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1.5 t ge mri scanner

Manufactured by GE Healthcare

The 1.5-T GE MRI scanner is a magnetic resonance imaging (MRI) system designed for clinical use. It operates at a magnetic field strength of 1.5 Tesla, which is a common field strength for MRI scanners. The core function of this system is to generate detailed images of the body's internal structures, such as organs, muscles, tendons, and other soft tissues, by using strong magnetic fields and radio waves to interact with the hydrogen atoms in the body.

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3 protocols using 1.5 t ge mri scanner

1

Resting-State fMRI Protocol for 1.5T MRI

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We used a 1.5 T GE MRI scanner (GE Healthcare, Milwaukee, WI) with an 8-channel receiver coil to collect anatomical and resting-state fMRI data. The settings for single-shot fast spin-echo anatomical T2-weighted images (i.e., sagittal, axial, and coronal slices) were as follows: TR= 1100 ms, TE = 160 ms, flip angle = 90°, and slice thickness = 2 mm. The following were the resting-state echo planar images (EPI) scanning parameters: TR = 3000 ms, TE = 60 ms, voxel size = 2.578 mm × 2.578 mm × 3 mm, flip angle = 90°, field of view = 33 cm, matrix size = 128 × 128, and scan duration = 7 min (140 volumes). On average, 5.35 min (25, 75 IQR: 4.6, 6) of resting-state data (107 volumes) were available after preprocessing.
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2

Automated Brain Structural Analysis

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High-resolution T1-weighted anatomic data were obtained from a 1.5-T GE MRI scanner (General Electric, Waukesha, Wisconsin) using a 3-dimensional magnetization-prepared rapid acquisition gradient echo sequence with the following parameters: time of echo, 2.8 ms; time of repetition, 6.3 ms; preparation time, 1,000 ms; flip angle, 8°; field of view, 24 × 24 cm; 160 slices; 1-mm slice thickness; 224 × 192 image matrix reconstructed to 256 × 256; 2 repetitions (27 (link)). MRI data were automatically segmented with FreeSurfer (an open source software suite for processing and analyzing [human] brain MRI images). When necessary, manual intervention was used to increase the accuracy of labeling. Total volumes (adding left and right sides) were calculated and converted from cubic millimeters to tenths of percentage of intracranial volume (using the estimate of intracranial volume from FreeSurfer, version 5.0). In this study, the volumes of hippocampus, white matter hyperintensities (WMH), cerebellum white matter, cortical white matter, total white matter, cortical gray matter, cerebellum gray matter, subcortical gray matter structures, total gray matter, and total brain were obtained. The units for the volume were cubic centimeters. For WMH, the volume was transformed by taking the logarithm because of its skewed distribution.
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3

Automated Brain Structural Analysis

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High-resolution T1-weighted anatomic data were obtained from a 1.5-T GE MRI scanner (General Electric, Waukesha, Wisconsin) using a 3-dimensional magnetization-prepared rapid acquisition gradient echo sequence with the following parameters: time of echo, 2.8 ms; time of repetition, 6.3 ms; preparation time, 1,000 ms; flip angle, 8°; field of view, 24 × 24 cm; 160 slices; 1-mm slice thickness; 224 × 192 image matrix reconstructed to 256 × 256; 2 repetitions (27 (link)). MRI data were automatically segmented with FreeSurfer (an open source software suite for processing and analyzing [human] brain MRI images). When necessary, manual intervention was used to increase the accuracy of labeling. Total volumes (adding left and right sides) were calculated and converted from cubic millimeters to tenths of percentage of intracranial volume (using the estimate of intracranial volume from FreeSurfer, version 5.0). In this study, the volumes of hippocampus, white matter hyperintensities (WMH), cerebellum white matter, cortical white matter, total white matter, cortical gray matter, cerebellum gray matter, subcortical gray matter structures, total gray matter, and total brain were obtained. The units for the volume were cubic centimeters. For WMH, the volume was transformed by taking the logarithm because of its skewed distribution.
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