Effect of data-driven motion correction for respiratory movement on lesion detectability in PET-CT: a phantom study

Area of Science:

• Nuclear medicine
• Medical imaging
• Radiochemistry

Background:

• Data-driven motion correction (DDMC) techniques enhance lesion visibility in PET-CT scans.
• The impact of DDMC on overall lesion detectability remains unclear.

Purpose of the Study:

• To investigate if DDMC improves lesion detectability in 18F-FDG PET-CT imaging.
• To assess the effect of DDMC on contrast and detectability metrics.

Main Methods:

• A NEMA-IEC body phantom simulated respiratory motion with varying amplitudes (0-30 mm) and target-to-background ratios.
• PET-CT scans were reconstructed with and without DDMC.
• Maximal and mean recovery coefficients (RC) and contrast-to-noise ratios (CNR) were measured.

Main Results:

• DDMC increased RC values in target spheres.
• CNR improved for small targets with high motion but decreased for larger spheres with low motion.
• DDMC increased sphere contrast by 36% but also increased background noise.

Conclusions:

• DDMC enhances contrast but has a less profound impact on detectability due to increased background noise.
• CNR improved for small, high-motion targets, potentially aiding detection of low-uptake lesions.
• DDMC reconstructions are recommended in addition to non-DDMC reconstructions to balance motion correction benefits with noise impact.