Purpose: Magnetic resonance imaging protocols for the assessment of quantitative information suffer from long acquisition times since multiple measurements in a parametric dimension are required. To facilitate the clinical applicability, accelerating the acquisition is of high importance. To this end, we propose a model‐based optimization framework in conjunction with undersampling 3D radial stack‐of‐stars data.Theory and Methods: High resolution 3D T₁ maps are generated from subsampled data by employing model‐based reconstruction combined with a regularization functional, coupling information from the spatial and parametric dimension, to exploit redundancies in the acquired parameter encodings and across parameter maps. To cope with the resulting non‐linear, non‐differentiable optimization problem, we propose a solution strategy based on the iteratively regularized Gauss‐Newton method. The importance of 3D‐spectral regularization is demonstrated by a comparison to 2D‐spectral regularized results. The algorithm is validated for the variable flip angle (VFA) and inversion recovery Look‐Locker (IRLL) method on numerical simulated data, MRI phantoms, and in vivo data.Results: Evaluation of the proposed method using numerical simulations and phantom scans shows excellent quantitative agreement and image quality. T₁ maps from accelerated 3D in vivo measurements, e.g. 1.8 s/slice with the VFA method, are in high accordance with fully sampled reference reconstructions.Conclusions: The proposed algorithm is able to recover T₁ maps with an isotropic resolution of 1 mm³ from highly undersampled radial data by exploiting structural similarities in the imaging volume and across parameter maps.

Infusion of high-density lipoprotein (HDL) mimetics aimed at reducing atherosclerotic burden has led to equivocal results, which may relate in part to the inability of HDL mimetics to adequately reach atherosclerotic lesions in humans. This study evaluated delivery of recombinant human apolipoprotein A-I (apoA-I) containing HDL mimetic CER-001 in carotid plaques in patients. CER-001 was radiolabeled with the long-lived positron emitter zirconium-89 ((89)Zr) to enable positron emission tomography with computed tomography (PET/CT) imaging. Eight patients with atherosclerotic carotid artery disease (>50% stenosis) received a single infusion of unlabeled CER-001 (3 mg/kg), co-administered with 10 mg of (89)Zr-labeled CER-001 (18 MBq). Serial PET/CT imaging and contrast enhanced-magnetic resonance imaging (CE-MRI) were performed to evaluate targeted delivery of CER-001. One hour after infusion, mean plasma apoA-I levels increased by 9.9 mg/dL (p = 0.026), with a concomitant relative increase in the plasma cholesterol efflux capacity of 13.8% (p < 0.001). Using serial PET/CT imaging, we showed that arterial uptake of CER-001 expressed as target-to-background ratio (TBRmax) increased significantly 24 h after infusion, and remained increased up to 48 h (TBRmax t = 10 min: 0.98; t = 24 h: 1.14 (p = 0.001); t = 48 h: 1.12 (p = 0.007)). TBRmax was higher in plaque compared with non-plaque segments (1.18 vs. 1.05; p < 0.001). Plaque TBRmax correlated with local plaque contrast enhancement (r = 0.56; p = 0.019) as assessed by CE-MRI. Infusion of HDL mimetic CER-001 increases plasma apoA-I concentration and plasma cholesterol efflux capacity. Our data support the concept that CER-001 targets plaque regions in patients, which correlates with plaque contrast enhancement. These clinical findings may also guide future nanomedicine development using HDL particles for drug delivery in atherosclerosis. Netherlands Trial Registry - NTR5178. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5178.

4D flow cardiovascular magnetic resonance (CMR) enables visualization of complex blood flow and quantification of biomarkers for vessel wall disease, such as wall shear stress (WSS). Because of the inherently long acquisition times, many efforts have been made to accelerate 4D flow acquisitions, however, no detailed analysis has been made on the effect of Cartesian compressed sensing accelerated 4D flow CMR at different undersampling rates on quantitative flow parameters and WSS. We implemented a retrospectively triggered 4D flow CMR acquisition with pseudo-spiral Cartesian k-space filling, which results in incoherent undersampling of k-t space. Additionally, this strategy leads to small jumps in k-space thereby minimizing eddy current related artifacts. The pseudo-spirals were rotated in a tiny golden-angle fashion, which provides optimal incoherence and a variable density sampling pattern with a fully sampled center. We evaluated this 4D flow protocol in a carotid flow phantom with accelerations of R = 2–20, as well as in carotids of 7 healthy subjects (27 ± 2 years, 4 male) for R = 10–30. Fully sampled 2D flow CMR served as a flow reference. Arteries were manually segmented and registered to enable voxel-wise comparisons of both velocity and WSS using a Bland-Altman analysis. Magnitude images, velocity images, and pathline reconstructions from phantom and in vivo scans were similar for all accelerations. For the phantom data, mean differences at peak systole for the entire vessel volume in comparison to R = 2 ranged from − 2.3 to − 5.3% (WSS) and − 2.4 to − 2.2% (velocity) for acceleration factors R = 4–20. For the in vivo data, mean differences for the entire vessel volume at peak systole in comparison to R = 10 were − 9.9, − 13.4, and − 16.9% (WSS) and − 8.4, − 10.8, and − 14.0% (velocity), for R = 20, 25, and 30, respectively. Compared to single slice 2D flow CMR acquisitions, peak systolic flow rates of the phantom showed no differences, whereas peak systolic flow rates in the carotid artery in vivo became increasingly underestimated with increasing acceleration. Acquisition of 4D flow CMR of the carotid arteries can be highly accelerated by pseudo-spiral k-space sampling and compressed sensing reconstruction, with consistent data quality facilitating velocity pathline reconstructions, as well as quantitative flow rate and WSS estimations. At an acceleration factor of R = 20 the underestimation of peak velocity and peak WSS was acceptable (< 10%) in comparison to an R = 10 accelerated 4D flow CMR reference scan. Peak flow rates were underestimated in comparison with 2D flow CMR and decreased systematically with higher acceleration factors.