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1.5 tesla scanner

Manufactured by Siemens
Sourced in Germany

The 1.5 Tesla scanner is a medical imaging device that generates a strong magnetic field to produce detailed images of the human body. It uses magnetic resonance imaging (MRI) technology to capture high-quality, cross-sectional images of internal structures without the use of ionizing radiation. This scanner is a core component of modern medical diagnostics and can be utilized for a variety of clinical applications.

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25 protocols using 1.5 tesla scanner

1

Contrast-Enhanced Cardiac MRI Protocol

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Contrast-enhanced cardiac MRI was performed on a 1.5 Tesla (T) scanner (Siemens Medical Systems, Germany) providing a gradient strength of 40 mT/m and maximum slew rate of 200 mT/m/msec. An advanced cardiac software package was used. Images were acquired with the subject in the supine position, by applying electrocardiographically gated breath-hold sequences as described before [15 (link)]. For LGE imaging a two-dimensional inversion-recovery segmented k-space gradient-echo MR sequence was performed using 0.15 mmol gadobutrol per kilogram of body weight (Gadovist, Bayer Healthcare, Germany) [15 (link)]. Two experienced investigators independently reviewed the image loops of each subject in a random fashion. For LGE image analysis both investigators visually judged the occurrence (presence versus absence), localization, and pattern of LGE [10 (link), 29 (link)].
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2

Quantifying Glioblastoma Tumor Volumes

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MRI was performed for all patients using a 1.5 Tesla (T) scanner (Siemens Espree, Erlangen, Germany). The digital imaging and communications in medicine (DICOM) data of all MRI sequences were transferred to iPlan software 2.6 (Brainlab Feldkirchen, Germany). Pre-and postoperative tumor volumes (cm3) were calculated automatically by the software based on the tumor tissue seen on postcontrast 3D T1-weighted MR images of GBM. The EOR was defined as follows: (preoperative tumor volume – postoperative residual tumor volume)/preoperative tumor volume × 100.
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3

Quantifying Hepatic Fat Fraction Using MRI

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The full imaging protocol has been reported [30] . In brief, a Dixon-based MRI sequence was used on a 1.5 Tesla Siemens scanner to obtain images from the neck to the knee (excluding arms). 384 contiguous, axial T1-weighted gradient-echo images with a slice thickness of 3mm were acquired, from which fat and water images were produced as part of the Dixon sequence. MRI data were analysed using the open source image analysis software HOROS V 1.1.7 (www.horosproject.org; accessed 21/10/2017) by a single, blinded analyst (OH).
In each participant, two abdominal MRI images approximately 30mm apart were selected, representing the superior and inferior sections of the liver. In each pair of water and fat MRI images, 4 circular regions of interest (ROIs) in identical positions were placed within the liver tissue. The hepatic fat fraction (HFF) was quantified in each ROI by using the formula %HFF = (F/(F+W)) *100 where F is the pixel signal intensity of the fat image and W is the pixel signal intensity of the water image. Intrahepatic lipid (IHL) was calculated as the mean of all 8 ROIs.
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4

MRI Imaging for Visceral Adipose Tissue

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A Dixon-based MRI sequence was used on a 1.5-Tesla Siemens scanner to obtain images from the neck to the knee (excluding arms). Three hundred and eighty-four contiguous, axial T1-weighted gradient-echo images with a slice thickness of 3 mm were acquired, from which fat and water images were produced as part of the Dixon sequence. MRI data were analysed using the open-source image analysis software HOROS V 1.1.7 (www.horosproject.org; accessed 21/10/2017) by a single analyst who was blinded to clinical data. Areas of visceral adipose tissue (VAT) were quantified from an axial MRI image at the L4-5 spinal anatomical position.
Assessments were performed in random order at the Clinical Research Facility, King’s College Hospital, London, UK, while MRI imaging took place at Guy’s Hospital, London, UK, with at least 7 days between visits.
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5

Multimodal Brain Imaging Protocol

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Subjects underwent MRI on a 1.5 tesla Siemens scanner. Diffusion-weighted data was acquired using an echo planar imaging sequence (field of view 256x208 mm 2 , matrix 128x104, slice thickness 2 mm, in plane resolution 2x2 mm 2 , repetition time 15 s, echo time 106.2 ms, 32 directions, b value 1000 s/mm 2 , one image without diffusion weighting was obtained). A high-resolution T1-weighted structural image (voxel size 1x1x1 mm 3 ) was acquired to check for gross structural abnormalities, with a threedimensional 'FLASH' sequence (TR 12 ms, TE 5.6ms, flip angle 19 o , with elliptical sampling of k-space, giving a voxel size of 1x1x1 mm 3 in 5.05 min).
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6

High-Resolution MRI of Whole Brain

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Whole brain high-resolution MR images were collected on a Siemens 1.5 Tesla scanner at the MGH Martinos Center. Two sagittal 3D MP-RAGE sequences were used for morphometric analyses (TR/TE/T1/flip = 2.73s/3.39ms/1.0s/7, bandwidth = 190 Hz/pixel, sampling matrix = 256 × 192 pixels, FOV = 256 × 256 mm, effective slice thickness = 1.33 mm on a 170 mm slab of 128 partitions). Images were coded for blind image analysis and transferred to the MGH Center for Morphometric Analysis (CMA) using Cardviews software.
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7

Intraoperative Diffusion Tensor Imaging

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MRI scans were performed using a 1.5 Tesla scanner (Siemens Espree, Erlangen, Germany). The DTI data was acquired with single-shot spin-echo diffusion-weighted echo-planar sequence (TE 147 ms, TR 9400 ms, matrix size 128 × 128, FOV 251 × 251 mm, slice thickness 3 mm). The diffusion-weighting (high b value) was 1000 s/mm 2 . 12 gradient directions were obtained. The voxel size was 1.9 × 1.9 × 3 mm. Applying five averages; the total DTI measurement required 10 min. The anatomic images were obtained by T1WI 3D MPRAGE sequence (TE 3.02 ms, TR 1650 ms, matrix size 256 × 256, FOV 250 × 250 mm, slice thickness 1 mm). Intraoperative DT imaging was performed using the same SS-EPI sequence after tumor removal. Further T1WI MPRAGE scanning was also performed to record changes of brain tissue. All data were transferred to the planning software (iPlan 2.6, BrainLab, Feldkirchen, Germany) for processing. DTI data was directly imported into the iPlan. FA and tensor map were calculated automatically. Anatomic datasets were converted and exported to iPlan using PatXfer 5.2 (BrainLab, Feldkirchen, Germany). These sequences were co-registered by a semiautomatic rigid registration algorithm for further processing.
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8

MRI Acquisition Protocol for Surgical Imaging

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MRI images of all patients were acquired before surgery using a 1.5 Tesla scanner (Siemens Espree, Erlangen, Germany). DICOM images of axial T1CE with a thickness of 1 mm were collected. The parameters for T1CE were as follows, Slice thickness = 1 mm, Field-of-view = 130 mm, Matrix size = 512 × 512 × 176, Flip angle = 15°, Echo time = 3.02 ms, Repetition time = 1,650 ms, and Voxel dimensions = 0.997 × 0.997 × 1 mm3. Coronal and sagittal T1CE images were reconstructed from thin-sliced axial T1CE images with 3D Slicer software (version 4.10, Harvard University, Boston, United States).
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9

CMR Imaging Using Siemens Avanto 1.5T Scanner

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CMR was accomplished using a 1.5-Tesla scanner (Siemens Avanto, Erlangen, Germany) with an 8-element cardiac-phased array receiver surface coil.
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10

Postmortem Brain Sampling for Neuroimaging

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Ten brains (five females with age range of 59–86 years, and five males with age range of 30–75 years, mean age of 65, 8 years) were obtained from the body donor program of the Department of Anatomy at the University Hospital Düsseldorf of the Heinrich-Heine-University in accordance with legal requirements with no indications of neurologic or psychiatric diseases in clinical records. The postmortem delay did not exceed 24–36 h (Table 1). The brains were fixed in 4% buffered formalin (pH 7.4) or Bodian’s fixative for at least 6 months. All brains underwent magnetic resonance imaging on a Siemens 1.5 Tesla scanner (Erlangen, Germany) using a T1-weighted 3D FLASH sequence (flip angle 40°, repetition time TR 40 ms, echo time TE 5 ms). Obtained images were used as an undistorted spatial reference for the 3D-reconstruction of the histological sections as previously described (Bludau et al., 2014 (link)).
Brains were embedded in paraffin and serially sectioned in the coronal plane on a large-scale microtome (thickness of 20 μm). Every 15th section (corresponding to a distance of 300 μm) was mounted on a glass slide covered with gelatin, stained for cell bodies using a silver staining technique (Merker, 1983 (link)), and digitized on a flatbed scanner (resolution of 1,200 dpi). At least every 60th section was analyzed (distance between them of 1.200 μm).
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