Publications by Year: 2019

PURPOSE: To analyze the impact on image quality and motion fidelity of a motion-weighted space-time variant regularization term in compressed sensing cardiac cine MRI. METHODS: k-t SPARSE-SENSE with temporal total variation (tTV) is used as the base reconstruction algorithm. Motion in the dynamic image is estimated by means of a robust registration technique for non-rigid motion. The resulting deformation fields are used to leverage the regularization term. The results are compared with standard k-t SPARSE-SENSE with tTV regularization as well as with an improved version of this algorithm that makes use of tTV and temporal Fast Fourier Transform regularization in x-f domain. RESULTS: The proposed method with space-time variant regularization provides higher motion fidelity and image quality than the two previously reported methods. Difference images between undersampled reconstruction and fully sampled reference images show less systematic errors with the proposed approach. CONCLUSIONS: Usage of a space-time variant regularization offers reconstructions with better image quality than the state of the art approaches used for comparison.

Diffusion magnetic resonance imaging (dMRI) yields parameters sensitive to brain tissue microstructure. A structurally important aspect of this microstructure is the myelin wrapping around the axons. This paper investigated the forward problem concerning whether water exchange via the spiraling structure of the myelin can meaningfully contribute to the signal in dMRI. Monte Carlo simulations were performed in a system with intra-axonal, myelin, and extra-axonal compartments. Diffusion in the myelin was simulated as a spiral wrapping the axon, with a custom number of wraps. Exchange (or intra-axonal residence) times were analyzed for various number of wraps and axon diameters. Pulsed gradient sequences were employed to simulate the dMRI signal, which was analyzed using different methods. Diffusional kurtosis imaging analysis yielded the radial diffusivity (RD) and radial kurtosis (RK), while the two-compartment Kärger model yielded estimates the intra-axonal volume fraction ( ν ) and exchange time ( τ ). Results showed that τ was on the sub-second level for geometries with axon diameters below 1.0 μ m and less than eight wraps. Otherwise, exchange was negligible compared to typical experimental durations, with τ of seconds or longer. In situations where exchange influenced the signal, estimates of RK and ν increased with the number of wraps, while RD decreased. τ estimates from simulated signals were in agreement with predicted ones. In conclusion, exchange through spiraling myelin permits sub-second τ for small diameters and low number of wraps. Such conditions may arise in the developing brain or in neurodegenerative disease, and thus the results could aid the interpretation of dMRI studies.

Cranial radiotherapy (CRT) is a known risk factor for neurocognitive impairment in survivors of childhood acute lymphoblastic leukemia (ALL). Diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) are MRI techniques that quantify microstructural changes in brain white matter (WM) and DKI is regarded as the more sensitive of them. Our aim was to more thoroughly understand the nature of cognitive deficits after cranial radiotherapy (CRT) in adulthood after childhood ALL. Thirty-eight (21 women) ALL survivors, median age 38 (27-46) years, were investigated at median 34 years after diagnosis. All had been treated with a CRT dose of 24 Gy and with 11 years of complete hormone supplementation. DTI and DKI parameters were determined and neurocognitive tests were performed in ALL survivors and 29 matched controls. ALL survivors scored lower than controls in neurocognitive tests of vocabulary, memory, learning capacity, spatial ability, executive functions, and attention (

BACKGROUND: Brainstem-focused mechanisms supporting transcutaneous auricular VNS (taVNS) effects are not well understood, particularly in humans. We employed ultrahigh field (7T) fMRI and evaluated the influence of respiratory phase for optimal targeting, applying our respiratory-gated auricular vagal afferent nerve stimulation (RAVANS) technique. HYPOTHESIS: We proposed that targeting of nucleus tractus solitarii (NTS) and cardiovagal modulation in response to taVNS stimuli would be enhanced when stimulation is delivered during a more receptive state, i.e. exhalation. METHODS: Brainstem fMRI response to auricular taVNS (cymba conchae) was assessed for stimulation delivered during exhalation (eRAVANS) or inhalation (iRAVANS), while exhalation-gated stimulation over the greater auricular nerve (GANctrl, i.e. earlobe) was included as control. Furthermore, we evaluated cardiovagal response to stimulation by calculating instantaneous HF-HRV from cardiac data recorded during fMRI. RESULTS: Our findings demonstrated that eRAVANS evoked fMRI signal increase in ipsilateral pontomedullary junction in a cluster including purported NTS. Brainstem response to GANctrl localized a partially-overlapping cluster, more ventrolateral, consistent with spinal trigeminal nucleus. A region-of-interest analysis also found eRAVANS activation in monoaminergic source nuclei including locus coeruleus (LC, noradrenergic) and both dorsal and median raphe (serotonergic) nuclei. Response to eRAVANS was significantly greater than iRAVANS for all nuclei, and greater than GANctrl in LC and raphe nuclei. Furthermore, eRAVANS, but not iRAVANS, enhanced cardiovagal modulation, confirming enhanced eRAVANS response on both central and peripheral neurophysiological levels. CONCLUSION: 7T fMRI localized brainstem response to taVNS, linked such response with autonomic outflow, and demonstrated that taVNS applied during exhalation enhanced NTS targeting.

Progress in neurodevelopmental brain research has been achieved through the use of animal models. Such models not only help understanding biological changes that govern brain development, maturation and aging, but are also essential for identifying possible mechanisms of neurodevelopmental and age-related chronic disorders, and to evaluate possible interventions with potential relevance to human disease. Genetic relationship of rhesus monkeys to humans makes those animals a great candidate for such models. With the typical lifespan of 25 years, they undergo cognitive maturation and aging that is similar to this observed in humans. Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking white matter brain maturation and aging. While lifespan trajectories of white matter changes have been mapped in humans, such knowledge is not available for nonhuman primates. Here, we analyze and model lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys. We report quantitative parameters (including slopes and peaks) of lifespan trajectories for 8 individual white matter tracts. We show different trajectories for cellular and extracellular microstructural imaging components that are associated with white matter maturation and aging, and discuss similarities and differences between those in humans and rhesus monkeys, the importance of our findings, and future directions for the field. Significance Statement: Quantitative structural neuroimaging has been proposed as one of the candidate in vivo biomarkers for tracking brain maturation and aging. While lifespan trajectories of structural white matter changes have been mapped in humans, such knowledge is not available for rhesus monkeys. We present here results of the analysis and modeling of the lifespan trajectories of white matter microstructure using in vivo diffusion imaging in a sample of 44 rhesus monkeys (age 4-27). We report and anatomically map lifespan changes related to cellular and extracellular microstructural components that are associated with white matter maturation and aging.

Lung vessel segmentation has been widely explored by the biomedical image processing community; however, the differentiation of arterial from venous irrigation is still a challenge. Pulmonary artery-vein (AV) segmentation using computed tomography (CT) is growing in importance owing to its undeniable utility in multiple cardiopulmonary pathological states, especially those implying vascular remodelling, allowing the study of both flow systems separately. We present a new framework to approach the separation of tree-like structures using local information and a specifically designed graph-cut methodology that ensures connectivity as well as the spatial and directional consistency of the derived subtrees. This framework has been applied to the pulmonary AV classification using a random forest (RF) pre-classifier to exploit the local anatomical differences of arteries and veins. The evaluation of the system was performed using 192 bronchopulmonary segment phantoms, 48 anthropomorphic pulmonary CT phantoms, and 26 lungs from noncontrast CT images with precise voxel-based reference standards obtained by manually labelling the vessel trees. The experiments reveal a relevant improvement in the accuracy ( \~ 20%) of the vessel particle classification with the proposed framework with respect to using only the pre-classification based on local information applied to the whole area of the lung under study. The results demonstrated the accurate differentiation between arteries and veins in both clinical and synthetic cases, specifically when the image quality can guarantee a good airway segmentation, which opens a huge range of possibilities in the clinical study of cardiopulmonary diseases.

Research on age-related memory alterations traditionally targets individuals aged >=65 years. However, recent studies emphasize the importance of early aging processes. We therefore aimed to characterize variation in brain gray matter structure in early midlife as a function of sex and menopausal status. Subjects included 94 women (33 premenopausal, 29 perimenopausal, and 32 postmenopausal) and 99 demographically comparable men from the New England Family Study. Subjects were scanned with a high-resolution T1 sequence on a 3 T whole body scanner. Sex and reproductive-dependent structural differences were evaluated using Box’s M test and analysis of covariances (ANCOVAs) for gray matter volumes. Brain regions of interest included dorsolateral prefrontal cortex (DLPFC), inferior parietal lobule (iPAR), anterior cingulate cortex (ACC), hippocampus (HIPP), and parahippocampus. While we observed expected significant sex differences in volume of hippocampus with women of all groups having higher volumes than men relative to cerebrum size, we also found significant differences in the covariance matrices of perimenopausal women compared with postmenopausal women. Associations between ACC and HIPP/iPAR/DLPFC were higher in postmenopausal women and correlated with better memory performance. Findings in this study underscore the importance of sex and reproductive status in early midlife for understanding memory function with aging.

Conventional diffusion MRI yields voxel-averaged parameters that suffer from ambiguities for heterogeneous anisotropic materials such as brain tissue. Using principles from solid-state NMR spectroscopy, we have previously introduced the shape of the diffusion encoding tensor as a separate acquisition dimension that disentangles isotropic and anisotropic contributions to the observed diffusivities, thereby allowing for unconstrained data inversion into diffusion tensor distributions with "size," "shape," and orientation dimensions. Here we combine our recent non-parametric data inversion algorithm and data acquisition protocol with an imaging pulse sequence to demonstrate spatial mapping of diffusion tensor distributions using a previously developed composite phantom with multiple isotropic and anisotropic components. We propose a compact format for visualizing two-dimensional arrays of the distributions, new scalar parameters quantifying intra-voxel heterogeneity, and a binning procedure giving maps of all relevant parameters for each of the components resolved in the multidimensional distribution space.