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Details of Grant 

EPSRC Reference: EP/P006833/1
Title: Cerebral Blood Flow Imaging based on 3D Electrical Impedance Tomography
Principal Investigator: Jia, Dr J
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Sch of Engineering
Organisation: University of Edinburgh
Scheme: First Grant - Revised 2009
Starts: 01 February 2017 Ends: 31 May 2018 Value (£): 100,894
EPSRC Research Topic Classifications:
Med.Instrument.Device& Equip.
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
04 Oct 2016 Engineering Prioritisation Panel Meeting 4 October 2016 Announced
Summary on Grant Application Form
Cerebral Blood Flow (CBF) is an importance marker to indicate the status of blood perfusion in the brain. The change of CBF is always associated with brain disease and disorder, for instance, stroke. Imaging is critical for human brain research. Various clinical neuroimaging equipment allows measurement of regional CBF, however, their temporal resolution can only reach the scale of seconds, which is not fast enough to monitor the rapid change of CBF. In addition, expensive operation cost of these equipment limits the availability of continuous bedside online monitoring.

This project aims to develop a novel approach of imaging CBF using 3D Electrical Impedance Tomography (EIT). Since the electrical conductivity of blood has the distinctive difference with that of other brain tissue, EIT is able to noninvasively produce the 3D images of the electrical conductivity distribution in the brain with 2-millisecond temporal resolution. Pioneering research has been carried out and the results demonstrated EIT was a promising technique for brain imaging. Following three objectives are proposed to improve EIT's performance: (1) To explore the rich spectroscopic information of brain tissue and select optimal working frequency for EIT; (2) To develop advanced image reconstruction algorithm to improve image resolution; (3) To compute 3D velocity field of CBF from series EIT images. These objectives will be implemented in four work packages: (1) Wideband multifrequency EIT based on Chirp signal and wavelet transform; (2) 3D brain image reconstructions using sparsity constraint as prior information; (3) 3D Velocity field of CBF using voxel-to-voxels cross-correlation algorithm; (4) Validation of system performance on realistic head-shaped phantom.

The proposed method could potentially be used to diagnose brain diseases (e.g. stroke, epilepsy, brain tumours), monitor cerebral activities (e.g. Non-invasive measurement of cerebral perfusion in traumatic brain injury), and learn more about the human cognitive process (e.g. increased understanding and early identification of dementia). Ultimately this research will lead to new insights into brain diseases and brain function.

Key Findings
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Potential use in non-academic contexts
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