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Correlating Lung CT HU with Transformation-Based and Xe-CT Derived Ventilation


K Du

K Du1*, T Patton1 , J Reinhardt2 , G Christensen2 , J Bayouth1 , (1) University of Wisconsin, Madison, WI, (2) The University of Iowa, Iowa City, IA

Presentations

WE-AB-202-6 (Wednesday, August 3, 2016) 7:30 AM - 9:30 AM Room: 202


Purpose: Regional lung ventilation is useful to reduce radiation-induced function damage during lung cancer radiation therapy. Recently a new direct HU (Hounsfield unit)-based method was proposed to estimate the ventilation potential without image registration. The purpose of this study is to examine if there is a functional dependence between HU values and transformation-based or Xe-CT derived ventilation.

Methods: 4DCT images acquired from 13 patients prior to radiation therapy and 4 mechanically ventilated sheep subjects which also have associated Xe-CT images were used for this analysis. Transformation-based ventilation was computed using Jacobian determinant of the transformation field between peak-exhale and peak-inhale 4DCT images. Both transformation and Xe-CT derived ventilation was computed for each HU bin. Color scatter plot and cumulative histogram were used to compare and validate the direct HU-based method.

Results: There was little change of the center and shape of the HU histograms between free breathing CT and 4DCT average, with or without smoothing, and between the repeated 4DCT scans. HU of -750 and -630 were found to have the greatest transformation-based ventilation for human and sheep subjects, respectively. Maximum Xe-CT derived ventilation was found to locate at HU of -600 in sheep subjects. The curve between Xe-CT ventilation and HU was noisy for tissue above HU -400, possibly due to less intensity change of Xe gas during wash-out and wash-in phases.

Conclusion: Both transformation-based and Xe-CT ventilation demonstrated that lung tissues with HU values in the range of (-750, -600) HU have the maximum ventilation potential. The correlation between HU and ventilation suggests that HU might be used to help guide the ventilation calculation and make it more robust to noise and image registration errors.

Funding Support, Disclosures, and Conflict of Interest: Research support from NIH grants CA166703 and CA166119 and a gift from Roger Koch.


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