UNLABELLED: The independent component analysis (ICA) method is suggested to be useful for separation of the ventricles and the myocardium and for extraction of the left ventricular input function from the dynamic H(2)(15)O myocardial PET. The ICA-generated input function was validated with the sampling method, and the myocardial blood flow (MBF) calculated with this input function was compared with the microsphere results. METHODS: We assumed that the elementary activities of the ventricular pools and the myocardium were spatially independent and that the mixture of them composed dynamic PET image frames. The independent components were estimated by recursively minimizing the mutual information (measure of dependence) between the components. The ICA-generated input functions were compared with invasively derived arterial blood samples. Moreover, the regional MBF calculated using the ICA-generated input functions and single-compartment model was correlated with the results obtained from the radiolabeled microspheres. RESULTS: The ventricles and the myocardium were successfully separated in all cases within a short computation time (<15 s). The ICA-generated input functions displayed shapes similar to those obtained by arterial sampling except that they had a smoother tail than those obtained by sampling, which meant that ICA removed the statistical noise from the time--activity curves. The ICA-generated input function showed a longer time delay of peaks than those obtained by arterial sampling. MBFs estimated using the ICA-generated input functions ranged from 1.10 to approximately 2.52 mL/min/g at rest and from 1.69 to approximately 8.00 mL/min/g after stress and correlated well with those calculated with microspheres (y = 0.45 + 0.98x; r = 0.95, P < 0.000). CONCLUSION: ICA, a rapid and reliable method for extraction of the pure physiologic components, was a valid and useful method for quantification of the regional MBF using H(2)(15)O PET.
UNLABELLED: The independent component analysis (ICA) method is suggested to be useful for separation of the ventricles and the myocardium and for extraction of the left ventricular input function from the dynamic H(2)(15)O myocardial PET. The ICA-generated input function was validated with the sampling method, and the myocardial blood flow (MBF) calculated with this input function was compared with the microsphere results. METHODS: We assumed that the elementary activities of the ventricular pools and the myocardium were spatially independent and that the mixture of them composed dynamic PET image frames. The independent components were estimated by recursively minimizing the mutual information (measure of dependence) between the components. The ICA-generated input functions were compared with invasively derived arterial blood samples. Moreover, the regional MBF calculated using the ICA-generated input functions and single-compartment model was correlated with the results obtained from the radiolabeled microspheres. RESULTS: The ventricles and the myocardium were successfully separated in all cases within a short computation time (<15 s). The ICA-generated input functions displayed shapes similar to those obtained by arterial sampling except that they had a smoother tail than those obtained by sampling, which meant that ICA removed the statistical noise from the time--activity curves. The ICA-generated input function showed a longer time delay of peaks than those obtained by arterial sampling. MBFs estimated using the ICA-generated input functions ranged from 1.10 to approximately 2.52 mL/min/g at rest and from 1.69 to approximately 8.00 mL/min/g after stress and correlated well with those calculated with microspheres (y = 0.45 + 0.98x; r = 0.95, P < 0.000). CONCLUSION:ICA, a rapid and reliable method for extraction of the pure physiologic components, was a valid and useful method for quantification of the regional MBF using H(2)(15)O PET.
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