Scatter correction based on an artificial neural network for99mTc and123I 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-methyl-paraiodophenyl-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.