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Clinical cerebral blood flow (CBF) maps generated through dynamic- susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging are currently cross-calibrated with PET studies. The cross-calibration is achieved by rescaling the MR CBF values so that normal white matter CBF corresponds to 22 ml/100 g/min. Examples are provided in this paper to show how this rescaling procedure changes both the clinical interpretation of CBF maps and the manner by which the performance of a given deconvolution algorithm should be assessed. (i) Singular-value decomposition-based (SVD) algorithms produce absolute CBF estimates that are inherently under-estimated for all tissue mean transit times (MTT) but, after rescaling, will generate CBF maps that are over-estimated for MTT >4.8 s. (ii) In principle, frequency-domain modelling techniques are expected to be inherently less sensitive to contrast recirculation biases than the time-domain SVD algorithms. However, it is shown that both CBF algorithms become greatly less sensitive to distortions from recirculation after clinical cross-calibration through rescaling has been performed. It is concluded that, when rescaling procedures are employed, it is relatively more important to develop deconvolution algorithms that produce CBF estimates with accuracies that vary little with MTT than to produce algorithms that provide inherently more accurate CBF estimates, but whose relative accuracy varies significantly with MTT.
Frayne et al. (2005) studied this question.