RESUMEN
In the Caribbean island of Guadeloupe, patients with atypical parkinsonism develop a progressive supranuclear palsy-like syndrome, named Guadeloupean parkinsonism. Unlike the classical forms of progressive supranuclear palsy, they develop hallucinations and myoclonus. As lesions associated with Guadeloupean parkinsonism are poorly characterized, it is not known to what extent they differ from progressive supranuclear palsy. The aim of the present study was to determine the structural and metabolic profiles of Guadeloupean parkinsonism compared with progressive supranuclear palsy and controls using combined structural and diffusion magnetic resonance imaging and magnetic resonance spectroscopy. We included 9 patients with Guadeloupean parkinsonism, 10 with progressive supranuclear palsy and 9 age-matched controls. Magnetic resonance imaging examination was performed at 1.5 T and included 3D T(1)-weighted and fluid-attenuated inversion recovery images, diffusion tensor imaging and single voxel magnetic resonance spectroscopy in the lenticular nucleus. Images were analysed using voxel-based morphometry, voxel-based diffusion tensor imaging and brainstem region of interest measurements. In patients with Guadeloupean parkinsonism, structural and diffusion changes predominated in the temporal and occipital lobes, the limbic areas (medial temporal, orbitofrontal and cingulate cortices) and the cerebellum. In contrast to patients with progressive supranuclear palsy, structural changes predominated in the midbrain and the basal ganglia and diffusion abnormalities predominated in the frontocentral white matter, the basal ganglia and the brainstem. Compared with controls, the N-acetylaspartate to creatinine ratio was decreased in patients with progressive supranuclear palsy and to a lesser extent in patients with Guadeloupean parkinsonism. The pattern of structural and diffusion abnormalities differed between progressive supranuclear palsy and Guadeloupean parkinsonism. Widespread cortical atrophy was observed in patients with Guadeloupean parkinsonism who presented marked cognitive changes and hallucinations, whereas midbrain lesions were less severe than in progressive supranuclear palsy. Midbrain (progressive supranuclear palsy) or cortical (Guadeloupean parkinsonism) atrophy was a distinctive neuroimaging feature for differential diagnosis.
Asunto(s)
Encéfalo/metabolismo , Encéfalo/patología , Trastornos Parkinsonianos/metabolismo , Trastornos Parkinsonianos/patología , Parálisis Supranuclear Progresiva/metabolismo , Parálisis Supranuclear Progresiva/patología , Anciano , Ácido Aspártico/análogos & derivados , Ácido Aspártico/metabolismo , Estudios de Casos y Controles , Trastornos del Conocimiento/complicaciones , Trastornos del Conocimiento/metabolismo , Trastornos del Conocimiento/patología , Creatinina/metabolismo , Diagnóstico Diferencial , Imagen de Difusión por Resonancia Magnética/instrumentación , Imagen de Difusión por Resonancia Magnética/métodos , Imagen de Difusión Tensora/instrumentación , Imagen de Difusión Tensora/métodos , Femenino , Guadalupe , Alucinaciones/complicaciones , Alucinaciones/metabolismo , Alucinaciones/patología , Humanos , Procesamiento de Imagen Asistido por Computador , Espectroscopía de Resonancia Magnética/instrumentación , Espectroscopía de Resonancia Magnética/métodos , Masculino , Trastornos Parkinsonianos/complicacionesRESUMEN
Magnetic Resonance Imaging (MRI) is increasingly used for the diagnosis and monitoring of neurological disorders. In particular Diffusion-Weighted MRI (DWI) is highly sensitive in detecting early cerebral ischemic changes in acute stroke. Cerebral infarction lesion segmentation from DWI is accomplished in this work by applying nonparametric density estimation. The quality of the class boundaries is improved by including an edge confidence map, that is the confidence of truly being in the presence of a border between adjacent regions. The adjacency graph, that is constructed with the label regions, is analyzed and pruned to merge adjacent regions. The method was applied to real images, keeping all parameters constant throughout the process for each data set. The combination of region segmentation and edge detection proved to be a robust automatic technique of segmentation from DWI images of cerebral infarction regions in acute ischemic stroke. In a comparison with the reference infarct lesions segmentation, the automatic segmentation presented a significant correlation (r=0.935), and an average Tanimoto index of 0.538.