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Department of Medical Biophysics, University of Western Ontario, London, Ontario
Department of Nuclear Medicine, London Health Sciences Centre, London, Ontario, Canada
Department of Nuclear Medicine, Klinikum Grosshadern, University of Munich, Munich, Germany
Correspondence: For correspondence or reprints contact: Piotr J. Slomka, PhD, London Health Sciences Centre, Victoria Campus, Department of Nuclear Medicine, 375 South Street, London, Ontario, N6A 4G5, Canada.
ABSTRACT
Evaluation of therapies for parkinsonism by dopamine receptor SPECT requires a reproducible, optimized quantitation technique. This study presents a new, objective, automated technique for semiquantitative analysis of dopamine receptor density, as applied to the differential diagnosis of parkinsonism. Methods: Dopamine receptor density measured by 123I-iodobenza-mide (IBZM) SPECT was retrospectively analyzed in nonidiopathic parkinsonism (NIPS), in Parkinson's disease (PD), and in healthy volunteers (n = 19, 38, and 13, respectively). A mean template was created from coregistered control studies. Registration errors were assessed using studies with simulated binding deficits. Patient studies were registered to the mean template, and striatal binding was calculated from a corresponding map of 3-dimensional regions of interest (ROIs). The striatal binding ratio and deficits determined by voxelwise comparison with the normal template were investigated and tested with various 3-dimensional ROI sizes and positions. Separation of patient groups was determined by f score after automatically processing all studies. Results were compared with manual ROI analyses. Results: The automatic method was completely reproducible in 64 of 70 cases. The best diagnostic discriminator was the minimum binding ratio of the 2 striatal nuclei, with the following values: NIPS, 1.33 ± 0.13; PD, 1.50 ± 0.12; healthy volunteers, 1.49 ± 0.08 (±SD). The deficit size from voxelwise analysis was: NIPS, 20.5 ± 8.2 mL; PD, 9.5 ± 8.3; healthy volunteers, 8.9 ± 6.0 (±SD). The accuracy, measured by receiver operating characteristic areas, was 0.85 ± 0.05, 0.77 ± 0.06, and 0.80 ± 0.06 (±SE) for the optimal predictor (automated) and 2 blinded observers (manual), respectively. Conclusion: A new 3-dimensional, automated technique has been developed to semiquantitate receptor density that dramatically improves reproducibility. The optimal diagnostic discriminator of parkinsonism determined by the automatic technique has good accuracy compared with the manual technique.
Key Words: automatic registration dopamine imaging Parkinson's disease reproducibility receptors SPECT
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