32 channel dstream head coil

Manufactured by Philips

The 32-channel dStream head coil is a specialized piece of lab equipment designed for magnetic resonance imaging (MRI) applications. It is an integral component of MRI systems, responsible for the acquisition of high-quality images of the human head and brain. The coil's primary function is to transmit and receive radiofrequency (RF) signals, enabling the MRI system to generate detailed, high-resolution images for diagnostic and research purposes.

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Lab products found in correlation

Achieva xt mri scanner, by Philips (1 mentions) Ingenia cx mri, by Philips (1 mentions) Ingenia cx mri scanner, by Philips (1 mentions)

3 protocols using 32 channel dstream head coil

Functional MRI of the Locus Coeruleus

Cited 2 times

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MRI data were acquired on a 3 T Philips Achieva XT MRI scanner (Amsterdam, the Netherlands) using a 32‐channel dStream head coil across four sessions. Single‐shot, 2D gradient echo‐planar images (EPI) were acquired in 33 slices oriented perpendicular to the floor of the fourth ventricle and to the longitudinal extent of the LC (Keren, Lozar, Harris, Morgan, & Eckert, 2009 (link)): 2 × 2 mm in‐plane resolution, 3 mm slice thickness (no gaps), FOV 192 × 192 × 99 mm. TR = 2 s; echo time [TE] = 27.62 ms; flip angle = 76.1°; SENSE acceleration factor = 3.0; bandwidth = 2,213 Hz/pixel. A structural T1‐weighted scan was acquired for anatomical co‐registration (voxel size: 1 × 1 × 1 mm³, TR = 8.13 ms, TE = 3.7 ms, flip angle = 8°). A B0‐field map was acquired for unwarping (voxel size: 2 × 2 × 2 mm³, TR = 10.85 ms, TE = 3.03, flip angle = 8°). Slices were acquired sequentially in the ascending (foot to head) direction.
We chose anisotropic voxels and the above orientation of the imaging volume for EPI to optimize spatial sampling for the LC (for details, see de Gee et al., 2017 (link)). The LC is an elongated structure with small diameter (a few millimeters) and comparably large longitudinal extent (~15 mm) along the floor of the fourth ventricle (Betts et al., 2019 (link)). The rationale was that the LC was the smallest brainstem nucleus to be assessed here.

Colizoli O., de Gee J.W., van der Zwaag W, & Donner T.H. (2021). Functional magnetic resonance imaging responses during perceptual decision‐making at 3 and 7 T in human cortex, striatum, and brainstem. Human Brain Mapping, 43(4), 1265-1279.

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Multimodal MRI Acquisition Protocol

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All MRI data were acquired with a 3-Tesla Philips INGENIA CX MRI scanner with a 32-channel dStream head coil. BOLD-fMRI data were collected using single-shot gradient echo type echo planar imaging. The acquisition parameters were as follows: TR = 2000 ms, TE = 30 ms, and flip angle = 90°. During the same session, DTI data were acquired using a single-shot EPI sequence with 32 diffusion directions and b-value of 800. To provide co-registration of functional images, 3D high-resolution T1-weighted images were also acquired. Scan acquisition parameters were as follows: TR = 8.2 ms, TE = 3.7 ms, and flip angle = 8°.

Frizzell T.O., Phull E., Khan M., Song X., Grajauskas L.A., Gawryluk J, & D’Arcy R.C. (2021). Imaging functional neuroplasticity in human white matter tracts. Brain Structure & Function, 227(1), 381-392.

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Multimodal Neuroimaging Protocol for Brain Imaging

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MRI scans were acquired from using a 3 Tesla Philips Ingenia CX MRI scanner with a 32-channel dStream head coil. Functional MRI images were acquired using an FFE single-shot GRE-EPI sequence. The acquisition parameters were as follows: TR = 2,000 ms, TE = 30 ms, and flip angle = 90°. Data were collected with an in-plane resolution of 3 × 3 mm and slice thickness 3 mm with matrix dimensions of 80 × 80 voxels and 36 slices.
High-resolution T1-weighted images were collected at each session for co-registration of functional images. The acquisition parameters were as follows: TR = 8.2 ms, TE = 3.7 ms, and flip angle = 8°. Data were collected with an in-plane resolution of 1 × 1 mm and slice thickness of 1 mm with matrix dimensions of 288 × 288 voxels and 213 slices.

Frizzell T.O., Grajauskas L.A., Liu C.C., Ghosh Hajra S., Song X, & D’Arcy R.C. (2020). White Matter Neuroplasticity: Motor Learning Activates the Internal Capsule and Reduces Hemodynamic Response Variability. Frontiers in Human Neuroscience, 14, 509258.

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