Quantification of myocardial perfusion in human subjects using Rb-82 and wavelet-based noise reduction

Quantification of myocardial perfusion with Rb-82 has been difficult to ach ieve because of the low signal-to-noise ratio of the dynamic data curves. T his study evaluated the accuracy of flow estimates after the application of a novel multidimensional wavelet-based noise-reduction protocol. Methods: Myocardial perfusion was estimated using Rb-82 and a two-compartment model from dynamic PET scans on 11 healthy volunteers at rest and after hyperemic stress with dipyridamole. Midventricular planes were divided into eight re gions of interest, and a wavelet transform protocol was applied to images a nd time-activity curves. Flow estimates without and with the wavelet approa ch were compared with those obtained using (H2O)-O-15, Results: Over a wide flow range (0.45-2.75 mL/g/min), flow achieved with the wavelet approach c orrelated extremely closely with values obtained with (H2O)-O-15 (y = 1.03 x -0.12; n = 23 studies, r = 0,94, P < 0.001). If the wavelet noise-reducti on technique was not used, the correlation was less strong (y = 1.11 x + 0. 24; n = 23 studies, r = 0.79, P < 0.001), In addition, the wavelet approach reduced the regional variation from 75% to 12% and from 62% to 11% (P < 0. 001 for each comparison) for resting and stress studies, respectively. Conc lusion: The use of a wavelet protocol allows near-optimal noise reduction, markedly enhances the physiologic flow signal within the PET images, and en ables accurate measurement of myocardial perfusion with Rb-82 in human subj ects over a wide range of flows.