DocumentCode :
2553895
Title :
Myocardial blood flow from dynamic PET using Independent Component Analysis
Author :
Karpikov, Alexander ; Tagare, Hemant ; Mulnix, T. ; Gallezot, Jean-Dominique ; Sinusas, Albert ; Chi Liu ; Carson, Richard E.
Author_Institution :
PET Center, Yale Univ., New Haven, CT, USA
fYear :
2012
fDate :
Oct. 27 2012-Nov. 3 2012
Firstpage :
2222
Lastpage :
2226
Abstract :
Generation of parametric images of myocardial blood flow (MBF) from dynamic PET requires a reproducible and reliable method to obtain left and right ventricular time-activity curves. We propose the use of Independent Component Analysis (ICA) on PET temporal information to segment the image data into three categories: right ventricle (RV), left ventricle (LV) and myocardium. ICA is an established signal processing technique that assumes that the dynamic signal in each voxel is a linear mixture of signals from statistically independent sources. The mixing process is due to cardiac motion and partial volume effects. Due to its ability to find the intensity of the underlying sources, ICA generates a 3D map of the mixing coefficients that allows the segmentation of structures. Dynamic cardiac PET data were acquired with a Siemens Biograph mCT PET/CT scanner using Rb-82 and [15O]water in nonhuman primate and pigs with injections of different activities. The Dice similarity coefficient (DSC) was used to compare the segmentations between scans of different species with different tracers. The LV and RV regions were used to calculate input functions for kinetic analysis and MBF estimation. Pairwise comparisons of the segmentations between different [15O]water PET scans gave DSC of 0.91 ± 0.09 and 0.92±0.08 for the RV and LV segmentations, respectively. For Rb-82 PET scans, the DSC values were of 0.89 ± 0.09 and 0.85±0.10 for RV and LV. We used contrast CT as a gold standard for the LV and RV segmentations. Pairwise comparisons of the segmentations between different contrast CT and Rb-82 PET scans gave DSC of 0.86 ± 0.09 and 0.85±0.09 for the RV and LV, respectively. Our work shows the reliability and reproducibility of the results of the segmentation algorithm. High quality parametric images of MBF and the kinetic parameters were obtained. These results suggest that ICA may be useful to extract time-activi- y curves for kinetic MBF analysis. The effects of partial volume on input TAC determination were also evaluated.
Keywords :
cardiology; computerised tomography; haemodynamics; image segmentation; independent component analysis; medical image processing; positron emission tomography; reliability; 3D map; ICA; LV segmentations; MBF estimation; PET temporal information; RV segmentations; Rb-82 PET scans; Siemens biograph mCT PET-CT scanner; [150] water PET scans; cardiac motion; dice similarity coefficient; dynamic cardiac PET data; gold standard; high quality parametric images; image data segmentation; independent component analysis; input TAC determination; kinetic MBF analysis; kinetic analysis; kinetic parameters; left ventricular time-activity curves; linear signal mixture; mixing coefficients; mixing process; myocardial blood flow; parametric image generation; partial volume effects; right ventricular time-activity curves; segmentation algorithm; signal processing technique; statistically independent sources; time-activity curves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2012 IEEE
Conference_Location :
Anaheim, CA
ISSN :
1082-3654
Print_ISBN :
978-1-4673-2028-3
Type :
conf
DOI :
10.1109/NSSMIC.2012.6551506
Filename :
6551506
Link To Document :
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