A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techniques can alleviate this limitation via randomly undersampled acquisitions. A frequent sampling strategy is to prescribe for each acquisition a different random pattern drawn from a common sampling density. However, naive random patterns often contain gaps or clusters across the acquisition dimension that in turn can degrade reconstruction quality or reduce scan efficiency. To address this problem, a statistically-segregated sampling method is proposed for multiple-acquisition MRI. This method generates multiple patterns sequentially, while adaptively modifying the sampling density to minimize k-space overlap across patterns. As a result, it improves incoherence across acquisitions while still maintaining similar sampling density across the radial dimension of k-space. Comprehensive simulations and in vivo results are presented for phase-cycled balanced steady-state free precession and multi-echo T 2 -weighted imaging. Segregated sampling achieves significantly improved quality in both Fourier and compressedsensing reconstructions of multiple-acquisition datasets.

Multi‐contrast images are commonly acquired together to maximize complementary diagnostic information, albeit at the expense of longer scan times. A time‐efficient strategy to acquire high‐quality multi‐contrast images is to accelerate individual sequences and then reconstruct undersampled data with joint regularization terms that leverage common information across contrasts. However, these terms can cause features that are unique to a subset of contrasts to leak into the other contrasts. Such leakage‐of‐features may appear as artificial tissues, thereby misleading diagnosis. The goal of this study is to develop a compressive sensing method for multi‐channel multi‐contrast magnetic resonance imaging (MRI) that optimally utilizes shared information while preventing feature leakage. Joint regularization terms group sparsity and colour total variation are used to exploit common features across images while individual sparsity and total variation are also used to prevent leakage of distinct features across contrasts. The multi‐channel multi‐contrast reconstruction problem is solved via a fast algorithm based on Alternating Direction Method of Multipliers. The proposed method is compared against using only individual and only joint regularization terms in reconstruction. Comparisons were performed on single‐channel simulated and multi‐channel in‐vivo datasets in terms of reconstruction quality and neuroradiologist reader scores. The proposed method demonstrates rapid convergence and improved image quality for both simulated and in‐vivo datasets. Furthermore, while reconstructions that solely use joint regularization terms are prone to leakage‐of‐features, the proposed method reliably avoids leakage via simultaneous use of joint and individual terms, thereby holding great promise for clinical use.

Purpose: Magnetostimulation, also known as peripheral nerve stimulation (PNS), is the dominant safety constraint in magnetic resonance imaging (MRI) for the gradient magnetic fields that operate around 0.1-1 kHz, and for the homogeneous drive field in magnetic particle imaging (MPI) that operates around 10-150 kHz. Previous studies did not report correlations between anatomical measures and magnetostimulation thresholds for the gradient magnetic fields in MRI. In contrast, a strong linear correlation was shown between the thresholds and the inverse of body part size in MPI. Yet, the effects of other anatomical measures on the thresholds for the drive field remain unexplored. Here, we investigate the effects of fat percentage on magnetostimulation thresholds for kHz-range homogeneous magnetic fields such as the drive field in MPI, with the ultimate goal of predicting subject-specific thresholds based on simple anatomical measures. Methods: Human subject experiments were performed on the upper arms of 10 healthy male subjects (age: 26 AE 2 yr) to determine magnetostimulation thresholds. Experiments were repeated three times for each subject, with brief resting periods between repetitions. Using a solenoidal magnetostimulation coil, a homogeneous magnetic field at 25 kHz with 100 ms pulse duration was applied at 4-s intervals, while the subject reported stimulation via a mouse click. To determine the thresholds, individual subject responses were fitted to a cumulative distribution function modeled by a sigmoid curve. Next, anatomical images of the upper arms of the subjects were acquired on a 3 T MRI scanner. A two-point Dixon method was used to obtain separate images of water and fat tissues, from which several anatomical measures were derived: the effective outer radius of the upper arm, the effective inner radius (i.e., the muscle radius), and fat percentage. Pearson's correlation coefficient was used to assess the relationship between the threshold and anatomical measures. This statistical analysis was repeated after factoring out the expected effects of body part size. An updated model for threshold prediction is provided, where in addition to scaling in proportion with the inverse of the outer radius, the threshold has an affine dependence on fat percentage. Results: A strong linear correlation (r = 0.783, P < 0.008) was found between magnetostimulation threshold and fat percentage, and the correlation became stronger after factoring out the effects of outer radius (r = 0.839, P < 0.003). While considering body part size alone did not explain any significant variance in measured thresholds (P > 0.398), the updated model that also incorporates fat percentage yielded substantially improved threshold predictions with R 2 = 0.654 (P < 0.001). Conclusions: This work shows for the first time that fat percentage strongly correlates with magnetostimulation thresholds for kHz-range homogenous magnetic fields such as the drive field in MPI, and that the correlations get even stronger after factoring out the effects of b...

Özetçe-Popüler bir manyetik rezonans görüntüleme (MRG) teknigi olan uçuş-zamanlı MR anjiyografi sekansı, kafatası içi damarların görüntülenmesinde yaygın olarak kullanılmaktadır. Ancak akış etkisini güçlendirerek damar kontrastını artırmak için kullanılan yöntemler çekim süresinin uzamasına sebep olmaktadır. Bu çalışma, sıkıştırılmış algılama (SA) yardımıyla faz kodlama boyutlarında 2 boyutlu (2B) hızlandırma ve eko zamanını azaltmak amacıyla frekans kodlama yönünde bir boyutlu (1B) kısmi Fourier veri alımını birleştirmektedir. Bu çalışma, dışbükey kümelere izdüşüm (DKİ) metodunu 1B kısmi Fourier izdüşümlerini frekans kodlama yönünde; 2B sıkıştırılmış algılama izdüşümlerini de faz kodlama yönlerinde yaparak geriçatım işlemini uygulamaktadır. Önerilen yöntem uçuş-zamanlı MR anjiyografi görüntülerindeki çekim verimliligini artırırken damararka plan kontrastının korunmasını saglamaktadır. Anahtar Kelimeler-sıkıştırılmış algılama, uçuş-zamanlı MR anjiyografi, kısmi Fourier geriçatımı Abstract-Time-of-flight (TOF) magnetic resonance (MR) angiography is a popular tool for non-contrast-enhanced angiographic imaging of intracranial vasculature. However, strategies that lead to enhancement of inflow effects come at the expense of prolonged scan times. This study proposes a combination of two dimensional (2D) acceleration in the phase-encode dimensions via compressed sensing (CS) and one dimensional (1D) partial Fourier (PF) data acquisition in the readout dimension to reduce echo time. An improved projections-onto-convex-sets (POCS) reconstruction framework is utilized, which decomposes the problem into 1D PF projections along the readout dimension, and 2D CS projections along the phase-encode dimensions. This framework enables scan-efficient TOF MR angiography imaging to help maintain high vessel-background contrast.

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