(Sunday, 7/14/2019) 5:00 PM - 6:00 PM
Room: 221AB
Purpose: Lung function has been conventionally characterized using ventilation, which includes both static and dynamic lung compliance (DLC) factors. DLC is a key lung physiological parameter as it actively drives breathing. Regions that demonstrate a lowered DLC physiologically represent reduced regional lung function. Computing regional DLC is important for function preserving lung radiotherapy treatment planning.
Methods: We present a novel approach for quantitatively measuring the regional DLC using 5DCT imaging and biomechanical lung model development. The 5DCTs were acquired for a set of 10 lung cancer patients. From each of the 5DCTs, we then generated the 5% and 85% lung volume CT images that represented the end-inhalation and end-exhalation CT images. Each voxel in the 5% lung volume were directly mapped using the motion model to the 85% lung volume. A finite element biomechanical lung model was then developed with the source lung geometry using the 5% lung volume CT. The voxel-specific elasticity was extracted from the deformation vector map (DVF) using a gradient descent optimization algorithm. The finite element model now represented the lung deformation associated with the static lung compliance. The subsequent model-based deformation was removed from the ground truth DVF to compute the regional DLC.
Results: DLC was observed to be heterogeneous and vary from one patient to another. The measured values correlated well with the underlying lung tissue. The DLC was observed to be reduced in patients with airway related diseases. For one lobectomy patient with no airway complications, the DLC was observed to be greater than the non-lobectomy cohort of patients.
Conclusion: The measured regional DLC values correlate well with the underlying patient physiology, showing promise as a key metric for function-preserving lung radiotherapy.
Funding Support, Disclosures, and Conflict of Interest: This work was funded by the National Institute of Health, R56 HL139767 award.
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