Feasibility of a Prototype Image Reconstruction Algorithm for Motion Correction in Interventional Cone-Beam CT Scans

Area of Science:

• Medical Imaging
• Radiology
• Image Reconstruction

Background:

• Motion artifacts degrade image quality in cone-beam CT (CBCT) scans, particularly during lung interventions.
• Accurate visualization of interventional instruments is crucial for navigation bronchoscopy procedures.

Purpose of the Study:

• To assess the feasibility of a prototype algorithm for correcting motion artifacts in lung CBCT scans.
• To evaluate the algorithm's effectiveness in improving the sharpness of interventional instruments.

Main Methods:

• Phantom experiments with moving catheters under sinusoidal and breath-hold patterns.
• Application of the algorithm to CBCT data from 27 navigation bronchoscopy procedures.
• Quantitative assessment using edge-sharpness measurements and qualitative assessment by specialists.

Main Results:

• The algorithm improved sharpness in most phantom scans, especially with larger motion amplitudes.
• Motion-corrected CBCT reconstructions showed significantly sharper edges compared to standard reconstructions (p=0.003).
• Qualitative assessment confirmed improved sharpness of instrument-tissue interfaces, though tumor demarcation was inconsistent.

Conclusions:

• The prototype motion correction algorithm is feasible for CBCT imaging in lung interventions.
• The algorithm effectively enhances the sharpness of medical instruments in navigation bronchoscopy scans.
• Further refinement may be needed to address overall image quality and inter-rater variability in tumor demarcation.