Signa pioneer 3.0t

Manufactured by GE Healthcare

Sourced in United Kingdom, United States

The Signa Pioneer 3.0T is a magnetic resonance imaging (MRI) system manufactured by GE Healthcare. It operates at a field strength of 3.0 Tesla and is designed to provide high-quality diagnostic images for a variety of medical applications.

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Lab products found in correlation

D8 advance, by Bruker (1 mentions) Agilent icpoes730, by Agilent Technologies (1 mentions) Thermo escalab 250xi, by Thermo Fisher Scientific (1 mentions) Zeta sizer nano zs90, by Thermo Fisher Scientific (1 mentions) Jem 2100f, by JEOL (1 mentions) Su8020, by Hitachi (1 mentions)

4 protocols using signa pioneer 3.0t

MRI Assessment of Temporal Muscle Thickness

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We collected data of age, sex, height, weight, and body mass index (BMI). We used SIGNA Pioneer 3.0T (GE Healthcare Life Sciences, Buckinghamshire, England) by a 24-channel head-neck coil and acquired MR images. We measured TMT on an axial plane of the T1-weighted image (T1WI) in the previously reported way.[39 ] Predefined anatomical landmarks, such as the Sylvian fissure (anterior-posterior orientation) and the orbital roof (craniocaudal orientation), were used to guarantee a high reproducibility of TMT values. Two investigators measured the TMT using SYNAPSE V 4.1.5 imaging software (Fujifilm Medical, Tokyo, Japan). TMT was assessed on both sides in each individual, and the mean TMT was calculated by summing up those measurements and dividing them by two. There were no individuals with muscle edema, atrophy due to craniotomy or radiation therapy, trigeminal nerve disease, nor myopathy, which might be related to smaller TMT.
According to the Fazekas scale, we also evaluated periventricular hyperintensity (PVH) on fluid-attenuated inversion recovery images.[9 (link)] We also counted the number of microbleeds on the T2* image and detected intracranial cerebral aneurysm on magnetic resonance angiography.

Katsuki M., Narita N., Sasaki K., Sato Y., Suzuki Y., Mashiyama S, & Tominaga T. (2021). Standard values for temporal muscle thickness in the Japanese population who undergo brain check-up by magnetic resonance imaging. Surgical Neurology International, 12, 67.

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Resting-State fMRI Processing Protocol

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The MRI data were obtained from a GE Signa Pioneer 3.0T magnetic resonance scanner at the Third People’s Hospital of Foshan (Foshan Mental Health Center), Guangdong Province. A high-resolution T1-weighted structural image was obtained using a 3D-T1WI sequence, and resting-state data were collected using a GRE-SS-EPI sequence. The data underwent preprocessing using DPABI_V6.1, including removal of the first 10 time points, slice timing correction, realignment, normalization, smoothing, covariate regression, and band-pass temporal filtering (0.01–0.08 Hz). The fALFF analysis employed fast Fourier transform (FFT) to calculate power spectra and compute the square root of the power spectrum within the 0.01–0.08 Hz range to obtain fALFF values. The fALFF value represents the ratio of the power spectrum within the low-frequency range to that within the entire frequency range [30 (link)]. Only the rs-fMRI signals within the filtered slow-5 (0.01–0.027 Hz) and slow-4 (0.027–0.073 Hz) frequency bands were retained for subsequent analysis. Data quality control was performed using DPABI’s Quality Control program, discarding data with head motion exceeding 2.5 mm or rotation angles exceeding 2.5°.

Chen W., Liang J., Qiu X., Sun Y., Xie Y., Shangguan W., Zhang C, & Wu W. (2024). Differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognitive function between untreated major depressive disorder and schizophrenia with depressive mood patients. BMC Psychiatry, 24, 313.

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Diffusion Kurtosis Imaging on 3T MRI

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MRI acquisition was performed on 3T MR scanner (GE Signa Pioneer 3.0T). Thirty minutes before examination, all participants were given chloral hydrate (0.5 ml/kg) enemas. For stable image quality, earplugs with cotton balls were used to keep them from noise from the machine. After routine sequences scan, axial DKI was performed on all participants. The scanning parameters were: TR/TE = 8,200 ms/2.3 ms, FOV = 200 mm×200 mm, acquisition matrix = 256 × 256, NEX = 1, slices thickness = 4 mm, number of slices = 27; gradient values b: 0, 1,000 and 2,000 s/mm²; scanning time = 7 min 23 s. All subjects had no apparent structural damage, who were examined by two radiologists based on conventional MRI images.

He X., Zhao X., Sun Y., Geng P, & Zhang X. (2023). Application of TBSS-based machine learning models in the diagnosis of pediatric autism. Frontiers in Neurology, 13, 1078147.

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Comprehensive Multi-Technique Characterization of Magnetic Nanoparticles

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The morphology and
particle size of the NPs were observed by field-emission TEM (JEM
2100F, JEOL, Japan) and field-emission scanning electron microscopy
(SEM) (SU8020, Hitachi, Japan). The active functional groups modified
on the surface of the particles were analyzed using a Fourier transform
infrared (FT-IR) spectrometer (Nicolet IS10, Nicolet, USA). The hydrodynamic
size and the surface potential were measured by dynamic light scattering
(Zetasizer Nano ZS90, Thermo Fisher, USA) and ζ potential analysis,
respectively. The concentration of Fe³⁺ was measured via
inductively coupled plasma atomic emission spectrometry (ICP-AES)
(Agilent ICPOES730, Agilent, USA). The ionic valency and crystal morphology
of the NPs were separately analyzed through X-ray photoelectron spectroscopy
(XPS) (Thermo ESCALAB 250Xi, Thermo Fisher, USA) and X-ray powder
diffraction (XRPD) (Bruker D8 ADVANCE, Bruker, Germany). A vibrating-sample
magnetometer (VSM) (SQUID-VSM MPMS-3, Quantum Design, USA) was employed
to measure the saturation magnetization value (M_s). Moreover, the characteristics of the element distribution
were analyzed by energy-dispersive spectroscopy (EDS), and MRI (SIGNA
Pioneer 3.0-T, GE, USA) was adopted for image acquisition and signal
analysis of different MRI sequences.

Hu F., Wang D., Ma X., Hu T., Yue Y., Tang W., Wu P., Tong T, & Peng W. (2023). Concurrent Dual-Contrast Enhancement Using Fe3O4 Nanoparticles to Achieve a CEST Signal Controllability. ACS Omega, 8(27), 24153-24164.

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