METHODS: 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3.
RESULTS: Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified.
CONCLUSION: Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD.
KEY POINTS: • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.
METHODS: In this three-year longitudinal study, 125 subjects (77 PD patients and 48 spousal/sibling controls) underwent clinical, biochemical and body composition assessments using dual-energy X-ray absorptiometry.
RESULTS: Patients were older than controls (65.6 ± 8.9 vs. 62.6 ± 7.1, P = 0.049), with no significant differences in gender, comorbidities, dietary intake and physical activity. Clinically significant weight loss (≥5% from baseline weight) was recorded in 41.6% of patients, with a doubling of cases (6.5 to 13.0%) classified as underweight at study end. Over three years, patients demonstrated greater reductions in BMI (mean -1.2 kg/m2, 95%CI-2.0 to -0.4), whole-body fat percentage (-2.5% points, 95%CI-3.9 to -1.0), fat mass index (FMI) (-0.9 kg/m2, 95%CI-1.4 to -0.4), visceral fat mass (-0.1 kg, 95%CI-0.2 to 0.0), and subcutaneous fat mass (-1.9 kg, 95%CI-3.4 to -0.5) than in controls, with significant group-by-time interactions after adjusting for age and gender. Notably, 31.2% and 53.3% of patients had FMI<3rd (severe fat deficit) and <10th centiles, respectively. Muscle mass indices decreased over time in both groups, without significant group-by-time interactions. Multiple linear regression models showed that loss of body weight and fat mass in patients were associated with age, dyskinesia, psychosis and constipation.
CONCLUSIONS: We found progressive loss of weight in PD patients, with greater loss of both visceral and subcutaneous fat, but not muscle, compared to controls. Several associated factors (motor and non-motor disease features) were identified for these changes, providing insights on possible mechanisms and therapeutic targets.