CMRsim-A python package for cardiovascular MR simulations incorporating complex motion and flow.

PURPOSE: To present an open-source MR simulation framework that facilitates the incorporation of complex motion and flow for studying cardiovascular MR (CMR) acquisition and reconstruction. METHODS: CMRsim is a Python package that allows simulation of CMR images using dynamic digital phantoms with complex motion as input. Two simulation paradigms are available, namely, numerical and analytical solutions to the Bloch equations, using a common motion representation. Competitive simulation speeds are achieved using TensorFlow for GPU acceleration. To demonstrate the capability of the package, one introductory and two advanced CMR simulation experiments are presented. The latter showcase phase-contrast imaging of turbulent flow downstream of a stenotic section and cardiac diffusion tensor imaging on a contracting left ventricle. Additionally, extensive documentation and example resources are provided. RESULTS: The Bloch simulation with turbulent flow using approximately 1.5 million particles and a sequence duration of 710 ms for each of the seven different velocity encodings took a total of 29 min on a NVIDIA Titan RTX GPU. The results show characteristic phase contrast and magnitude modulation present in real data. The analytical simulation of cardiac diffusion tensor imaging with bulk-motion phase sensitivity took approximately 10 s per diffusion-weighted image, including preparation and loading steps. The results exhibit the expected alteration of diffusion metrics due to strain. CONCLUSION: CMRsim is the first simulation framework that allows one to feasibly incorporate complex motion, including turbulent flow, to systematically study advanced CMR acquisition and reconstruction approaches. The open-source package features modularity and transparency, facilitating maintainability and extensibility in support of reproducible research.

Ramping down a clinical 3 T scanner: a journey into MRI and MRS at 0.75 T.

OBJECT: Lower-field MR is reemerging as a viable, potentially cost-effective alternative to high-field MR, thanks to advances in hardware, sequence design, and reconstruction over the past decades. Evaluation of lower field strengths, however, is limited by the availability of lower-field systems on the market and their considerable procurement costs. In this work, we demonstrate a low-cost, temporary alternative to purchasing a dedicated lower-field MR system. MATERIALS AND METHODS: By ramping down an existing clinical 3 T MRI system to 0.75 T, proton signals can be acquired using repurposed 13C transmit/receive hardware and the multi-nuclei spectrometer interface. We describe the ramp-down procedure and necessary software and hardware changes to the system. RESULTS: Apart from presenting system characterization results, we show in vivo examples of cardiac cine imaging, abdominal two- and three-point Dixon-type water/fat separation, water/fat-separated MR Fingerprinting, and point-resolved spectroscopy. In addition, the ramp-down approach allows unique comparisons of, e.g., gradient fidelity of the same MR system operated at different field strengths using the same receive chain, gradient coils, and amplifiers. DISCUSSION: Ramping down an existing MR system may be seen as a viable alternative for lower-field MR research in groups that already own multi-nuclei hardware and can also serve as a testing platform for custom-made multi-nuclei transmit/receive coils.

Fundamentals of turbulent flow spectrum imaging.

PURPOSE: To introduce a mathematical framework and in-silico validation of turbulent flow spectrum imaging (TFSI) of stenotic flow using phase-contrast MRI, evaluate systematic errors in quantitative turbulence parameter estimation, and propose a novel method for probing the Lagrangian velocity spectra of turbulent flows. THEORY AND METHODS: The spectral response of velocity-encoding gradients is derived theoretically and linked to turbulence parameter estimation including the velocity autocorrelation function spectrum. Using a phase-contrast MRI simulation framework, the encoding properties of bipolar gradient waveforms with identical first gradient moments but different duration are investigated on turbulent flow data of defined characteristics as derived from computational fluid dynamics. Based on theoretical insights, an approach using velocity-compensated gradient waveforms is proposed to specifically probe desired ranges of the velocity autocorrelation function spectrum with increased accuracy. RESULTS: Practical velocity-encoding gradients exhibit limited encoding power of typical turbulent flow spectra, resulting in up to 50% systematic underestimation of intravoxel SD values. Depending on the turbulence level in fluids, the error due to a single encoding gradient spectral response can vary by 20%. When using tailored velocity-compensated gradients, improved quantification of the Lagrangian velocity spectrum on a voxel-by-voxel basis is achieved and used for quantitative correction of intravoxel SD values estimated with velocity-encoding gradients. CONCLUSION: To address systematic underestimation of turbulence parameters using bipolar velocity-encoding gradients in phase-contrast MRI of stenotic flows with short correlation times, tailored velocity-compensated gradients are proposed to improve quantitative mapping of turbulent blood flow characteristics.