Effects of SPECT collimation and system geometry on classification tasks related to Parkinson's disease

We assessed the potential performance of three commercial SPECT systems in simulated, but realistic imaging tasks related to the diagnosis and managem ent of Parkinson's disease (PD). Images of I-123 altropane activity distrib utions in normal and PD brains were modeled assuming values from the litera ture for striatal sizes and activity concentrations, as well as for nonspec ific activity. Imaging characteristics of the three systems were determined by phantom studies. The expected distributions of estimates of activity co ncentration and striatal volume were based on covariance matrices determine d by the Cramer-Rao lower bounds calculated for a simultaneous estimation o f these two parameters, as well as background activity concentration. Poten tial performance in several binary classification tasks was assessed by fit ting ROC curves to simulated likelihood ratios for 5000 "subjects" in each category. For all conditions studied, ROC areas were similar for the higher resolution instruments and lower for the lower resolution system. These re sults imply a diagnostic advantage for higher resolution systems in imaging tasks related to PD.