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A discriminant method for optimizing activity in nuclear medicine studies is validated by comparison with ROC (received operating characteristic)-curves. The method is tested in 21 single photon emission computerized tomography (SPECT), performed with a cardiac phantom. Three different lesions (L1, L2 and L3) were placed in the myocardium-wall by pairs for each SPECT. Three activities (84, 37 or 18.5 MBq) of 99mTc were used as background. Linear discriminant analysis was used to select the parameters that characterize image quality among the measured variables in the images [(Background-to-Lesion (B/Li) and Signal-to-Noise (Si/N) ratios)]. Two clusters with different image quality (P=0.021) were obtained. The ratios B/L1, B/L2 and B/L3 are the parameters used to construct the function with 100% of cases correctly classified into the clusters. The value of 37 MBq was the lowest tested activity for which good results for the B/Li ratios were obtained. The result coincides with the applied ROC-analysis (r=0.89).
A discriminant method for optimizing activity in nuclear medicine studies is validated by comparison with ROC (received operating characteristic) -curves. The method is tested in 21 single photon emission computerized tomography (SPECT), performed with a cardiac phantom. Three different lesions (L1 Linear activities were used in the myocardium-wall by pairs for each SPECT. Three activities (84, 37 or 18.5 MBq) of 99mTc were used as background. Linear discriminant analysis was used to select the parameters that characterize image quality among the The ratios B to Li and the signal-to-noise (Si / N) ratios)]. Two clusters with different image quality (P = 0.021) were obtained. The ratios B / L1, B / L2 and B / L3 are the parameters used to construct the function with 100% of the cases classified classified into the clusters. The value of 37 MBq was the best tested activity for which good results for the B / Li were obtained The result coincides with the applie d ROC-analysis (r = 0.89).