Triotim 3t scanner

Manufactured by Siemens

Sourced in Germany

The TrioTim 3T scanner is a magnetic resonance imaging (MRI) device manufactured by Siemens. It operates at a magnetic field strength of 3 Tesla, which is commonly used for advanced medical imaging applications. The TrioTim 3T scanner is designed to capture high-resolution images of the human body for diagnostic and research purposes.

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Lab products found in correlation

12 channel phased array whole head coil, by Siemens (3 mentions) Prisma 3t scanner, by Siemens (2 mentions) 32 channel head coil, by Siemens (2 mentions) 12 channel head coil, by Siemens (1 mentions) Biograph 64, by Siemens (1 mentions)

Spelling variants of this product

3T scanner (160 citations) 3T TrioTim (31 citations) Siemens scanners (11 citations) 3T TrioTim MRI scanner (7 citations) Magnetom TrioTim 3T scanner (5 citations)

22 protocols using triotim 3t scanner

High-resolution MRI and resting-state fMRI data

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All images were obtained on a Siemens TrioTim 3T scanner using a 20-channel head coil. Anatomical T1-weighted 3D gradient echo pulse sequence scans were acquired with the following parameters: flip angle = 8°, TR/TE = 2400/3.16 ms, FOV 256 × 256 mm, voxel size was 1.1 × 1.1 × 1.2 mm³ isotropic, length of scan = 7.04 minutes. rsfMRI scans were acquired eyes closed with the following parameters: flip angle 90°, TR/TE = 2200/27 ms, FOV 384 × 384 mm, voxel size: 4 mm³ isotropic, scan time = 6.01 minutes.

Contreras J.A., Aslanyan V., Sweeney M.D., Sanders L.M., Sagare A.P., Zlokovic B.V., Toga A.W., Han S.D., Morris J.C., Fagan A., Massoumzadeh P., Benzinger T.L, & Pa J. (2019). Functional connectivity among brain regions affected in Alzheimer’s disease is associated with CSF TNF-α in APOE4 carriers. Neurobiology of aging, 86, 112-122.

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Functional Brain Imaging with 3T MRI

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Functional brain activity was measured using a Siemens TrioTim 3T scanner, covering the brain in 26 interleaved transversal slices (3.4mm isomorphic voxels), with a T2* weighted EPI GRAPPA sequence (TR = 1.3s, TE = 25ms, flip angle = 50°, FOV = 220mm). SPM8 was used for preprocessing for functional images, using a standard pipeline for motion correction, slice-time correction, spatial normalization to MNI space, and spatial smoothing of images using an 8mm FWHM Gaussian kernel. For spatial normalization, T1 structural MPRAGE images (1mm isomorphic voxels) were first coregistered to the mean functional image and then normalized to the SPM template using unified segmentation. Preprocessed functional images were resampled at a voxel size of 2×2×2mm. Regarding motion correction, translation and rotation estimates (x, y, z) were less than 2 mm or 2°, respectively, for all participants.

López-Solà M., Koban L, & Wager T.D. (2018). Transforming pain with prosocial meaning: an fMRI study. Psychosomatic medicine, 80(9), 814-825.

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3T MRI Structural Imaging Protocol

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MRI scanning was conducted with a Siemens Trio TIM 3T scanner at Tamagawa University (Japan). The parameters used were: repetition time 2 s, echo time 25 ms, flip angle 90°, field of view 192 mm, and resolution 3 × 3 × 3 mm. High-resolution (T1 [1 × 1 × 1 mm] and T2 [0.6 × 0.4 × 3 mm]) structural images were also acquired for each participant. In addition to the experimental trials, the session contained three initial dummy scans.

Tanaka T., Nishimura F., Kakiuchi C., Kasai K., Kimura M, & Haruno M. (2019). Interactive effects of OXTR and GAD1 on envy-associated behaviors and neural responses. PLoS ONE, 14(1), e0210493.

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Functional MRI Acquisition and Preprocessing Protocol

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A Siemens Trio Tim 3 T scanner with a 12 channel head coil was used for image acquisition. Functional images were obtained using a Gradient-echo T2^*-weighted echo planar sequence and consisted in 32 non-contiguous oblique axial planes (in order to minimize signal drop-out in ventral regions, which was especially important according to our hypothesis). Other parameters included relaxation time = 2000 ms; echo time = 30 ms; flip angle = 78; voxel size = 3.14 × 3.14 × 3.75 mm³, matrix size 64 × 64; bandwidth 2232 HZ/Px. The structural image was obtained using a high-resolution T1-weighted three-dimensional MP-RAGE sequence.
Imaging preprocessing and analysis was carried out using the FEAT v5.98 (FMRI Expert Analysis Tool) routine within the FSL program (FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl). Functional time-series were sequentially realigned, coregistered to a whole brain echo-planar image and finally to the structural high resolution T1 image, and non-brain components were removed. Functional images were also spatially smoothed using a 6 mm at full width half-maximum (FWHM) Gaussian kernel and frequency filtered (130 s cut off). Images were normalized to the Montreal Neurological Institute (MNI) standard template and the first six volumes were discarded to allow for T1 equilibration effects.

Arrondo G., Segarra N., Metastasio A., Ziauddeen H., Spencer J., Reinders N.R., Dudas R.B., Robbins T.W., Fletcher P.C, & Murray G.K. (2015). Reduction in ventral striatal activity when anticipating a reward in depression and schizophrenia: a replicated cross-diagnostic finding. Frontiers in Psychology, 6, 1280.

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Functional MRI Acquisition and Preprocessing

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Functional brain images were acquired using a Siemens TrioTim 3 T scanner (n = 16) and a Siemens Prisma 3 T scanner (n = 16, following a scanner update at the University of Colorado Boulder scanning facility). The proportion of patients and controls was identical before and after the update. Individual differences in signal largely outweighed differences in scanners, evidenced by the finding that adding scanner as a 2^nd-level covariate did not meaningfully alter the results. A T2* weighted EPI GRAPPA sequence (TR = 1.3, TE = 25 ms, flip angle=50°, FOV = 220 mm) covered the brain in 26 interleaved transversal slices (3.4 mm isotropic voxels). SPM8 was used for preprocessing for functional images, using a standard pipeline of motion correction, slice-time correction, spatial normalization to MNI space, and spatial smoothing of images using an 8 mm FWHM Gaussian kernel. For spatial normalization, T1 structural MPRAGE images (1 mm isomorphic voxels) were first co-registered to the mean functional image and then normalized to the SPM template using unified segmentation. Preprocessed functional images were resampled to a voxel size of 3 × 3 × 3 mm.

Koban L., Andrews-Hanna J.R., Ives L., Wager T.D, & Arch J.J. (2023). Brain mediators of biased social learning of self-perception in social anxiety disorder. Translational Psychiatry, 13, 292.

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Multimodal MRI Brain Imaging Protocol

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All participants underwent non-sedated, non-contrast-enhanced structural magnetic resonance imaging (MRI) of the brain after MRI safety screening. Scans were acquired using a GE Discovery 750 W 3Tesla) scanner (N = 36) and Siemens TrioTim 3T scanner (N = 6), both equipped with a 32-channel head coil. T1/T2-weighted images were acquired for registration purposes. Anatomical T1-weighted were acquired as follows for GE (with Siemens measures in parentheses): coronal BRAVO (MPRAGE), repetition time = 8.392 (2300) ms, time to echo = 3.184 (2.82) ms, inversion time = 450 (900) ms, flip angle = 12 (10)°, field of view = 282 × 282 × 264 mm, matrix = 256 × 256 × 240. The measures for T2-weighted images were as follows: coronal, repetition time = 3000 (4800) ms, time to echo = 85.925 (430) ms, field of view = 256 × 256 × 224 mm, matrix = 256 × 256 × 160. Participants completed diffusion-weighted magnetic resonance imaging acquisitions with either a single-shell (B1000, 64 directions), multi-shell (B1000 and B2000, 29–30 directions per shell), or both. Anatomical T1-weighted and T2-weighted images were collected and used for co-registration, normalization, and labeling purposes using the acquisition measures described previously.²⁶ Diffusion-weighted images were collected using echo planar recovery-magnitude sequences collected in the axial plane.

van der Plas E., Solomon M.A., Hopkins L., Koscik T., Schultz J., Brophy P.D., Nopoulos P.C, & Harshman L.A. (2021). Global and regional white matter fractional anisotropy in children with chronic kidney disease. The Journal of pediatrics, 242, 166-173.e3.

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High-resolution MRI and resting-state fMRI data

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Magnetic Resonance Imaging Acquisition Protocol

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Magnetic Resonance Imaging (MRI) data used in this study were collected at both the HBN Rutgers University Brain Imaging Center site on a Siemens Trio Tim 3T scanner and the HBN CitiGroup Cornell Brain Imaging Center site on a Siemens Prisma 3T scanner. The scan parameters at both sites were identical: TR = 800ms, TE = 30ms, # slices = 60, flip angle = 31°, # volumes = 750, voxel size = 2.4 mm. Complete information regarding the scan parameters used for the Healthy Brain Network project can be found at: http://fcon_1000.projects.nitrc.org/indi/cmi_healthy_brain_network/MRI%20Protocol.html.

Cohen S.S., Tottenham N, & Baldassano C. (2022). Developmental changes in story-evoked responses in the neocortex and hippocampus. eLife, 11, e69430.

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Functional Brain Imaging Preprocessing Protocol

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Functional brain activity was acquired using a Siemens TrioTim 3T scanner, covering the brain in 26 interleaved transversal slices (3.4 -mm isotropic voxels), with a T2* weighted EPI GRAPPA sequence (TR = 1.3, TE = 25 ms, flip angle = 50°, FOV = 220 mm). Prior to preprocessing of functional data, time points that are potential global outliers (spikes) were identified based on meeting any of the following criteria: (a) absolute value of global signal > 10 median absolute deviations (m.a.d.), or (b) mahalanobis distance across slice-specific global means and spatial standard deviation > 10 median absolute deviations. These time points are identified on a per-run basis using recursive exclusion of outliers in a step-down test, so that outliers are removed before recursively identifying additional outliers (three iterations). SPM8 was used for preprocessing for functional images, using a standard pipeline of motion correction, slice-time correction, spatial normalization to MNI space, and spatial smoothing of images using an 8 -mm FWHM Gaussian kernel. For spatial normalization, T1-structural MPRAGE images (1 mm isomorphic voxels) were first coregistered to the mean functional image and then normalized to the SPM template using unified segmentation. Preprocessed functional images were resampled at a voxel size of 3 × 3 × 3 mm.

Koban L., Jepma M., López-Solà M, & Wager T.D. (2019). Different brain networks mediate the effects of social and conditioned expectations on pain. Nature Communications, 10, 4096.

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Schizophrenia Neuroimaging Protocol from COBRE

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sMRI data were acquired from the Center for Biomedical Research Excellence database (http://fcon_1000.project.nitrc.org/indi/retro/cobre.html). The dataset received full approval of local ethics committees in accordance with the Declaration of Helsinki. All subjects gave informed consent and their anonymity was preserved in the dataset. A total of 147 samples were obtained, including 72 patients with schizophrenia and 75 control subjects. The diagnosis of schizophrenia patients was based on the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV SCID). The subjects were all right-handed. Specifically, 15 patients with schizophrenia and 6 healthy controls were excluded during data preprocessing, leaving a total of 126 participants, including 57 patients with schizophrenia and 69 healthy controls. Among the 57 schizophrenia patients, there were 3 disorganized type (295.1), 37 paranoid type (295.3), 9 residual type (295.6), 4 schizoaffective type (295.7), and 4 unspecified type (295.9).
T1-weighted MRI data were acquired using a Siemens Trio Tim 3T scanner (Munich, Germany). MPRAGE sequence was used with the following parameters: echo time (TE) = 1.64 ms, time of repetition (TR) = 2.530 ms, field of view (FOV) = 256 × 256 mm, flip angle = 7°, slice thickness = 1.0 mm, and voxel size = 1 × 1 × 1 mm³.

Guo Y., Qiu J, & Lu W. (2020). Support Vector Machine-Based Schizophrenia Classification Using Morphological Information from Amygdaloid and Hippocampal Subregions. Brain Sciences, 10(8), 562.

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