Reducing 4DCBCT scan time and dose through motion compensated acquisition and reconstruction.

Area of Science:

• Medical Imaging
• Radiotherapy Physics
• Computational Imaging

Background:

• Conventional 4D cone-beam CT (4DCBCT) involves lengthy scan times and high imaging doses.
• Adaptive 4DCBCT has been developed to mitigate these limitations by modulating acquisition parameters.
• Optimizing reconstruction algorithms is crucial for maximizing the benefits of adaptive 4DCBCT.

Purpose of the Study:

• To evaluate reconstruction algorithms for adaptive 4DCBCT in lung cancer radiotherapy.
• To compare image quality, dose reduction, and scan time against conventional 4DCBCT.
• To establish optimal acquisition-reconstruction protocols for adaptive 4DCBCT.

Main Methods:

• Adaptive 4DCBCT was implemented in a clinical trial, acquiring 200- and 600-projection datasets.
• Reconstructions were performed using Feldkamp-Davis-Kress (FDK), McKinnon-Bates (MKB), and their motion-compensated variants (MCFDK, MCMKB).
• Image quality was assessed using SSIM, SNR, CNR, and tissue interface sharpness metrics.

Main Results:

• Adaptive 4DCBCT with 200 and 600 projections reduced imaging dose by 85% and 55%, respectively.
• Scan times were reduced to approximately 90s and 236s.
• Motion-compensated algorithms (MCFDK, MCMKB) with 200 projections improved SNR, CNR, and sharpness metrics significantly compared to conventional 4DCBCT.

Conclusions:

• Adaptive 4DCBCT, particularly with 200 projections and motion-compensated reconstruction, offers substantial reductions in scan time and imaging dose.
• Image quality can be maintained or improved, demonstrating the potential of these optimized protocols.
• This study establishes effective acquisition-reconstruction strategies for adaptive 4DCBCT in thoracic radiotherapy.