Wavelet analysis of dynamic PET data: Application to the parametric imaging of benzodiazepine receptor concentration

Receptor density and ligand affinity can be assessed using positron emissio n tomography (PET). Biological parameters (B-max', k(1), k(2), k(on)/V-R, k (off)) are estimated using a compartmental model and a multi-injection prot ocol. Parametric imaging of the ligand-receptor model has been shown to be of special interest to study certain brain disorders. However, the low sign al-to-noise ratio in kinetic curves at the pixel level hampers an adequate estimation of model parameters during the optimization procedure. For this reason, mapping requires a spatial filter, resulting in a loss of resolutio n. Filtering the kinetic curves in the frequency domain using the Fourier t ransform is not appropriate, because of difficulties in choosing a correct and efficient cutoff frequency, A wavelet-based filter is more appropriate to such tracer kinetics. The purpose of this study is to build up parametri c images at the pixel level while conserving the original spatial resolutio n, using wavelet-based filtering. Data from [C-11]flumazenil studies, mappi ng the benzodiazepine receptor density, were used. An invertible discrete w avelet transform was used to calculate the time-frequency signals of the ti me-concentration PET curves on a pixel-by-pixel basis. Kinetic curves obser ved from large regions of interest in high and low receptor-density regions were used to calibrate the threshold of wavelet coefficients. The shrunken wavelet coefficients were then transformed back to the original domain in order to obtain the filtered PET signal. Maps of all binding parameters wer e obtained at the pixel level with acceptable coefficients of variation of less than 30% for the B-max' parameter in most of the gray matter, A strong correlation between model parameter estimates using the usual regions of i nterest and parametric imaging was observed for all model parameters (r = 0 .949 for the parameter B-max'). We conclude that wavelet-based filters are useful for building binding parameter maps without loss of the original spa tial resolution of the PET scanner. The use of the wavelet-based filtering method can be extended far beyond the multi injection protocol, It is likel y to be also effective for other dynamic PET studies. (C) 2000 Academic Pre ss.