Quantitative characterization of human subcortical hemodynamic response

NIH RePORTER · NIH · K25 · $144,317 · view on reporter.nih.gov ↗

Abstract

Project summary Subcortical human brain regions play critical roles in functions from homeostasis to cognition. However, there has been a dearth of research on full assessments of human subcortical health. Quantitative characterization of subcortical responses has a great potential to unveil the mechanisms of various neurodegenerative disorders including Alzheimer's, Huntington's, and Parkinson's Disease and cerebrovascular pathology such as traumatic brain injury (TBI). Here, we use functional magnetic resonance imaging (fMRI) to measure the blood oxygen level dependent (BOLD) response in subcortical regions. We will create simple multisensory integration tasks that produce BOLD response evoked by this brief brain activation – so called BOLD hemodynamic response function (HRF). We will also use various MRI methods such as proton-density weighted imaging (PDWI), and diffusion tensor imaging (DTI) for structural assessments. BOLD HRF combined with PDWI and DTI will enable remarkably complete assessments of subcortical neurovascular health, including quantification of nuclear volumes, white matter connectivity, and correlations among these metrics. In the proposed research study, we will obtain health control database for this novel metrics. We will develop a novel biomechanical transport model to predict underlying cerebral blood flow and oxygen metabolism corresponding to BOLD HRFs. We will also develop a simple but effective linear flow model based on an electrical circuit analogy to show mechanisms of blood flow response driven by local neural activity. This flow network model will be validated with flow measurement from arterial spin labelling perfusion MR imaging. The proposed model will address a critical gap in our knowledge of subcortical cerebrovascular physiology. We will test our measurement and modeling schemes for characterization of subcortical HRFs in the mild traumatic brain injury (TBI) population. This will demonstrate the feasibility of our metrics as clinical diagnostic tools. The proposed experimental and modeling schemes can be applied more broadly to other brain regions, such as cerebral cortex. It will be a very effective and reliable diagnostic tools, especially for neurological disorders and cerebrovascular pathology that cause functional deficits without structural abnormality, such as subarachnoid hemorrhage, early stage Alzheimer's disease, and mild cognitive impairment.

Key facts

NIH application ID
9843719
Project number
5K25HL131997-04
Recipient
BAYLOR COLLEGE OF MEDICINE
Principal Investigator
JungHwan Kim
Activity code
K25
Funding institute
NIH
Fiscal year
2020
Award amount
$144,317
Award type
5
Project period
2017-01-01 → 2022-01-09