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Signa excite hdxt scanner

Manufactured by GE Healthcare
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The Signa EXCITE HDxt scanner is a magnetic resonance imaging (MRI) system developed by GE Healthcare. It is designed to provide high-quality imaging for diagnostic and research purposes. The core function of the Signa EXCITE HDxt scanner is to generate detailed images of the body's internal structures using a powerful magnetic field and radio waves.

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Lab products found in correlation

Smartbrush, by Brainlab (1 mentions) Eovist, by Bayer (1 mentions)

Close spelling variants of this product

Signa EXCITE HDxt 3.0 T MR scanner Signa Excite HDxt MR Scanner Signa Excite HDxt Signa HDxt scanner Signa Excite scanner Signa HDxt Signa Excite Signa scanner Scanners

5 protocols using signa excite hdxt scanner

1

Multimodal MRI Neuroimaging Protocol

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All MR imaging was performed on a 3T Signa Excite HDxt scanner (GE Healthcare, Milwaukee, Wisconsin). As part of the standard protocol we included a 3D volumetric T1-weighted inversion recovery spoiled gradient-echo sequence pre- and post-gadolinium (TE = 2.8 ms, TR = 6.5 ms, TI = 450 ms, flip angle = 8°, FOV = 24 cm; 0.93 x 0.93 x 1.2 mm). Our diffusion protocol consisted of a single-shot pulsed-field gradient Stejskal-Tanner EPI sequence with 4 b-values (b = 0, 500, 1500, and 4000 s/mm2) and 1, 6, 6, and 15 unique diffusion directions, respectively (TE = 96 ms, TR = 17 s, flip angle = 8°, FOV = 24 cm; 1.875 x 1.875 x 2.5 mm).
Treiber J.M., White N.S., Steed T.C., Bartsch H., Holland D., Farid N., McDonald C.R., Carter B.S., Dale A.M, & Chen C.C. (2016). Characterization and Correction of Geometric Distortions in 814 Diffusion Weighted Images. PLoS ONE, 11(3), e0152472.
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2

Quantitative Liver MRI Protocol

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Children were asked to fast for 4 hours before the MRI exam and were scanned at 3T (Signa EXCITE HDxt scanner, GE Medical Systems, Waukesha WI) in a supine position with an eight-channel torso phased-array coil centered over the liver. A dielectric pad was placed between the coil and the abdomen. Each MR exam included chemical-shift-encoded MRI-M and MRI-C techniques as illustrated in Figure 1 and described below. Acquisition parameters are summarized in Table 2. Both techniques assumed exponential R2* signal decay and applied the same multi-peak fat spectral model derived from human liver triglyceride composition (28 (link)).
Mamidipalli A., Hamilton G., Manning P., Hong C.W., Park C.C., Wolfson T., Hooker J., Heba E., Schlein A., Gamst A., Durelle J., Paiz M., Middleton M.S., Schwimmer J.B, & Sirlin C.B. (2017). Cross-sectional correlation between hepatic R2* and proton density fat fraction (PDFF) in children with hepatic steatosis. Journal of magnetic resonance imaging : JMRI, 47(2), 418-424.
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3

Preoperative MRI Tractography for Tumor Resection

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Gadolinium MRI data were acquired with a General Electric Signa Excite HDXT scanner (1.5T GE Healthcare, Milwaukee, WI, USA). For each patient, a presurgical brain magnetic resonance imaging (MRI) image was acquired with diffusion tensor imaging (DTI) of 140 T1 slices (1 mm thick) without GAP. After obtaining the images, they were merged and processed with the help of the neuronavigation system (Kick, Curve TM and SmartBrush, BrainLab, Munich, Germany). Information regarding white matter tracts was processed, preventing potential damage during the approach and/or resection. According to the location of the tumor, the following tracts were considered for reconstruction: Aslant’s tract, superior longitudinal fasciculus (SLF), arcuate fasciculus, inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), geniculo-calcarine fasciculus (GCT), corticospinal tract (CST) and thalamocortical tract. A Gadolinium MRI scan and a CT with contrast were performed 24–48 h postoperatively in each case.
Abdala-Vargas N.J., Umana G.E., Patiño-Gomez J.G., Ordoñez-Rubiano E., Cifuentes-Lobelo H.A., Palmisciano P., Ferini G., Viola A., Zagardo V., Casanova-Martínez D., Tomasi O.S., Campero A, & Baldoncini M. (2023). Standardization of Strategies to Perform a Parafascicular Tubular Approach for the Resection of Brain Tumors in Eloquent Areas. Brain Sciences, 13(3), 498.
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4

Liver Donor Imaging with MRI and Eovist

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Ten potential liver donors (6 females, 4 males; mean age of 39.1 ± 6.8 years) were imaged using a 3T MRI system (Signa EXCITE HDxt scanner, GE Medical Systems, Waukesha, WI) in supine position with an eight-channel torso phased-array coil centered over the liver. Intravenous Gd-EOB-DTPA (Eovist, Bayer Healthcare, Whippany, NJ) 0.1 mL/kg was injected at a rate of 1.0 mL/s. Axial breath-hold 3D SPGR and 2D ME SPGR sequences (parameters summarized in Table 1) were obtained through the liver 20 min after contrast injection. For the 2D ME SPGR sequence, six echoes were obtained per repetition time (TR) at nominally out-of-phase and in-phase echo times (TEs). 2D R2* maps were generated inline by the scanner computer using a custom algorithm that assumes exponential decay and corrects for fat-water or fat-fat signal interference effects [5 (link)].
Dehkordy S.F., Fowler K.J., Wolfson T., Igarashi S., Constantino C.P., Hooker J.C., Hong C.W., Mamidipalli A., Gamst A.C., Hemming A, & Sirlin C.B. (2018). Technical report: gadoxetate-disodium-enhanced 2D R2* mapping: a novel approach for assessing bile ducts in living donors. Abdominal radiology (New York), 43(7), 1656-1660.
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5

Liver Fat Quantification in Children

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Children were asked to fast for 4 hours before the MR exam and were scanned at 3T (Signa EXCITE HDxt scanner, GE Healthcare, Waukesha WI) in a supine position with an eight-channel torso phased-array coil centered over the liver. A dielectric pad was placed between the coil and the abdomen. Each MR exam included MRS, MRI-M and MRI-C fat quantification acquisitions.
Haufe W.M., Wolfson T., Hooker C.A., Hooker J.C., Covarrubias Y., Schlein A.N., Hamilton G., Middleton M.S., Angeles J.E., Hernando D., Reeder S.B., Schwimmer J.B, & Sirlin C.B. (2017). Accuracy of PDFF estimation by magnitude-based and complex-based MRI in children with magnetic resonance spectroscopy as a reference. Journal of magnetic resonance imaging : JMRI, 46(6), 1641-1647.
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