We present an isotropic diffusion MRI phantom, together with its temperature calibration curve, that is easy-to-use in a clinical environment, cost-effective, reproducible to produce, and that contains no harmful substances.

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Purpose To determine whether sacrificing part of the scan time of pseudo‐continuous arterial spin labeling (PCASL) for measurement of the labeling efficiency and blood is beneficial in terms of CBF quantification reliability. Methods In a simulation framework, 5‐minute scan protocols with different scan time divisions between PCASL data acquisition and supporting measurements were evaluated in terms of CBF estimation variability across both noise and ground truth parameter realizations taken from the general population distribution. The entire simulation experiment was repeated for a single‐post‐labeling delay (PLD), multi‐PLD, and free‐lunch time‐encoded (te‐FL) PCASL acquisition strategy. Furthermore, a real data study was designed for preliminary validation. Results For the considered population statistics, measuring the labeling efficiency and the blood proved beneficial in terms of CBF estimation variability for any distribution of the 5‐minute scan time compared to only acquiring ASL data. Compared to single‐PLD PCASL without support measurements as recommended in the consensus statement, a 26%, 33%, and 42% reduction in relative CBF estimation variability was found for optimal combinations of supporting measurements with single‐PLD, free‐lunch, and multi‐PLD PCASL data acquisition, respectively. The benefit of taking the individual variation of blood into account was also demonstrated in the real data experiment. Conclusions Spending time to measure the labeling efficiency and the blood instead of acquiring more averages of the PCASL data proves to be advisable for robust CBF quantification in the general population.

Multi-post-labeling-delay pseudo-continuous arterial spin labeling (multi-PLD PCASL) allows for absolute quantification of the cerebral blood flow (CBF) as well as the arterial transit time (ATT). Estimating these perfusion parameters from multi-PLD PCASL data is a non-linear inverse problem, which is commonly tackled by fitting the singlecompartment model (SCM) for PCASL, with CBF and ATT as free parameters. The longitudinal relaxation time of tissue T 1t is an important parameter in this model, as it governs the decay of the perfusion signal entirely upon entry in the imaging voxel. Conventionally, T 1t is fixed to a population average. This approach can cause CBF quantification errors, as T 1t can vary significantly inter-and intra-subject. This study compares the impact on CBF quantification, in terms of accuracy and precision, of either fixing T 1t , the conventional approach, or estimating it alongside CBF and ATT. It is shown that the conventional approach can cause a significant bias in CBF. Indeed, simulation experiments reveal that if T 1t is fixed to a value that is 10% off its true value, this may already result in a bias of 15% in CBF. On the other hand, as is shown by both simulation and real data experiments, estimating T 1t along with CBF and ATT results in a loss of CBF precision of the same order, even if the experiment design is optimized for the latter estimation problem. Simulation experiments suggest that an optimal balance between accuracy and precision of CBF estimation from multi-PLD PCASL data can be expected when using the two-parameter estimator with a fixed T 1t value between population averages of T 1t and the longitudinal relaxation time of blood T 1b .