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Elevated mean pulmonary arterial pressure (mPAP), or pulmonary hypertension (PH), is associated with vortical blood flow along the main pulmonary artery. We present and validate a method for automated detection and tracking of the PH-related vortex from magnetic resonance 4D flow data that allows estimation of mPAP.The proposed method detects the presence of a PH-related vortex in the main pulmonary artery based on geometrical properties of swirling streamlines and estimates mPAP from the PH-related vortex duration (tVisually and automatically determined tAn automated method for PH-related vortex detection and tracking from magnetic resonance 4D flow data was introduced, which demonstrated very good agreement with visual analysis and accurate estimation of elevated mPAP.

Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.

Purpose Recent developments in hardware design enable the use of fast field‐cycling (FFC) techniques in MRI to exploit the different relaxation rates at very low field strength, achieving novel contrast. The method opens new avenues for in vivo characterizations of pathologies but at the expense of longer acquisition times. To mitigate this, we propose a model‐based reconstruction method that fully exploits the high information redundancy offered by FFC methods. Methods The proposed model‐based approach uses joint spatial information from all fields by means of a Frobenius ‐ total generalized variation regularization. The algorithm was tested on brain stroke images, both simulated and acquired from FFC patients scans using an FFC spin echo sequences. The results are compared to three non‐linear least squares fits with progressively increasing complexity. Results The proposed method shows excellent abilities to remove noise while maintaining sharp image features with large signal‐to‐noise ratio gains at low‐field images, clearly outperforming the reference approach. Especially patient data show huge improvements in visual appearance over all fields. Conclusion The proposed reconstruction technique largely improves FFC image quality, further pushing this new technology toward clinical standards.

Non-selective inversion pulses find widespread use in MRI applications, where requirements on them are increasingly demanding. With the use of high and ultra-high field strength systems, robustness to

BACKGROUND Quantification of myocardial blood flow (MBF) from dynamic contrast-enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T1 values of blood and myocardium. PURPOSE To assess the impact of T1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population-averaged vs. subject-specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T1 values. STUDY TYPE Prospective. SUBJECTS Fifteen patients with chronic coronary heart disease. FIELD STRENGTH/SEQUENCE 3T; modified Look-Locker inversion recovery for T1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid-ventricular short-axis slice in systole and diastole. ASSESSMENT MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T1 values: study population-averaged blood and myocardial, subject-specific systolic and diastolic, and segmental T1 values. Myocardial segments with perfusion deficits were identified visually from DCE series. STATISTICAL TESTS The relationships between MBF parameters derived by different methods were analyzed by Bland-Altman analysis; corresponding mean values were compared by t-test. RESULTS Using subject-specific diastolic T1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population-averaged T1 (P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T1 values differed (P

Abstract. Neurofeedback allows participants to voluntarily control their own brain activity. Consequently, neurofeedback is a potential intervention tool in diverse clinical domains. Different brain signals can be fed back to the neurofeedback users, such as the hemodynamic response of the brain using functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) or electrophysiological brain signals as measured with electroencephalography (EEG). Each of these neuroscientific methods has its advantages and disadvantages. For instance, using fMRI all brain regions can be targeted, while in EEG and NIRS signals from deeper regions cannot be precisely differentiated. Hence, fMRI-based neurofeedback allows treatment of mental and physical diseases, which are associated with activation patterns in deeper brain regions. Until now, only the blood oxygen level dependent signal (BOLD) has been used as feedback signal in fMRI-based neurofeedback studies. However, we have started to develop a neurofeedback pipeline using a different fMRI signal, namely arterial spin labeling (ASL), which will be introduced in this article. ASL neurofeedback enables a direct modulation of the cerebral blood flow and, consequently, might improve rehabilitation of disorders caused by perfusion imbalance in the future.

Deep neural networks are increasingly used for neurological disease classification by MRI, but the networks9 decisions are not easily interpretable by humans. Heat mapping by deep Taylor decomposition revealed that (potentially misleading) image features even outside of the brain tissue are crucial for the classifier9s decision. We propose a regularization technique to train convolutional neural network (CNN) classifiers utilizing relevance-guided heat maps calculated online during training. The method was applied using T1-weighted MR images from 128 subjects with Alzheimer9s disease (mean age=71.9+-8.5 years) and 290 control subjects (mean age=71.3+-6.4 years). The developed relevance-guided framework achieves higher classification accuracies than conventional CNNs but more importantly, it relies on less but more relevant and physiological plausible voxels within brain tissue. Additionally, preprocessing effects from skull stripping and registration are mitigated, rendering this practically useful in deep learning neuroimaging studies. Understanding the decision mechanisms underlying CNNs, these results challenge the notion that unprocessed T1-weighted brain MR images in standard CNNs yield higher classification accuracy in Alzheimer9s disease than solely atrophy.

Objectives This feasibility study aimed to investigate the reliability of multi-factorial age estimation based on MR data of the hand, wisdom teeth and the clavicles with reduced acquisition time. Methods The raw MR data of 34 volunteers—acquired on a 3T system and using acquisition times (TA) of 3:46 min (hand), 5:29 min (clavicles) and 10:46 min (teeth)—were retrospectively undersampled applying the commercially available CAIPIRINHA technique. Automatic and radiological age estimation methods were applied to the original image data as well as undersampled data to investigate the reliability of age estimates with decreasing acquisition time. Reliability was investigated determining standard deviation (SSD) and mean (MSD) of signed differences, intra-class correlation (ICC) and by performing Bland-Altman analysis. Results Automatic age estimation generally showed very high reliability (SSD TA of 4 min). Radiological age estimation provided highly reliable results for images of the hand (ICC ≥ 0.96) and the teeth (ICC ≥ 0.79) for short acquisition times (TA = 16 s for the hand, TA = 2:21 min for the teeth), imaging data of the clavicles allowed for moderate acceleration (TA = 1:25 min, ICC ≥ 0.71). Conclusions The results demonstrate that reliable multi-factorial age estimation based on MRI of the hand, wisdom teeth and the clavicles can be performed using images acquired with a total acquisition time of 4 min.

Diagnosis of ischaemia-related sudden cardiac death in the absence of microscopic and macroscopic ischaemic lesions remains a challenge for medical examiners. Medical imaging techniques increasingly provide support in post-mortem examinations by detecting and documenting internal findings prior to autopsy. Previous studies have characterised MR relaxation times to investigate post-mortem signs of myocardial infarction in forensic cohorts. In this prospective study based on an ex situ porcine heart model, we report fundamental findings related to intramyocardial variability and temporal stability of T2 as well as the effects of permanent coronary occlusion on T2 and T2∗ relaxation in post-mortem myocardium. The ex situ porcine hearts included in this study (n= 19) were examined in two groups (Ss, n= 11 and Si, n= 8). All magnetic resonance imaging (MRI) examinations were performed ex situ, at room temperature and at 3 T. In the Ss group, T2 mapping was performed on slaughterhouse porcine hearts at different post-mortem intervals (PMI) between 7 and 26 h. Regarding the intramyocardial variability, no statistically significant differences in T2 were observed between myocardial segments (p= 0.167). Assessment of temporal stability indicated a weak negative correlation (r=− 0.21) between myocardial T2 and PMI. In the Si group, animals underwent ethanol-induced complete occlusion of the left anterior descending artery. T2 and T2∗ mapping were performed within 3 h of death. Differences between the expected ischaemic and remote regions were statistically significant for T2 (p= 0.007), however not for T2∗ (p= 0.062). Our results provide important information for future assessment of the diagnostic potential of quantitative MRI in the post-mortem detection of early acute myocardial infarction.

Background Quantification of myocardial blood flow (MBF) from dynamic contrast‐enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T1 values of blood and myocardium. Purpose To assess the impact of T1 values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population‐averaged vs. subject‐specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T1 values. Study Type Prospective. Subjects Fifteen patients with chronic coronary heart disease. Field Strength/Sequence 3T; modified Look–Locker inversion recovery for T1 mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid‐ventricular short‐axis slice in systole and diastole. Assessment MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T1 values: study population‐averaged blood and myocardial, subject‐specific systolic and diastolic, and segmental T1 values. Myocardial segments with perfusion deficits were identified visually from DCE series. Statistical Tests The relationships between MBF parameters derived by different methods were analyzed by Bland–Altman analysis; corresponding mean values were compared by t‐test. Results Using subject‐specific diastolic T1 values, global diastolic MBF was 0.61 ± 0.13 mL/(min·g). It did not differ from global MBF derived from the study population‐averaged T1 (P = 0.88), but the standard deviation of differences was large (0.07 mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62 ± 0.13 mL/(min·g)) and diastolic T1 values differed (P

Multi-Delay single-shot arterial spin labeling (ASL) imaging provides accurate cerebral blood flow (CBF) and, in addition, arterial transit time (ATT) maps but the inherent low SNR can be challenging. Especially standard fitting using non-linear least squares often fails in regions with poor SNR, resulting in noisy estimates of the quantitative maps. State-of-the-art fitting techniques improve the SNR by incorporating prior knowledge in the estimation process which typically leads to spatial blurring. To this end, we propose a new estimation method with a joint spatial total generalized variation regularization on CBF and ATT. This joint regularization approach utilizes shared spatial features across maps to enhance sharpness and simultaneously improves noise suppression in the final estimates. The proposed method is evaluated at three levels, first on synthetic phantom data including pathologies, followed by in vivo acquisitions of healthy volunteers, and finally on patient data following an ischemic stroke. The quantitative estimates are compared to two reference methods, non-linear least squares fitting and a state-of-the-art ASL quantification algorithm based on Bayesian inference. The proposed joint regularization approach outperforms the reference implementations, substantially increasing the SNR in CBF and ATT while maintaining sharpness and quantitative accuracy in the estimates., Comment: 35 pages, 20 figures, 3 tables, including supplementary material; submitted to Medical Image Analysis

Purpose Highly accelerated B 1 + -mapping based on the Bloch-Siegert shift to allow 3D acquisitions even within a brief period of a single breath-hold. Theory and methods The B 1 + dependent Bloch-Siegert phase shift is measured within a highly subsampled 3D-volume and reconstructed using a two-step variational approach, exploiting the different spatial distribution of morphology and B 1 + -field. By appropriate variable substitution the basic non-convex optimization problem is transformed in a sequential solution of two convex optimization problems with a total generalized variation (TGV) regularization for the morphology part and a smoothness constraint for the B 1 + -field. The method is evaluated on 3D in vivo data with retro- and prospective subsampling. The reconstructed B 1 + -maps are compared to a zero-padded low resolution reconstruction and a fully sampled reference. Results The reconstructed B 1 + -field maps are in high accordance to the reference for all measurements with a mean error below 1% and a maximum of about 4% for acceleration factors up to 100. The minimal error for different sampling patterns was achieved by sampling a dense region in k-space center with acquisition times of around 10-12 s for 3D-acquistions. Conclusions The proposed variational approach enables highly accelerated 3D acquisitions of Bloch-Siegert data and thus full liver coverage in a single breath hold.

In arterial spin labeling (ASL) a perfusion weighted image is achieved by subtracting a label image from a control image. This perfusion weighted image has an intrinsically low signal to noise ratio and numerous measurements are required to achieve reliable image quality, especially at higher spatial resolutions. To overcome this limitation various denoising approaches have been published using the perfusion weighted image as input for denoising. In this study we propose a new spatio-temporal filtering approach based on total generalized variation (TGV) regularization which exploits the inherent information of control and label pairs simultaneously. In this way, the temporal and spatial similarities of all images are used to jointly denoise the control and label images. To assess the effect of denoising, virtual ground truth data were produced at different SNR levels. Furthermore, high-resolution in-vivo pulsed ASL data sets were acquired and processed. The results show improved image quality, quantitative accuracy and robustness against outliers compared to seven state of the art denoising approaches.

Accurate T 2 mapping using multi-echo spin-echo is usually impaired by non-ideal refocusing due to B 1 + inhomogeneities and slice profile effects. Incomplete refocusing gives rise to stimulated echo and so called “ T 1 -mixing” and consequently a non-exponential signal decay. Here we present a time domain formula that incorporates all relaxation and pulse parameters and enables accurate and realistic modelling of the magnetization decay curve. By pulse parameters here we specifically mean the actual refocusing angle and axis, and phase angle of both the excitation and refocusing pulse. The method used for derivation comprises the so called Generating functions approach with subsequent back-transformation to the time domain. The proposed approach was validated by simulations using realistic RF pulse shapes as well as by comparison to phantom measurements. Excellent agreement between simulations and measurements underpin the validity of the presented approach. Conclusively, we here present a complete time domain formula ready to use for accurate T 2 mapping with multi-echo spin-echo sequences.

Purpose This study incorporates a gradient system imperfection model into an optimal control framework for radio frequency (RF) pulse design. Theory and Methods The joint design of minimum‐time RF and slice selective gradient shapes is posed as an optimal control problem. Hardware limitations such as maximal amplitudes for RF and slice selective gradient or its slew rate are included as hard constraints to assure practical applicability of the optimized waveforms. In order to guarantee the performance of the optimized waveform with possible gradient system disturbances such as limited system bandwidth and eddy currents, a measured gradient impulse response function (GIRF) for a specific system is integrated into the optimization. Results The method generates optimized RF and pre‐distorted slice selective gradient shapes for refocusing that are able to fully compensate the modeled imperfections of the gradient system under investigation. The results nearly regenerate the optimal results of an idealized gradient system. The numerical Bloch simulations are validated by phantom and in‐vivo experiments on 2 3T scanners. Conclusions The presented design approach demonstrates the successful correction of gradient system imperfections within an optimal control framework for RF pulse design.

Purpose To introduce new solution methods for the Bloch and Bloch-McConnell equations and compare them quantitatively to different known approaches. Theory and Methods A new exact solution per time step is derived by means of eigenvalues and generalized eigenvectors. Fast numerical solution methods based on asymmetric and symmetric operator splitting, which are already known for the Bloch equations, are extended to the Bloch-McConnell equations. Those methods are compared to other numerical methods including spin domain, one-step and multi-step methods, and matrix exponential. Error metrics are introduced based on the exact solution method, which allows to assess the accuracy of each solution method quantitatively for arbitrary example data. Results Accuracy and performance properties for nine different solution methods are analyzed and compared in extensive numerical experiments including various examples for non-selective and slice-selective MR imaging applications. The accuracy of the methods heavily varies, in particular for short relaxation times and long pulse durations. Conclusion In absence of relaxation effects, the numerical results confirm the rotation matrices approach as accurate and computationally efficient Bloch solution method. Otherwise, as well as for the Bloch-McConnell equations, symmetric operator splitting methods are recommended due to their excellent numerical accuracy paired with efficient run time.

Purpose To accelerate dynamic MR applications using infimal convolution of total generalized variation functionals (ICTGV) as spatio-temporal regularization for image reconstruction. Theory and Methods ICTGV comprises a new image prior tailored to dynamic data that achieves regularization via optimal local balancing between spatial and temporal regularity. Here it is applied for the first time to the reconstruction of dynamic MRI data. CINE and perfusion scans were investigated to study the influence of time dependent morphology and temporal contrast changes. ICTGV regularized reconstruction from subsampled MR data is formulated as a convex optimization problem. Global solutions are obtained by employing a duality based non-smooth optimization algorithm. Results The reconstruction error remains on a low level with acceleration factors up to 16 for both CINE and dynamic contrast-enhanced MRI data. The GPU implementation of the algorithm suites clinical demands by reducing reconstruction times of one dataset to less than 4 min. Conclusion ICTGV based dynamic magnetic resonance imaging reconstruction allows for vast undersampling and therefore enables for very high spatial and temporal resolutions, spatial coverage and reduced scan time. With the proposed distinction of model and regularization parameters it offers a new and robust method of flexible decomposition into components with different degrees of temporal regularity. Magn Reson Med 78:142–155, 2017. © 2016 International Society for Magnetic Resonance in Medicine

In view of a potential future use for dating hemorrhage in forensic medicine the correlation of MR relaxation parameters with time was evaluated in blood samples. A systematic relationship could be valuable for using MRI for estimating the age of hemorrhage and soft tissue hematomas particularly in clinical forensic medicine. Relaxation times T1, T2, and T2(*) of venous blood samples from 6 volunteers were measured using 3T MRI regularly up to 30 days. The time progression of the relaxation parameters was systematically analyzed and examined for possible interrelations. T2 initially decreased to a minimum, and then increased again (range 24-97ms), while T1 started with a plateau phase followed by an almost linear decrease (range 333-2153ms). T2(*) remained relatively constant during the entire investigation period. The higher the initial T2 was, the lower was its minimum, and the greater was the decrease of the associated T1. The inter- and intra-individual variability was relatively large, one reason being very likely the metabolic differences in the blood samples. The observed characteristic changes in blood samples over time measured by quantitative MR techniques add objective information in view of an estimation of the age of hemorrhage. However, in vivo studies will be needed to verify the data with respect to influencing metabolic factors.

Diagnosis of ischaemia-related sudden cardiac death in the absence of microscopic and macroscopic ischaemic lesions remains a challenge for medical examiners. Medical imaging techniques increasingly provide support in post-mortem examinations by detecting and documenting internal findings prior to autopsy. Previous studies have characterised MR relaxation times to investigate post-mortem signs of myocardial infarction in forensic cohorts. In this prospective study based on an ex situ porcine heart model, we report fundamental findings related to intramyocardial variability and temporal stability of T

Purpose In magnetic resonance elastography (MRE), a series of time-shifted images is acquired at specific phase offsets in relation to an induced mechanical excitation. To efficiently gather the set of phase offset images and to overcome limitations due to prolonged TEs and related susceptibility artifacts at low-frequency MRE, we developed an improved displacement encoding with a stimulated echoes (DENSE) method. Methods The proposed multiphase DENSE-MRE acquisition scheme allows full sampling of the wave propagation in 1 encoding direction during each TR using multiple readouts at specific phase offsets. With this approach, all phase offsets can be imaged in 1 TR without the need for whole sequence repetitions at time-shifted offsets relative to the excitation motion. We tested this technique in phantom experiments with 60 Hz and in the brain of 4 volunteers using 20-Hz harmonic excitation. Results Three-dimensional wave propagation could be acquired in 7 minutes 30 seconds. Following background phase elimination, clear wave images were obtained, showing the propagation of the waves over time. Calculated shear modulus maps of the phantom matched well to the maps obtained by conventional gradient-echo MRE. In the brain, low-frequency DENSE-MRE images were free of susceptibility-induced artifacts and the calculated maps showed a median global complex shear modulus magnitude of 0.72 kPa and phase angle of 1.03 rad across volunteers. Conclusion The proposed multiphase DENSE approach allows efficient low-frequency MRE with short TEs and is well-suited for low-frequency MRE of the human brain.

RF pulse design via optimal control is typically based on gradient and quasi-Newton approaches and therefore suffers from slow convergence. We present a flexible and highly efficient method that uses exact second-order information within a globally convergent trust-region CG-Newton method to yield an improved convergence rate. The approach is applied to the design of RF pulses for single- and simultaneous multi-slice (SMS) excitation and validated using phantom and in-vivo experiments on a 3T scanner using a modified gradient echo sequence.

Purpose: Joint design of minimum duration RF pulses and slice-selective gradient shapes for MRI via time optimal control with strict physical constraints, and its application to simultaneous multislice imaging. Theory and Methods: The minimization of the pulse duration is cast as a time optimal control problem with inequality constraints describing the refocusing quality and physical constraints. It is solved with a bilevel method, where the pulse length is minimized in the upper level, and the constraints are satisfied in the lower level. To address the inherent nonconvexity of the optimization problem, the upper level is enhanced with new heuristics for finding a near global optimizer based on a second optimization problem. Results: A large set of optimized examples shows an average temporal reduction of 87.1% for double diffusion and 74% for turbo spin echo pulses compared to power independent number of slices pulses. The optimized results are validated on a 3T scanner with phantom measurements. Conclusion: The presented design method computes minimum duration RF pulse and slice-selective gradient shapes subject to physical constraints. The shorter pulse duration can be used to decrease the effective echo time in existing echo-planar imaging or echo spacing in turbo spin echo sequences. European Research Council 668998 Accepted version

Knowledge of the lung vessel morphology in healthy subjects is necessary to improve our understanding about the functional network of the lung and to recognize pathologic deviations beyond the normal inter-subject variation. Established values of normal lung morphology have been derived from necropsy material of only very few subjects. In order to determine morphologic readouts from a large number of healthy subjects, computed tomography pulmonary angiography (CTPA) datasets, negative for pulmonary embolism, and other thoracic pathologies, were analyzed using a fully-automatic, in-house developed artery/vein separation algorithm. The number, volume, and tortuosity of the vessels in a diameter range between 2 and 10 mm were determined. Visual inspection of all datasets was used to exclude subjects with poor image quality or inadequate artery/vein separation from the analysis. Validation of the algorithm was performed manually by a radiologist on randomly selected subjects. In 123 subjects (men/women: 55/68), aged 59 ± 17 years, the median overlap between visual inspection and fully-automatic segmentation was 94.6% (69.2-99.9%). The median number of vessel segments in the ranges of 8-10, 6-8, 4-6, and 2-4 mm diameter was 9, 34, 134, and 797, respectively. Number of vessel segments divided by the subject's lung volume was 206 vessels/L with arteries and veins contributing almost equally. In women this vessel density was about 15% higher than in men. Median arterial and venous volumes were 1.52 and 1.54% of the lung volume, respectively. Tortuosity was best described with the sum-of-angles metric and was 142.1 rad/m (138.3-144.5 rad/m). In conclusion, our fully-automatic artery/vein separation algorithm provided reliable measures of pulmonary arteries and veins with respect to age and gender. There was a large variation between subjects in all readouts. No relevant dependence on age, gender, or vessel type was observed. These data may provide reference values for morphometric analysis of lung vessels.

Optimal control approaches have proved useful in designing RF pulses for large tip-angle applications. A typical challenge for optimal control design is the inclusion of constraints resulting from physiological or technical limitations that assure the realizability of the optimized pulses. In this paper, we show how to treat such inequality constraints, in particular, amplitude constraints on the B1 field, the slice-selective gradient, and its slew rate, as well as constraints on the slice profile accuracy. For the latter, a pointwise profile error and additional phase constraints are prescribed. Here, a penalization method is introduced that corresponds to a higher order tracking instead of the common quadratic tracking. The order is driven to infinity in the course of the optimization. We jointly optimize for the RF and slice-selective gradient waveform. The amplitude constraints on these control variables are treated efficiently by semismooth Newton or quasi-Newton methods. The method is flexible, adapting to many optimization goals. As an application, we reduce the power of refocusing pulses, which is important for spin echo-based applications with a short echo spacing. Here, the optimization method is tested in numerical experiments for reducing the pulse power of simultaneous multislice refocusing pulses. The results are validated by phantom and in-vivo experiments.

As the implementation of minimally invasive imaging techniques in both forensic and pathological practice increases, research in this area focuses on addressing recognised diagnostic weaknesses of current approaches. Assessment of sudden cardiac death (SCD) can be considered one such area in which post-mortem imaging still shows diagnostic weaknesses. We hypothesise that magnetic resonance imaging (MRI) with an angiographic adjunct may improve the visualisation and interpretation of cardiac pathologies in a post-mortem setting. To systematically investigate this hypothesis, selected perfusates (paraffin oil, Gadovist®;-doped physiological solution and polyethylene glycol (PEG)) were injected into the left anterior descending (LAD) artery of ex situ porcine hearts to assess the visualisation of perfusates in MRI as well as their intravascular retention over 12 h. Morphological images were acquired and quantitative T1 maps were generated from inversion recovery data. Visualisation of vascular structure and image quality were assessed using signal-to-noise and contrast-to-noise ratios. Intravascular retention was assessed both visually and statistically using a volume of interest (VOI) approach to analyse significant changes in signal intensity in and around the filled LAD artery, as well as changes in the longitudinal relaxation time (T1) in adjacent myocardium. In addition to presenting possible mechanisms explaining perfusate extravasation given the increased permeability of post-mortem vessels, the potential diagnostic consequences of this phenomenon and the importance of contrast stability and extended intravascular retention are discussed. In light of our findings and these considerations, paraffin oil emerged as the preferred perfusate for use in post-mortem MR angiography.