Scatter correction based on an artificial neural network for ^99mTc and ¹²³I dual-isotope SPECT in myocardial and brain imaging

The aim of this study was to elucidate the clinical usefulness of scatter correction with an artificial neural network (ANN) in ^99mTc and ¹²³I dual-isotope SPECT. Methods: Two algorithms for ANN scatter correction were tested: ANN-10 and ANN-3 employing 10 and 3 energy windows for data acquisition, respectively. Three patients underwent myocardial or brain SPECT with one of the following combinations of radiopharmaceuticals administered: ^99mTc-tetrofosmin and ¹²³I- metaiodobenzylguanidine (MIBG), ^99mTc-methoxyisobutylisonitrile (MIBI) and ¹²³I-beta-methylparaiodophenyl-pentadecanoic acid (BMIPP), or ^99mTc-ethyl-cistainate dimmer (ECD) and ¹²³I- iomazenil. The patients were also referred for single-isotope imaging incorporating conventional triple-energy window (TEW) scatter correction. Crosstalk- and scatter-corrected ^99mTc- and ¹²³I-SPECT images in dual-isotope acquisition with ANN were compared with those in single-isotope acquisition. Results: The ANN method well separated ¹²³I and ^99mTc primary photons. Although ANN-10 yielded images of poor quality, ANN-3 offered comparable image quality with the single-isotope scan without significant increase of acquisition time. Conclusion: The proposed method is clinically useful because it provides various combinations of information without anatomical misregistration with one acquisition.