Aarhus University Seal / Aarhus Universitets segl

Reliable estimation of capillary transit time distributions using DSC-MRI

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

The regional availability of oxygen in brain tissue is traditionally inferred from the magnitude of cerebral blood flow (CBF) and the concentration of oxygen in arterial blood. Measurements of CBF are therefore widely used in the localization of neuronal response to stimulation and in the evaluation of patients suspected of acute ischemic stroke or flow-limiting carotid stenosis. It was recently demonstrated that capillary transit time heterogeneity (CTH) limits maximum oxygen extraction fraction (OEF(max)) that can be achieved for a given CBF. Here we present a statistical approach for determining CTH, mean transit time (MTT), and CBF using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). Using numerical simulations, we demonstrate that CTH, MTT, and OEF(max) can be estimated with low bias and variance across a wide range of microvascular flow patterns, even at modest signal-to-noise ratios. Mean transit time estimated by singular value decomposition (SVD) deconvolution, however, is confounded by CTH. The proposed technique readily identifies malperfused tissue in acute stroke patients and appears to highlight information not detected by the standard SVD technique. We speculate that this technique permits the non-invasive detection of tissue with impaired oxygen delivery in neurologic disorders such as acute ischemic stroke and Alzheimer's disease during routine diagnostic imaging.

Original languageEnglish
JournalJournal of Cerebral Blood Flow and Metabolism
Volume34
Issue9
Pages (from-to)1511-21
Number of pages11
ISSN0271-678X
DOIs
Publication statusPublished - 2014

    Research areas

  • Animals, Brain, Capillaries, Cerebrovascular Circulation, Humans, Magnetic Resonance Angiography, Microcirculation, Models, Cardiovascular, Oxygen

See relations at Aarhus University Citationformats

ID: 84647411