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Optimized dynamic framing for PET-based myocardial blood flow estimation.

Jeffrey A Kolthammer1, Raymond F Muzic

  • 1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA. jeffrey.kolthammer@case.edu

Physics in Medicine and Biology
|August 6, 2013
PubMed
Summary

Optimizing dynamic positron emission tomography (PET) framing schedules improves myocardial blood flow estimation using Rubidium-82. A new method ensures precise measurements across various physiological conditions and infusion durations.

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Area of Science:

  • Nuclear Medicine
  • Medical Imaging Physics
  • Biomedical Engineering

Background:

  • Dynamic Positron Emission Toming (PET) requires precise framing schedules for accurate myocardial blood flow (MBF) estimation.
  • Current methods for selecting PET framing schedules may not be optimal for all physiological conditions or tracer infusion durations.

Purpose of the Study:

  • To develop an optimal experiment design methodology for selecting dynamic PET framing schedules.
  • To improve the precision of MBF estimation using Rubidium-82 ((82)Rb).

Main Methods:

  • A compartment model and measured arterial input function were used to calculate a D-optimality criterion for candidate framing schedules.
  • Noisy time-activity curves were simulated to validate optimality calculations and estimate parameters.

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  • Robustness was assessed by simulating various physiological conditions and infusion durations.

    • Main Results:

    • D-optimized framing schedules significantly improved estimate precision compared to non-optimized and previously published schedules.
    • Optimized schedules demonstrated robustness across a range of physiological conditions.
    • Optimality was better for shorter infusion durations, with the shortest-duration optimal schedule performing well for others.

    Conclusions:

    • A general method for optimizing dynamic PET framing schedules was developed, enhancing MBF estimation precision.
    • Optimized schedules are robust to variations in physiological conditions and infusion durations, simplifying study protocols.
    • This methodology can be applied to other dynamic PET imaging applications.