Characterization of 4D Lung Ventilation Based On 4DCT Lung Density
G Li1*, J Wei2, D Li3, A Ballangrud4, (1) Memorial Sloan-Kettering Cancer Center, NEW YORK, NY, (2) City College of New York, NYC, NY, (3) Memorial Sloan-Kettering Cancer Center, New York, NY, (4) Memorial Sloan-Kettering Cancer Center, New York, NYSU-E-J-120 Sunday 3:00:00 PM - 6:00:00 PM Room: Exhibit Hall
Purpose: To characterize patient's 4D lung ventilation and motion using 4DCT images aiming to extract pulmonary features for developing a biomechanical model to predict lung tumor motion.
Methods: 4DCT images of sixteen patients were used for initial 4D-ventilation evaluation. A program was developed for visualization and quantification of 4D lung ventilation. Lung density gradient and pleural pressure variation were evaluated based on the gravity. Freeform deformable image registration (DIR) was applied to map the lung density from one phase to another, with linearly interpolated voxel density. The warped lung density from a secondary CT was compared with the primary CT (full-exhalation) for quantification. To minimize the uncertainty from motion artifacts for quantitative ventilation/motion analysis, we developed two screening algorithms (based on Fourier Transformation and Generalized Linear Regression) to quantify the regularity (score: 0 to 1) of the RPM waveform, assuming the higher the regularity in RPM the less motion artifacts in 4DCT. Ninety-seven RPM curves (54 free-breathing and 43 audio-coaching patients) were used to qualitatively test these screening methods.
Results: Lung density gradient in anterior-posterior direction for supine patients is observed in 15/16 patients at scale of >100-200HU. The gravity pressure due to lung tissue weight is estimated to be ~4mmHg, which could neutralize the pleural pressure at the posterior chest wall. The different pleural pressures at anterior/posterior chest walls may explain the difference in local diaphragm muscle engagement and motion range: 8±5mm (anterior) and 23±12mm (posterior). Motion artifacts and DIR uncertainty affected quantitative ventilation mapping. In the RPM regularity assessment, audio-coaching patients score higher than free-breathing patients: 0.76±0.13 vs. 0.50±0.19 (Fourier method) and 0.74±0.19 vs. 0.66±0.17 (Regression method). High-quality 4DCTs can be readily selected for further quantitative ventilation/motion analysis.
Conclusions: We have characterized several basic features of lung ventilation and motion and developed two effective screening methods for high-quality 4DCT for on-going quantitative studies.