Literature DB >> 27605037

The coil array method for creating a dynamic imaging volume.

Elliot Smith1, Fabio Freschi1,2, Maurizio Repetto1,2, Stuart Crozier1.   

Abstract

PURPOSE: Gradient strength and speed are limited by peripheral nerve stimulation (PNS) thresholds. The coil array method allows the gradient field to be moved across the imaging area. This can help reduce PNS and provide faster imaging for image-guided therapy systems such as the magnetic resonance imaging-guided linear accelerator (MRI-linac). THEORY: The coil array is designed such that many coils produce magnetic fields, which combine to give the desired gradient profile. The design of the coil array uses two methods: either the singular value decomposition (SVD) of a set of field profiles or the electromagnetic modes of the coil surface.
METHODS: Two whole-body coils and one experimental coil were designed to investigate the method. The field produced by the experimental coil was compared to simulated results.
RESULTS: The experimental coil region of uniformity (ROU) was moved along the z axis as shown in simulation. The highest observed field deviation was 16.9% at the edge of the ROU with a shift of 35 mm. The whole-body coils showed a median field deviation across all offsets below 5% with an eight-coil basis when using the SVD design method.
CONCLUSION: Experimental results show the feasibility of a moving imaging region within an MRI with a low number of coils in the array. Magn Reson Med 78:784-793, 2017.
© 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  PNS; coil array; gradient coil; local encoding

Mesh:

Year:  2016        PMID: 27605037     DOI: 10.1002/mrm.26404

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  1 in total

1.  Switching Circuit Optimization for Matrix Gradient Coils.

Authors:  Stefan Kroboth; Kelvin J Layton; Feng Jia; Sebastian Littin; Huijun Yu; Jürgen Hennig; Maxim Zaitsev
Journal:  Tomography       Date:  2019-06
  1 in total

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