Pelvic phased array coil

Manufactured by GE Healthcare

Sourced in United States

The Pelvic phased-array coil is a medical imaging device designed for use in magnetic resonance imaging (MRI) procedures. It is a specialized component that is placed around the patient's pelvis to enhance the quality and resolution of the acquired images. The coil's primary function is to improve the signal-to-noise ratio, which is a critical factor in producing high-quality MRI images for diagnostic purposes.

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Lab products found in correlation

Endorectal coil, by Bayer (1 mentions)

2 protocols using pelvic phased array coil

Multiparametric MRI Protocol for Prostate Cancer Imaging

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mpMRI studies were performed with a 3.0 T whole-body MR scanner (GE Healthcare;
Waukesha, WI, USA). All patients were imaged in a supine position using a body
coil for excitation, and a pelvic phased-array coil (GE Healthcare; Waukesha,
WI, USA) and an endorectal coil (Medrad; Pittsburgh, PA, USA) for signal
reception. After a three-dimensional localizer scan, axial T2-weighted and
diffusion-weighted MR images were obtained. Dynamically contrast enhanced images
were also acquired. Protocol details are given in Table 1.

Baghdanian A.A., Kim Y.J., Baghdanian A.H., Nguyen H.N., Shinohara K, & Westphalen A.C. (2019). Differences in negative predictive value of prostate MRI based in men with suspected or known cancer. Radiologia Brasileira, 52(5), 281-286.

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Prostate MRI Imaging Protocol

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All MR examinations were carried out on a 1.5 Tesla MR scanner (Signa TM; GE Medical Systems, Milwaukee, WI, USA) using a pelvic phased-array coil (GE Medical Systems). All routine prostate MR examinations followed standardised protocols. T2-weighted turbo-spin-echo images were obtained in the axial, sagittal, and coronal planes without fat suppression with TR: 3500 ms; TE: 85 ms; FOV: 240 mm×240 mm; matrix: 320×256; slice thickness: 4 mm with no gap; number of signals acquired: 4.

Zhao K., Wang C., Hu J., Yang X., Wang H., Li F., Zhang X., Zhang J, & Wang X. (2015). Prostate cancer identification: quantitative analysis of T2-weighted MR images based on a back propagation artificial neural network model. Science China. Life sciences, 58(7).

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