Cerebral small vessel disease (SVD) gives rise to one in five strokes worldwide and constitutes a major source of cognitive decline in the elderly. SVD is known to occur in relation to hypertension, diabetes, smoking, radiation therapy and in a range of inherited and genetic disorders, autoimmune disorders, connective tissue disorders, and infections. Until recently, changes in capillary patency and blood viscosity have received little attention in the aetiopathogenesis of SVD and the high risk of subsequent stroke and cognitive decline. Capillary flow patterns were, however, recently shown to limit the extraction efficacy of oxygen in tissue and capillary dysfunction therefore proposed as a source of stroke-like symptoms and neurodegeneration, even in the absence of physical flow-limiting vascular pathology. In this review, we examine whether capillary flow disturbances may be a shared feature of conditions that represent risk factors for SVD. We then discuss aspects of capillary dysfunction that could be prevented or alleviated and therefore might be of general benefit to patients at risk of SVD, stroke or cognitive decline.

The pathophysiology of cerebral ischemia is traditionally understood in relation to reductions in cerebral blood flow (CBF). However, a recent reanalysis of the flow-diffusion equation shows that increased capillary transit time heterogeneity (CTTH) can reduce the oxygen extraction efficacy in brain tissue for a given CBF. Changes in capillary morphology are typical of conditions predisposing to stroke and of experimental ischemia. Changes in capillary flow patterns have been observed by direct microscopy in animal models of ischemia and by indirect methods in humans stroke, but their metabolic significance remain unclear. We modeled the effects of progressive increases in CTTH on the way in which brain tissue can secure sufficient oxygen to meet its metabolic needs. Our analysis predicts that as CTTH increases, CBF responses to functional activation and to vasodilators must be suppressed to maintain sufficient tissue oxygenation. Reductions in CBF, increases in CTTH, and combinations thereof can seemingly trigger a critical lack of oxygen in brain tissue, and the restoration of capillary perfusion patterns therefore appears to be crucial for the restoration of the tissue oxygenation after ischemic episodes. In this review, we discuss the possible implications of these findings for the prevention, diagnosis, and treatment of acute stroke.

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. Keywords: brain ischemia; imaging; kinetic modeling; mathematical modeling; MRI; neuroradiology INTRODUCTION Normal brain function requires a continuous supply of oxygen to meet the metabolic demands of neuroglial activity. 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. Cerebral blood flow is sensitive to regional levels of neuronal activity-known as neurovascular coupling-and methods to detect changes in CBF therefore provide powerful means of mapping brain function. Journal of Cerebral BloodIn disease, measurements of CBF are widely used in the evaluation of patients suspected having acute ischemic stroke or stenoocclusive carotid artery disease. The extent of CBF reduction below the ischemic threshold is thought to predict the development of permanent infarction in acute stroke, 1 while the CBF response to well-defined vasodilator responses is used in the assessment of carotid artery disease severity. 2 The microscopic distribution of CBF in brain tissue is rarely considered in the study of the pathogenesis of brain disorders. We recently demonstrated that the heterogeneity of capillary transit times affect oxygen extraction efficacy in tissue.3 By extending the classic flow-diffusion equation, we showed that the capillary blood mean transit time (MTT) and capillary transit time heterogeneity (CTH) combined determines the maximum oxygen extraction fraction (OEF max ) that can be achieved for a given tissue oxygen tension. In a series of recent papers, we review the putative effects...

A new implementation of the vibrational self-consistent field (VSCF) method is presented on the basis of a second quantization formulation. A so-called active terms algorithm is shown to be a significant improvement over a standard implementation reducing the computational effort by one order in the number of degrees of freedom. Various types of screening provide even further reductions in computational scaling and absolute CPU time. VSCF calculations on large polyaromatic hydrocarbon model systems are presented. Further, it is demonstrated that in cases where distant modes are not directly coupled in the Hamiltonian, down to linear scaling of the required CPU time with respect to the number of vibrational modes can be obtained. This is illustrated with calculations on simple model systems with up to 1 million degrees of freedom.

The considerable prediction improvement accuracy over current state of the art increases the potential for automated decision support in providing recommendations for personalized treatment plans.

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In acute ischemic stroke, critical hypoperfusion is a frequent cause of hypoxic tissue injury: As cerebral blood flow (CBF) falls below the ischemic threshold of 20 mL/100 mL/min, neurological symptoms develop and hypoxic tissue injury evolves within minutes or hours unless the oxygen supply is restored. But is ischemia the only hemodynamic source of hypoxic tissue injury?Reanalyses of the equations we traditionally use to describe the relation between CBF and tissue oxygenation suggest that capillary flow patterns are crucial for the efficient extraction of oxygen: without close capillary flow control, “functional shunts” tend to form and some of the blood’s oxygen content in effect becomes inaccessible to tissue.This phenomenon raises several questions: Are there in fact two hemodynamic causes of tissue hypoxia: Limited blood supply (ischemia) and limited oxygen extraction due to capillary dysfunction? If so, how do we distinguish the two, experimentally and in patients? Do flow-metabolism coupling mechanisms adjust CBF to optimize tissue oxygenation when capillary dysfunction impairs oxygen extraction downstream?Cardiovascular risk factors such as age, hypertension, diabetes, hypercholesterolemia, and smoking increase the risk of both stroke and dementia. The capillary dysfunction phenomenon therefore forces us to consider whether changes in capillary morphology or blood rheology may play a role in the etiology of some stroke subtypes and in Alzheimer’s disease.Here, we discuss whether certain disease characteristics suggest capillary dysfunction rather than primary flow-limiting vascular pathology and how capillary dysfunction may be imaged and managed.

Background and PurposePerfusion weighted imaging (PWI) is inherently unreliable in patients with severe perfusion abnormalities. We compared the diagnostic accuracy of a novel index of microvascular flow-patterns, so-called capillary transit time heterogeneity (CTH) to that of the commonly used delay parameter Tmax in patients with bilateral high grade internal carotid artery stenosis (ICAS).MethodsConsecutive patients with bilateral ICAS ≥ 70%NASCET who underwent PWI were retrospectively examined. Maps of CTH and Tmax were analyzed with a volumetric approach using several thresholds. Predictors of favorable outcome (modified Rankin scale at discharge 0–2) were identified using univariate and receiver operating characteristic (ROC) curve analysis.ResultsEighteen patients were included. CTH ≥ 30s differentiated best between patients with favorable and unfavorable outcome when both hemispheres were taken into account (sensitivity 83%, specificity 73%, area under the curve [AUC] 0.833 [confidence interval (CI) 0.635; 1.000]; p = 0.027). The best discrimination using Tmax was achieved with a threshold of ≥ 4s (sensitivity 83%, specificity 64%, AUC 0.803 [CI 0.585;1.000]; p = 0.044). The highest AUC was found for left sided volume with CTH ≥ 15s (sensitivity 83%, specificity 91%, AUC 0.924 [CI 0.791;1.000]; p = 0.005).ConclusionThe study suggests that CTH is superior to Tmax in discriminating ICAS patients with favorable from non-favorable outcome. This finding may reflect the simultaneous involvement of large vessels and microvessels in ICAS and underscore the need to diagnose and manage both aspects of the disease.