Discovery mr750 3.0t mr scanner

Manufactured by GE Healthcare

Sourced in United States

The Discovery MR750 3.0T MR scanner is a magnetic resonance imaging (MRI) system manufactured by GE Healthcare. It is designed to acquire high-quality images of the human body using a 3.0 Tesla (3.0T) static magnetic field.

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Lab products found in correlation

8 channel head receiver coil, by GE Healthcare (1 mentions)

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3 protocols using discovery mr750 3.0t mr scanner

Multiparametric MRI in Prostate Cancer Diagnosis

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T2w MRI provides an excellent depiction of prostate anatomy with lower signal intensity in prostate cancer. [24 (link)] Diffusion Weighted Imaging (DWI) is sensitive to water molecule diffusion and the derived Apparent Diffusion Coefficient (ADC) values are significantly lower in tumor than in normal prostate due to restricted water diffusion. The lower the ADC value, the greater the chance of diagnosing Gleason score (GS) 7 disease [25 (link)-27 (link)]. Dynamic contrast enhanced (DCE)-MRI has also been applied to discriminate normal from malignant prostate tissues, with earlier and greater enhancement followed by washout seen in the latter. DCE-MRI measures vascularity and hence angiogenesis. Both DWI and DCE have a relatively high sensitivity and specificity for prostate cancer [25 (link), 28 (link)-30 (link)]. mpMRI that includes T2-weighted, T1 non-contrast, DCE-MRI, and DWI sequences results in higher sensitivity, specificity and accuracy of tumor localization [30 (link), 31 (link)].
mpMRI of the prostate was performed on a Discovery MR750 3.0T MR scanner (GE Medical Systems, Milwaukee, WI, USA) with 32-channel phased array pelvis coil. A typical exam consisted of:

Stoyanova R., Pollack A., Takhar M., Lynne C., Parra N., Lam L.L., Alshalalfa M., Buerki C., Castillo R., Jorda M., Ashab H.A., Kryvenko O.N., Punnen S., Parekh D.J., Abramowitz M.C., Gillies R.J., Davicioni E., Erho N, & Ishkanian A. (2016). Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies. Oncotarget, 7(33), 53362-53376.

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Neuroimaging Protocol for LHON Study

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The MRI data were obtained on a GE Discovery MR750 3.0T MR scanner (GE Healthcare, Waukesha, WI, USA) with an 8-channel head receiver coil. The routine MRI was initially performed to exclude subjects with brain and spinal abnormalities. High-resolution 3D T1-weighted images were acquired using a brain volume (BRAVO) sequence with parameters as follows: repetition time (TR) = 8.2 ms, echo time (TE) = 3.2 ms, inversion time (TI) = 450 ms, matrix size = 256 × 256, field of view (FOV) = 256 mm × 256 mm, flip angle = 12°, slice thickness = 1 mm, and 176 slices with no gap. The resting-state functional MRI (fMRI) images were obtained using a single-shot gradient-echo echo-planar imaging sequence: TR = 2,000 ms, TE = 30 ms, flip angle = 90 degree, matrix = 64 × 64, FOV = 22 × 22 cm, slice thickness =3.4 mm, gap = 1.0 mm, 33 slices, interleaved transverse slices, and 210 volumes. All subjects were asked to keep awake with eyes closed and heads static during the fMRI scan. One patient with chronic LHON and one sighted control were excluded from the imaging analysis due to poor MRI data quality.

Tian Q., Wang L., Zhang Y., Fan K., Liang M., Shi D., Qin W, & Ding H. (2022). Brain Gray Matter Atrophy and Functional Connectivity Remodeling in Patients With Chronic LHON. Frontiers in Neuroscience, 16, 885770.

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MRI-Based Rectal Cancer Treatment Workflow

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The study cohort consisted of 90 patients diagnosed with rectal cancer from April 2018 to March 2021 at Peking University People's Hospital (PUPH) and 19 patients diagnosed with rectal or prostate cancer in public datasets from three different Swedish radiotherapy departments [28] . Enough patient data of rectal cancer with consistent standards can be provided in this center. One of the aim of this work is to build an MR-only workflow for rectal cancer treatment. The data acquisition parameters are shown in Table 1.
The age distribution of patients was 43-83 years in PUPH cohort. CT scanning was performed with a Philips 16-row large-aperture analog positioning machine with a flat table top. Scan parameters: 140 kV, 280 mAs, layer thickness 3 mm. MRI of the pelvis was performed using a GE Discovery MR750 3.0T MR scanner with the curved table top. The scanning sequence and parameters are as follows: High-resolution non-fat-suppressed fast recovery fast spin-echo (FRFSE) T2-weighted imaging [29] , and the registration results were revised by an experienced physician.
The three-fold cross-validation was used in this study. The specific division of data is as follows: 30 cases were randomly selected from PUPH cohort and one center was picked from public datasets as test datasets and the rest data served as train datasets in each fold.

Li X., Jia L., Lin F., Chai F., Liu T., Zhang W., Wei Z., Xiong W., Li H., Zhang M, & Wang Y. (2024). Synthetic CT generation for pelvic cases based on deep learning in multi-center datasets. Radiation oncology (London, England), 19(1).

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