C. A. Clark

Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles.

Magnetic resonance diffusion tensor imaging (DTI) provides information about fiber local directions in brain white matter. This paper addresses inference of the connectivity induced by fascicles made up of numerous fibers from such diffusion data. The usual fascicle tracking idea, which consists of following locally the direction of highest diffusion, is prone to erroneous forks because of problems induced by fiber crossing. In this paper, this difficulty is partly overcomed by the use of a priori knowledge of the low curvature of most of the fascicles. This knowledge is embedded in a model of the bending energy of a spaghetti plate representation of the white matter used to compute a regularized fascicle direction map. A new tracking algorithm is then proposed to highlight putative fascicle trajectories from this direction map. This algorithm takes into account potential fan shaped junctions between fascicles. A study of the tracking behavior according to the influence given to the a priori knowledge is proposed and concrete tracking results obtained with in vivo human brain data are illustrated. These results include putative trajectories of some pyramidal, commissural, and various association fibers.

Water diffusion compartmentation and anisotropy at high b values in the human brain

Biexponential diffusion decay is demonstrated in the human brain in vivo using b factors up to 4000 sec mm−2. Fitting of the signal decay data yields values for the slow and fast diffusion components and volume fractions in agreement with previous studies in rat and human brain. In addition, differences in the fitted parameters are demonstrated in the white and gray matter and diffusion anisotropy is demonstrated in both the slow and fast diffusing components. Apparent anisotropy in the component fractions is discussed in terms of directionally dependent exchange rates between the compartments. The lack of a relationship between the estimated contribution to the signal of the fast and slow components and echo time appears to rule out T2 differences in the observed water compartments. Values obtained for the fast diffusion coefficient, including differences between white and gray matter and the degree of anisotropy are compatible with the predictions of extracellular diffusion of water based on tortuosity models and the diffusion of tetramethylammonium ions in rat brain. Magn Reson Med 44:852–859, 2000.

Distortion Correction and Robust Tensor Estimation for MR Diffusion Imaging

This paper presents a new procedure to estimate the diffusion tensor from a sequence of diffusion-weighted images. The first step of this procedure consists of the correction of the distortions usually induced by eddy-current related to the large diffusion-sensitizing gradients. This correction algorithm relies on the maximization of mutual information to estimate the three parameters of a geometric distortion model inferred from the acquisition principle. The second step of the procedure amounts to replacing the standard least squares-based approach by the Geman-McLure M-estimator, in order to reduce outlier-related artefacts. Several experiments prove that the whole procedure highly improves the quality of the final diffusion maps.

Clinical severity in CADASIL related to ultrastructural damage in white matter: in vivo study with diffusion tensor MRI.

BACKGROUND AND PURPOSE CADASIL is a newly recognized cause of subcortical ischemic strokes that progressively leads to dementia associated with pseudobulbar palsy and severe motor disability. This deleterious progression and the severity of clinical presentation are widely variable among affected subjects. The exact role played by MRI white-matter abnormalities, a hallmark of the disease, in the severity of the clinical phenotype remains poorly understood. METHODS To address this issue, we used diffusion tensor imaging (DTI), a new MRI technique highly sensitive to white-matter microstructural changes, in 16 symptomatic patients and 10 age-matched controls. Mean diffusivity and anisotropy of diffusion were measured within hyperintensities identified on T2-weighted images (T2WI) and outside these lesions on 4 slices at the level of centrum semiovale. RESULTS We found a 60% increase of water mean diffusivity and a parallel loss of diffusion anisotropy in hyperintensities identified on T2WI. The same pattern of diffusion changes, but of lesser intensity, was found in the normal-appearing white matter on T2WI. Mean diffusivity in regions with increased signal on T2WI was higher in patients with severe clinical disability compared with those with no or mild deficit (1.33+/-0.11 versus 1.13+/-0.11 10(-3) mm(2)/s, P<0.01). Furthermore, diffusion measured within T2 hyperintensities correlated with both the Mini-Mental State Examination and Rankin scale scores. In patients with a severe clinical status, the increase of water diffusion in these regions exceeded 70% in comparison with values obtained in the normal white matter in control subjects. CONCLUSIONS These results indicate that DTI is able to detect important ultrastructural changes in regions with increased signal on T2WI and within the normal-appearing white matter in CADASIL. The diffusion changes might be related to both neuronal loss and demyelination. The degree of the underlying ultrastructural alterations is related to the severity of the clinical status with a possible threshold level of white-matter damage above which severe neurological impairment may occur in this disease. DTI appears to be a promising technique for monitoring disease progression in CADASIL.

Cerebral Hemodynamics in CADASIL Before and After Acetazolamide Challenge Assessed With MRI Bolus Tracking

BACKGROUND White matter lesions in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) are underlaid by severe ultrastructural changes of the arteriolar wall. Although chronic ischemia is presumed to cause the tissue lesions, the pattern of perfusion abnormalities and hemodynamic reserve in CADASIL, particularly within the white matter, remains unknown. METHODS We used the MRI bolus tracking method in 15 symptomatic patients with CADASIL (5 with dementia) and 10 age-matched control subjects before and 20 minutes after the intravenous injection of acetazolamide (ACZ, 17 mg/kg). Cerebral blood flow (CBF), blood volume (CBV), and mean transit time (MTT) were calculated both in the cortex and in the white matter according to the singular value decomposition technique. Perfusion parameters were obtained in regions of hyperintensities and within the normal-appearing white matter as observed on T2-weighted images. Analysis was performed with both absolute and relative (region/whole brain) values. RESULTS A significant reduction in absolute and relative CBF and CBV was found within areas of T2 hyperintensities in white matter in the absence of significant variations of MTT. This reduction was more severe in demented than in nondemented patients. No significant change in absolute CBF and CBV values was observed in the cortex of patients with CADASIL. A decrease in relative CBF and CBV values was detected in the occipital cortex. After ACZ administration, CBF and CBV increased significantly in both the cortex and white matter of affected subjects, but the increase in absolute CBF was lower within areas of increased signal on T2-weighted images in patients than in the white matter of control subjects. CONCLUSIONS In CADASIL, both basal perfusion and hemodynamic reserve are decreased in areas of T2 hyperintensities in the white matter. This hypoperfusion appears to be related to the clinical severity. The significant effect of ACZ on CBF and CBV suggests that cerebral perfusion might be increased using pharmacological vasodilation in CADASIL.

Towards inference of human brain connectivity from MR diffusion tensor data.

This paper describes a method to infer the connectivity induced by white matter fibers in the living human brain. This method stems from magnetic resonance tensor imaging (DTI), a technique which gives access to fiber orientations. Given typical DTI spatial resolution, connectivity is addressed at the level of fascicles made up by a bunch of parallel fibers. We propose first an algorithm dedicated to fascicle tracking in a direction map inferred from diffusion data. This algorithm takes into account fan-shaped fascicle forks usual in actual white matter organization. Then, we propose a method of inferring a regularized direction map from diffusion data in order to improve the robustness of the tracking. The regularization stems from an analogy between white matter organization and spaghetti plates. Finally, we propose a study of the tracking behavior according to the weight given to the regularization and some examples of the tracking results with in vivo human brain data.

In vivo mapping of the fast and slow diffusion tensors in human brain

Recent studies have shown that the diffusional signal decay in human brain is non‐monoexponential and may be described in terms of compartmentalized water fractions. Diffusion tensor imaging (DTI), which provides information about tissue structure and orientation, typically uses b values up to 1000 s mm−2 so that the signal is dominated by the fast diffusing fraction. In this study b factors up to 3500 s mm−2 are utilized, allowing the diffusion tensor properties of the more slowly diffusing fraction to be mapped for the first time. The mean diffusivity (MD) of the slow diffusion tensor was found to exhibit strong white/gray matter (WM/GM) contrast. Maps depicting the principal direction of the slow tensor indicated alignment with the fast tensor and the known orientation of the WM pathways. Magn Reson Med 47:623–628, 2002.

Decreased hemispheric water mobility in hemiplegic migraine related to mutation of CACNA1A gene

Article abstract We report a reversible reduction of water diffusion in the brain during a prolonged attack of hemiplegic migraine. The patient had a sporadic mutation of the CACNA1A gene. The diffusion changes were observed in the contralateral hemisphere 3 and 5 weeks after the onset of hemiplegia. These results suggest the occurrence of hemispheric cytotoxic edema during severe attacks of hemiplegic aura. The mechanisms underlying such ultrastructural modifications are unknown but an abnormal release of excitatory amino acids can be hypothesized.

Diffusion time dependence of the apparent diffusion tensor in healthy human brain and white matter disease.

The diffusion time dependence of the brain water diffusion tensor provides information regarding diffusion restriction and hindrance but has received little attention, primarily due to limitations in gradient amplitude available on clinical MRI systems, required to achieve short diffusion times. Using new, more powerful gradient hardware, the diffusion time dependence of tensor‐derived metrics were studied in human brain in the range 8–80 ms, which encompasses the shortest diffusion times studied to date. There was no evidence for a change in mean diffusivity, fractional anisotropy, or in the eigenvalues with diffusion time in healthy human brain. The findings are consistent with a model of unrestricted, but hindered water diffusion with semipermeable membranes, likely originating from the extracellular space in which the average extracellular separation is less than 7 microns. Similar findings in two multiple sclerosis plaques indicated that the size of the water diffusion space in the lesion did not exceed this dimension. Magn Reson Med 45:1126–1129, 2001.

Eddy-Current Distortion Correction and Robust Tensor Estimation for MR Diffusion Imaging

This paper presents a new procedure to estimate the diffusion tensor from a sequence of diffusion-weighted images. The first step of this procedure consists of the correction of the distortions usually induced by eddy-current related to the large diffusion-sensitizing gradients. This correction algorithm relies on the maximization of mutual information to estimate the three parameters of a geometric distortion model inferred from the acquisition principle. The second step of the procedure amounts to replacing the standard least squares based approach by the Geman-McLure M-estimator, in order to get rid of outlier related artefacts. Several experiments prove that the whole procedure highly improves the quality of the final diffusion maps.