subjects. Similar results were obtained by using a model-dependent approach that assumes an exponential residue function, but not for a Gaussian-shaped residue function or for either Fourier or regularization-based model-independent approaches. Pilot studies of our CBF mapping techniques in patients with tumor, stroke, and migraine aura demonstrated that these techniques can be readily used on data routinely acquired by using current echo planar imaging technology. By using these techniques, the authors visualized important regional hemodynamic changes not detectable with rCBV mapping algorithms.

The impact of partial‐volume effects in dynamic susceptibility contrast magnetic resonance perfusion imaging

“…Images are typically acquired with an acquisition matrix of 192 ϫ 116, a field of view (FOV) of 32 ϫ 19 cm, and a slice thickness of 5.0 mm with interslice gaps of 2 mm, implying a voxel size of 1.7 ϫ 1.7 ϫ 5.0 mm. This voxel size is similar to those published in other studies (2,6). Depending on its orientation with respect to the imaging plane, and its location relative to the interslice gap, the ratio of the MCA arterial volume to voxel volume (the In two cases (a and b), the MCA spans across four voxels of dimensions 1.7 ϫ 1.7 ϫ 5.0 mm.…”

“…From Eq. [2], CBF is found by deconvolving c VOI (t) by c a (t) (1,(3)(4)(5). Given a tissue region of constant blood volume, CBF varies inversely with the tissue MTT, which is the average time taken for blood to flow through the tissue region.…”

“…[5], as max-[c a_artery (t)]/max[c a_PVE (t)]. Finally, to demonstrate the error level that could be expected from the absolute CBF values obtained from cross-calibration, the CBF estimates were rescaled such that the CBF ratio was equal to 1 when MTT ϭ 4.8 seconds, corresponding to normal WM, which has been described as having an age-independent CBF of 22 mL minute -1 (100 g) -1 (2). The relative effectiveness of these approaches was assessed using the CBF ratios computed from the rescaled concentration curves.…”

Dynamic MR perfusion imaging: Capability for quantitative assessment of disease extent and prediction of outcome for patients with acute pulmonary thromboembolism

“…For this study, we adopted an algebraic approach based on singular value decomposition (SVD), which is robust against statistical noise. The details of this approach have been described elsewhere (32)(33)(34). We generated the PBF maps by applying this approach pixel by pixel.…”

Dynamic perfusion MRI: Capability for evaluation of disease severity and progression of pulmonary arterial hypertension in patients with connective tissue disease

“…In this study we adopted an algebraic approach based on singular value decomposition (SVD), which is robust against statistical noise. The details of this approach have been described elsewhere (31)(32)(33). We generated the PBF maps by applying this approach pixel-by-pixel.…”