Abstract
Ventilation imaging using 4D CT is a convenient and low‐cost functional imaging methodology which might be of value in radiotherapy treatment planning to spare functional lung volumes. Deformable image registration (DIR) is needed to calculate ventilation imaging from 4D CT. This study investigates the dependence of calculated ventilation on DIR methods and ventilation algorithms. DIR of the normal end expiration and normal end inspiration phases of the 4D CT images was used to correlate the voxels between the two respiratory phases. Three different DIR algorithms, optical flow (OF), diffeomorphic demons (DD), and diffeomorphic morphons (DM) were retrospectively applied to ten esophagus and ten lung cancer cases with 4D CT image sets that encompassed the entire lung volume. The three ventilation extraction methods were used based on either the Jacobian, the change in volume of the voxel, or directly calculated from Hounsfield units. The ventilation calculation algorithms used are the Jacobian, ΔV, and HU method. They were compared using the Dice similarity coefficient (DSC) index and Bland‐Altman plots. Dependence of ventilation images on the DIR was greater for the ΔV and the Jacobian methods than for the HU method. The DSC index for 20% of low‐ventilation volume for ΔV was 0.33±0.03(1SD) between OF and DM, 0.44±0.05 between OF and DD, and 0.51±0.04 between DM and DD. The similarity comparisons for Jacobian were 0.32±0.03,0.44±0.05, and 0.51±0.04, respectively, and for HU they were 0.53±0.03,0.56±0.03, and 0.76±0.04, respectively. Dependence of extracted ventilation on the ventilation algorithm used showed good agreement between the ΔV and Jacobian methods, but differed significantly for the HU method. DSC index for using OF as DIR was 0.86±0.01 between ΔV and Jacobian, 0.28±0.04 between ΔV and HU, and 0.28±0.04 between Jacobian and HU, respectively. When using DM or DD as DIR, similar values were obtained when comparing the different ventilation calculation methods. The similarity values for the 20% high‐ventilation volume were close to those found for the 20% low‐ventilation volume. The results obtained with DSC index were confirmed when using the Bland‐Altman plots for comparing the ventilation images. Our data suggest that ventilation calculated from 4D CT depends on the DIR algorithm employed. Similarities between ΔV and Jacobian are higher than between ΔV and HU, and Jacobian and HU.PACS number: 87.57.nj
Highlights
Radiation pneumonitis has traditionally been cited as the main dose limiting factor in radiation therapy for non-small cell lung cancer (NSCLC).(1) Previous studies evaluating the risks of pulmonary toxicity have typically reported that the two best predictors were the volume of lung receiving at least 20 Gy[2,3] and, alternatively, the mean radiation dose to normal lung.[4,5,6,7,8,9,10,11] To help predict radiation toxicity, many researchers have tried to model the effects of radiation by examining how much normal tissue receives a given dose.[5]. There has been much work presented on normal tissue complication probability (NTCP) models.[7,8,9,12,13]
Dice similarity coefficient (DSC) index analysis suggests that ventilation calculated from 4D CT depends on the Deformable image registration (DIR) algorithm employed
We believe that artifacts in 4D CT images are the reason why Hounsfield unit (HU) shows a smaller dependence on the choice of DIR
Summary
Radiation pneumonitis has traditionally been cited as the main dose limiting factor in radiation therapy for non-small cell lung cancer (NSCLC).(1) Previous studies evaluating the risks of pulmonary toxicity have typically reported that the two best predictors were the volume of lung receiving at least 20 Gy[2,3] and, alternatively, the mean radiation dose to normal lung.[4,5,6,7,8,9,10,11] To help predict radiation toxicity, many researchers have tried to model the effects of radiation by examining how much normal tissue receives a given dose.[5]. Most of the current models for radiation toxicity of the lung are based on a uniformly functioning lung.[5,7,8,9,12,13] most people have redundant pulmonary reserve, it is well known that lung function is not uniform, and there is a wide range of ventilation and perfusion levels throughout the lung.[14,15,16] In particular, lung cancer patients have been shown to have regions of lung with poor ventilation. The aerosol technique is better at identifying regions with low gamma ray emissions and low regional ventilation.[16,19,20,21,22] Other limitations of SPECT compared to 4D CT include its lower spatial resolution, as well as the longer time needed for image acquisition.[16,23]
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