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Rationale and Objectives The aim of this study was to examine changes of brain iron content and diffusion patterns longitudinally in early-stage Parkinson's disease (PD) patients using T2- and T2*-based magnetic resonance imaging (MRI) over 2-year follow-up. Materials and Methods We imaged 32 PD patients with tremor and 19 healthy controls. A follow-up study (median 25 months, range 22–31 months) was accomplished for 25 patients (men:women = 11:14; age range 44–87 years, median 73 years). All patients and healthy volunteers underwent clinical, neuropsychological, and MRI examinations on the same day. Three different MRI sequences were used and their results were compared: T2-weighted imaging, susceptibility-weighted imaging, and T2* mapping. Additionally, we evaluated diffusion tensor data between groups using tract-based spatial statistics. Results Over the 2-year follow-up, the iron-related relaxation increased in the globus pallidus anterior and the caudate nucleus and slightly in the substantia nigra pars compacta (SNc). In the globus pallidus anterior and medial SNc, the change was associated with mild cognitive impairment. In the caudate nucleus, the increase was pronounced in patients with disease onset at 67 years or older. In the SNc, medial transverse relaxation was increased, and in the thalamus, it was decreased, in patients with PD compared with healthy volunteers at 2-year follow-up. Tract-based spatial statistical data did not differ between groups based on gender or Unified Parkinson's Disease Rating Scale, but a slight tendency to decreasing fractional anisotropy ( P Conclusions PD-related changes were found in putative iron content over 2 years. Although mild in the initial stages, these changes were consistent over MRI sequences. Rather than correlating with disease duration, the rate of changes was associated with individual characters, such as cognitive decline and age.

We studied nonheme iron in Parkinson's disease (PD) using clinically available MRI in 36 patients and 21 healthy volunteers. The subjects underwent thorough clinical investigation, including 3-T MRI. Quantitative R2* was able to reflect symptoms of PD. In addition, the clinically used susceptibility-weighted imaging differentiated between controls and patients, whereas T2-weighted imaging did not. Disease-related changes were present not only in substantia nigra but also in globus pallidus. Such changes are associated with neurodegeneration, reflecting the severity of motor impairment.

Rationale and Objectives Early-stage diagnosis of Parkinson’s disease (PD) is essential in making decisions related to treatment and prognosis. However, there is no specific diagnostic test for the diagnosis of PD. The aim of this study was to evaluate the role of texture analysis (TA) of magnetic resonance images in detecting subtle changes between the hemispheres in various brain structures in patients with early symptoms of parkinsonism. In addition, functional TA parameters for detecting textural changes are presented. Materials and Methods Fifty-one patients with symptoms of PD and 20 healthy controls were imaged using a 3-T magnetic resonance device. Co-occurrence matrix–based TA was applied to detect changes in textures between the hemispheres in the following clinically interesting areas: dentate nucleus, basilar pons, substantia nigra, globus pallidus, thalamus, putamen, caudate nucleus, corona radiata, and centrum semiovale. The TA results were statistically evaluated using the Mann-Whitney U test. Results The results showed interhemispheric textural differences among the patients, especially in the area of basilar pons and midbrain. Concentrating on this clinically interesting area, the four most discriminant parameters were defined: co-occurrence matrix correlation, contrast, difference variance, and sum variance. With these parameters, differences were also detected in the dentate nucleus, globus pallidus, and corona radiata. Conclusions On the basis of this study, interhemispheric differences in the magnetic resonance images of patients with PD can be identified by the means of co-occurrence matrix–based TA. The detected areas correlate with the current pathophysiologic and neuroanatomic knowledge of PD.

Objectives:To compare quantitatively T2- and T2*-based magnetic resonance imaging sequences in patients with symptoms of Parkinson disease and to evaluate the information content of those sequences regarding brain iron concentration.Materials and Methods:We imaged 51 patients with symptoms of Parkin

Background Few of the structural changes caused by Parkinson’s disease (PD) are visible in magnetic resonance imaging (MRI) with visual inspection but there is a need for a method capable of observing the changes beyond the human eye. Texture analysis offers a technique that enables the quantification of the image gray-level patterns. Purpose To investigate the value of quantitative image texture analysis method in diagnosis and follow-up of PD patients. Material and Methods Twenty-six PD patients underwent MRI at baseline and after 2 years of follow-up. Four co-occurrence matrix-based texture parameters, describing the image homogeneity and complexity, were calculated within clinically interesting areas of the brain. In addition, correlations with clinical characteristics (Unified Parkinson’s Disease Ranking Scales I–III and Mini-Mental State Examination score) along with a comparison to healthy controls were evaluated. Results Patients at baseline and healthy volunteers differed in their brain MR image textures mostly in the areas of substantia nigra pars compacta, dentate nucleus, and basilar pons. During the 2-year follow-up of the patients, textural differences appeared mainly in thalamus and corona radiata. Texture parameters in all the above mentioned areas were also found to be significantly related to clinical scores describing the severity of PD. Conclusion Texture analysis offers a quantitative method for detecting structural changes in brain MR images. However, the protocol and repeatability of the method must be enhanced before possible clinical use.

Early-stage diagnosis of Parkinson's disease (PD) is essential in making decisions related to treatment and prognosis. However, there is no specific diagnostic test for the diagnosis of PD. The aim of this study was to evaluate the role of texture analysis (TA) of magnetic resonance images in detecting subtle changes between the hemispheres in various brain structures in patients with early symptoms of parkinsonism. In addition, functional TA parameters for detecting textural changes are presented.Fifty-one patients with symptoms of PD and 20 healthy controls were imaged using a 3-T magnetic resonance device. Co-occurrence matrix-based TA was applied to detect changes in textures between the hemispheres in the following clinically interesting areas: dentate nucleus, basilar pons, substantia nigra, globus pallidus, thalamus, putamen, caudate nucleus, corona radiata, and centrum semiovale. The TA results were statistically evaluated using the Mann-Whitney U test.The results showed interhemispheric textural differences among the patients, especially in the area of basilar pons and midbrain. Concentrating on this clinically interesting area, the four most discriminant parameters were defined: co-occurrence matrix correlation, contrast, difference variance, and sum variance. With these parameters, differences were also detected in the dentate nucleus, globus pallidus, and corona radiata.On the basis of this study, interhemispheric differences in the magnetic resonance images of patients with PD can be identified by the means of co-occurrence matrix-based TA. The detected areas correlate with the current pathophysiologic and neuroanatomic knowledge of PD.

Parkinson’s disease is the second most common neurodegenerative disorder of later life. Symptoms have proven to originate from the substantia nigra area. In our study, texture analysis was applied to 3-T magnetic resonance images of 28 patients with symptoms of parkinsonism. Of these, 14 had diagnosed Parkinson’s disease and 14 had no clinical confirmation for the particular disease. Areas of substantia nigra (pars reticulata, pars compacta and red nucleus), were analyzed with texture analysis software MaZda from both patient groups and results were further analyzed with the integrated software B11. Classification results show that substantia nigra areas of patients with and without diagnosis of Parkinson’s disease can be distinguished with high accuracy.

To compare quantitatively T2- and T2*-based magnetic resonance imaging sequences in patients with symptoms of Parkinson disease and to evaluate the information content of those sequences regarding brain iron concentration.We imaged 51 patients with symptoms of Parkinson disease on 3-T magnetic resonance imaging with T2-weighted sampling perfection with application optimized contrasts using different flip-angle evolution (SPACE), fluid attenuation inversion recovery (FLAIR)-SPACE, susceptibility-weighted imaging (SWI), and parametric T2* sequence (MapIt). Signal analysis was performed in 22 regions of interest in the brain.Correlations (r2 = 0.82...0.96) with brain iron concentration were excellent. Contrast and tissue separability ratios were best in the T2* maps and FLAIR-SPACE, respectively. Good correlations of contrast were reached between SWI and both T2-weighted SPACE and FLAIR-SPACE. Their relation to quantitative T2* values was reminiscent of a quadratic curve shape. However, separation into gray and white matter revealed a linear positive and negative correlation, respectively.SWI showed potential in differentiating illnesses characterized by brain iron deposition. Closely similar information was given by T2-weighted SPACE and FLAIR-SPACE, whereas other sequence comparisons revealed dispersion from intersequence agreement.