Parkinson’s studies are working to identify magnetic resonance imaging (MRI) biomarkers for early diagnosis, disease severity and progression. However, attempts to explore how brain changes influence these MRI biomarkers have not yet been performed. We propose to define brain changes underlying various MRI measures by relating postmortem MRI and other measures within the same patient. We also will investigate which of these disease-specific MRI biomarkers best correlate to cognitive decline in Parkinson’s, which is of key interest for patients, doctors, researchers and drug developers.
We aim to define pathology-specific MRI biomarkers for cognitive decline in Parkinson’s by studying brain changes such as inflammation and neuronal loss contributing to MRI changes in people with Parkinson’s compared to age-matched controls. We also will relate MRI biomarkers to cognitive measures in the Parkinson’s Progression Marker’s Initiative (PPMI) study cohort.
In collaboration with brain banks, we will obtain brain tissue from 30 Parkinson’s donors and 20 non-neurological controls. We will perform post-mortem MRI with subsequent autopsy, analyzing load and distribution patterns of brain disease hallmarks. We will then relate these measures to specific MRI measures in a statistical analysis. In addition, we will download available MRI and clinical/cognitive data from multicenter studies to calculate the same pathology-specific MRI measures and correlate these to clinical/cognitive outcomes to define PD imaging biomarkers of cognitive decline.
Impact on Diagnosis/Treatment of Parkinson’s Disease:
We aim to better understand what MRI is telling us about disease state in PD by looking at the relationship between MRI and pathology within the same patient. With this knowledge, physicians will be able to make a better judgement about underlying pathological change, disease severity and prognosis.
Next Steps for Development:
After validation of our results, we hope to implement the most promising pathology-specific MRI biomarker in the clinical research setting, where it can be used for more accurate selection and monitoring of participants for clinical trials.