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Robust fitting for neuroreceptor mapping.

Chung Chang1, R Todd Ogden

  • 1Department of Mathematical Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102-1982, USA. cchang@njit.edu

Statistics in Medicine
|December 26, 2008
PubMed
Summary
This summary is machine-generated.

Quantile regression (QR) offers a robust alternative to traditional nonlinear least-squares (LS) for analyzing positron emission tomography (PET) data, especially when artifacts are present. Simulations show QR performs well, and a new method helps choose between QR and LS.

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Biostatistics

Background:

  • Positron emission tomography (PET) quantifies neuroreceptor density using radiotracer kinetics.
  • Common kinetic modeling relies on nonlinear least-squares (LS) algorithms.
  • LS methods are sensitive to artifacts like head motion, violating underlying assumptions.

Purpose of the Study:

  • To evaluate quantile regression (QR) as a robust alternative to LS for PET kinetic modeling.
  • To compare the performance of QR and LS methods through simulation studies.
  • To propose and assess a data-adaptive method for selecting between LS and QR.

Main Methods:

  • Fitting various kinetic models to simulated PET data using both LS and QR.
  • Performance evaluation based on simulation outcomes.
  • Development and testing of a data-adaptive LS/QR selection algorithm.

Main Results:

  • Quantile regression (QR) demonstrates robustness in PET kinetic modeling, particularly with simulated artifacts.
  • Simulations indicate competitive or superior performance of QR compared to LS under certain conditions.
  • The proposed data-adaptive method shows promise in guiding the choice between LS and QR.

Conclusions:

  • QR is a valuable, robust tool for PET kinetic modeling, especially when data quality is compromised.
  • The data-adaptive selection method provides a practical approach to optimize model choice.
  • Further validation of QR and the selection method in real-world PET studies is warranted.