440 research outputs found

    T2 lesion location really matters: a 10 year follow-up study in primary progressive multiple sclerosis

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    Objectives: Prediction of long term clinical outcome in patients with primary progressive multiple sclerosis (PPMS) using imaging has important clinical implications, but remains challenging. We aimed to determine whether spatial location of T2 and T1 brain lesions predicts clinical progression during a 10-year follow-up in PPMS. Methods: Lesion probability maps of the T2 and T1 brain lesions were generated using the baseline scans of 80 patients with PPMS who were clinically assessed at baseline and then after 1, 2, 5 and 10 years. For each patient, the time (in years) taken before bilateral support was required to walk (time to event (TTE)) was used as a measure of progression rate. The probability of each voxel being ‘lesional’ was correlated with TTE, adjusting for age, gender, disease duration, centre and spinal cord cross sectional area, using a multiple linear regression model. To identify the best, independent predictor of progression, a Cox regression model was used. Results: A significant correlation between a shorter TTE and a higher probability of a voxel being lesional on T2 scans was found in the bilateral corticospinal tract and superior longitudinal fasciculus, and in the right inferior fronto-occipital fasciculus (p<0.05). The best predictor of progression rate was the T2 lesion load measured along the right inferior fronto-occipital fasciculus (p=0.016, hazard ratio 1.00652, 95% CI 1.00121 to 1.01186). Conclusion: Our results suggest that the location of T2 brain lesions in the motor and associative tracts is an important contributor to the progression of disability in PPMS, and is independent of spinal cord involvement

    A novel approach with "skeletonised MTR" measures tract-specific microstructural changes in early primary-progressive MS

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    We combined tract‐based spatial statistics (TBSS) and magnetization transfer (MT) imaging to assess white matter (WM) tract‐specific short‐term changes in early primary‐progressive multiple sclerosis (PPMS) and their relationships with clinical progression. Twenty‐one PPMS patients within 5 years from onset underwent MT and diffusion tensor imaging (DTI) at baseline and after 12 months. Patients' disability was assessed. DTI data were processed to compute fractional anisotropy (FA) and to generate a common WM “skeleton,” which represents the tracts that are “common” to all subjects using TBSS. The MT ratio (MTR) was computed from MT data and co‐registered with the DTI. The skeletonization procedure derived for FA was applied to each subject's MTR image to obtain a “skeletonised” MTR map for every subject. Permutation tests were used to assess (i) changes in FA, principal diffusivities, and MTR over the follow‐up, and (ii) associations between changes in imaging parameters and changes in disability. Patients showed significant decreases in MTR over one year in the corpus callosum (CC), bilateral corticospinal tract (CST), thalamic radiations, and superior and inferior longitudinal fasciculi. These changes were located both within lesions and the normal‐appearing WM. No significant longitudinal change in skeletonised FA was found, but radial diffusivity (RD) significantly increased in several regions, including the CST bilaterally and the right inferior longitudinal fasciculus. MTR decreases, RD increases, and axial diffusivity decreases in the CC and CST correlated with a deterioration in the upper limb function. We detected tract‐specific multimodal imaging changes that reflect the accrual of microstructural damage and possibly contribute to clinical impairment in PPMS. We propose a novel methodology that can be extended to other diseases to map cross‐subject and tract‐specific changes in MTR

    Intra-individual variability in information processing speed reflects white matter microstructure in multiple sclerosis

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    AbstractSlowed information processing speed is commonly reported in persons with multiple sclerosis (MS), and is typically investigated using clinical neuropsychological tests, which provide sensitive indices of mean-level information processing speed. However, recent studies have demonstrated that within-person variability or intra-individual variability (IIV) in information processing speed may be a more sensitive indicator of neurologic status than mean-level performance on clinical tests. We evaluated the neural basis of increased IIV in mildly affected relapsing–remitting MS patients by characterizing the relation between IIV (controlling for mean-level performance) and white matter integrity using diffusion tensor imaging (DTI). Twenty women with relapsing–remitting MS and 20 matched control participants completed the Computerized Test of Information Processing (CTIP), from which both mean response time and IIV were calculated. Other clinical measures of information processing speed were also collected. Relations between IIV on the CTIP and DTI metrics of white matter microstructure were evaluated using tract-based spatial statistics. We observed slower and more variable responses on the CTIP in MS patients relative to controls. Significant relations between white matter microstructure and IIV were observed for MS patients. Increased IIV was associated with reduced integrity in more white matter tracts than was slowed information processing speed as measured by either mean CTIP response time or other neuropsychological test scores. Thus, despite the common use of mean-level performance as an index of cognitive dysfunction in MS, IIV may be more sensitive to the overall burden of white matter disease at the microstructural level. Furthermore, our study highlights the potential value of considering within-person fluctuations, in addition to mean-level performance, for uncovering brain–behavior relationships in neurologic disorders with widespread white matter pathology

    Advanced Application of Diffusion Kurtosis Imaging

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    Diffusion tensor imaging (DTI) has become a standard procedure in clinical routine as well as research as it enables the reconstruction and visualization of fiber tracts in the human brain. Due to the simplified assumption the tensor model – a Gaussian distribution of the diffusion – it typically fails to provide neither accurate spatial mapping nor quantification of crossing or kissing fibers. A clinically feasible development might be diffusion kurtosis imaging (DKI), an extension of DTI also integrating non-Gaussian distribution diffusion processes and thereby shall overcome some of its limitations. The potential DKI will be evaluated in case of the detection of the interhemispheric asymmetry of the white matter in healthy volunteers (n = 20), as well as the analysis of tumor-related impairments of fiber tracts and their correlation with neurological deficits in patients (n = 13) diagnosed with glioma. In order to analyze interhemispheric asymmetry across the whole brain, especially of nine large fiber tracts, tract-based spatial statistics (TBSS) analysis was performed using DTI- and DKI-based parameters, a laterality index was calculated for asymmetries and DTI- and DKI-based results were compared. With regard to fractional anisotropy as marker of integrity, asymmetry was found for all nine fiber tracts based on DTI and seven tracts based on DKI. For mean diffusivity, asymmetries were found for three (DTI) and two (DKI) fiber tracts. Regarding mean kurtosis, asymmetry was found in one tract. The interhemispheric asymmetry thereby varied in anatomical location as well as in cluster size. Only small parts of the tracts were affected. A comparison of DTI and DKI showed significantly higher fractional anisotropy and mean diffusivity based on DKI compared to DTI. Gender and handedness did not seem to have any influence. For the assessment of tumor-related changes of fiber tracts in patients diagnosed with glioma, especially in relation to pre-existing and postoperative neurological deficits (hemiparesis, aphasia), templates for the corticospinal tract and the arcuate fasciculus were created based on DTI- and DKI-derived parameters, respectively. The corticospinal tract and the arcuate fasciculus were reconstructed for each patient and the associated parametric maps were projected onto the templates. Based on this, alterations along the tracts could be identified and quantified. Alterations were found on fiber tracts regardless of the spatial proximity to the lesion. There was a correlation between alterations based on fractional anisotropy, mean diffusivity and mean kurtosis. Increased mean diffusivity was associated with alteration in mean kurtosis, a decreased fractional anisotropy was found concurrent with a likewise decreased mean kurtosis. In the case of pre-existing neurological deficits (hemiparesis, aphasia) with regard to the changes along the fiber tracts (corticospinal tract, left arcuate fasciculus), most often increased mean diffusivity and altered mean kurtosis was found. Applying this pattern for prediction of corresponding postoperative neurological deficits a sensitivity of 75.0% and a specificity of 87.5% was achieved. DKI seems to more precisely estimated and depict the underlying microstructure in comparison to DTI. Thereby, in pathological cases especially the mean kurtosis seems to be of special interest. A combination of DTI- and DKI based parameters, particularly with regard to its clinical usability and value, offers great potential in clinical routine

    Exploring the relationship between white and grey matter damage in primary progressive multiple sclerosis with structural magnetic resonance imaging

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    In the first part of this thesis, an introduction of the main characteristics of the primary-progressive form of multiple sclerosis (PPMS) (Chapter I), and of the acquisition and post-processing of the conventional and quantitative magnetic resonance imaging techniques employed in the studies presented in this thesis (Chapter II), will be presented. In the second part of this thesis, several advanced imaging techniques will be employed to answer the following two key questions on PPMS: 1) Is there is a spatial and temporal link between the pathological processes occurring in the normal appearing white matter (WM) and in the grey matter (GM) of patients with PPMS?; 2) Which regions of WM and GM abnormalities significantly contribute to clinical progression and cognitive dysfunction over time in patients with PPMS? To answer the first question, I first used tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM), to explore the spatial relationship between the damage occurring in the normal-appearing WM and GM in patients with early PPMS (Chapter III). Then, I moved onto exploring the temporal relationship linking the pathological changes affecting the two compartments, employing magnetization transfer imaging (MTI) and diffusion-based tractography (Chapter IV). To answer the second question, I first looked at the prognostic role of WM lesion location in a study conducted on a large population of patients with well- established PPMS who were followed-up for ten years in five different European centres (Chapter V). Then, using a novel approach which combines MTI and TBSS, I explored the regions of short-term accrual of microstructural damage in patients with early PPMS (Chapter VI). Finally, I moved onto examining the relative contribution of WM and GM damage to long-term motor and cognitive disability in PPMS (Chapter VII). In the final Chapter, I will summarise the results of the studies presented in this thesis, provide an answer to the two key questions on PPMS, and propose future directions for research

    Assessing a standardised approach to measuring corticospinal integrity after stroke with DTI

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    The structural integrity of the corticospinal tract (CST) after stroke is closely linked to the degree of motor impairment. Simple and reliable methods of assessing white matter integrity within the CST would facilitate the use of this measure in routine clinical practice. Commonly, diffusion tensor imaging is used to measure voxel-wise fractional anisotropy (FA) in a variety of regions of interest (ROIs) representing the CST. Several methods are currently in use with no consensus about which approach is best. ROIs are usually either the whole CST or the posterior limb of the internal capsule (PLIC). These are created manually on brain images or with reference to an individual's CST determined by tractography. Once the ROI has been defined, the FA can be reported as an absolute measure from the ipsilesional side or as a ratio in comparison to the contralesional side. Both corticospinal tracking and manual ROI definition in individual stroke patients are time consuming and subject to bias. Here, we investigated whether using a CST template derived from healthy volunteers was a feasible method for defining the appropriate ROI within which to measure changes in FA. We reconstructed the CST connecting the primary motor cortex to the ipsilateral pons in 23 age-matched control subjects and 21 stroke patients. An average healthy CST template was created from the 23 control subjects. For each patient, FA values were then calculated for both the template CST and for their own CST. We compared patients' FA metrics between the two tracts by considering four measures (FA in the ipsilesional side, FA in the contralesional side, FA ratio of the ipsilesional side to the contralesional side and FA asymmetry between the two sides) and in two tract-based ROIs (whole tract and tract section traversing the PLIC). There were no significant differences in FA metrics for either method, except for contralesional FA. Furthermore, we found that FA metrics relating to CST damage all correlated with motor ability post-stroke equally well. These results suggest that the healthy CST template could be a surrogate structure for defining tract-based ROIs with which to measure stroke patients' FA metrics, avoiding the necessity for CST tracking in individual patients. CST template-based automated quantification of structural integrity would greatly facilitate implementation of practical clinical applications of diffusion tensor imaging

    Neuroimaging in Multiple Sclerosis

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