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: This study recruited 21 ALS patients, 19 age-matched PD patients, and 21 agematched healthy controls. Patient demographics and clinical scores relating to the respective diseases were documented. The RNFL thickness was measured using optical coherence tomography at baseline and after 6 months.
RESULTS: At baseline, the RNFL in the superior quadrant was significantly thinner in the patients with ALS than in healthy controls (109.90±22.41 µm vs. 127.81±17.05 µm [mean±standard deviation], p=0.008). The RNFL thickness did not differ significantly between the ALS and PD patients or between the PD patients and healthy controls. At 6 months, there was further significant RNFL thinning in patients with ALS, for both the overall thickness (baseline: median=94.5 µm, range=83.0-106.0 µm; follow-up: median=93.5 µm, range=82.5-104.5 µm, p=0.043) and the thickness in the inferior quadrant (median=126 µm, range=109.5-142.5 µm; and median=117.5 µm, range=98.5-136.5 µm; respectively, p=0.032). However, these changes were not correlated with the ALS functional scores. In contrast, the patients with PD did not demonstrate a significant change in RNFL thickness between the two time points.
CONCLUSIONS: The RNFL thickness is a promising biomarker of disease progression in patients with ALS but not in those with PD, which has a slower disease progression.