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Validation of conductivity tensor imaging using giant vesicle suspensions with different ion mobilities
- Source :
- BioMedical Engineering OnLine, Vol 19, Iss 1, Pp 1-17 (2020)
- Publication Year :
- 2020
- Publisher :
- BMC, 2020.
-
Abstract
- Abstract Background Electrical conductivity of a biological tissue at low frequencies can be approximately expressed as a tensor. Noting that cross-sectional imaging of a low-frequency conductivity tensor distribution inside the human body has wide clinical applications of many bioelectromagnetic phenomena, a new conductivity tensor imaging (CTI) technique has been lately developed using an MRI scanner. Since the technique is based on a few assumptions between mobility and diffusivity of ions and water molecules, experimental validations are needed before applying it to clinical studies. Methods We designed two conductivity phantoms each with three compartments. The compartments were filled with electrolytes and/or giant vesicle suspensions. The giant vesicles were cell-like materials with thin insulating membranes. We controlled viscosity of the electrolytes and the giant vesicle suspensions to change ion mobility and therefore conductivity values. The conductivity values of the electrolytes and giant vesicle suspensions were measured using an impedance analyzer before CTI experiments. A 9.4-T research MRI scanner was used to reconstruct conductivity tensor images of the phantoms. Results The CTI technique successfully reconstructed conductivity tensor images of the phantoms with a voxel size of $$0.5\times 0.5\times 0.5\hbox { mm}^3$$ 0.5 × 0.5 × 0.5 mm 3 . The relative $$L^2$$ L 2 errors between the conductivity values measured by the impedance analyzer and those reconstructed by the MRI scanner was between 1.1 and 11.5. Conclusions The accuracy of the new CTI technique was estimated to be high enough for most clinical applications. Future studies of animal models and human subjects should be pursued to show the clinical efficacy of the CTI technique.
Details
- Language :
- English
- ISSN :
- 1475925X
- Volume :
- 19
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BioMedical Engineering OnLine
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.637711ad059646a29aa799f8a6a97069
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12938-020-00780-5