Unknown

Dataset Information

0

Is Diffusion Tensor Imaging a Good Biomarker for Early Parkinson's Disease?


ABSTRACT: Objectives: To assess white matter abnormalities in Parkinson's disease (PD). Methods: A hundred and thirty-two patients with PD (mean age 60.93 years; average disease duration 7.8 years) and 137 healthy controls (HC; mean age 57.8 years) underwent the same MRI protocol. Patients were assessed by clinical scales and a complete neurological evaluation. We performed a TBSS analysis to compare patients and controls, and we divided patients into early PD, moderate PD, and severe PD and performed an ROI analysis using tractography. Results: With TBSS we found lower FA in patients in corpus callosum, internal and external capsule, corona radiata, thalamic radiation, sagittal stratum, cingulum and superior longitudinal fasciculus. Increased AD was found in the corpus callosum, fornix, corticospinal tract, superior cerebellar peduncle, cerebral peduncle, internal and external capsules, corona radiata, thalamic radiation and sagittal stratum and increased RD were seen in the corpus callosum, internal and external capsules, corona radiata, sagittal stratum, fornix, and cingulum. Regarding the ROIs, a GLM analysis showed abnormalities in all tracts, mainly in the severe group, when compared to HC, mild PD and moderate PD. Conclusions: Since major abnormalities were found in the severe PD group, we believe DTI analysis might not be the best tool to assess early alterations in PD, and probably, functional and other structural analysis might suit this purpose better. However it can be used to differentiate disease stages, and as a surrogate marker to assess disease progression, being an important measure that could be used in clinical trials. HIGHLIGHTS DTI is not the best tool to identify early PDDTI can differentiate disease stagesDTI analysis may be a useful marker for disease progression.

SUBMITTER: Guimaraes RP 

PROVIDER: S-EPMC6111994 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC5028727 | biostudies-literature
| S-EPMC2095589 | biostudies-literature
| S-EPMC4418199 | biostudies-literature
| S-EPMC3748146 | biostudies-literature
| S-EPMC9025175 | biostudies-literature
| S-EPMC4472452 | biostudies-literature
| S-EPMC7546271 | biostudies-literature
| S-EPMC5087900 | biostudies-literature
| S-EPMC6593682 | biostudies-literature
| S-EPMC7856641 | biostudies-literature