Literature DB >> 15005312

The effect of layers in imaging brain function using electrical impedance tomograghy.

A D Liston1, R H Bayford, D S Holder.   

Abstract

Electrical impedance tomography (EIT) has promise for imaging brain function with rings of scalp electrodes, but hitherto human images have been collected and reconstructed using a simple algorithm in which the head was modelled as a homogeneous sphere. The purpose of this work was to assess the improvement in image quality which could be achieved by adding layers to represent the cerebro-spinal fluid (CSF), skull and scalp in the forward model employed by the reconstruction algorithm. Solutions to the forward model were produced analytically and using the linear finite element method (FEM). This was undertaken for computer simulated data when a spherical conductivity change of 10%, radius 5 mm, was moved through 29 positions within a head modelled as four concentric spheres of radius 80-92 mm in order to verify the accuracy of the linear FEM by comparison with the analytical method. Test data were also recorded in a 93.5 mm, spherical, saline-filled tank in which the skull was simulated by a hollow sphere of plaster of Paris, 5 mm thick and a 20 x 20 mm right-cylindrical Perspex object, a 100% conductivity decrease, was moved through 39 positions. The best images were achieved by reconstruction with a four- or three-shell analytical model, giving a spatial accuracy of 5.8 +/- 2.2 mm for computer simulated or 14.0 +/- 5.8 mm for tank data. Mean FWHM was 57 mm and 91 mm in the XY-plane and along the z-axis, respectively. Reconstruction with a homogeneous analytical model gave localization errors greater by about 50-300%, but a reduction in FWHM of about 5% of the image diameter. Unexpectedly, reconstruction with FEM models gave poorer results similar to the analytical homogeneous case. This confirms that addition of shells to the forward model improves image quality as expected with an analytical model for reconstruction, but that the FEM method employed, which used a medium mesh and a linear element computation, requires improvement in order to yield the expected benefits.

Entities:  

Mesh:

Year:  2004        PMID: 15005312     DOI: 10.1088/0967-3334/25/1/022

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  7 in total

1.  Quantification of intraventricular hemorrhage with electrical impedance tomography using a spherical model.

Authors:  T Tang; R J Sadleir
Journal:  Physiol Meas       Date:  2011-06-07       Impact factor: 2.833

2.  A robust current pattern for the detection of intraventricular hemorrhage in neonates using electrical impedance tomography.

Authors:  T Tang; Sungho Oh; R J Sadleir
Journal:  Ann Biomed Eng       Date:  2010-03-18       Impact factor: 3.934

3.  Electrode configurations for detection of intraventricular haemorrhage in the premature neonate.

Authors:  R J Sadleir; Te Tang
Journal:  Physiol Meas       Date:  2008-12-15       Impact factor: 2.833

4.  Detection of intraventricular blood using EIT in a neonatal piglet model.

Authors:  R J Sadleir; Te Tang; Aaron S Tucker; Peggy Borum; Michael Weiss
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

Review 5.  Advances in electrical impedance tomography-based brain imaging.

Authors:  Xi-Yang Ke; Wei Hou; Qi Huang; Xue Hou; Xue-Ying Bao; Wei-Xuan Kong; Cheng-Xiang Li; Yu-Qi Qiu; Si-Yi Hu; Li-Hua Dong
Journal:  Mil Med Res       Date:  2022-02-28

6.  A finite element model of electrode placement during stimulus evoked electromyographic monitoring of iliosacral screw insertion.

Authors:  M A Kopec; B R Moed; D W Barnett
Journal:  Open Orthop J       Date:  2008-03-10

7.  A novel 3D-printed head phantom with anatomically realistic geometry and continuously varying skull resistivity distribution for electrical impedance tomography.

Authors:  Jie Zhang; Bin Yang; Haoting Li; Feng Fu; Xuetao Shi; Xiuzhen Dong; Meng Dai
Journal:  Sci Rep       Date:  2017-07-04       Impact factor: 4.379

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.