Literature DB >> 23460077

Simultaneous dual-isotope imaging based on an artificial neural network for evaluating myocardial perfusion and fatty acid metabolism.

Jun Hashimoto1, Koichi Ogawa, Jingming Bai, Atsushi Kubo, Yutaka Imai.   

Abstract

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.

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Year:  2013        PMID: 23460077     DOI: 10.1007/s12350-013-9699-x

Source DB:  PubMed          Journal:  J Nucl Cardiol        ISSN: 1071-3581            Impact factor:   5.952


  12 in total

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

Authors:  Jingming Bai; Jun Hashimoto; Koichi Ogawa; Tadaki Nakahara; Takayuki Suzuki; Atsushi Kubo
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