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Med. Phys. 37, 3995 (2010); http://dx.doi.org/10.1118/1.3438474 (16 pages)

Kinetic model-based factor analysis of dynamic sequences for 82-rubidium cardiac positron emission tomography

R. Klein, R. S. Beanlands, S. L. Thorn, M. Lamoureux, J. N. DaSilva, and R. A. deKemp

National Cardiac PET Centre, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, Ontario K1Y 4W7, Canada

R. W. Wassenaar

Division of Nuclear Medicine, The Ottawa Hospital, 1053 Carling Avenue, Ottawa, Ontario, K1Y 4E9, Canada

A. Adler

Systems and Computer Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada

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(Received 26 February 2010; accepted 5 May 2010; revised 23 April 2010; published online 13 July 2010)

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Purpose: Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique temporal signatures to improve quantification of physiological function. In this work, the authors present a novel kinetic model-based (MB) method that includes physiological models of factor relationships within the decomposition process. The physiological accuracy of MB decomposed 82Rb cardiac PET images is evaluated using simulated and experimental data. Precision of myocardial blood flow (MBF) measurement is also evaluated.
Methods: A gamma-variate model was used to describe the transport of 82Rb in arterial blood from the right to left ventricle, and a one-compartment model to describe the exchange between blood and myocardium. Simulations of canine and rat heart imaging were performed to evaluate parameter estimation errors. Arterial blood sampling in rats and 11CO blood pool imaging in dogs were used to evaluate factor and structure accuracy. Variable infusion duration studies in canine were used to evaluate MB structure and global MBF reproducibility. All results were compared to a previously published minimal structure overlap (MSO) method.
Results: Canine heart simulations demonstrated that MB has lower root-mean-square error (RMSE) than MSO for both factor (0.2% vs 0.5%, p<0.001 MB vs MSO, respectively) and structure (3.0% vs 4.7%, p<0.001) estimations, as with rat heart simulations (factors: 0.2% vs 0.9%, p<0.001 and structures: 3.0% vs 6.7%, p<0.001). MB blood factors compared to arterial blood samples in rats had lower RMSE than MSO (1.6% vs 2.2%, p = 0.025). There was no difference in the RMSE of blood structures compared to a 11CO blood pool image in dogs (8.5% vs 8.8%, p = 0.23). Myocardial structures were more reproducible with MB than with MSO (RMSE = 3.9% vs 6.2%, p<0.001), as were blood structures (RMSE = 4.9% vs 5.6%, p = 0.006). Finally, MBF values tended to be more reproducible with MB compared to MSO (CV = 10% vs 18%, p = 0.16). The execution time of MB was, on average, 2.4 times shorter than MSO (p<0.001) due to fewer free parameters.
Conclusions: Kinetic model-based factor analysis can be used to provide physiologically accurate decomposition of 82Rb dynamic PET images, and may improve the precision of MBF quantification.

© 2010 American Association of Physicists in Medicine

Article Outline

  1. INTRODUCTION
  2. METHODS AND MATERIALS
    1. Minimal structure overlap (MSO) constrained factor analysis
    2. MB factor analysis
      1. Optimization
    3. Number of factors
    4. Simulations
      1. Canine simulation
      2. Small animal simulation
      3. Analysis of simulation studies
    5. Experimental studies
      1. Factor validation with arterial blood sampling
      2. Structure validation with 11CO blood pool imaging
      3. Global MBF reproducibility using variable tracer infusion durations
      4. Structure reproducibility using variable tracer infusion durations
    6. Statistical analysis
  3. RESULTS
    1. Canine simulation
    2. Small animal simulation
    3. Experimental factor validation with arterial sampling
    4. Structure validation with 11CO blood pool imaging
    5. Structure reproducibility using variable tracer infusion durations
    6. Global MBF reproducibility using variable tracer infusion durations
  4. DISCUSSION
    1. Residual signal
    2. Penalty weights
    3. Execution time
    4. Blood clearance
    5. 11CO blood pool images
    6. 82Rb blood sampling in rats
    7. 82Rb infusion duration
    8. MB with other tracers
    9. Number of factors
    10. Application of FA to quantification of myocardial physiology
  5. CONCLUSION

KEYWORDS and PACS

PACS

PUBLICATION DATA

ISSN

0094-2405 (print)  

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