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3t prisma fit system

Manufactured by Siemens
Sourced in Germany

The 3T Prisma-Fit system is a magnetic resonance imaging (MRI) scanner designed by Siemens. It operates at a field strength of 3 Tesla, providing high-resolution imaging capabilities. The core function of this system is to generate detailed images of the body's internal structures for diagnostic and research purposes.

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6 protocols using 3t prisma fit system

1

Resting-State fMRI Acquisition Protocol

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Magnetic resonance imaging data were acquired at the MRC Cognition and Brain Sciences Unit, University of Cambridge. All scans were obtained on a Siemens 3T Prisma-Fit system (Siemens Healthcare, Erlangen, Germany) using a 32-channel head coil.
In the resting-state fMRI, 270 T2*-weighted whole-brain echo planar images (EPIs) were acquired over nine minutes (time repetition [TR] = 2s; time echo [TE] = 30ms; flip angle = 78 degrees, 3x3×3mm). The first 4 volumes were discarded to ensure steady state magnetization. Participants were instructed to lie still with their eyes closed and to not fall asleep. For registration of functional images, T1-weighted volume scans were acquired using a whole-brain coverage 3D Magnetization Prepared Rapid Acquisition Gradient Echo (MP RAGE) sequence acquired using 1-mm isometric image resolution (TR = 2.25s, TE = 2.99ms, flip angle = 9 degrees, 1x1x1mm).
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2

Multimodal MRI Connectivity Profiling

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The magnetic resonance imaging (MRI) data were collected on a Siemens 3T Prisma‐fit system using a 32‐channel quadrature head coil. T1‐weighted volume scans were acquired using a whole‐brain coverage 3D Magnetization Prepared Rapid Acquisition Gradient Echo (MP RAGE) sequence acquired using 1 mm isometric image resolution. Echo time was 2.98 ms, and repetition time was 2,250 ms. Diffusion scans were obtained using echo‐planar diffusion‐weighted images with an isotropic set of 68 noncollinear directions, using a weighting factor of b = 1,000 s × mm−2, interleaved with 4 T2‐weighted (b = 0) volume. Whole brain coverage was based on 60 contiguous axial slices and isometric image resolution of 2 mm. Echo time was 90 ms and repetition time was 8,500 ms. Both MRI pre‐processing and reconstruction were performed using QSIPrep 0.13.0RC1, which is based on Nipype 1.6.0 (Gorgolewski et al., 2011 (link)). All pre‐processing steps are reported in the Supporting Information (Appendix S3). Whole‐brain white matter connectivity matrices (i.e. connectomes) were constructed for each child based on the Brainnetome atlas (Fan et al., 2016 (link)). For each pairwise combination of regions (N = 246), the number of streamlines intersecting them was estimated and transformed to a 246 × 246 streamline matrix.
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3

Resting-state fMRI and Structural MRI Protocol

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Magnetic resonance imaging data were acquired at the MRC Cognition and Brain Sciences Unit, University of Cambridge. All scans were obtained on a Siemens 3 T Prisma-fit system (Siemens Healthcare, Erlangen, Germany), using a 32-channel quadrature head coil.
In the resting-state fMRI, 270 T2*-weighted whole-brain echo planar images (EPIs) were acquired over nine minutes (time repetition [TR] = 2 s; time echo [TE] = 30 ms; flip angle = 78 degrees, 3 ×3 ×3 mm). The first 4 volumes were discarded to ensure steady state magnetization. Participants were instructed to lie still with their eyes closed and to not fall asleep. For registration of functional images, T1-weighted volume scans were acquired using a whole-brain coverage 3D Magnetization Prepared Rapid Acquisition Gradient Echo (MP-RAGE) sequence acquired using 1-mm isometric image resolution (TR = 2.25 s, TE = 2.98 ms, flip angle = 9 degrees, 1×1x1mm).
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4

Quantifying Liver Steatosis via MRI-PDFF

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Liver steatosis was quantified by magnetic resonance imaging-proton
density fat fraction (MRI-PDFF) at baseline and week 20 (Siemens 3T
PrismaFit system).
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5

Resting-State fMRI Protocol for Brain Imaging

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Magnetic resonance imaging data were acquired at the MRC Cognition and Brain Sciences Unit, University of Cambridge. All scans were obtained on a Siemens 3T Prisma-fit system (Siemens Healthcare, Erlangen, Germany), using a 32-channel quadrature head coil.
In the resting-state fMRI, 270 T2*-weighted whole-brain echo planar images (EPIs) were acquired over nine minutes (time repetition [TR] = 2s; time echo [TE] = 30ms; flip angle = 78 degrees, 3x3×3mm). The first 4 volumes were discarded to ensure steady state magnetization. Participants were instructed to lie still with their eyes closed and to not fall asleep. For registration of functional images, T1-weighted volume scans were acquired using a whole-brain coverage 3D Magnetization Prepared Rapid Acquisition Gradient Echo (MP-RAGE) sequence acquired using 1-mm isometric image resolution (TR = 2.25s, TE = 2.98ms, flip angle = 9 degrees, 1x1x1mm).
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6

Voxel-Based Morphometry of Brain Anatomy

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High resolution T1-weighted MPRAGE (Magnetization Prepared Rapid Gradient Echo) sequences performed on a 3T Prisma Fit System (Siemens, Erlangen, Germany) were obtained as follow: 192 continuous sagittal slices, TR/TE/TI = 2300/2.28/900 ms, ip angle = 8•, FOV = 256 × 240 mm2, matrix = 256 × 240, isotropic voxel size = 1.0 × 1.0 × 1.0 mm3, bandwidth = 200 Hz/pixel. We used the Computational Anatomy Toolbox (http://dbm.neuro.uni-jena.de/cat12/) protocol in Statistical Parametric Mapping (SPM12) (http://Page | 6www. l.ion.ucl.ac.uk/spm/), to process the T1 images for voxel-based morphometry (VBM) analysis. Speci cally, all 3D T1-weighted MRI scans were normalized using an a ne transformation followed by non-linear registration, corrected for bias eld in homogeneities. Images were then segmented to derive subject-level GM, WM, and CSF components [26] . The Diffeomorphic Anatomic Registration Through Exponentiated Lie algebra algorithm (DARTEL) was used to normalize the segmented scans into the standard MNI space which provides better precision in spatial normalization to the template [27] . All obtained segmented, modulated, and normalized GM and WM images were then smoothed using an 8-mm full-width-half-maximum isotropic Gaussian smoothing kernel.
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