High-resolution, respiratory-resolved coronary MRA using a Phyllotaxis-reordered variable-density 3D cones trajectory.

PURPOSE: To develop a respiratory-resolved motion-compensation method for free-breathing, high-resolution coronary magnetic resonance angiography (CMRA) using a 3D cones trajectory. METHODS: To achieve respiratory-resolved 0.98 mm resolution images in a clinically relevant scan time, we undersample the imaging data with a variable-density 3D cones trajectory. For retrospective motion compensation, translational estimates from 3D image-based navigators (3D iNAVs) are used to bin the imaging data into four phases from end-expiration to end-inspiration. To ensure pseudo-random undersampling within each respiratory phase, we devise a phyllotaxis readout ordering scheme mindful of eddy current artifacts in steady state free precession imaging. Following binning, residual 3D translational motion within each phase is computed using the 3D iNAVs and corrected for in the imaging data. The noise-like aliasing characteristic of the combined phyllotaxis and cones sampling pattern is leveraged in a compressed sensing reconstruction with spatial and temporal regularization to reduce aliasing in each of the respiratory phases. RESULTS: In initial studies of six subjects, respiratory motion compensation using the proposed method yields improved image quality compared to non-respiratory-resolved approaches with no motion correction and with 3D translational correction. Qualitative assessment by two cardiologists and quantitative evaluation with the image edge profile acutance metric indicate the superior sharpness of coronary segments reconstructed with the proposed method (P < 0.01). CONCLUSION: We have demonstrated a new method for free-breathing, high-resolution CMRA based on a variable-density 3D cones trajectory with modified phyllotaxis ordering and respiratory-resolved motion compensation with 3D iNAVs.

Reconstruction of undersampled 3D non-Cartesian image-based navigators for coronary MRA using an unrolled deep learning model.

PURPOSE: To rapidly reconstruct undersampled 3D non-Cartesian image-based navigators (iNAVs) using an unrolled deep learning (DL) model, enabling nonrigid motion correction in coronary magnetic resonance angiography (CMRA). METHODS: An end-to-end unrolled network is trained to reconstruct beat-to-beat 3D iNAVs acquired during a CMRA sequence. The unrolled model incorporates a nonuniform FFT operator in TensorFlow to perform the data-consistency operation, and the regularization term is learned by a convolutional neural network (CNN) based on the proximal gradient descent algorithm. The training set includes 6,000 3D iNAVs acquired from 7 different subjects and 11 scans using a variable-density (VD) cones trajectory. For testing, 3D iNAVs from 4 additional subjects are reconstructed using the unrolled model. To validate reconstruction accuracy, global and localized motion estimates from DL model-based 3D iNAVs are compared with those extracted from 3D iNAVs reconstructed with l1 -ESPIRiT. Then, the high-resolution coronary MRA images motion corrected with autofocusing using the l1 -ESPIRiT and DL model-based 3D iNAVs are assessed for differences. RESULTS: 3D iNAVs reconstructed using the DL model-based approach and conventional l1 -ESPIRiT generate similar global and localized motion estimates and provide equivalent coronary image quality. Reconstruction with the unrolled network completes in a fraction of the time compared to CPU and GPU implementations of l1 -ESPIRiT (20× and 3× speed increases, respectively). CONCLUSIONS: We have developed a deep neural network architecture to reconstruct undersampled 3D non-Cartesian VD cones iNAVs. Our approach decreases reconstruction time for 3D iNAVs, while preserving the accuracy of nonrigid motion information offered by them for correction.

CFD assessment of the effect of convective mass transport on the intracellular clearance of intracellular triglycerides in macrosteatotic hepatocytes.

Donor livers available to transplant for patients with end-stage liver disease are in severe shortage. One possible avenue to expand the donor pool is to recondition livers that would be otherwise discarded due to excessive fat content. Severely steatotic livers (also known as fatty livers) are highly susceptible to ischemia-reperfusion injury and as a result, primary liver non-function post-transplantation. Prior studies in isolated perfused rat livers suggest that "defatting" may be possible in a timeframe of a few hours; thus, it is conceivable that fatty liver grafts could be recovered by machine perfusion to clear stored fat from the organ prior to transplantation. However, studies using hepatoma cells and adult hepatocytes made fatty in culture report that defatting may take several days. Because cell culture studies were done in static conditions, we hypothesized that the defatting kinetics are highly sensitive to flow-mediated transport of metabolites. To investigate this question, we experimentally evaluated the effect of increasing flow rate on the defatting kinetics of cultured HepG2 cells and developed an in silico combined reaction-transport model to identify possible rate-limiting steps in the defatting process. We found that in cultured fatty HepG2 cells, the time required to clear stored fat down to lean control cells can be reduced from 48 to 4-6 h by switching from static to flow conditions. The flow required resulted in a fluid shear of .008 Pa, which did not adversely affect hepatic function. The reaction-transport model suggests that the transport of L-carnitine, which is the carrier responsible for taking free fatty acids into the mitochondria, is the key rate-limiting process in defatting that was modulated by flow. Therefore, we can ensure higher levels of L-carnitine uptake by the cells by choosing flow rates that minimize the limiting mass transport while minimizing shear stress.

Metabolic Flux Distribution during Defatting of Steatotic Human Hepatoma (HepG2) Cells.

Methods that rapidly decrease fat in steatotic hepatocytes may be helpful to recover severely fatty livers for transplantation. Defatting kinetics are highly dependent upon the extracellular medium composition; however, the pathways involved are poorly understood. Steatosis was induced in human hepatoma cells (HepG2) by exposure to high levels of free fatty acids, followed by defatting using plain medium containing no fatty acids, or medium supplemented with a cocktail of defatting agents previously described before. We measured the levels of 28 extracellular metabolites and intracellular triglyceride, and fed the data into a steady-state mass balance model to estimate strictly intracellular fluxes. We found that during defatting, triglyceride content decreased, while beta-oxidation, the tricarboxylic acid cycle, and the urea cycle increased. These fluxes were augmented by defatting agents, and even more so by hyperoxic conditions. In all defatting conditions, the rate of extracellular glucose uptake/release was very small compared to the internal supply from glycogenolysis, and glycolysis remained highly active. Thus, in steatotic HepG2 cells, glycolysis and fatty acid oxidation may co-exist. Together, these pathways generate reducing equivalents that are supplied to mitochondrial oxidative phosphorylation.