No abstract

Abstract: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 (L 1 , L 2 and L 3 ) 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/L i ) and Signal-to-Noise (S i /N) ratios)]. Two clusters with different image quality (P=0.021) were obtained. The ratios B/L 1 , B/L 2 and B/L 3 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/L i ratios were obtained. The result coincides with the applied ROC-analysis (r=0.89).

This paper proposes a more inclusive statistical model for predicting image noise in Computed Tomography (CT), associated with scanning factors, considering the effect of beam hardening and image processing filters. It is based on power functions where the levels of the parameters will determine the rate of noise variation with respect to a given scanning factor. It includes the influence of tube potential, tube current, slice thickness, Field of View (FOV), reconstruction methods and post-processing filters. To validate the model, tomographic measurements were made by using a PMMA phantom that simulates paediatric head and adult abdomen, a PET bottle was used to simulate the head of the newborn. The influence of ROI (Region Of Interest) size over nonlinear model parameters was analysed, and high variations of powers of attenuation and FOV were found depending on ROI size. A nonlinear robust regression method was used. The validation was performed graphically by weighted residual analysis. A nonlinear noise model was obtained with an adjusted coefficient of determination ajNL R 2 > 0.99 for ROI sizes between 10% and 70% of the phantom diameter or FOV. The model confirms the significance of the tube current, slice thickness and beam hardening effect on image. The process of estimation of the parameters of the model by Nonlinear Robust Regression turned out to be optimal.

No abstract

No abstract