Biology subjects

Baron, C. A.

Publications and source records attributed to Baron, C. A..

2 recordsLinked to original sources

bioRxiv2020

Microstructural characterization and validation of a 3D printed phantom for diffusion MRI

PurposeTo introduce and characterize inexpensive and easily produced 3D-printed axon-mimetic (3AM) diffusion MRI (dMRI) phantoms in terms of pore geometry and diffusion kurtosis imaging (DKI) metrics. MethodsPhantoms were 3D-printed with a composite printing material that, after dissolution of the PVA, exhibits microscopic fibrous pores. Confocal microscopy and synchrotron phase contrast micro-CT imaging were performed to visualize and assess the pore sizes. dMRI scans of four identical phantoms and phantoms with varying print parameters in water were performed at 9.4T. DKI was fit to both datasets and used to assess the reproducibility between phantoms and effects of print parameters on DKI metrics. Identical scans were performed 25 and 76 days later to test their stability. ResultsSegmentation of pores in three microscopy images yielded a mean, median, and standard deviation of equivalent pore diameters of 7.57 m, 3.51 m, and 12.13 m, respectively. Phantoms with identical parameters showed a low coefficient of variation ([~]10%) in DKI metrics (D=1.38 x10-3 mm2/s and K=0.52, T1= 3960 ms and T2=119 ms). Printing temperature and speed had a small effect on DKI metrics (<16%) while infill density had a larger and more variable effect (>16%). The stability analysis showed small changes over 2.5 months (<7%). Conclusion3AM phantoms can mimic the fibrous structure of axon bundles on a microscopic scale, serving as complex, anisotropic dMRI phantoms.

neuroscience↗

bioRxiv2020

DIFFUSION MRI OF THE UNFOLDED HIPPOCAMPUS

The hippocampus is implicated in numerous neurological disorders and the ability to detect subtle or focal hippocampal abnormalities earlier in disease progression could significantly improve the treatment of patients. Ex vivo studies with ultra-high field have revealed that diffusion MRI (dMRI) can reveal microstructural variations within the hippocampal subfields and lamina, and may also be sensitive to intra-hippocampal pathways. However, translation to lower resolution in vivo dMRI studies of the hippocampus is challenging due to its complicated geometry. One novel way to overcome some of these obstacles is by transforming the usual Cartesian coordinates in an MRI image to coordinates that are crafted to curve themselves according to the complicated geometry of the hippocampus. This procedure allows us to virtually unfold the hippocampus into a thin sheet. In this work, we introduce an algorithm to map diffusion MRI data to this sheet, allowing us to overcome the difficulties associated with the hippocampus complicated geometry. We demonstrate how our method can be readily integrated into existing implementations of traditional tractography methods and how it leads to enhancements in the resulting tracts. Further, our results on high quality in vivo dMRI acquisitions show that unfolding the hippocampus leads to a more anatomically plausible modelling of the connectivity of the hippocampus as probed by probabilistic tractography, revealing key elements of the polysynaptic pathway and anterior-posterior connectivity gradients.

neuroscience↗