Abstract
PurposeArterial spin labeling (ASL) MRI is a non‐invasive perfusion imaging technique that is inherently SNR limited, so scan protocols ideally need to be rigorously optimized to provide the most accurate measurements. A general framework is presented for optimizing ASL experiments to achieve optimal accuracy for perfusion estimates and, if required, other hemodynamic parameters, within a fixed scan time. The effectiveness of this framework is then demonstrated by optimizing the post‐labeling delays (PLDs) of a multi‐PLD pseudo‐continuous ASL experiment and validating the improvement using simulations and in vivo data.Theory and MethodsA simple framework is proposed based on the use of the Cramér‐Rao lower bound to find the protocol design which minimizes the predicted parameter estimation errors. Protocols were optimized for cerebral blood flow (CBF) accuracy or both CBF and arterial transit time (ATT) accuracy and compared to a conventional multi‐PLD protocol, with evenly spaced PLDs, and a single‐PLD protocol, using simulations and in vivo experiments in healthy volunteers.ResultsSimulations and in vivo data agreed extremely well with the predicted performance of all protocols. For the in vivo experiments, optimizing for just CBF resulted in a 48% and 15% decrease in CBF errors, relative to the reference multi‐PLD and single‐PLD protocols, respectively. Optimizing for both CBF and ATT reduced CBF errors by 37%, without a reduction in ATT accuracy, relative to the reference multi‐PLD protocol.ConclusionThe presented framework can effectively design ASL experiments to minimize measurement errors based on the requirements of the scan.
Highlights
Arterial spin labeling (ASL) is a non‐invasive MRI technique that can be used to quantify brain tissue perfusion.[1,2] Blood water entering the brain is labeled by magnetic inversion and, after a post‐labeling delay (PLD), an image is acquired
We demonstrate the effectiveness of this framework by optimizing the PLDs for a multi‐PLD pseudo‐continuous ASL15 (PCASL) experiment, using a 2D multi‐slice readout across a uniform arterial transit time (ATT) distribution appropriate for gray matter (GM) in healthy volunteers
We demonstrated the practical benefits of using this framework in the specific case of fixed label duration, multi‐PLD PCASL experiments with a 5‐slice EPI readout
Summary
Arterial spin labeling (ASL) is a non‐invasive MRI technique that can be used to quantify brain tissue perfusion.[1,2] Blood. A protocol that minimizes the CRLB at single set CBF and ATT values (locally optimal), will be a poor choice at values far from these.[18,19] A priori information of the likely range of parameter values is required to minimize the estimator variance over them. Where l is a sample of parameters from the prior distribution, and r is the number of samples In previous work, both CBF and ATT prior probability distributions were used.[11,12,13] using Equations 6 and 7, we note that φL−optimal does not depend on CBF, and φD−optimal scales with CBF, the optimal protocol generated using each optimality criterion will be identical for any value of CBF (see Supporting Information Text S2 and Supporting Information Figure S1). The optimal design will only depend on the ATT distribution, which greatly reduces the required prior knowledge and the number of calculations involved in the optimization, because a point prior may be used for CBF
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