Discovery ste pet scanner

Manufactured by GE Healthcare

The Discovery STE PET scanner is a medical imaging device manufactured by GE Healthcare. It is designed to perform positron emission tomography (PET) scans, which are used to detect and diagnose various medical conditions by measuring the distribution of radioactive tracers in the body.

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Matlab, by MathWorks (2 mentions)

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Discovery STE scanner Discovery STE Scanners

3 protocols using discovery ste pet scanner

In Vivo Quantification of Dopamine D2/3 Receptors

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[¹⁸F]-Fallypride ((S)-N-[(1-allyl-2-pyrrolidinyl)methyl]-5-(3[¹⁸F]fluoropropyl)-2,3-dimethoxybenzamide) was produced in the radiochemistry laboratory attached to the PET unit at Vanderbilt University Medical Center, following synthesis and quality control procedures described in the US Food and Drug Administration IND 47 245. All the data were collected on the same GE Discovery STE PET scanner.
Serial scan acquisition was started simultaneously with a 5.0 mCi (185 MBq) slow bolus injection of DA D2/3 tracer [¹⁸F]-Fallypride (specific activity >3000 Ci mmol⁻¹). Computed tomographic scans were collected for attenuation correction before each of the three emission scans, which together lasted approximately 3.5 h with two breaks for subject comfort. Acquisition times for the dynamic PET scans were the same across all studies and have been reported previously.^{51 (link)}

Smith C.T., Dang L.C., Buckholtz J.W., Tetreault A.M., Cowan R.L., Kessler R.M, & Zald D.H. (2017). The impact of common dopamine D2 receptor gene polymorphisms on D2/3 receptor availability: C957T as a key determinant in putamen and ventral striatum. Translational Psychiatry, 7(4), e1091-.

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PET Imaging for Quantitative Analysis

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[18F]FDG-PET scans were acquired using a Discovery STE PET scanner (3.27 mm thickness; 5.55 mm in-plane FWHM), manufactured by GE Healthcare. The [18F]FDG-PET acquisition procedures conformed to the European Association of Nuclear Medicine guidelines [19 (link)]. Static emission images were acquired 45 min after injecting 185–250 MBq of [18F]FDG via a venous cannula, with 15-min scan duration. Data obtained from steady-state static [18F]FDG-PET acquisition were demonstrated to be comparable to the [18F]FDG-PET data obtained from dynamic quantitative acquisition procedures [20 (link)].
All images were reconstructed using an ordered subset-expectation maximization algorithm. Attenuation correction was based on CT scans. Each reconstructed image was visually inspected to check for major artifacts. Image pre-processing was performed using SPM5 software (http://www.fil.ion.ucl.ac.uk/spm/software/ spm5/), running in Matlab (MathWorks Inc., Sherborn, MA, USA. Images were spatially smoothed with an isotropic 3D Gaussian kernel (FWHM 8–8–8 mm). Global mean scaling was applied to each image in order to account for between-subject uptake variability [21 (link)].

Caminiti S.P., Sala A., Iaccarino L., Beretta L., Pilotto A., Gianolli L., Iannaccone S., Magnani G., Padovani A., Ferini-Strambi L, & Perani D. (2019). Brain glucose metabolism in Lewy body dementia: implications for diagnostic criteria. Alzheimer's Research & Therapy, 11, 20.

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Standardized [18F]FDG-PET Acquisition and Preprocessing

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The [18F]FDG-PET scans were acquired using a Discovery STE PET scanner (3.27 mm thickness; 5.55 mm in-plane full width at half maximum (FWHM)), manufactured by GE Healthcare. The [18F]FDG-PET acquisition procedures conformed to the European Association of Nuclear Medicine guidelines^{69 (link)}. Static emission images were acquired 45 min after injecting 185–250 MBq of [18F]FDG via a venous cannula, with scan duration of 15 min.
Uniform reconstruction protocols were applied in order to factor out possible sources of variability. All images were reconstructed using an ordered subset-expectation maximization algorithm (OSEM). Attenuation correction was based on CT scans. Each reconstructed image was visually inspected in order to check for major artefacts, i.e. defective image uniformity/orientation or attenuation correction due to mismatch between CT and PET images.
Images underwent general pre-processing procedures, using the MATLAB (Mathworks Inc., Sherborn, Mass., USA) based software SPM5 (http://www.fil.ion.ucl.ac.uk/spm/software/SPM5/). Each image was first normalized to a [18F]FDG-PET specific template registered to the MNI standard space^{70 (link)} and spatially smoothed with an 8 mm isotropic 3D Gaussian FWHM kernel. Images were then proportionally scaled to the global mean.

Sala A., Caminiti S.P., Presotto L., Premi E., Pilotto A., Turrone R., Cosseddu M., Alberici A., Paghera B., Borroni B., Padovani A, & Perani D. (2017). Altered brain metabolic connectivity at multiscale level in early Parkinson’s disease. Scientific Reports, 7, 4256.

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