KMID : 1148920130470020104
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Nuclear Medicine and Molecular Imaging 2013 Volume.47 No. 2 p.104 ~ p.114
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Is it Feasible to Use the Commercially Available Autoquantitation Software for the Evaluation of Myocardial Viability on Small-Animal Cardiac F-18 FDG PET Scan?
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Pahk Ki-Soo
Oh Sun-Young Jeong Eu-Gene Lee Sung-Ho Woo Sang-Keun Yu Jung-Woo Choe Jae-Gol Cheon Gi-Jeong
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Abstract
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Purpose: To evaluate the reliability of quantitation of myocardial viability on cardiac F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) scans with three different methods of visual scoring system, autoquantitation using commercially available autoquantitation software, and infarct-size measurement using histogram-based maximum pixel threshold identification on polar-map in rat hearts.
Methods: A myocardial infarct (MI) model was made by left anterior descending artery (LAD) ligation in rat hearts. Eighteen MI rats underwent cardiac FDG-PET-computed tomography (CT) twice within a 4-week interval. Myocardium was partitioned into 20 segments for the comparison, and then we quantitated non-viable myocardium on cardiac FDG PET-CT with three different methods: method A?infarct-size measurement using histogram-based maximum pixel threshold identification on polar-map; method B?summed MI score (SMS) by a four-point visual scoring system; method C?metabolic non-viable values by commercially available autoquantitation software. Changes of non-viable myocardium on serial PET-CT scans with three different methods were calculated by the change of each parameter. Correlation and reproducibility were evaluated between the different methods.
Results: Infarct-size measurement, visual SMS, and non-viable values by autoquantitation software presented proportional relationship to each other. All the parameters of methods A, B, and C showed relatively good correlation between each other. Among them, infarct-size measurement (method A) and autoquantitation software (method C) showed the best correlation (r?=?0.87, p?0.001). When we evaluated the changes of non-viable myocardium on the serial FDG-PET-CT- however, autoquantitation program showed less correlation with the other methods. Visual assessment (method B) and those of infarct size (method A) showed the best correlation (r?=?0.54, p?=?0.02) for the assessment of interval changes.
Conclusions: Commercially available quantitation software could be applied to measure the myocardial viability on small animal cardiac FDG-PET-CT scan. This kind of quantitation showed good correlation with infarct size measurement by histogram-based maximum pixel threshold identification. However, this method showed the weak correlation when applied in the measuring the changes of non-viable myocardium on the serial scans, which means that the caution will be needed to evaluate the changes on the serial monitoring.
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KEYWORD
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Myocardial viability, FDG PET, Autoquantitation, Myocardial infarct model
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