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Electrical conductivity-based contrast imaging for characterizing prostatic tissues: in vivo animal feasibility study
Yong Soo Cho1, Young Hoe Hur2, Hyun Ju Seon1
1Department of Radiology, Chosun University Hospital and Chosun University College of Medicine, 365 Pilmun-daero, Dong-gu, Gwangju, 61453, South Korea.
BMC Urology
|October 23, 2019
Summary
Electrical conductivity-based magnetic resonance (MR) imaging differentiates canine prostate tissues by mapping ion concentrations. This novel technique provides anatomical insights without contrast agents, paving the way for human applications.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Electrical Engineering
Background:
- Electrical conductivity-based magnetic resonance (MR) imaging offers unique tissue contrast derived from ion concentration and mobility.
- This technique may reveal insights into tissue condition not visible with conventional MR imaging.
Purpose of the Study:
- To image the electrical conductivity of normal canine prostate in vivo.
- To evaluate the tissue contrast of conductivity-based MR imaging based on conductivity distribution and anatomical significance.
Main Methods:
- Five healthy beagles underwent MR scanning with electrodes attached to the pelvis.
- Imaging currents were injected in orthogonal directions during MR scanning.
- A multi-spin echo pulse sequence and projected current density algorithm were used to reconstruct conductivity images.
Main Results:
- Conductivity images revealed distinct contrasts among prostatic tissues.
- Conductivity was highest in the central area (11.2% and 25.5% higher than middle and outer areas).
- Anatomically, conductivity was highest in the central zone (7.5% and 17.8% higher than transitional and peripheral zones).
Conclusions:
- Conductivity-based MR imaging successfully differentiates prostatic tissues without contrast media or additional scans.
- The unique contrast of electrical conductivity images provides in situ tissue information.
- This method holds potential for future human imaging applications.
