Investigating 4D respiratory cone-beam CT imaging for thoracic interventions on robotic C-arm systems: a deformable...

Area of Science:

• Medical Imaging
• Thoracic Interventions
• Cone-Beam CT

Background:

• Interventional thoracic procedures increasingly use cone-beam CT (CBCT) for enhanced navigation and diagnosis.
• Motion artifacts in CBCT can degrade image quality, particularly in patients unable to perform breath-holds or during mechanical ventilation.

Purpose of the Study:

• To investigate the feasibility of free-breathing 4D respiratory CBCT for motion-mitigated imaging during thoracic interventions.
• To evaluate the impact of different gantry velocities and motion-compensated reconstruction algorithms on image quality.

Main Methods:

• Implemented circular 4D respiratory CBCT trajectories on a robotic CBCT system with real-time control.
• Acquired data using an anthropomorphic breathing thorax phantom simulating patient breathing traces at gantry velocities of 2°/s, 10°/s, and 20°/s.
• Reconstructed images using filtered back projection, model-based, and iterative motion-compensated algorithms, comparing them to conventional circular acquisitions.

Main Results:

• All acquisitions showed motion blurring, with 4D respiratory CBCT exhibiting lower contrast than conventional methods.
• Motion-compensated algorithms improved image sharpness at slower gantry velocities (2°/s and 10°/s) compared to conventional acquisitions.
• Quantitative metrics like Edge Response Width (ERW) and Contrast-to-Noise Ratio (CNR) confirmed these findings.

Conclusions:

• The implemented 4D respiratory CBCT shows potential for motion mitigation in free-breathing thoracic interventions.
• Slower gantry velocities combined with motion-compensated algorithms offer improved image sharpness, crucial for challenging patient populations.
• Further optimization is needed to address contrast reduction and fully realize the benefits of this technique.