Simulating the progression of brain structural alterations in Parkinson's disease

Chang-Hyun Park1,2, Na-Young Shin3, Sang-Won Yoo4

  • 1Department of Radiology, College of Medicine, Catholic University of Korea, Seoul, Korea.

Insights

Parkinson's disease (PD) progression can be inferred by tracking brain structural changes. White matter disintegrity often precedes gray matter thinning, with these alterations appearing before major symptoms and correlating with severity.

Area of Science:

  • Neuroscience
  • Radiology
  • Neurology

Background:

  • Parkinson's disease (PD) involves progressive neurodegeneration affecting brain structure.
  • Understanding the sequence of structural alterations is crucial for predicting PD progression.
  • Magnetic Resonance Imaging (MRI) offers insights into brain structural changes.

Purpose of the Study:

  • To infer the progression of Parkinson's disease (PD) by ordering observed brain structural alterations.
  • To correlate the sequence and staging of structural changes with clinical status in PD patients.

Main Methods:

  • Cross-sectional MRI scans were used to measure cortical thinning (gray matter) and white matter (WM) disintegrity in 130 PD patients.
  • Stochastic simulation, based on probabilistic relationships between brain regions, was employed.
  • The study inferred the ordering and staging of structural alterations relative to clinical progression.

Main Results:

  • White matter (WM) disintegrity was observed to occur earlier than gray matter (GM) cortical thinning.
  • Structural alterations predominantly preceded major clinical complications like postural instability and dementia.
  • The inferred sequence of structural alterations significantly correlated with the severity of clinical symptoms.

Conclusions:

  • The specific ordering of brain structural alterations provides a potential biomarker for predicting Parkinson's disease progression.
  • This sequence-based approach may offer clinical feasibility for staging PD and anticipating disease severity.
  • Early detection of WM and GM changes can inform prognosis and management strategies.