Alteration of Diffusion-Tensor Magnetic Resonance Imaging Measures in Brain Regions Involved in Early Stages of Parkinson's Disease

Nan Kuei Chen, Ying Hui Chou, Mark Sundman, Patrick Hickey, Willard S. Kasoff, Adam Bernstein, Theodore P. Trouard, Tanya Lin, Steven Z. Rapcsak, Scott J. Sherman, Carol P. Weingarten

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Many nonmotor symptoms (e.g., hyposmia) appear years before the cardinal motor features of Parkinson's disease (PD). It is thus desirable to be able to use noninvasive brain imaging methods, such as magnetic resonance imaging (MRI), to detect brain abnormalities in early PD stages. Among the MRI modalities, diffusion-tensor imaging (DTI) is suitable for detecting changes in brain tissue structure due to neurological diseases. The main purpose of this study was to investigate whether DTI signals measured from brain regions involved in early stages of PD differ from those of healthy controls. To answer this question, we analyzed whole-brain DTI data of 30 early-stage PD patients and 30 controls using improved region of interest-based analysis methods. Results showed that (i) the fractional anisotropy (FA) values in the olfactory tract (connected with the olfactory bulb: one of the first structures affected by PD) are lower in PD patients than healthy controls; (ii) FA values are higher in PD patients than healthy controls in the following brain regions: corticospinal tract, cingulum (near hippocampus), and superior longitudinal fasciculus (temporal part). Experimental results suggest that the tissue property, measured by FA, in olfactory regions is structurally modulated by PD with a mechanism that is different from other brain regions.

Original languageEnglish (US)
Pages (from-to)343-349
Number of pages7
JournalBrain Connectivity
Volume8
Issue number6
DOIs
StatePublished - Aug 2018

Keywords

  • Parkinson's disease
  • diffusion-tensor imaging
  • olfactory tract

ASJC Scopus subject areas

  • Neuroscience(all)

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