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Magnetom trio a 3t mr scanner

Manufactured by Siemens
Sourced in Germany

The Magnetom Trio A 3T MR Scanner is a magnetic resonance imaging (MRI) system manufactured by Siemens. It operates at a magnetic field strength of 3 Tesla, which allows for high-quality imaging and detailed visualization of the body's internal structures. The core function of the Magnetom Trio A 3T MR Scanner is to provide medical professionals with advanced imaging capabilities for diagnostic and research purposes.

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2 protocols using magnetom trio a 3t mr scanner

1

Resting-state fMRI Acquisition Protocol

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Each participant was instructed before scanning to remain at rest and awake without thinking or falling asleep. Matching hoods and foam pads were used to fix the head and reduce head motion. The images were acquired using a Magnetom Trio A 3T MR Scanner (Siemens AG, Erlangen, Germany). Rs-fMRI images were acquired using a gradient echo-echo planar imaging (GRE-EPI) sequence with the following parameters: interleaved scanning order; slice number = 43; matrix size = 64 × 64; field of view (FOV) = 240 mm × 240 mm; repetition time/echo time (TR/TE) = 3,000/30 ms; flip angle = 90°; slice thickness = 3.0 mm; acquisition voxel size = 3.2 mm × 3.2 mm × 3.40 mm; and number of repetitions = 240 for a total acquisition time of 12 min.
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2

Resting-state fMRI preprocessing pipeline

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Before scanning, the participants were told to remain at rest and awake without thinking or falling asleep. Their heads were fixed to reduce any head motion. The images were collected by using a Magnetom Trio A 3T MR Scanner (Siemens AG, Erlangen, Germany). Rs-fMRI images were acquired using a Gradient Echo-Echo Planar Imaging (GRE-EPI) sequence with the following parameters: interleaved scanning order; Field of view = 240 × 240 mm2; matrix size = 64 × 64; slice number = 43; Time of repetition/echo = 3000/30 ms; flip angle = 90°; slice thickness = 3.0 mm; acquisition voxel size = 3.4 × 3.4 × 3.2 mm3; and number of repetitions = 240. The Graph-theoretical Network Analysis Toolkit (GRETNA, www.nitrc.org) was applied for data preprocessing as follows: remove the first 10 volume, slice timing, realignment, normalization by the EPI template of the Montreal Neurological Institute (MNI) space, resampling to 3.0 × 3.0 × 3.0 mm3, spatial smoothing with a 4-mm full-width at half-maximum Gaussian kernel, temporal detrending and filtering (0.01–0.1 Hz), regressing out of covariates. Finally, the data from four HCs and three patients were excluded because of excessive head motion (more than 2° and 2 mm) or serious artifacts. The data of forty-six participants were analyzed in the next steps.
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