Estimation of and correction for finite motion sampling errors in small animal PET rigid motion correction

Area of Science:

• Medical Imaging
• Biophysics
• Image Reconstruction

Background:

• Finite time sampling of motion data in positron emission tomography (PET) leads to residual motion, degrading spatial resolution in motion-corrected reconstructions.
• Small animal PET imaging requires accurate motion correction to maintain image quality, especially during dynamic scans with moving subjects.

Purpose of the Study:

• To develop a method for estimating the impact of finite motion sampling on PET spatial resolution.
• To correct for residual motion and minimize resolution loss in motion-corrected PET images.

Main Methods:

• Calculation of a spatially variant deconvolution kernel from measured motion data.
• Application of the deconvolution kernel to motion-corrected PET images using a 3D Richardson-Lucy algorithm.

Main Results:

• A reduction in average rod full-width at half-maximum (FWHM) differences from 9.7% to 5.8% in microDerenzo phantom experiments comparing slow and fast motion.
• Demonstrated mitigation of spatial resolution degradation due to finite sampling in awake animal PET experiments.

Conclusions:

• The proposed deconvolution method effectively corrects for residual motion caused by finite sampling in PET motion correction.
• This technique minimizes resolution loss, improving the accuracy and reliability of small animal PET imaging, particularly for dynamic studies involving subject motion.