Room: Karl Dean Ballroom B1
Purpose: 4DCT lung elastography is an effective characterization of the functional lung regions and lung disease heterogeneity. However, 4DCT is a high dose procedure which may limit adoption. We performed an analysis examining the accuracy of elastography at lower doses that may enable its use outside of treatment planning.
Methods: A cohort of 10 patient 5DCT scans were acquired for estimating ground-truth lung elasticity. Synthetic low dose CT scans were generated from the 5DCT scans to simulate 25%, 50%, and 75% dose reductions. For the synthetic scans, end-exhalation and end-inhalation datasets were registered using an in-house optical flow deformable image registration algorithm. The registered deformation vector fields (DVFs) at full dose were taken to be ground-truth for the elastography process. A model-based elasticity estimation was performed for each synthetic low dose dataset, with a goal to optimize the elasticity distribution to best represent the deformation vector fields. The estimated elasticity and the DVFs of the dose-reduced scans were then compared to the results of the original 5DCT scans for quantitative accuracy purposes.
Results: The DVFs for the low dose and original 5DCT scans differed from each other on average by 1.42 mm, which can be attributed to the simulated dose reduction. However, the elastography results using the DVFs from the 25% and 50% reduced dose scans were not significantly different from the results obtained using the 5DCT, with average elasticity differences of 0.64 kPa and 0.73 kPa, respectively. In addition, the DVFs generated from the elasticity for given boundary conditions were similar, with an average difference of 0.52 mm thereby demonstrating the low-dose 4DCT elastography to be feasible.
Conclusion: 4DCT lung elastography can be performed using low-dose CT scans thereby expanding its usage beyond the treatment planning stage within the radiotherapy context and applications in diagnostic, mid-, and post-treatment stages.
Funding Support, Disclosures, and Conflict of Interest: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1144087, the Ken and Wendy Ruby Foundation, the US Department of Defense Virtual Tissue Consortium, and the UCLA Department of Radiation Oncology.
Not Applicable / None Entered.