MRI-Based Quantitative Mapping of Oxygen Extraction Fraction in MS

NIH RePORTER · NIH · R01 · $398,013 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY Multiple sclerosis (MS), one of the most common nontraumatic disabling neurological disorders, affects 309 per 100,000 adults in the United States, yet currently no cure exists. This is partly due to a lack of sensitive biomarkers for detecting disease-related changes, which impairs the development of effective treatments. One potential solution to this issue is to image oxygen extraction fraction (OEF), the ratio of oxygen a tissue extracts from the blood. As OEF directly quantifies tissue viability and functional activities, it can serve as a useful biomarker for better understanding, monitoring, and predicting prognosis of neurological disorders including MS. For instance, progressive neurodegeneration is a critical hallmark of MS. Though the comprehensive mechanism is not yet clear, it may be caused by mitochondrial dysfunction and/or sustained inflammation in chronic active MS lesions. Recently, our studies on quantitative mapping of OEF (qmOEF) suggested that the regional mitochondrial dysfunction and lesion inflammation activity can be measured by decreased and increased OEF, respectively. These findings highlight the capability of qmOEF to study progressive neurodegeneration in MS. However, no qmOEF technique is currently available in a routine clinical setting. The reference standard, positron emission tomography (PET), is critically limited in availability and has poor spatial resolution. Moreover, although magnetic resonance imaging (MRI) is widely available, current MRI-based methods suffer from poor sensitivity and clinically impractical data acquisition. Recently, we proposed a novel MRI-based qmOEF technique with high clinical potential. It utilizes a routine sequence available on current MRI scanners and eliminates the need for impractical multiple gas inhalations. By integrating quantitative susceptibility mapping (QSM) modeling of often neglected MRI phase signal and quantitative blood level dependent (qBOLD) modeling of magnitude signal, our model (QSM+qBOLD=QQ) can estimate OEF by distinguishing deoxyheme iron in venous vasculature from other diffusive susceptibility sources. In our preliminary data, we validated QQ against 15O-PET in healthy adults and demonstrated OEF abnormalities in MS, ischemic stroke, brain tumor, dementia, pre-eclampsia, and hydrocephalus. However, for clinical use, the QQ methodology should be improved to ensure accurate OEF measurements as unreliable model assumptions in QQ, including negligible water diffusion and a fixed vasculature (e.g., numerous randomly oriented long cylinders), hinder accurate estimation of OEF. In this project, we aim to establish a clinically readily applicable, validated MRI toolset for qmOEF that is available on every MRI scanner, by improving QQ. We will achieve this through 3 specific aims. Aim 1. Develop a novel, realistic OEF mapping technique (QQ+MR vascular fingerprinting=QQvF). Aim 2. Validate QQvF against 15O PET. Aim 3. Evaluate the feasibility o...

Key facts

NIH application ID
10856206
Project number
1R01NS136369-01
Recipient
STATE UNIVERSITY OF NEW YORK AT BUFFALO
Principal Investigator
Junghun Cho
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$398,013
Award type
1
Project period
2024-04-01 → 2029-03-31