Abnormalities in normal-appearing white matter from which multiple sclerosis lesions arise.

Normal-appearing white matter is far from normal in multiple sclerosis; little is known about the precise pathology or spatial pattern of this alteration and its relation to subsequent lesion formation. This study was undertaken to evaluate normal-appearing white matter abnormalities in brain areas where multiple sclerosis lesions subsequently form, and to investigate the spatial distribution of normal-appearing white matter abnormalities in persons with multiple sclerosis. Brain MRIs of pre-lesion normal-appearing white matter were analysed in participants with new T2 lesions, pooled from three clinical trials: SYNERGY (NCT01864148; n = 85 with relapsing multiple sclerosis) was the test data set; ASCEND (NCT01416181; n = 154 with secondary progressive multiple sclerosis) and ADVANCE (NCT00906399; n = 261 with relapsing-remitting multiple sclerosis) were used as validation data sets. Focal normal-appearing white matter tissue state was analysed prior to lesion formation in areas where new T2 lesions later formed (pre-lesion normal-appearing white matter) using normalized magnetization transfer ratio and T2-weighted (nT2) intensities, and compared with overall normal-appearing white matter and spatially matched contralateral normal-appearing white matter. Each outcome was analysed using linear mixed-effects models. Follow-up time (as a categorical variable), patient-level characteristics (including treatment group) and other baseline variables were treated as fixed effects. In SYNERGY, nT2 intensity was significantly higher, and normalized magnetization transfer ratio was lower in pre-lesion normal-appearing white matter versus overall and contralateral normal-appearing white matter at all time points up to 24 weeks before new T2 lesion onset. In ASCEND and ADVANCE (for which normalized magnetization transfer ratio was not available), nT2 intensity in pre-lesion normal-appearing white matter was significantly higher compared to both overall and contralateral normal-appearing white matter at all pre-lesion time points extending up to 2 years prior to lesion formation. In all trials, nT2 intensity in the contralateral normal-appearing white matter was also significantly higher at all pre-lesion time points compared to overall normal-appearing white matter. Brain atlases of normal-appearing white matter abnormalities were generated using measures of voxel-wise differences in normalized magnetization transfer ratio of normal-appearing white matter in persons with multiple sclerosis compared to scanner-matched healthy controls. We observed that overall spatial distribution of normal-appearing white matter abnormalities in persons with multiple sclerosis largely recapitulated the anatomical distribution of probabilities of T2 hyperintense lesions. Overall, these findings suggest that intrinsic spatial properties and/or longstanding precursory abnormalities of normal-appearing white matter tissue may contribute to the risk of autoimmune acute demyelination in multiple sclerosis.

White matter changes in paediatric multiple sclerosis and monophasic demyelinating disorders.

See Hacohen et al. (doi:10.1093/awx075) for a scientific commentary on this article. Most children who experience an acquired demyelinating syndrome of the central nervous system will have a monophasic disease course, with no further clinical or radiological symptoms. A subset will be diagnosed with multiple sclerosis, a life-long disorder. Using linear mixed effects models we examined longitudinal diffusion properties of normal-appearing white matter in 505 serial scans of 132 paediatric participants with acquired demyelinating syndromes followed for a median of 4.4 years, many from first clinical presentation, and 106 scans of 80 healthy paediatric participants. Fifty-three participants with demyelinating syndromes eventually received a diagnosis of paediatric-onset multiple sclerosis. Diffusion tensor imaging measures properties of water diffusion through tissue, which normally becomes increasingly restricted and anisotropic in the brain during childhood and adolescence, as fibre bundles develop and myelinate. In the healthy paediatric participants, our data demonstrate the expected trajectory of more restricted and anisotropic white matter diffusivity with increasing age. However, in participants with multiple sclerosis, fractional anisotropy decreased and mean diffusivity of non-lesional, normal-appearing white matter progressively increased after clinical presentation, suggesting not only a failure of age-expected white matter development but also a progressive loss of tissue integrity. Surprisingly, patients with monophasic disease failed to show age-expected changes in diffusion parameters in normal-appearing white matter, although they did not show progressive loss of integrity over time. Further analysis demonstrated that participants with monophasic disease experienced different post-onset trajectories in normal-appearing white matter depending on their presenting phenotype: those with acute disseminated encephalomyelitis demonstrated abnormal trajectories of diffusion parameters compared to healthy paediatric participants, as did patients with non-acute disseminated encephalomyelitis presentations associated with lesions in the brain at onset. Patients with monofocal syndromes such as optic neuritis, transverse myelitis, or isolated brainstem syndromes in whom multifocal brain lesions were absent, showed trajectories more closely approximating normal-appearing white matter development. Our findings also suggest the existence of sexual dimorphism in the effects of demyelinating syndromes on normal-appearing white matter development. Overall, we demonstrate failure of white matter maturational changes and progressive loss of white matter integrity in paediatric-onset multiple sclerosis, but also show that even a single demyelinating attack-when associated with white matter lesions in the brain-negatively impacts subsequent normal-appearing white matter development.

Beyond crossing fibers: bootstrap probabilistic tractography using complex subvoxel fiber geometries.

Diffusion magnetic resonance imaging fiber tractography is a powerful tool for investigating human white matter connectivity in vivo. However, it is prone to false positive and false negative results, making interpretation of the tractography result difficult. Optimal tractography must begin with an accurate description of the subvoxel white matter fiber structure, includes quantification of the uncertainty in the fiber directions obtained, and quantifies the confidence in each reconstructed fiber tract. This paper presents a novel and comprehensive pipeline for fiber tractography that meets the above requirements. The subvoxel fiber geometry is described in detail using a technique that allows not only for straight crossing fibers but for fibers that curve and splay. This technique is repeatedly performed within a residual bootstrap statistical process in order to efficiently quantify the uncertainty in the subvoxel geometries obtained. A robust connectivity index is defined to quantify the confidence in the reconstructed connections. The tractography pipeline is demonstrated in the human brain.

3D stochastic completion fields for mapping connectivity in diffusion MRI.

The 2D stochastic completion field algorithm, introduced by Williams and Jacobs [1], [2], uses a directional random walk to model the prior probability of completion curves in the plane. This construct has had a powerful impact in computer vision, where it has been used to compute the shapes of likely completion curves between edge fragments in visual imagery. Motivated by these developments, we extend the algorithm to 3D, using a spherical harmonics basis to achieve a rotation invariant computational solution to the Fokker-Planck equation describing the evolution of the probability density function underlying the model. This provides a principled way to compute 3D completion patterns and to derive connectivity measures for orientation data in 3D, as arises in 3D tracking, motion capture, and medical imaging. We demonstrate the utility of the approach for the particular case of diffusion magnetic resonance imaging, where we derive connectivity maps for synthetic data, on a physical phantom and on an in vivo high angular resolution diffusion image of a human brain.

Rotation invariant completion fields for mapping diffusion MRI connectivity.

Partial differential equations have been successfully used for fibre tractography and for mapping connectivity indices in the brain. However, the current implementation of methods which require 3D orientation to be tracked can suffer from serious shortcomings when invariance to 3D rotation is desired. In this paper we focus on the 3D stochastic completion field and introduce a new methodology to solve the underlying PDE in a manner that achieves rotation invariance. The key idea is to use spherical harmonics to solve the Fokker-Planck equation representing the evolution of the probability density function of a 3D directional random walk. We validate the new approach by presenting improved connectivity indices on synthetic data, on the MICCAI 2009 Fibre Cup phantom and on a biological phantom comprised of two rat spinal chords in a crossing configuration.

Probabilistic anatomical connectivity using completion fields.

Diffusion magnetic resonance imaging has led to active research in the analysis of anatomical connectivity in the brain. Many approaches have been proposed to model the diffusion signal and to obtain estimates of fibre tracts. Despite these advances, the question of defining probabilistic connectivity indices which utilize the relevant information in the diffusion MRI signal to indicate connectivity strength, remains largely open. To address this problem we introduce a novel numerical implementation of a stochastic completion field algorithm, which models the diffusion of water molecules in a medium while incorporating the local diffusion MRI data. We show that the approach yields a valid probabilistic estimate of connectivity strength between two seed regions, with experimental results on the MICCAI 2009 Fibre Cup phantom.