[Transcranial sonography findings in Parkinson's disease].
ABSTRACT Interest in diagnostic biomarkers that improve identification of Parkinson's disease (PD) in the early stages has been recently increasing. Accurate diagnosis of PD is currently a challenge for clinical neurologists. In addition, recent advances in basic research towards neuroprotective strategies for PD are increasingly highlighting the need for diagnostic biomarkers that improve identification of PD in the early stages. As such, substantia nigra hyperechogenicity visualized by transcranial sonography (TCS) has gained increasing attention and has been implemented in PD diagnosis globally. As substantia nigra hyperechogenicity offers unique information supplementary to those provided by other neuroimaging techniques, and this echofeature is stable during the disease course, it is very helpful in early and differential diagnosis of PD. The pathophysiologic conditions underlying this echofeature are not fully understood; however, it maybe associated with increased amounts of iron. It should be reminded that there are several limitations in conducting TCS. The main limitation is that in Japanese subjects the rate of temporal bone window sufficient for an adequate sonographic analysis prominently decreases with advancing age, particularly in females. Another limitation is that measurements may vary between two laboratories. Therefore, investigators are required to generate their own reference values. Despite these limitations, TCS can be recommended as a useful technique for the diagnosis of PD owing to its fast and easy use, low cost, and noninvasive nature. This review summarizes the TCS technique, the typical findings, and their value in the diagnosis and differential diagnosis of PD.
SourceAvailable from: Miho Murata[Show abstract] [Hide abstract]
ABSTRACT: Clinical differentiation of parkinsonian syndromes such as the Parkinson variant of multiple system atrophy (MSA-P) and cerebellar subtype (MSA-C) from Parkinson's disease is difficult in the early stage of the disease. To identify the correlative pattern of brain changes for differentiating parkinsonian syndromes, we applied discriminant analysis techniques by magnetic resonance imaging (MRI). T1-weighted volume data and diffusion tensor images were obtained by MRI in eighteen patients with MSA-C, 12 patients with MSA-P, 21 patients with Parkinson's disease, and 21 healthy controls. They were evaluated using voxel-based morphometry and tract-based spatial statistics, respectively. Discriminant functions derived by step wise methods resulted in correct classification rates of 0.89. When differentiating these diseases with the use of three independent variables together, the correct classification rate was the same as that obtained with step wise methods. These findings support the view that each parkinsonian syndrome has structural deviations in multiple brain areas and that a combination of structural brain measures can help to distinguish parkinsonian syndromes.Computational and Mathematical Methods in Medicine 03/2013; 2013:571289. DOI:10.1155/2013/571289 · 1.02 Impact Factor