Magnetic resonance imaging in spinocerebellar ataxias.
ABSTRACT Magnetic resonance (MR) imaging is widely used to visualize atrophic processes that occur during the pathogenesis of spinocerebellar ataxias (SCAs). T1-weighted images are utilized to rate the atrophy of cerebellar vermis, cerebellar hemispheres, pons and midbrain. Signal changes in the basal ganglia and ponto-cerebellar fibers are evaluated by T2-weighted and proton density-weighted images. However, two-dimensional (2D) images do not allow a reliable quantification of the degree of atrophy. The latter is now possible through the application of three-dimensional (3D) true volumetric methods, which should be used for research purposes. Ideally, these methods should allow automated segmentation of contrast-defined boundaries by using region growing algorithms, which can be applied successfully in structures of the posterior fossa and basal ganglia. Thin slice thickness helps to minimize partial volume effects. Whereas volumetric approaches rely on predetermined anatomical boundaries, voxel-based morphometry has been developed to determine group differences between different types of SCA (cross-sectional studies) or within one SCA entity (longitudinal studies). We will review recent results and how these methods are currently used to (i) separate sporadic and dominantly inherited forms of cerebellar ataxias; (ii) identify specific SCA genotypes; (iii) correlate patho-anatomical changes with SCA disease symptoms or severity; and (iv) visualize and estimate the rate of progression in SCA.
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ABSTRACT: Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine.The Cerebellum 11/2014; · 2.86 Impact Factor
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ABSTRACT: A large body of evidence has shown olfactory deficits in many neurodegenerative diseases. However, the nature of the olfactory impairment remains poorly understood partly because the majority of studies have only explored smell identification capabilities. The purpose of the present study was twofold. First we wanted to test if patients with spinocerebellar ataxia type 7 (SCA7), a progressive neurodegenerative disorder characterized by cerebellar ataxia and visual loss, also have olfactory deficits. Secondly, we wanted to test the nature of the olfactory deficits by testing not only the identification level but also olfactory threshold and discrimination. Based on the olfactory dysfunction found in different neurodegenerative diseases and functional neuroimaging data showing cerebellar activation during olfaction, we hypothesized that SCA7 patients would show an olfactory impairment. To test this hypothesis we studied twenty-eight genetically confirmed SCA7 patients and twenty-seven matched controls using the Sniffing Sticks Test and the University of Pennsylvania Smell Identification Test (UPSIT). The results show that SCA7 patients’ ability to discriminate and identify odours is significantly impaired, although their odour detection thresholds were at normal levels. These results suggest that SCA7 neurological damage affects olfactory perception but spares the patients’ olfactory sensory capabilities.Parkinsonism & Related Disorders 05/2014; 20(5). · 4.13 Impact Factor
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ABSTRACT: Background: Spinocerebellar ataxia type 7 (SCA7) is a genetic disorder characterized by degeneration of the motor and visual systems. Besides neural deterioration, these patients also show functional connectivity changes linked to the degenerated brain areas. However, it is not known if there are functional connectivity changes in regions not necessarily linked to the areas undergoing structural deterioration. Therefore, in this study we have explored the whole-brain functional connectivity of SCA7 patients in order to find the overall abnormal functional pattern of this disease. Twenty-six patients and age-and-gender-matched healthy controls were recruited. Whole-brain functional connectivity analysis was performed in both groups. A classification algorithm was used to find the discriminative power of the abnormal connections by classifying patients and healthy subjects. Results: Nineteen abnormal functional connections involving cerebellar and cerebral regions were selected for the classification stage. Support vector machine classification reached 92.3% accuracy with 95% sensitivity and 89.6% specificity using a 10-fold cross-validation. Most of the selected regions were well known degenerated brain regions including cerebellar and visual cortices, but at the same time, our whole-brain connectivity analysis revealed new regions not previously reported involving temporal and prefrontal cortices. Conclusion: Our whole-brain connectivity approach provided information that seed-based analysis missed due to its region-specific searching method. The high classification accuracy suggests that using resting state functional connectivity may be a useful biomarker in SCA 7.Cerebellum & Ataxias. 06/2014; 1(2).