Browsing by Author "Maharjan, Surendra"

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    Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging
    (Frontiers Media, 2022-08-17) Maharjan, Surendra; Tsai, Andy P.; Lin, Peter B.; Ingraham, Cynthia; Jewett, Megan R.; Landreth, Gary E.; Oblak, Adrian L.; Wang, Nian; Radiology and Imaging Sciences, School of Medicine
    Purpose: To evaluate the age-dependent microstructure changes in 5xFAD mice using high-resolution diffusion tensor imaging (DTI). Methods: The 5xFAD mice at 4, 7.5, and 12 months and the wild-type controls at 4 months were scanned at 9.4T using a 3D echo-planar imaging (EPI) pulse sequence with the isotropic spatial resolution of 100 μm. The b-value was 3000 s/mm2 for all the diffusion MRI scans. The samples were also acquired with a gradient echo pulse sequence at 50 μm isotropic resolution. The microstructure changes were quantified with DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD). The conventional histology was performed to validate with MRI findings. Results: The FA values (p = 0.028) showed significant differences in the cortex between wild-type (WT) and 5xFAD mice at 4 months, while hippocampus, anterior commissure, corpus callosum, and fornix showed no significant differences for either FA and MD. FA values of 5xFAD mice gradually decreased in cortex (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) and fornix (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) with aging. Both FA (p = 0.029) and MD (p = 0.037) demonstrated significant differences in corpus callosum between 4 and 12 months age old. FA and MD were not significantly different in the hippocampus or anterior commissure. The age-dependent microstructure alterations were better captured by FA when compared to MD. Conclusion: FA showed higher sensitivity to monitor amyloid deposition in 5xFAD mice. DTI may be utilized as a sensitive biomarker to monitor beta-amyloid progression for preclinical studies.
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    Characterizing Molecular and Synaptic Signatures in mouse models of Late-Onset Alzheimer’s Disease Independent of Amyloid and Tau Pathology
    (bioRxiv, 2023-12-20) Kotredes, Kevin P.; Pandey, Ravi S.; Persohn, Scott; Elderidge, Kierra; Burton, Charles P.; Miner, Ethan W.; Haynes, Kathryn A.; Santos, Diogo Francisco S.; Williams, Sean-Paul; Heaton, Nicholas; Ingraham, Cynthia M.; Lloyd, Christopher; Garceau, Dylan; O’Rourke, Rita; Herrick, Sarah; Rangel-Barajas, Claudia; Maharjan, Surendra; Wang, Nian; Sasner, Michael; Lamb, Bruce T.; Territo, Paul R.; Sukoff Rizzo, Stacey J.; Carter, Gregory W.; Howell, Gareth R.; Oblak, Adrian L.; Medical and Molecular Genetics, School of Medicine
    Introduction: MODEL-AD is creating and distributing novel mouse models with humanized, clinically relevant genetic risk factors to more accurately mimic LOAD than commonly used transgenic models. Methods: We created the LOAD2 model by combining APOE4, Trem2*R47H, and humanized amyloid-beta. Mice aged up to 24 months were subjected to either a control diet or a high-fat/high-sugar diet (LOAD2+HFD) from two months of age. We assessed disease-relevant outcomes, including in vivo imaging, biomarkers, multi-omics, neuropathology, and behavior. Results: By 18 months, LOAD2+HFD mice exhibited cortical neuron loss, elevated insoluble brain Aβ42, increased plasma NfL, and altered gene/protein expression related to lipid metabolism and synaptic function. In vivo imaging showed age-dependent reductions in brain region volume and neurovascular uncoupling. LOAD2+HFD mice also displayed deficits in acquiring touchscreen-based cognitive tasks. Discussion: Collectively the comprehensive characterization of LOAD2+HFD mice reveal this model as important for preclinical studies that target features of LOAD independent of amyloid and tau.
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    Corrigendum: Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging
    (Frontiers Media, 2022-10-13) Maharjan, Surendra; Tsai, Andy P.; Lin, Peter B.; Ingraham, Cynthia; Jewett, Megan R.; Landreth, Gary E.; Oblak, Adrian L.; Wang, Nian; Radiology and Imaging Sciences, School of Medicine
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    Magic Angle Effect on Diffusion Tensor Imaging in Ligament and Brain
    (Elsevier, 2022) Wang, Nian; Wen, Qiuting; Maharjan, Surendra; Mirando, Anthony J.; Qi, Yi; Hilton, Matthew J.; Spritzer, Charles E.; Radiology and Imaging Sciences, School of Medicine
    Purpose: To evaluate the magic angle effect on diffusion tensor imaging (DTI) measurements in rat ligaments and mouse brains. Methods: Three rat knee joints and three mouse brains were scanned at 9.4 T using a modified 3D diffusion-weighted spin echo pulse sequence with the isotropic spatial resolution of 45 μm. The b value was 1000 s/mm2 for rat knee and 4000 s/mm2 for mouse brain. DTI model was used to investigate the quantitative metrics at different orientations with respect to the main magnetic field. The collagen fiber structure of the ligament was validated with polarized light microscopy (PLM) imaging. Results: The signal intensity, signal-to-noise ratio (SNR), and DTI metrics in the ligament were strongly dependent on the collagen fiber orientation with respect to the main magnetic field from both simulation and actual MRI scans. The variation of fractional anisotropy (FA) was about ~32%, and the variation of mean diffusivity (MD) was ~11%. These findings were further validated with the numerical simulation at different SNRs (~10.0 to 86.0). Compared to the ligament, the DTI metrics showed little orientation dependence in mouse brains. Conclusion: Magic angle effect plays an important role in DTI measurements in the highly ordered collagen-rich tissues, while MD showed less orientation dependence than FA.
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    Resolution and b value dependent structural connectome in ex vivo mouse brain
    (Elsevier, 2022) Crater, Stephanie; Maharjan, Surendra; Qi, Yi; Zhao, Qi; Cofer, Gary; Cook, James C.; Johnson, G. Allan; Wang, Nian; Radiology and Imaging Sciences, School of Medicine
    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 μm 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 μm 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 (1000s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 µm to 200 µm). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles is 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.
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    Use of multimodality imaging, histology, and treatment feasibility to characterize a transgenic Rag2-null rat model of glioblastoma
    (Frontiers, 2022-11-22) Jackson, Luke R.; Masi, Megan R.; Selman, Bryce M.; Sandusky, George E.; Zarrinmayeh, Hamideh; Das, Sudip K.; Maharjan, Surendra; Wang, Nian; Zheng, Qi-Huang; Pollok, Karen E.; Snyder, Scott E.; Sun, Phillip Zhe; Hutchins, Gary D.; Butch, Elizabeth R.; Veronesi, Michael C.; Pediatrics, School of Medicine
    Many drugs that show potential in animal models of glioblastoma (GBM) fail to translate to the clinic, contributing to a paucity of new therapeutic options. In addition, animal model development often includes histologic assessment, but multiparametric/multimodality imaging is rarely included despite increasing utilization in patient cancer management. This study developed an intracranial recurrent, drug-resistant, human-derived glioblastoma tumor in Sprague–Dawley Rag2-Rag2 tm1Hera knockout rat and was characterized both histologically and using multiparametric/multimodality neuroimaging. Hybrid 18F-fluoroethyltyrosine positron emission tomography and magnetic resonance imaging, including chemical exchange saturation transfer (18F-FET PET/CEST MRI), was performed for full tumor viability determination and characterization. Histological analysis demonstrated human-like GBM features of the intracranially implanted tumor, with rapid tumor cell proliferation (Ki67 positivity: 30.5 ± 7.8%) and neovascular heterogeneity (von Willebrand factor VIII:1.8 to 5.0% positivity). Early serial MRI followed by simultaneous 18F-FET PET/CEST MRI demonstrated consistent, predictable tumor growth, with exponential tumor growth most evident between days 35 and 49 post-implantation. In a second, larger cohort of rats, 18F-FET PET/CEST MRI was performed in mature tumors (day 49 post-implantation) for biomarker determination, followed by evaluation of single and combination therapy as part of the model development and validation. The mean percentage of the injected dose per mL of 18F-FET PET correlated with the mean %CEST (r = 0.67, P < 0.05), but there was also a qualitative difference in hot spot location within the tumor, indicating complementary information regarding the tumor cell demand for amino acids and tumor intracellular mobile phase protein levels. Finally, the use of this glioblastoma animal model for therapy assessment was validated by its increased overall survival after treatment with combination therapy (temozolomide and idasanutlin) (P < 0.001). Our findings hold promise for a more accurate tumor viability determination and novel therapy assessment in vivo in a recently developed, reproducible, intracranial, PDX GBM.