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Signa 3 tesla lx scanner

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The Signa 3-Tesla LX scanner is a magnetic resonance imaging (MRI) system manufactured by GE Healthcare. It operates at a field strength of 3 Tesla, providing high-resolution imaging capabilities. The Signa 3-Tesla LX scanner is designed for clinical applications requiring advanced MRI technology.

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Signa scanner (128 citations) Signa LX (27 citations) 3 Tesla scanner (20 citations) Signa 3 Tesla scanner (8 citations) Scanners (2 citations)

5 protocols using signa 3 tesla lx scanner

1

Resting-State fMRI Acquisition Protocol

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Participants were scanned using a General Electric Signa 3-Tesla LX scanner (Milwaukee, WI). A high resolution T1-weighted fast field echo (FFE) structural scan was acquired, followed by two 5-minute resting state axial echo-planar imaging (EPI) scans (TR = 2200 ms, TE = 30 ms, 90 degree flip angle, slice thickness = 3.5 mm, 140 slices, 24 × 24 cm field of view and 64 × 64 matrix, providing a resolution of 3.75 × 3.75 × 3.5 mm and whole-brain coverage), using a standard quadrature 32-channel head coil. For resting state image acquisition, participants were instructed to rest quietly and let their minds wander while focusing their eyes on a white fixation cross without falling asleep for the duration of two 5-minute scans. An eye-tracking camera allowed the examiner to ensure that participants kept their eyes open during these scans.
Davis K., Margolis A.E., Thomas L., Huo Z, & Marsh R. (2017). Amygdala sub-regional functional connectivity predicts anxiety in children with reading disorder. Developmental science, 21(5), e12631.
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2

MRI Acquisition Parameters Standardization

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All MRI data were acquired on a General Electric Signa 3 Tesla LX scanner (Milwaukee, WI). Specific acquisition parameters from each study are presented in Supplementary Table 1. To account for slight differences in MRI acquisition (flip angle, TR, and run length), a three-group dummy code was included as a covariate in all imaging analyses.
Ramphal B., DeSerisy M., Pagliaccio D., Raffanello E., Rauh V., Tau G., Posner J., Marsh R, & Margolis A.E. (2020). Associations between Amygdala-Prefrontal Functional Connectivity and Age Depend on Neighborhood Socioeconomic Status. Cerebral Cortex Communications, 1(1), tgaa033.
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3

Multimodal Neuroimaging Protocol for Task and Resting-State fMRI

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Imaging was performed on a GE Signa 3-Tesla LX scanner (Milwaukee, WI) with a standard quadrature GE head coil. Head positioning was standardized using the canthometal line. A T1-weighted sagittal localizing scan was used to position the axial functional images parallel to anterior commissure-posterior commissure line. A 3D spoiled gradient recall (SPGR) image was acquired for coregistration with functional images and standard Montreal Neurological Institute (MNI) coordinates. Task-based and resting state functional images were obtained using a T2*-sensitive gradient-recalled, single-shot, echo-planar pulse sequence (3mm isotropic voxels) in runs of 140 images, plus 6 dummy frames discarded for steady state. Task imaging parameters were repetition time (TR) of 2,200ms, echo time (TE) of 30ms, 90° flip angle, single excitation per image, 24 × 24 cm field of view, no gap, covering the entire brain. Resting state imaging parameters were repetition time (TR) of 2,000ms, echo time (TE) of 30ms, 77° flip angle, single excitation per image, 24 × 24 cm field of view, no gap, covering the entire brain. Three runs of the Simon task (5 minutes, 21 seconds per run) and two resting state runs (4 minutes, 52 seconds per run) were collected.
Margolis A.E., Pagliaccio D., Davis K.S., Thomas L., Banker S.M., Cyr M, & Marsh R. (2020). Neural Correlates of Cognitive Control Deficits in Children with Reading Disorder. Brain imaging and behavior, 14(5), 1531-1542.
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4

3T fMRI Acquisition Protocol for Whole-Brain Analysis

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Images were acquired on a GE Signa 3 Tesla LX scanner (Milwaukee, WI) with a 55 cm diameter bore equipped with an 8-channel receive-only head coil. A three-plane localization scan was used to verify head position, and motion was minimized with restraint pads around the head. A T1-weighted sagittal localizing scan was used to position the axial functional images parallel to the anterior commissure-posterior commissure [AC-PC] line. A high-resolution 3D spoiled gradient recall [SPGR] anatomical image was acquired for coregistration with the axial functional images and with the standard MNI [Montreal Neurological Institute] coordinate system. Functional images were obtained using a T2*-sensitive gradient-recalled, single-shot, echo-planar imaging [EPI] pulse sequence with a 2800 msec repetition time (TR), 25 msec echo time [TE], 90° flip angle, 24 × 24 cm field of view [FOV] and 64 × 64 voxel matrix. Forty-three oblique slices positioned parallel to the AC-PC line were acquired per volume, providing whole brain coverage with 185 volumes (preceded by 6 dummy volumes) per run, and 3 runs per participant. Slice thickness was 3.0mm throughout, with 0.5mm spacing between slices. Effective spatial resolution was therefore 3.75 × 3.75 × 3.5 mm.
Carnell S., Benson L., Chang K.Y., Wang Z., Huo Y., Geliebter A, & Peterson B.S. (2017). Neural correlates of familial obesity risk and overweight in adolescence. NeuroImage, 159, 236-247.
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5

Multimodal Neuroimaging Protocol

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All participants were scanned on the same General Electric Signa 3-Tesla LX scanner (Milwaukee, WI). Included participants completed at least one T1-weighted fast field echo (FFE) structural scan and at least 5 min of concatenated resting state axial echo-planar imaging (EPI) scan time using a standard quadrature 32-channel head coil. Specific scan parameters varied slightly across studies (see Table S1); statistical analyses included pulse sequence as a covariate to control for differences across studies. Participants were instructed to rest quietly and let their minds wander while focusing on a white fixation cross for the duration of resting state scans.
DeSerisy M., Ramphal B., Pagliaccio D., Raffanello E., Tau G., Marsh R., Posner J, & Margolis A.E. (2021). Frontoparietal and default mode network connectivity varies with age and intelligence. Developmental Cognitive Neuroscience, 48, 100928.
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