Vespa: Integrated applications for RF pulse design, spectral simulation and MRS data analysis.

PURPOSE: The Vespa package (Versatile Simulation, Pulses, and Analysis) is described and demonstrated. It provides workflows for developing and optimizing linear combination modeling (LCM) fitting for 1 H MRS data using intuitive graphical user interface interfaces for RF pulse design, spectral simulation, and MRS data analysis. Command line interfaces for embedding workflows in MR manufacturer platforms and utilities for synthetic dataset creation are included. Complete provenance is maintained for all steps in workflows. THEORY AND METHODS: Vespa is written in Python for compatibility across operating systems. It embeds the PyGAMMA spectral simulation library for spectral simulation. Multiprocessing methods accelerate processing and visualization. Applications use the Vespa database for results storage and cross-application access. Three projects demonstrate pulse, sequence, simulation, and data analysis workflows: (1) short TE semi-LASER single-voxel spectroscopy (SVS) LCM fitting, (2) optimizing MEGA-PRESS (MEscher-GArwood Point RESolved Spectroscopy) flip angle and LCM fitting, and (3) creating a synthetic short TE dataset. RESULTS: The LCM workflows for in vivo basis set creation and spectral analysis showed reasonable results for both the short TE semi-LASER and MEGA-PRESS. Examples of pulses, simulations, and data fitting are shown in Vespa application interfaces for various steps to demonstrate the interactive workflow. CONCLUSION: Vespa provides an efficient and extensible platform for characterizing RF pulses, pulse design, spectral simulation optimization, and automated LCM fitting via an interactive platform. Modular design and command line interface make it easy to embed in other platforms. As open source, it is free to the MRS community for use and extension. Vespa source code and documentation are available through GitHub.

Effect of dual sintering with laser irradiation and thermal treatment on printed copper nanoparticle patterns.

The dual sintering of copper (Cu) nanoparticles (NPs) was introduced to produce conductive patterns suitable for flexible electronics applications. In this method, laser irradiation using a Nd:YAG laser with a wavelength of 1064 nm was performed at laser powers of 400, 600 and 800 mJ. The laser irradiation time was 15 and 30 s for each laser power. After laser irradiation, all of the Cu NP patterns were thermally sintered under formic acid vapors. The temperature and time for thermal treatment were selected as 260 °C and 15 min, respectively. The resultant physical, chemical, electrical and mechanical properties were evaluated and compared considering the six different dual sintering conditions. The Cu NP patterns sintered using 800 mJ for 30 s showed increased necking and coalescence compared to the other patterns and featured a microstructure with increased density. Despite being oxidized, the Cu NP patterns sintered with 800 mJ for 30 s showed the lowest electrical resistivity of 11.25µΩ cm. The surface of every sintered Cu pattern was oxidized, and mechanical hardness increased with increasing laser power. The Cu NP pattern sintered with 800 mJ for 30 s demonstrated the highest hardness of 48.64 N mm-2. After sintering using the six different conditions, the Cu NP patterns exhibited a weight loss of 0.02-3.87 wt%, and their roughness varied in the range of 26.15-74.08 nm. This can be attributed to the effective removal of organic residues and the degree of particle agglomeration. After performing folding tests up to 50 cycles, Cu NP patterns showed an upward trend in resistance with increasing laser power and time. The highest and lowest resistance ratios were observed as 3.97 and 17.24 for the patterns sintered at 400 mJ for 15 s and 800 mJ for 30 s, respectively.

Quantitative framework for prospective motion correction evaluation.

PURPOSE: Establishing a framework to evaluate performances of prospective motion correction (PMC) MRI considering motion variability between MRI scans. METHODS: A framework was developed to obtain quantitative comparisons between different motion correction setups, considering that varying intrinsic motion patterns between acquisitions can induce bias. Intrinsic motion was considered by replaying in a phantom experiment the recorded motion trajectories from subjects. T1-weighted MRI on five volunteers and two different marker fixations (mouth guard and nose bridge fixations) were used to test the framework. Two metrics were investigated to quantify the improvement of the image quality with PMC. RESULTS: Motion patterns vary between subjects as well as between repeated scans within a subject. This variability can be approximated by replaying the motion in a distinct phantom experiment and used as a covariate in models comparing motion corrections. We show that considering the intrinsic motion alters the statistical significance in comparing marker fixations. As an example, two marker fixations, a mouth guard and a nose bridge, were evaluated in terms of their effectiveness for PMC. A mouth guard achieved better PMC performance. CONCLUSION: Intrinsic motion patterns can bias comparisons between PMC configurations and must be considered for robust evaluations. A framework for evaluating intrinsic motion patterns in PMC is presented.

Millimeter-wave broadband antireflection coatings using laser ablation of subwavelength structures.

We report on the first use of laser ablation to make submillimeter, broadband, antireflection coatings (ARCs) based on subwavelength structures (SWSs) on alumina and sapphire. We used a 515 nm laser to produce pyramid-shaped structures with a pitch of about 320 µm and a total height of near 800 µm. Transmission measurements between 70 and 140 GHz are in agreement with simulations using electromagnetic propagation software. The simulations indicate that SWS-ARCs with the fabricated shape should have a fractional bandwidth response of Δν/νcenter=0.55 centered on 235 GHz for which reflections are below 3%. Extension of the bandwidth to both lower and higher frequencies, between a few tens of gigahertz and a few terahertz, should be straightforward with appropriate adjustment of laser ablation parameters.

A two-level multimodality imaging Bayesian network approach for classification of partial epilepsy: preliminary data.

BACKGROUND: Quantitative neuroimaging analyses have demonstrated gray and white matter abnormalities in group comparisons of different types of non-lesional partial epilepsy. It is unknown to what degree these type-specific patterns exist in individual patients and if they could be exploited for diagnostic purposes. In this study, a two-level multi-modality imaging Bayesian network approach is proposed that uses information about individual gray matter volume loss and white matter integrity to classify non-lesional temporal lobe epilepsy with (TLE-MTS) and without (TLE-no) mesial-temporal sclerosis and frontal lobe epilepsy (FLE). METHODS: 25 controls, 19 TLE-MTS, 22 TLE-no and 14 FLE were studied on a 4T MRI and T1 weighted structural and DTI images acquired. Spatially normalized gray matter (GM) and fractional anisotropy (FA) abnormality maps (binary maps with voxels 1 SD below control mean) were calculated for each subject. At the first level, each group's abnormality maps were compared with those from all the other groups using Graphical-Model-based Morphometric Analysis (GAMMA). GAMMA uses a Bayesian network and a Markov random field based contextual clustering method to produce maps of voxels that provide the maximal distinction between two groups and calculates a probability distribution and a group assignment based on this information. The information was then combined in a second level Bayesian network and the probability of each subject to belong to one of the three epilepsy types calculated. RESULTS: The specificities of the two level Bayesian network to distinguish between the three patient groups were 0.87 for TLE-MTS and TLE-no and 0.86 for FLE, the corresponding sensitivities were 0.84 for TLE-MTS, 0.72 for TLE-no and 0.64 for FLE. CONCLUSION: The two-level multi-modality Bayesian network approach was able to distinguish between the three epilepsy types with a reasonably high accuracy even though the majority of the images were completely normal on visual inspection.

Cardiogenic Shock From Heart Failure Versus Acute Myocardial Infarction: Clinical Characteristics, Hospital Course, and 1-Year Outcomes.

BACKGROUND: Little is known about clinical characteristics, hospital course, and longitudinal outcomes of patients with cardiogenic shock (CS) related to heart failure (HF-CS) compared to acute myocardial infarction (AMI; CS related to AMI [AMI-CS]). METHODS: We examined in-hospital and 1-year outcomes of 520 (219 AMI-CS, 301 HF-CS) consecutive patients with CS (January 3, 2017-December 31, 2019) in a single-center registry. RESULTS: Mean age was 61.5±13.5 years, 71% were male, 22% were Black patients, and 63% had chronic kidney disease. The HF-CS cohort was younger (58.5 versus 65.6 years, P<0.001), had fewer cardiac arrests (15.9% versus 35.2%, P<0.001), less vasopressor utilization (61.8% versus 82.2%, P<0.001), higher pulmonary artery pulsatility index (2.14 versus 1.51, P<0.01), lower cardiac power output (0.64 versus 0.77 W, P<0.01) and higher pulmonary capillary wedge pressure (25.4 versus 22.2 mm Hg, P<0.001) than patients with AMI-CS. Patients with HF-CS received less temporary mechanical circulatory support (34.9% versus 76.3% P<0.001) and experienced lower rates of major bleeding (17.3% versus 26.0%, P=0.02) and in-hospital mortality (23.9% versus 39.3%, P<0.001). Postdischarge, 133 AMI-CS and 229 patients with HF-CS experienced similar rates of 30-day readmission (19.5% versus 24.5%, P=0.30) and major adverse cardiac and cerebrovascular events (23.3% versus 28.8%, P=0.45). Patients with HF-CS had lower 1-year mortality (n=123, 42.6%) compared to the patients with AMI-CS (n=110, 52.9%, P=0.03). Cumulative 1-year mortality was also lower in patients with HF-CS (log-rank test, P=0.04). CONCLUSIONS: Patients with HF-CS were younger, and despite lower cardiac power output and higher pulmonary capillary wedge pressure, less likely to receive vasopressors or temporary mechanical circulatory support. Although patients with HF-CS had lower in-hospital and 1-year mortality, both cohorts experienced similarly high rates of postdischarge major adverse cardiovascular and cerebrovascular events and 30-day readmission, highlighting that both cohorts warrant careful long-term follow-up. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03378739.

A Standardized and Regionalized Network of Care for Cardiogenic Shock.

BACKGROUND: The benefits of standardized care for cardiogenic shock (CS) across regional care networks are poorly understood. OBJECTIVES: The authors compared the management and outcomes of CS patients initially presenting to hub versus spoke hospitals within a regional care network. METHODS: The authors stratified consecutive patients enrolled in their CS registry (January 2017 to December 2019) by presentation to a spoke versus the hub hospital. The primary endpoint was 30-day mortality. Secondary endpoints included bleeding, stroke, or major adverse cardiovascular and cerebrovascular events. RESULTS: Of 520 CS patients, 286 (55%) initially presented to 34 spoke hospitals. No difference in mean age (62 years vs 61 years; P = 0.38), sex (25% vs 32% women; P = 0.10), and race (54% vs 52% white; P = 0.82) between spoke and hub patients was noted. Spoke patients more often presented with acute myocardial infarction (50% vs 32%; P < 0.01), received vasopressors (74% vs 66%; P = 0.04), and intra-aortic balloon pumps (88% vs 37%; P < 0.01). Hub patients were more often supported with percutaneous ventricular assist devices (44% vs 11%; P < 0.01) and veno-arterial extracorporeal membrane oxygenation (13% vs 0%; P < 0.01). Initial presentation to a spoke was not associated with increased risk-adjusted 30-day mortality (adjusted OR: 0.87 [95% CI: 0.49-1.55]; P = 0.64), bleeding (adjusted OR: 0.89 [95% CI: 0.49-1.62]; P = 0.70), stroke (adjusted OR: 0.74 [95% CI: 0.31-1.75]; P = 0.49), or major adverse cardiovascular and cerebrovascular events (adjusted OR 0.83 [95% CI: 0.50-1.35]; P = 0.44). CONCLUSIONS: Spoke and hub patients experienced similar short-term outcomes within a regionalized CS network. The optimal strategy to promote standardized care and improved outcomes across regional CS networks merits further investigation.

Multivariate statistical mapping of spectroscopic imaging data.

For magnetic resonance spectroscopic imaging studies of the brain, it is important to measure the distribution of metabolites in a regionally unbiased way; that is, without restrictions to a priori defined regions of interest. Since magnetic resonance spectroscopic imaging provides measures of multiple metabolites simultaneously at each voxel, there is furthermore great interest in utilizing the multidimensional nature of magnetic resonance spectroscopic imaging for gains in statistical power. Voxelwise multivariate statistical mapping is expected to address both of these issues, but it has not been previously employed for spectroscopic imaging (SI) studies of brain. The aims of this study were to (1) develop and validate multivariate voxel-based statistical mapping for magnetic resonance spectroscopic imaging and (2) demonstrate that multivariate tests can be more powerful than univariate tests in identifying patterns of altered brain metabolism. Specifically, we compared multivariate to univariate tests in identifying known regional patterns in simulated data and regional patterns of metabolite alterations due to amyotrophic lateral sclerosis, a devastating brain disease of the motor neurons.

Improved pseudo-continuous arterial spin labeling for mapping brain perfusion.

PURPOSE: To investigate arterial spin labeling (ASL) methods for improved brain perfusion mapping. Previously, pseudo-continuous ASL (pCASL) was developed to overcome limitations inherent with conventional continuous ASL (CASL), but the control scan (null pulse) in the original method for pCASL perturbs the equilibrium magnetization, diminishing the ASL signal. Here, a new modification of pCASL, termed mpCASL is reported, in which the perturbation caused by the null pulse is reduced and perfusion mapping improved. MATERIALS AND METHODS: improvements with mpCASL are demonstrated using numerical simulations and experiments. ASL signal intensity as well as contrast and reproducibility of in vivo brain perfusion images were measured in four volunteers who had MRI scans at 4 Tesla and the data compared across the labeling methods. RESULTS: Perfusion maps with mpCASL showed, on average, higher ASL signal intensity and higher image contrast than those from CASL or pCASL. Furthermore, mpCASL yielded better reproducibility in repeat scans than the other methods. CONCLUSION: The experimental results are consistent with the hypothesis that the new null pulse of mpCASL leads to improved brain perfusion images.

K-Bayes reconstruction for perfusion MRI II: modeling and technical development.

Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. Here, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study, described in Part I (Concepts and Applications), was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT.

K-Bayes reconstruction for perfusion MRI. I: concepts and application.

Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities, such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. In this study, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach (described in detail in Part II: Modeling and Technical Development) combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT.

Patterns of structural complexity in Alzheimer's disease and frontotemporal dementia.

The goal of this project was to utilize an information theoretic formalism for medical image analysis initially proposed in [Young et al. (2005): Phys Rev Lett 94:098701-1] to detect and quantify subtle global and regional differences in spatial patterns in patients suffering from Alzheimer's disease (AD) and frontotemporal dementia (FTD) by estimating the structural complexity of anatomical brain MRI. The sensitivity and specificity of the results are compared with those of a recent analysis, currently considered state of the art for MR studies of neurodegeneration. The previous study used regional estimates of cortical thinning and/or volume loss to differentiate between normal aging, AD, and FTD. The analysis illustrates that the structural complexity estimation method, a general multivariate approach to the study of variation in brain structure which does not depend on highly specialized volumetric and thickness estimates, is capable of providing sensitive and interpretable diagnostic information.

Comparison of the USCOM ultrasound cardiac output monitor with pulmonary artery catheter thermodilution in patients undergoing liver transplantation.

The aim of the study was to compare the standard technique of cardiac output determination by pulmonary artery catheter thermodilution (PAC-TD) with a noninvasive ultrasound Doppler monitor (USCOM Pty., Ltd., Coffs Harbour, Australia) in surgery for liver transplantation. We wished to determine if the degree of accuracy would allow the ultrasound cardiac output monitor (USCOM) to be used as an alternative monitor in a clinical setting in which wide fluctuations in cardiac output could be expected. This was a prospective method comparison study, with 71 paired measurements obtained in 12 patients undergoing liver transplantation in a university teaching hospital. Bland-Altman analysis of the 2 techniques showed a bias of 0.39 L/minute, with the USCOM cardiac output lower compared with that of PAC-TD. The bias was small and did not vary with the magnitude of the cardiac output. The 95% limits of agreement were -1.47 and 2.25 L/minute. There was good repeatability for USCOM measurements, with a repeatability coefficient of 0.43 for USCOM versus 0.77 for PAC-TD. We conclude that USCOM is acceptable for the clinical determination of noninvasive cardiac output, particularly in situations in which tracking changes over time is more important than knowing the precise value. However, the utility of USCOM is limited by its inability to measure pulmonary artery pressure.

GAVA: spectral simulation for in vivo MRS applications.

An application that provides a flexible and easy to use interface to the GAMMA spectral simulation package is described that is targeted at investigations using in vivo MR spectroscopic methods. The program makes available a number of widely used spatially localized MRS pulse sequences and NMR parameters for commonly observed tissue metabolites, enabling spectra to be simulated for any pulse sequence parameter and viewed in an integrated display. The application is interfaced with a database for storage of all simulation parameters and results of the simulations. This application provides a convenient method for generating a priori spectral information used in parametric spectral analyses and for visual examination of the effects of difference pulse sequences and parameter settings.

Complication of venovenous extracorporeal membrane oxygenation cannulation - the significance of an inferior vena cava anomaly.

Physicians should be aware of possible anatomical variants during cannulation for extracorporeal membrane oxygenation (ECMO). Particular attention to ensure continual visualization of the guidewire before proceeding to final positioning of the ECMO cannulae should be paid. Alternative imaging modalities should be contemplated when uncertainties arise to minimize the risk of inadvertent vascular injuries.

Numerical simulation of PRESS localized MR spectroscopy.

Numerical simulations of NMR spectra can provide a rapid and convenient method for optimizing acquisition sequence parameters and generating prior spectral information required for parametric spectral analysis. For spatially resolved spectroscopy, spatially dependent variables affect the resultant spectral amplitudes and phases, which must therefore be taken into account in any spectral simulation model. In this study, methods for numerical simulation of spectra obtained using the PRESS localization pulse sequence are examined. A comparison is made between three different simulation models that include different levels of detail regarding the spatial distributions of the excitation functions, and spin evolution during application of the pulses. These methods were evaluated for measurement of spectra from J-coupled spin systems that are of interest for in vivo proton spectroscopy and results compared with experimental data. It is demonstrated that for optimized refocusing pulses it is sufficient to account for chemical shift effects only, although there is some advantage to implementing a more general numerical simulation approach that includes information on RF pulse excitation profiles, which provides sufficient accuracy while maintaining moderate computational requirements and flexibility to handle different spin systems.