Biology subjects

Cofer, G.

Publications and source records attributed to Cofer, G..

3 recordsLinked to original sources

bioRxiv2022

Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain

Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 m isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 m isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000 s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 {micro}m to 200 {micro}m). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles are necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.

neuroscience↗

bioRxiv2021

Multimodal Magnetic Resonance Histology and Light Sheet Imaging for Quantitative Neurogenetics of the Mouse

Paul Lauterbur closed his seminal paper on MRI with the statement that "zeugmatographic (imaging) techniques should find many useful applications in studies of the internal structures, states and composition of microscopic objects" [1]. Magnetic resonance microscopy was subsequently demonstrated in 1986 by three groups [2] [3] [4]. The application of MRI to the study of tissue structure, i.e. magnetic resonance histology (MRH) was suggested in 1993 [5]. MRH, while based on the same physical principals as MRI is something fundamentally different than the clinical exams which are typically limited to voxel dimensions of ~ 1 mm3. Preclinical imaging systems can acquire images with voxels ~ 1000 times smaller. The MR histology images presented here have been acquired at yet another factor of 1000 increase in spatial resolution. Figure S1 in the supplement shows a comparison of a state-of-the-art fractional anisotropy images of a C57 mouse brain in vivo @ 150 m resolution (voxel volume of 3.3 x10-3 mm3) with the atlas we have generated for this work at 15 m spatial resolution (voxel volume of 3.3 x 10-6 mm3). In previous work, we have demonstrated the utility of MR histology in neurogenetics at spatial/angular resolution of 45 m /46 angles [6]. At this spatial/angular resolution it is possible to map whole brain connectivity with high correspondence to retroviral tracers [7]. But the MRH derived connectomes can be derived in less than a day where the retroviral tracer studies require months/years [8]. The resolution index (angular samples/voxel volume) for this previous work was >500,000 [9]. Figure S2 shows a comparison between that previous work and the new atlas presented in this paper with a resolution index of 32 million. Light sheet microscopy (LSM) has undergone similar rapid evolution over the last 20 years. The invention of tissue clearing, advances in immunohistochemistry and development of selective plane illumination microscopy (SPIM) now make it possible to acquire whole mouse brain images at submicron spatial resolution with a vast array of cell specific markers [10] [11] [12] [13]. And these advantages can be realized in scan times of < 6hrs. The major limitation from these studies is the distortion in the tissue from dissection from the cranium, swelling from clearing and staining, and tissue damage from handling. We report here the merger of these two methods: O_LIMRH with the brain in the skull to provide accurate geometry, cytoarchitectural measures using scalar imaging metrics and whole brain connectivity at 15 m isotropic spatial resolution with super resolution track density images @ 5 m isotropic resolution; C_LIO_LIwhole brain multichannel LSM @ 1.8x1.8x4.0 m; C_LIO_LIa big image data infrastructure that enables label mapping from the atlas to the MR image, geometric correction to the light sheet data, label mapping to the light sheet volumes and quantitative extraction of regional cell density. These methods make it possible to generate a comprehensive collection of image derived phenotypes (IDP) of cells and circuits covering the whole mouse brain with throughput that can be scaled for quantitative neurogenetics. C_LI

neuroscience↗

bioRxiv2020

A time-course study of actively stained mouse brains: DTI parameter and connectomic stability over one year

While the application of diffusion tensor imaging (DTI), tractography, and connectomics to fixed ex-vivo tissue is a common practice today, there have been limited studies examining the effects of fixation on brain microstructure over extended periods. This time-course study reports the changes of regional brain volumes and diffusion scalar parameters, such as fractional anisotropy across twelve representative brain regions as measures of brain structural stability. The scalar DTI parameters and regional volumes were highly variable over the first two weeks after fixation. The same parameters were stable over a two to eight-week window after fixation which means confounds from tissue stability over that scanning window are minimal. Quantitative connectomes were analyzed over the same time period with extension out to one year. While there is some change in the scalar metrics at one year after fixation, these changes are sufficiently small, particularly in white matter to support reproducible connectomes over a period ranging from two weeks to one year post fixation. These findings delineate a stable scanning period during which brain volumes, diffusion scalar metrics and connectomes are remarkably stable.

neuroscience↗