A data-driven respiratory motion correction for pediatric DMSA renal SPECT imaging: A simulation study.

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Pediatric Imaging

Background:

• Technetium-99m-dimercaptosuccinic acid (DMSA) renal scintigraphy is crucial for evaluating pediatric urinary tract infections.
• Pyelonephritis and scarring appear as defects on DMSA renal scintigraphy, including SPECT imaging.
• Respiratory motion degrades SPECT image quality, necessitating motion correction.

Purpose of the Study:

• Develop and evaluate a data-driven method for estimating respiratory motion signals.
• Apply these signals to correct respiratory motion in pediatric DMSA renal SPECT imaging.
• Improve diagnostic accuracy through enhanced image quality.

Main Methods:

• Utilized XCAT phantom and SPECT Monte Carlo simulation for 100 ms projections.
• Employed axial center-of-count-mass (aCOM) to estimate surrogate respiratory signals.
• Reconstructed images across seven motion states and applied rigid-body registration for motion correction.

Main Results:

• Achieved a Pearson's correlation coefficient (r) of 0.76 between estimated and true respiratory motion.
• Demonstrated significant improvement in Normalized Root Mean Square Error (NRMSE) with motion correction for motion amplitudes >10 mm.
• No significant difference in NRMSE for motion amplitudes between 6-10 mm.

Conclusions:

• Data-driven respiratory motion correction enhances pediatric renal SPECT image quality.
• The method shows potential for improved diagnostic accuracy in studies with moderate motion.
• Further validation is recommended for clinical application.