Purpose: Presence of photon attenuation severely challenges quantitative accuracy
in single-photon emission computed tomography (SPECT) imaging. Subsequently,
various attenuation correction methods have been developed to compensate for
this degradation. The present study aims to implement an attenuation correction
method and then to evaluate quantification accuracy of attenuation correction in
small-animal SPECT imaging.
Methods: Images were reconstructed using an iterative reconstruction method
based on the maximum-likelihood expectation maximization (MLEM) algorithm
including resolution recovery. This was implemented in our designed dedicated
small-animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values
were converted to activity concentration via a calculated calibration factor. An
attenuation correction algorithm was developed based on the first-order Chang’s
method. Both phantom study and experimental measurements with four rats were
used in order to validate the proposed method.
Results: The phantom experiments showed that the error of �15.5% in the estimation
of activity concentration in a uniform region was reduced to +5.1% when
attenuation correction was applied. For in vivo studies, the average quantitative
error of �22.8 � 6.3% (ranging from �31.2% to �14.8%) in the uncorrected images
was reduced to +3.5 � 6.7% (ranging from �6.7 to +9.8%) after applying attenuation
correction.
Conclusion: The results indicate that the proposed attenuation correction algorithm
based on the first-order Chang’s method, as implemented in our dedicated small-animal
SPECT system, significantly improves accuracy of the quantitative analysis as
well as the absolute quantification
