Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors

High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber configurations at high spatio-angular resolution relying on a 3D kq-space under-sampling scheme to enable accelerated acquisitions. The inverse problem for the reconstruction of the fiber orientation distribution (FOD) is regularized by a structured sparsity prior promoting simultaneously voxel-wise sparsity and spatial smoothness of fiber orientation. Prior knowledge of the spatial distribution of white matter, gray matter, and cerebrospinal fluid is also leveraged. A minimization problem is formulated and solved via a stochastic forward–backward algorithm. Simulations and real data analysis suggest that accurate FOD mapping can be achieved from severe kq-space under-sampling regimes potentially enabling high spatio-angular resolution dMRI in the clinical setting.

MICROSTRUCTURAL CORRELATIONS IN SHORT-ALIGNED GLASS FIBER COMPOSITES

Research shows that in unidirectional composites, fiber breaks and clusters of fiber breaks play a role in the failure onset of the composites [1]. So far, we know no attempts to the date have been made to analyze the fiber break development in short-aligned fiber composites, specifically using E-glass HYBON 2026. O[1]ur challenge is to determine whether there is a similar behavior in aligned short composites and its relationship with the microstructural parameter of fiber orientation distribution. This is important as it is measurable parameter to add value to recycled fiber composites. The more aligned the composite the higher mechanical properties and the higher the added value for recycling. We focused on using synchrotron x-ray computed tomography while performing hold-at-displacement scans to evaluate the fiber microstructure. We found the fiber breaks do not have the same orientation distribution as the non-broken fibers.

REACTIVE EXTRUSION ADDITIVE MANUFACTURING OF A SHORT FIBER REINFORCED THERMOSET COMPOSITE

Additive manufacturing (AM) of high-performance composites has gained increasing interest over the last few years. Commercially available AM technologies often use thermoplastics as they are easy to process, i.e., to melt and re-solidify. However, thermosetting polymers generally achieve superior mechanical properties and thermostability. This study investigates reactive extrusion additive manufacturing (REAM) of a thermosetting polymer reinforced with carbon fibers. The process utilizes highly exothermic and fast curing resin/catalyst systems, eliminating the need for post-curing. The rheological properties of the liquid resin are first tuned for REAM using ~2wt.% fumed silica and ~10vol.% milled carbon fibers. Then, a robotic arm is used to print the composite samples. The coupons’ longitudinal and transverse tensile properties are measured and correlated with the degree of cure, porosity, fiber length distribution, and fiber orientation distribution. The incorporation of milled carbon fibers, 50-200 m long, primarily affects the stiffness. Compared to neat polymer parts, carbon fiber reinforced composites are 51% stiffer and 8% stronger. In addition, polymeric crosslinking between part layers resulted in strong inter-layer bonding. Short fibers were also randomly oriented within parts due to the nozzle size and shape, resulting in nearly isotropic parts. The results presented here pave the road for fast and low-energy AM of high-performance composites.

Enabling constrained spherical deconvolution and diffusional variance decomposition with tensor-valued diffusion MRI

Diffusion tensor imaging (DTI) is widely used to extract valuable tissue measurements and white matter (WM) fiber orientations, even though its lack of specificity is now well-known, especially for WM fiber crossings. Models such as constrained spherical deconvolution (CSD) take advantage of HARDI data to compute fiber orientation distribution functions (fODF) and tackle the orientational part of the DTI limitations. Furthermore, the recent introduction of tensor-valued diffusion MRI allows for diffusional variance decomposition (DIVIDE), opening the door to the computation of measures more specific to microstructure than DTI measures, such as microscopic fractional anisotropy (μFA). However, tensor-valued diffusion MRI data is not compatible with latest versions of CSD and the impacts of such atypical data on fODF reconstruction with CSD are yet to be studied. In this work, we lay down the mathematical and computational foundations of a tensor-valued CSD and use simulated data to explore the effects of various combinations of diffusion encodings on the angular resolution of extracted fOFDs. We also compare the combinations with regards to their performance at producing accurate and precise μFA with DIVIDE, and present an optimised protocol for both methods. We show that our proposed protocol enables the reconstruction of both fODFs and μFA on in vivo data.

Individualized Thalamic Parcellation Reveals Alterations in Shape and Microstructure of Thalamic Nuclei in Patients with Disorder of Consciousness

The thalamus plays crucial roles in consciousness generation and information processing. Previous evidence suggests that disorder of consciousness (DOC) caused by severe brain injury, is potentially related to thalamic abnormalities. However, how the morphology and microstructure change in thalamic subfields and thalamocortical fiber pathways in patients with DOC, and the relationships between these changes and the consciousness status remain unclear. Here, we generated the individual-specific thalamic parcellation in 10 DOC patients and 10 healthy controls (HC) via a novel thalamic segmentation framework based on the fiber orientation distribution (FOD) derived from 7-Tesla diffusion MRI, and investigated the shape deformation of thalamic nuclei as well as the microstructural changes associated with thalamic nuclei and thalamocortical pathways in patients with DOC. Enlargement of dorsal posterior nucleus and atrophy of anterior nucleus in the right thalamus were observed in DOC cohort relative to the HCs, and the former was closely linked to the consciousness level of the patients. We also found significant reductions of fiber density, but not fiber bundle cross-section, within several thalamic nuclei and most of the thalamocortical fiber pathways, suggesting that loss of axons might take primary responsibility for the impaired thalamocortical connections in patients with DOC rather than the change in fiber-bundle morphology. Furthermore, the individual-specific thalamic parcellation achieved 80% accuracy in classifying patients at the minimally conscious state from the vegetative state, compared to around 60% accuracy based on group-level parcellations. Our findings provide the first evidence for the shape deformation of thalamic nuclei in DOC patients and the microstructural basis of the disrupted thalamocortical connections.