Reliable estimation of capillary transit time distributions using DSC-MRI

Area of Science:

• Neuroimaging
• Medical Physics
• Neurology

Background:

• Cerebral blood flow (CBF) and arterial oxygen concentration traditionally infer regional brain oxygen availability.
• CBF measurements are crucial for localizing neuronal responses and evaluating conditions like ischemic stroke and carotid stenosis.
• Capillary transit time heterogeneity (CTH) was recently found to limit the maximum oxygen extraction fraction (OEF(max)) for a given CBF.

Purpose of the Study:

• To present a novel statistical approach for quantifying CTH, mean transit time (MTT), and CBF using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI).
• To demonstrate the accuracy of this technique in estimating CTH, MTT, and OEF(max) across diverse microvascular flow patterns, even with limited signal-to-noise ratios.

Main Methods:

• Development and application of a statistical method for analyzing DSC-MRI data.
• Utilizing numerical simulations to validate the accuracy and reliability of the proposed technique.
• Comparison with standard singular value decomposition (SVD) deconvolution methods for MTT estimation.

Main Results:

• The proposed statistical approach accurately estimates CTH, MTT, and OEF(max) with low bias and variance.
• The method effectively identifies malperfused tissue in acute stroke patients, offering insights beyond standard SVD techniques.
• MTT estimation using SVD deconvolution is shown to be confounded by CTH.

Conclusions:

• The novel statistical technique provides a robust method for assessing CTH, MTT, and CBF from DSC-MRI data.
• This approach offers superior detection of malperfused tissue compared to conventional methods, particularly in acute stroke.
• The technique holds potential for non-invasive detection of impaired oxygen delivery in neurological disorders like stroke and Alzheimer's disease during routine imaging.