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

Rationale and Objectives: Assess the feasibility of a prototype image reconstruction algorithm in correcting motion artifacts in cone-beam computed tomography (CBCT) scans of interventional instruments in the lung.
Materials and Methods: First, phantom experiments were performed to assess the algorithm, using the Xsight lung phantom with custom inserts containing straight or curved catheters. During scanning, the inserts moved in a continuous sinusoidal or breath-hold mimicking pattern, with varying amplitudes and frequencies. Subsequently, the algorithm was applied to CBCT data from navigation bronchoscopy procedures. The algorithm's performance was assessed quantitatively via edge-sharpness measurements and qualitatively by three specialists.
Results: In the phantom study, the algorithm improved sharpness in 13 out of 14 continuous sinusoidal motion and five out of seven breath-hold mimicking scans, with more significant effects at larger motion amplitudes. Analysis of 27 clinical scans showed that the motion corrected reconstructions had significantly sharper edges than standard reconstructions (2.81 (2.24-6.46) vs. 2.80 (2.16-4.75), p = 0.003). These results were consistent with the qualitative assessment, which showed higher scores in the sharpness of bronchoscope-tissue interface and catheter-tissue interface in the motion-corrected reconstructions. However, the tumor demarcation ratings were inconsistent between raters, and the overall image quality of the new reconstructions was rated lower.
Conclusion: Our findings suggest that applying the new prototype algorithm for motion correction in CBCT images is feasible. The algorithm improved the sharpness of medical instruments in CBCT scans obtained during diagnostic navigation bronchoscopy procedures, which was demonstrated both quantitatively and qualitatively.
Competing Interests: Declaration of Competing Interest J.J.F. and M.M.R. have received a research grant from Siemens Healthineers, which was paid to the institute, without restrictions regarding publications or data. R.L.J.V. declares that his department has a research contract with Siemens Healthineers. P.F. is an employee of Siemens Healthcare GmbH. His contribution to this research was primarily in providing technical expertise and ensuring the accuracy of the technical content in the paper. All other authors declare no conflict of interest that could have affected the work reported in this paper. Siemens Healthineers had no role in data collection, data analysis, interpretation of the results, or the decision to submit for publication.
(Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)