Purpose: Lung expansions/contractions are not only spatially but also temporally heterogeneous during respiration. Current static lung function imaging techniques cannot assess the entire breathing cycle. To address this gap, we present a streamlined "map-and-warp" phase-resolved ventilation imaging method based on 4DCT to recover the dynamic lung ventilation process.
Methods: Ten-phase free-breathing 4DCT scans of 15 lung or esophageal cancer patients were collected from the public datasets. The lung region was first delineated in each phase, then the mask-free deformable image registration was used to derive the deformation vector fields between the end-expiration (EE) phase and other phases. In the EE phase coordinate, the parameterized Integrated Jacobian Formulation method with modified linear constraints estimated the voxel-wise local expansion ratio of each phase relative to the EE phase as a surrogate of ventilation. Lastly, the dynamic ventilation images were generated by warping these phase-specific local expansion distributions with a same geometry into their respective breathing phases. Inter-phase correlation analysis, voxel-wise and regional-wise expansion/contraction tracking were performed for validation.
Results: The proposed method maintains the physiological meaning of ventilation on each phase, and enables to describe the regional lung expansion/contraction patterns throughout the entire respiration cycle. The mean inter-phase Spearman correlations ranged between 0.23 (0.20) and 0.93 (0.04), and decreased near the EE phase. Only 26.2% (2.59E+6 out of 9.89E+6) of lung voxels exhibited the same expansion/contraction pattern as the global lung. Qualitative and quantitative evaluations of the inter-phase ventilation distribution difference show that ventilation spatiotemporal heterogeneities generally exist during respiration.
Conclusion: A method to generate dynamic phase-resolved ventilation images based on 4DCT has been successfully demonstrated. This method has the potential to facilitate more accurate implementation of functional lung avoidance radiotherapy, and further our understanding of lung function and respiration mechanics.
Funding Support, Disclosures, and Conflict of Interest: This work was supported in part by General Research Fund (GRF15103520) from The University Grants Committee, and Health and Medical Research Fund (HMRF07183266) from The Food and Health Bureau, The Government of the Hong Kong Special Administrative Regions.