3214 - Respiratory Cycle-Resolved Ventilation Imaging Based on Dynamic CBCT for Quantitative Analysis of Lung Function
Presenter(s)
T. Zhuang1,2, R. Zuo1, H. C. Shao1, S. J. Domal1, S. Stojadinovic1, K. D. Westover1, S. B. Jiang1,2, and Y. Zhang1,2; 1Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 2MAIA Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX
Purpose/Objective(s): Ventilation imaging (VI) from motion-resolved tomography is increasingly used for noninvasive lung function assessment, but current approaches mainly rely on 4D-CT/CBCT, which suffer from phase-sorting artifacts, intra-phase residual motion, and only provide a nominal, motion-averaged breathing cycle. As a result, temporal motion variability and true lung function dynamics are not captured. In this study, we propose dynamic CBCT for VI. By eliminating phase sorting and reconstructing a CBCT volume from each X-ray projection, dynamic CBCT enables time-resolved volumetric imaging to capture both regular and irregular motion cycle-to-cycle. We hypothesize that dynamic CBCT-derived VI can quantify cycle-resolved lung function and improve correlation between functional changes and radiation dose.
Materials/Methods:
Four patients with locally advanced lung cancer treated to 60 Gy in 30 fractions were retrospectively analyzed. Dynamic CBCT was reconstructed using a recently PMF-STINR technique to derive cycle-resolved VI (CR-VI). PMF-STINR reconstructs a reference CBCT and an eigenvector-based motion model from a standard CBCT scan. Concurrently-solved projection-specific weighting factors scale the motion eigenvectors to generate time-resolved deformation vector fields (DVFs), which deform the reference CBCT into a dynamic CBCT series. From the solved dynamic DVFs, voxel-wise Jacobians were computed for each breathing cycle, and their mean (J-mean), standard deviation (J-std), and probability distributions were obtained across cycles. Lung function changes were quantified by differences in J-mean and J-std, and by the Wasserstein distance (WD) between voxel-wise Jacobian distributions at the beginning and end of treatment course. Conventional 4D-CBCT-derived Jacobian metrics were calculated using the same scan data. Correlations between Jacobian metrics (J-mean, J-std, and WD) and planned dose were evaluated for voxels within high functional lung receiving 15-40 Gy. Dose-function relationships across patients were analyzed using a linear mixed-effects model.Results:
Among J-mean, J-std and WD in dynamic CBCT-derived CR-VI, J-mean changes showed statistically significant (p<0.05) correlations with dose in both individual patients and in the linear mixed-effects model, that indicating greater functional loss at higher radiation doses. Overall, no significant correlations were observed using 4D-CBCT-derived metrics across the whole dataset.Conclusion:
We demonstrated the feasibility of quantifying lung function changes using dynamic CBCT-derived, respiratory cycle-resolved ventilation imaging, achieving improved correlation with planned dose compared with 4D-CBCT-based ventilation imaging.| Dynamic CBCT (J-mean ratio between fx30 and fx1) | 4D CBCT (J ratio between fx30 and fx1) | |
| P1 | -0.97 | -0.54(p>0.1) |
| P2 | -0.86 | -0.81 |
| P3 | -0.99 | +0.94 |
| P4 | -0.78 | -0.84 |
| Linear Mixed-effect Model (slope/p-value) | -0.03/0.02 | -0.0007/0.97 |