Feasibility of using geometric descriptors of tracer distribution for disease assessment

The objective of this work was to investigate if geometry and texture-based metrics contain brain disease-related information similar to measures typically derived from kinetic modeling- based approaches. Using co-registered PET and MRI images from an ongoing Parkinson´s disease imaging study, the shape, size and texture of the striatal regions containing high tracer concentration were estimated, and regressed against the subject´s disease duration. A novel inter-modality region fusion method was used for a systematic metric characterization and evaluation. It was established that several regional measures such as the region volume, surface area, moment invariants, and others were very good predictors of the clinical disease duration. Interestingly, some metrics revealed good correlation with the disease duration only when evaluated on the fused inter-modality PET-MRI regions. These results demonstrate that geometric features that do not rely on kinetic modeling may be used for disease characterization.