Shape analysis of 123I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography images in the assessment of patients with parkinsonian syndromes.
Staff RT., Ahearn TS., Wilson K., Counsell CE., Taylor K., Caslake R., Davidson JE., Gemmell HG., Murray AD.
PURPOSE: The purpose of this study was to show the viability and performance of a shape-based pattern recognition technique applied to I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography (FP-CIT SPECT) in patients with parkinsonism. METHODS: A fully automated pattern recognition tool, based on the shape of FP-CIT SPECT images, was written using Java. Its performance was evaluated and compared with QuantiSPECT, a region-of-interest-based quantitation tool, and observer performance using receiver operating characteristic analysis and kappa statistics. The techniques were compared using a sample of patients and controls recruited from a prospective community-based study of first presentation of parkinsonian symptoms with longitudinal follow up (median 3 years). RESULTS: The shape-based technique as well as the conventional semiquantitative approach was performed by experienced observers. The technique had a high level of automation, thereby avoiding observer/operator variability. CONCLUSION: A pattern recognition approach is a viable alternative to traditional methods of analysis in FP-CIT SPECT and has additional advantages.