Transmission-dependent convolution subtraction of 99mTc-HMPAO rCBF SPECT-a Monte Carlo study

Transmission-dependent convolution subtraction has been shown to be useful when correcting for malpositioned scattered events in single photon emission computed tomography (SPECT). The method is based on convolution subtraction but includes a matrix of scatter fractions instead of a global scatter fraction. In this study, this method is evaluated for regional cerebral blood flow SPECT with ^99mTc-hexamethyl propylene-amine oxime (HMPAO) by using Monte Carlo simulations. Different geometries for generating the scatter fractions as a function of the attenuation path length are studied and compared. The most optimal value of the exponential describing the falloff of the monoexponential scatter kernel is determined for each geometry. The method is also compared with convolution subtraction with a global scatter fraction. It is shown that the most optimal of the tested geometries is a homogeneous activity distribution. A scatter kernel with an exponential of 0.15 pixel^-1 is most optimal for this geometry. A comparison with convolution subtraction shows that transmission-dependent convolution subtraction can give more accurate results if used with optimal parameters.