We examined the feasibility of the local deformations on the surface of subcortical structures as an alternative biomarker to the classical volumetric metrics for the diagnosis and tracking progression of Parkinsons’ disease.
Key findings:
- Local deformations in the shape of subcortical structures like the Thalamus is a more sensitive biomarker than volume for tracking the progression of atrophy in PD.
- Power analysis based on surface deformation analysis determined that, compared to volumes, a much lower sample size is required to detect statistically significant longitudinal changes in PD.
- Surface-based deformations in the Midbrain can be used as accurate predictors of DaTScan density.
By accurately identifying subcortical regions with significant morphological changes, our approach enhances our ability to track disease progression, evaluate therapeutic interventions, and reduce the sample size requirements for clinical trials. Our predictive models allowed us to use anatomical T1-weighted MRI data as a surrogate for DaTscan SPECT for eligibility screening for clinical trials of disease-modifying therapeutics.
We examined the feasibility of the local deformations on the surface of subcortical structures as an alternative biomarker to the classical volumetric metrics for the diagnosis and traking progression of PD.
By accurately identifying subcortical regions with significant morphological changes, our approach enhances our ability to track disease progression, evaluate therapeutic interventions, and reduce the sample size requirements for clinical trials. Our predictive models allowed us to use anatomical T1-weighted MRI data as a surrogate for DaTscan SPECT for eligibility screening for clinical trials of disease-modifying therapeutics.