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Longitudinal mouse-PET imaging: a reliable method for estimating binding parameters without a reference region or

Catriona Wimberley1,2, Duc Loc Nguyen3, Charles Truillet3

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|March 27, 2020
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Summary

This study introduces a novel factor analysis method for extracting image-derived input functions in longitudinal mouse PET imaging. This approach improves quantification accuracy and avoids challenging blood sampling, yielding results closer to ex vivo measurements.

Keywords:
Factor analysisImage-derived input functionMousePETTSPO

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Area of Science:

  • Nuclear medicine
  • Medical imaging
  • Pharmacokinetics

Background:

  • Longitudinal mouse PET imaging is crucial for disease modeling but faces challenges due to small brain size and difficult blood sampling.
  • Accurate quantification in these studies is hindered by limited spatial resolution and the absence of a true reference region.

Purpose of the Study:

  • To develop and validate a robust method for extracting an image-derived input function (IDIF) for accurate quantification in longitudinal mouse PET studies.
  • To improve spatial resolution and reduce noise in dynamic PET data using a 4D-resolution recovery and denoising (4D-RRD) technique.

Main Methods:

  • Dynamic, whole-body 18F-DPA-714 PET scans were acquired in a mouse model of hippocampal sclerosis.
  • A factor analysis (FA) approach was used to extract an image-derived input function (IDIF).
  • The IDIF was applied to 4D-resolution recovery and denoising (4D-RRD), and total volume of distribution (VT) was calculated using a basis function approach.

Main Results:

  • The factor analysis-derived input function (IDIF) showed strong correlation with injected dose.
  • Quantification using 4D-resolution recovery and denoising (4D-RRD) demonstrated improved regional correlations with ex vivo autoradiography for both %ID (R=0.72) and VT (R=0.79) estimates.
  • The developed method yielded parameter estimates closer to ex vivo measurements compared to semi-quantitative methods.

Conclusions:

  • The factor analysis (FA) approach for image-derived input function (IDIF) extraction is robust, reproducible, and suitable for advanced quantification in longitudinal mouse PET studies.
  • This method enhances resolution recovery, denoising, and parameter estimation, providing more accurate results than traditional methods.
  • The approach enables precise quantification in longitudinal mouse PET studies without the need for repeated arterial blood sampling.