Toward global tractography.

Diffusion-based tractography is an ill-posed problem, because the step-by-step reconstruction of a fibre bundle trajectory cannot afford any serious mistake in the evaluation of the local fibre orientations. Such evaluation is difficult, however, because the myriad fibres passing through a single voxel follow different directions. Modelling tractography as a global inverse problem is a simple framework which addresses the ill-posed nature of the problem. The key idea is that the results of tractography in the neighbourhood of an ambiguous local diffusion profile can help to infer the local fibre directions. This paper provides an overview of past achievements of global tractography and proposes guidelines for a future research programme in the hope that the potential of the technique will increase the interest of the community.

Automatic fiber bundle segmentation in massive tractography datasets using a multi-subject bundle atlas.

This paper presents a method for automatic segmentation of white matter fiber bundles from massive dMRI tractography datasets. The method is based on a multi-subject bundle atlas derived from a two-level intra-subject and inter-subject clustering strategy. This atlas is a model of the brain white matter organization, computed for a group of subjects, made up of a set of generic fiber bundles that can be detected in most of the population. Each atlas bundle corresponds to several inter-subject clusters manually labeled to account for subdivisions of the underlying pathways often presenting large variability across subjects. An atlas bundle is represented by the multi-subject list of the centroids of all intra-subject clusters in order to get a good sampling of the shape and localization variability. The atlas, composed of 36 known deep white matter bundles and 47 superficial white matter bundles in each hemisphere, was inferred from a first database of 12 brains. It was successfully used to segment the deep white matter bundles in a second database of 20 brains and most of the superficial white matter bundles in 10 subjects of the same database.

Diffusion tensor imaging characteristics of the corpus callosum in mild, moderate, and severe traumatic brain injury.

BACKGROUND AND PURPOSE: The corpus callosum is an important predilection site for traumatic axonal injury but may be unevenly affected in head trauma. We hypothesized that there were local differences in axonal injury within the corpus callosum as investigated with diffusion tensor imaging (DTI), varying among patients with differing severity of traumatic brain injury (TBI). MATERIALS AND METHODS: Ethics committee approval and informed consent were obtained. Ten control subjects (7 men, 3 women; mean age, 37 +/- 9 years) and 39 patients with TBI (27 men, 12 women; 34 +/- 12 years) were investigated, of whom 24 had mild; 9, moderate; and 6, severe TBI. Regions of interest were selected in the callosal genu, body, and splenium to calculate fractional anisotropy (FA), apparent diffusion coefficient (ADC), and the number of fibers passing through. Statistical comparison was made through analysis of variance with the Scheffé post hoc analysis. RESULTS: Compared with controls, patients with mild TBI investigated <3 months posttrauma (n = 12) had reduced FA (P < .01) and increased ADC (P < .05) in the genu, whereas patients with mild TBI investigated > or =3 months posttrauma (n = 12) showed no significant differences. Patients with moderate and severe TBI, all investigated <3 months posttrauma, had reduced FA (P < .001) and increased ADC (P < .01) in the genu compared with controls and reduced FA in the splenium (P < .001) without significant ADC change. CONCLUSION: Mild TBI is associated with DTI abnormalities in the genu <3 months posttrauma. In more severe TBI, both the genu and splenium are affected. DTI suggests a larger contribution of vasogenic edema in the genu than in the splenium in TBI.

White matter abnormalities in mild traumatic brain injury: a diffusion tensor imaging study.

BACKGROUND AND PURPOSE: Traumatic axonal injury is a primary brain abnormality in head trauma and is characterized by reduction of fractional anisotropy (FA) on diffusion tensor imaging (DTI). Our hypothesis was that patients with mild traumatic brain injury (TBI) have widespread brain white matter regions of reduced FA involving a variety of fiber bundles and show fiber disruption on fiber tracking in a minority of these regions. MATERIALS AND METHODS: Ethics committee approval and informed consent were obtained. Twenty-one patients with mild TBI were investigated (men:women, 12:9; mean age +/- SD, 32 +/- 9 years). In a voxel-based comparison with 11 control subjects (men:women, 8:3; mean age, 37 +/- 9 years) using z score analysis, patient regions with abnormally reduced FA were defined in brain white matter. MR imaging, DTI, and fiber tracking characteristics of these regions were described and analyzed using Pearson correlation, linear regression analysis, or the chi(2) test when appropriate. RESULTS: Patients had on average 9.1 regions with reduced FA, with a mean region volume of 525 mm(3), predominantly found in cerebral lobar white matter, cingulum, and corpus callosum. These regions mainly involved supratentorial projection fiber bundles, callosal fibers, and fronto-temporo-occipital association fiber bundles. Internal capsules and infratentorial white matter were relatively infrequently affected. Of all of the involved fiber bundles, 19.3% showed discontinuity on fiber tracking. CONCLUSION: Patients with mild TBI have multiple regions with reduced FA in various white matter locations and involving various fiber bundles. A minority of these fiber bundles show discontinuity on fiber tracking.

MR diffusion tensor imaging and fiber tracking in spinal cord arteriovenous malformations: a preliminary study.

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) of the spinal cord in patients harboring spinal arteriovenous malformations (AVMs) was carried out to evaluate the feasibility of this new technique to determine the displacement of the spinal cord tracts and to correlate morphologic and functional DTI data (fractional anisotropy [FA] and apparent diffusion coefficient [ADC]) with the clinical symptoms. MATERIALS AND METHODS: Nine patients with spinal cord AVMs were investigated at 1.5T using a sagittal spin-echo single-shot echo-planar generalized autocalibrating partially parallel acquisition diffusion-weighted imaging sequence. ADC and FA maps were computed in different regions of interest (both above and below the nidus), and tractography was used to visualize the course of the tracts. The data were correlated with the clinical symptoms and compared with 12 healthy control subjects. RESULTS: At the level of the nidus, tracts were normal, shifted, separated, or interrupted but not intermingled with the nidus. Interruption of the tracts was coherent with the clinical symptoms. In patients with severe neurologic deficits, FA values caudal to the nidus showed a reduced anisotropy consistent with loss of white matter tracts. CONCLUSIONS: We demonstrate that AVMs may interrupt, displace, or separate the fiber tracts and that clinical symptoms may be reflected by the quantitative FA results and the morphologic loss of fibers distant to the lesion. DTI with fiber tracking offers a novel approach to image spinal cord AVMs and may open a window to understand the complex pathophysiology of these lesions.

MR diffusion tensor imaging and fiber tracking in inflammatory diseases of the spinal cord.

PURPOSE: Our aim was to study the fractional anisotropy (FA) variations and the fiber tracking (FT) patterns observed in patients with myelitis. MATERIAL AND METHODS: Fifteen patients with symptomatic myelitis and 11 healthy subjects were prospectively selected. We performed T2-weighted and diffusion tensor imaging on a 1.5T MR scanner. FA and apparent diffusion coefficient maps were computed in both healthy subjects and patients. In each patient, we performed FT to study pathologic aspects on this imaging method. FA data were analyzed by using z-scores. RESULTS: For the healthy subjects, averaged FA values ranged from 0.745 to 0.751. All abnormal areas seen on T2-weighted imaging had a significantly decreased FA value. In 9 patients (60%), FA maps showed decreased FA areas, whereas T2-weighted imaging findings were normal. These areas matched the neurologic deficit in 33%. Eighty percent of patients had multiple decreased FA areas. Five patients (33%) had increased FA values in normal T2-weighted areas. CONCLUSION: We observed specific FA and FT pattern variations in patients with myelitis.

[Functional MRI in brain tumours]. / IRM fonctionnelle en pathologie cérébrale tumorale.

Functional MRI is a technique of imaging which is developing fast as it allows non-aggressive evaluation of brain functions. Diffusion, perfusion and activation are each used to study brain responsiveness to a given task. As a pretherapeutic routine investigation, in brain tumours, it can be helpful as an additional tool to morphological MRI in evaluating the prognosis of patients.

[Diffusion tensor imaging and tractography of central pontine myelinolysis]. / Suivi évolutif d'une myelinolyse centro-pontique en irm de tenseur de diffusion et de tracking de fibres.

OBJECTIVES: To illustrate the value of diffusion tensor imaging and tractography in the diagnosis and follow-up of central pontine myelinolysis. CASE REPORT: We report a case of central pontine myelinolysis in a 29 year old woman, also anorexic, studied using MR Diffusion Tensor Imaging (DTI) and Fibre Tracking (FT) focused on the pons, and compared with the studies of 5 normal volunteers. Tractography showed a swollen aspect of the right corticospinal fiber tract correlating with mild left lower extremity deficit at clinical evaluation. The pontine fibers were posteriorly displaced but intact. The sensory tracts were also intact. Apparent Diffusion Coefficient values were increased and Fractional Anisotropy was decreased in the lesions. Follow up imaging showed persistent abnormal ADC and FA values in the pons although the left cortico-spinal tract returned to normal, consistent with the clinical outcome. CONCLUSION: Diffusion Tensor Imaging MR and Fiber tractography are a new method to analyse white matter tracts. It can be used to prospectively evaluate the location of white matter tract lesions at the acute phase of central pontine myelinolysis and follow up.

MR diffusion tensor imaging and fiber tracking in 5 spinal cord astrocytomas.

Spinal cord astrocytomas are rare neoplasms that can result in alteration of the spinal cord structural integrity, which can be assessed by using diffusion tensor imaging methods. Our objective was to visualize the deformation of the posterior spinal cord lemniscal and corticospinal tracts in 5 patients with low-grade astrocytomas compared with 10 healthy volunteers by using 3D fiber-tracking reconstructions.

Brain MR diffusion tensor imaging and fibre tracking to differentiate between two diffuse axonal injuries.

We report here two cases of diffuse axonal injury (DAI) studied by MR diffusion tensor imaging (DTI) and fibre tracking (FT) focused on the corpus callosum. In one case, DTI and FT pattern matched the diagnosis of broken white matter tracts. In the other case there was a discrepancy between DTI and FT data that showed unaltered white matter tracts with the presence of intra-cellular oedema. These data suggested that DTI and FT are able to differentiate between traumatic cytotoxic oedema and broken fibres in the case of DAI.

Riemannian elasticity: a statistical regularization framework for non-linear registration.

In inter-subject registration, one often lacks a good model of the transformation variability to choose the optimal regularization. Some works attempt to model the variability in a statistical way, but the re-introduction in a registration algorithm is not easy. In this paper, we interpret the elastic energy as the distance of the Green-St Venant strain tensor to the identity, which reflects the deviation of the local deformation from a rigid transformation. By changing the Euclidean metric for a more suitable Riemannian one, we define a consistent statistical framework to quantify the amount of deformation. In particular, the mean and the covariance matrix of the strain tensor can be consistently and efficiently computed from a population of non-linear transformations. These statistics are then used as parameters in a Mahalanobis distance to measure the statistical deviation from the observed variability, giving a new regularization criterion that we called the statistical Riemannian elasticity. This new criterion is able to handle anisotropic deformations and is inverse-consistent. Preliminary results show that it can be quite easily implemented in a non-rigid registration algorithms.