Standardized Semi-Quantitative Evaluation of [123I]FP-CIT SPECT in a Multicenter Study

Abstract

Background and Purpose: To the best of our knowledge no multicenter studies have been published using standardized semi-quantitative evaluation of [123I]FP-CIT scan (DAT-SPECT). The aims of this study were: 1) to cross-compare semi-quantitative software-assisted evaluations of DAT-SPECTs performed in three centers with different equipments; 2) to assess the accuracy of semi-quantitative evaluations of DAT-SPECT and 3) to identify the threshold with the best accuracy, sensitivity and specificity in a patient population with suspected parkinsonian syndrome. Materials and Methods: Two hundred twenty patients (mean age at the time of SPECT acquisition, 67.4 ± 9.5 yy) acquired in three centers (Ospedale San Luigi Gonzaga; Ospedale San Giovanni Battista Molinette; Ospedale Mauriziano Umberto I) were included. All of them underwent DAT-SPECT from January 2006 to July 2010. All exams were analyzed with the freely available software BASGAN and semi-quantitative data were used to predict disease. In particular, analyses were based on the values from the most deteriorated putamen and caudate, normalized for age and corrected for equipment. ROC analysis was performed and area under the curve (AUC) was estimated. Results: Analysis showed high AUCs (0.898, 0.864, 0.900 and 0.891 for each center and for the multicenter setting, respectively) confirming the very good accuracies reached. The best cutoff were 0.72 and 0.82 for putamen and caudate respectively. These thresholds allowed sensitivities and specificities in each center and in the multicenter setting of 76% and 96%, 91% and 82%, 93% and 90%, 86% and 89% respectively. No significant differences were observed between sensibility and specificity in each center. Conclusion: A unique threshold useful for all centers with high and similar sensitivities and specificities is possible after correction for age and equipments. The high accuracy reached in this multicenter trial by the semi-quantitative analysis seems similar to accuracies from qualitative analysis in other multicenter studies.