Biology subjects

Baron, C. A.

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

4 recordsLinked to original sources

bioRxiv2021

Test-retest reproducibility of in vivo magnetization transfer ratio and saturation index in mice at 9.4 Tesla

BackgroundMagnetization transfer saturation (MTsat) imaging was developed to reduce T1 dependence and improve specificity to myelin compared to the widely used MT ratio (MTR), while maintaining a feasible scan time. Knowledge of MTsat reproducibility is necessary to apply MTsat in preclinical neuroimaging. PurposeTo assess the test-retest reproducibility of MTR and MTsat in the mouse brain at 9.4 T and calculate sample sizes required to detect various effect sizes. Study TypeProspective Animal ModelC57Bl/6 Mouse Model (6 females and 6 males, aged 12 - 14 weeks) Field Strength/SequenceMagnetization Transfer Imaging at 9.4 T AssessmentAll mice were scanned at two timepoints (5 days apart). MTR and MTsat maps were analyzed using mean region-of-interest (ROI), and whole brain voxel-wise analysis. Statistical TestsBland-Altman plots assessed biases between test and retest measurements. Test-retest reproducibility was evaluated via between and within-subject coefficients of variation (CV). Sample sizes required were calculated (at a 95 % significance level and power of 80 %), given various minimum detectable effect sizes, using both between and within-subject approaches. ResultsBland-Altman plots showed negligible biases between test and retest sessions. ROI-based and voxel-wise CVs revealed high reproducibility for both MTR (ROI: CVs < 8 %) and MTsat (ROI: CVs < 10 %). With a sample size of 6, changes on the order of 15% can be detected in MTR and MTsat, both between and within subjects, while smaller changes (6 - 8 %) require sample sizes of 10 - 15 for MTR, and 15 - 20 for MTsat. Data ConclusionMTsat exhibits comparable reproducibility to MTR, while providing sensitivity to myelin with less T1 dependence than MTR. Our findings suggest both MTR and MTsat can detect moderate changes, common in pathologies, with feasible preclinical sample sizes.

neuroscience↗

bioRxiv2021

Integration of a radiofrequency coil and commercial field camera for ultra-high-field MRI

PurposeTo develop an RF coil with an integrated commercial field camera for ultra-high field (7 T) neuroimaging. The RF coil will operate within a head-only gradient coil and be subject to the corresponding design constraints. The RF coil can thereafter be used for subject-specific correction of k-space trajectories--notably in gradient-sensitive sequences such as single-shot spiral imaging. MethodsThe transmit and receive performance was evaluated before and after the integration of field probes, while field probes were evaluated when in an optimal configuration external to the coil and after their integration. Diffusion-weighted EPI and single-shot spiral acquisitions were employed to evaluate the efficacy of correcting higher order field perturbations and the consequent effect on image quality. ResultsField probes had a negligible effect on RF-coil performance, including the transmit efficiency, transmit uniformity, and mean SNR over the brain. Modest reductions in field-probe signal lifetimes were observed, caused primarily by non-idealities in the gradient and shim fields of the head-only gradient coil at the probe positions. The field monitoring system could correct up to second-order field perturbations in single-shot spiral imaging. ConclusionThe integrated RF coil and field camera was capable of concurrent field monitoring within a 7T head-only scanner and facilitated the subsequent correction of k-space trajectories during spiral imaging.

biophysics↗

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↗