Background: We contrived a scatter correction method based on an artificial neural network (ANN) and applied it to the simultaneous evaluation of myocardial perfusion and fatty acid metabolism in single-photon emission computed tomography (SPECT).
Methods: The count data of three energy windows were used as inputs of the ANN. The count ratios of the estimated primary-to-total photons for (99m)Tc and (123)I, which were used to reconstruct (99m)Tc and (123)I images, were calculated using the ANN. In a phantom study, single- and dual-isotope imaging with (99m)Tc/(123)I and (201)Tl/(123)I was performed by means of a cardiac phantom simulating patients with and without obesity. In a human study, five normal volunteers and ten patients with myocardial infarction underwent myocardial perfusion and fatty acid metabolism imaging with single and dual SPECT with combinations of (99m)Tc-methoxyisobutylisonitrile/(123)I-beta-methyl(p-iodophenyl)pentadecanoic acid (BMIPP) and (201)Tl/(123)I-BMIPP as tracers.
Results: Technetium-99m yielded more homogeneous images than (201)Tl because of the lower degree of photon attenuation, especially in the condition of obese patients, resulting in clearer visualization of the perfusion-metabolism mismatch. Dual (99m)Tc/(123)I SPECT offered comparable images with single SPECT in assessing myocardial damage.
Conclusions: The method effectively separated (99m)Tc and (123)I primary photons and proved applicable to (99m)Tc/(123)I dual-isotope myocardial SPECT.