Quick and Efficient Extraction of Patient Specific SBR Ratios for Parkinson’s Disease

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Overview

Parkinson's disease is a complex neurological disorder, marked by a wide array of symptoms ranging from motor impairments to cognitive changes. Our research aims to enhance early biomarker discovery for Parkinson's disease through analyzing and correlating imaging, clinical, and biological data.

Early Biomarker Discovery Pipeline

Early Biomarker Discovery Pipeline

Early Detection Primary Data

The primary data we investigated for early detection was:

  1. Variables from curated data sheet (survey results)
  2. REM Sleep data (sleep metrics)
  3. Biologic data including CSF (Project 171)
  4. Imaging data (T1 MRI, DaTSCAN, DTI)
  5. UPDRS III for state representation (Part III: Motor examination: 18 items. Score range: 0–132, 32 and below is mild, 59 and above is severe.)
Table of primary data used in early detection

Biomarker Agent Training with DaTSCAN and T1 MRI

For the identification of imaging patterns we started out investigating T1 - MRI data

  1. T1 - MRI highlights anatomy, providing crisp structural delineation. Volumes from T1- MRI for 112 prespecified regions were extracted for each patient
  2. DaTSCAN images visualize striatal dopamine transporter intensity; commonly known to be a biomarker for PD. We utilize it to make improvement on SBR ratio extraction.
Diagram pointing to different sections of the brain

Biomarker Agent Training with DTI, T2 MRI, and fMRI

  1. DTI images detect the diffusion of water molecules in the white matter of the brain. We begin by extracting mean diffusivity and fractional anisotropy from 112 regions
    • Substantia Nigra is the ROI based on literature
    • Will be investigated when T2 MRI is integrated
  2. This will eventually branch out into combining MRI with other imaging types such as T2-MRI and fMRI
DTI images with overlays