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Title: WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT

Abstract

Purpose: Variation in function of different lung regions has been ignored so far for conventional lung cancer treatment planning, which may lead to higher risk of radiation induced lung disease. 4DCT based lung ventilation imaging provides a novel yet convenient approach for lung functional imaging as 4DCT is taken as routine for lung cancer treatment. Our work aims to evaluate the impact of accounting for spatial heterogeneity in lung function using 4DCT based lung ventilation imaging for proton and IMRT plans. Methods: Six patients with advanced stage lung cancer of various tumor locations were retrospectively evaluated for the study. Proton and IMRT plans were designed following identical planning objective and constrains for each patient. Ventilation images were calculated from patients’ 4DCT using deformable image registration implemented by Velocity AI software based on Jacobian-metrics. Lung was delineated into two function level regions based on ventilation (low and high functional area). High functional region was defined as lung ventilation greater than 30%. Dose distribution and statistics in different lung function area was calculated for patients. Results: Variation in dosimetric statistics of different function lung region was observed between proton and IMRT plans. In all proton plans, high function lung regions receive lowermore » maximum dose (100.2%–108.9%), compared with IMRT plans (106.4%–119.7%). Interestingly, three out of six proton plans gave higher mean dose by up to 2.2% than IMRT to high function lung region. Lower mean dose (lower by up to 14.1%) and maximum dose (lower by up to 9%) were observed in low function lung for proton plans. Conclusion: A systematic approach was developed to generate function lung ventilation imaging and use it to evaluate plans. This method hold great promise in function analysis of lung during planning. We are currently studying more subjects to evaluate this tool.« less

Authors:
; ; ; ;  [1]
  1. Rutgers University, New Brunswick, NJ (United States)
Publication Date:
OSTI Identifier:
22654106
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; BIOMEDICAL RADIOGRAPHY; COMPUTER CODES; IMAGES; LUNGS; NEOPLASMS; PATIENTS; PLANNING; PROTON BEAMS; RADIATION DOSE DISTRIBUTIONS; RADIOTHERAPY; STATISTICS

Citation Formats

Huang, Q, Zhang, M, Chen, T, Yue, N, and Zou, J. WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT. United States: N. p., 2016. Web. doi:10.1118/1.4957745.
Huang, Q, Zhang, M, Chen, T, Yue, N, & Zou, J. WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT. United States. doi:10.1118/1.4957745.
Huang, Q, Zhang, M, Chen, T, Yue, N, and Zou, J. Wed . "WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT". United States. doi:10.1118/1.4957745.
@article{osti_22654106,
title = {WE-AB-202-04: Statistical Evaluation of Lung Function Using 4DCT Ventilation Imaging: Proton Therapy VS IMRT},
author = {Huang, Q and Zhang, M and Chen, T and Yue, N and Zou, J},
abstractNote = {Purpose: Variation in function of different lung regions has been ignored so far for conventional lung cancer treatment planning, which may lead to higher risk of radiation induced lung disease. 4DCT based lung ventilation imaging provides a novel yet convenient approach for lung functional imaging as 4DCT is taken as routine for lung cancer treatment. Our work aims to evaluate the impact of accounting for spatial heterogeneity in lung function using 4DCT based lung ventilation imaging for proton and IMRT plans. Methods: Six patients with advanced stage lung cancer of various tumor locations were retrospectively evaluated for the study. Proton and IMRT plans were designed following identical planning objective and constrains for each patient. Ventilation images were calculated from patients’ 4DCT using deformable image registration implemented by Velocity AI software based on Jacobian-metrics. Lung was delineated into two function level regions based on ventilation (low and high functional area). High functional region was defined as lung ventilation greater than 30%. Dose distribution and statistics in different lung function area was calculated for patients. Results: Variation in dosimetric statistics of different function lung region was observed between proton and IMRT plans. In all proton plans, high function lung regions receive lower maximum dose (100.2%–108.9%), compared with IMRT plans (106.4%–119.7%). Interestingly, three out of six proton plans gave higher mean dose by up to 2.2% than IMRT to high function lung region. Lower mean dose (lower by up to 14.1%) and maximum dose (lower by up to 9%) were observed in low function lung for proton plans. Conclusion: A systematic approach was developed to generate function lung ventilation imaging and use it to evaluate plans. This method hold great promise in function analysis of lung during planning. We are currently studying more subjects to evaluate this tool.},
doi = {10.1118/1.4957745},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: Four-dimensional computed tomography (4DCT) and image registration can be used to determine regional lung ventilation changes after radiation therapy (RT). This study aimed to determine if lung ventilation change following radiation therapy was affected by the pre-RT ventilation of the lung. Methods: 13 subjects had three 4DCT scans: two repeat scans acquired before RT and one three months after RT. Regional ventilation was computed using Jacobian determinant calculations on the registered 4DCT images. The post-RT ventilation map was divided by the pre-RT ventilation map to get a voxel-by-voxel Jacobian ratio map depicting ventilation change over the course of RT.more » Jacobian ratio change was compared over the range of delivered doses. The first pre-RT ventilation image was divided by the second to establish a control for Jacobian ratio change without radiation delivered. The functional change between scans was assessed using histograms of the Jacobian ratios. Results: There were significantly (p < 0.05) more voxels that had a large decrease in Jacobian ratio in the post-RT divided by pre-RT map (15.6%) than the control (13.2%). There were also significantly (p < .01) more voxels that had a large increase in Jacobian ratio (16.2%) when compared to control (13.3%). Lung regions with low function (<10% expansion by Jacobian) showed a slight linear reduction in expansion (0.2%/10 Gy delivered), while high function regions (>10% expansion) showed a greater response (1.2% reduction/10 Gy). Contiguous high function regions > 1 liter occurred in 11 of 13 subjects. Conclusion: There is a significant change in regional ventilation following a course of radiation therapy. The change in Jacobian following RT is dependent both on the delivered dose and the initial ventilation of the lung tissue: high functioning lung has greater ventilation loss for equivalent radiation doses. Substantial regions of high function lung tissue are prevalent. Research support from NIH grants CA166119 and CA166703, a gift from Roger Koch, and a Pilot Grant from University of Iowa Carver College of Medicine.« less
  • Purpose: The current standard-of-care imaging used to evaluate lung cancer patients for surgical resection is nuclear-medicine ventilation. Surgeons use nuclear-medicine images along with pulmonary function tests (PFT) to calculate percent predicted postoperative (%PPO) PFT values by estimating the amount of functioning lung that would be lost with surgery. 4DCT-ventilation is an emerging imaging modality developed in radiation oncology that uses 4DCT data to calculate lung ventilation maps. We perform the first retrospective study to assess the use of 4DCT-ventilation for pre-operative surgical evaluation. The purpose of this work was to compare %PPO-PFT values calculated with 4DCT-ventilation and nuclear-medicine imaging. Methods:more » 16 lung cancer patients retrospectively reviewed had undergone 4DCTs, nuclear-medicine imaging, and had Forced Expiratory Volume in 1 second (FEV1) acquired as part of a standard PFT. For each patient, 4DCT data sets, spatial registration, and a density-change based model were used to compute 4DCT-ventilation maps. Both 4DCT and nuclear-medicine images were used to calculate %PPO-FEV1 using %PPO-FEV1=pre-operative FEV1*(1-fraction of total ventilation of resected lung). Fraction of ventilation resected was calculated assuming lobectomy and pneumonectomy. The %PPO-FEV1 values were compared between the 4DCT-ventilation-based calculations and the nuclear-medicine-based calculations using correlation coefficients and average differences. Results: The correlation between %PPO-FEV1 values calculated with 4DCT-ventilation and nuclear-medicine were 0.81 (p<0.01) and 0.99 (p<0.01) for pneumonectomy and lobectomy respectively. The average difference between the 4DCT-ventilation based and the nuclear-medicine-based %PPO-FEV1 values were small, 4.1±8.5% and 2.9±3.0% for pneumonectomy and lobectomy respectively. Conclusion: The high correlation results provide a strong rationale for a clinical trial translating 4DCT-ventilation to the surgical domain. Compared to nuclear-medicine, 4DCT-ventilation is cheaper, does not require a radioactive contrast agent, provides a faster imaging procedure, and has improved spatial resolution. 4DCT-ventilation can reduce the cost and imaging time for patients while providing improved spatial accuracy and quantitative results for surgeons. YV discloses grant from State of Colorado.« less
  • Purpose: To date, lung CT-ventilation imaging has been based on quantification of local breathing-induced changes in Hounsfield Units (HU) or volume. This work investigates the use of a stress map resulting from a biomechanical deformable image registration (DIR) algorithm as a metric of the ventilation function. Method: Eight lung cancer patients presenting different kinds of ventilation defects were retrospectively analyzed. Additionally, to the 4DCT acquired for radiotherapy planning, five of them had PET and three had SPECT imaging following inhalation of Ga-68 and Tc-99m, respectively. For each patient, the inhale phase of the 4DCT was registered to the exhale phasemore » using Morfeus, a biomechanical DIR algorithm based on the determination of boundary conditions on the lung surfaces and vessel tree. To take into account the heterogeneity of the tissue stiffness in the stress map estimation, each tetrahedral element of the finite-element model was assigned a Young’s modulus ranging from 60kPa to 12MPa, as a function of the HU in the inhale CT. The node displacements and element stresses resulting from the numerical simulation were used to generate three CT-ventilation maps based on: (i) volume changes (Jacobian determinant), (ii) changes in HU, (iii) the maximum principal stress. The voxel-wise correlation between each CT-ventilation map and the PET or SPECT V image was computed in a lung mask. Results: For patients with PET, the mean (min-max) Spearman correlation coefficients r were: 0.33 (0.19–0.45), 0.36 (0.16–0.51) and 0.42 (0.21–0.59) considering the Jacobian, changes in HU and maximum principal stress, respectively. For patients with SPECT V, the mean r were: 0.12 (−0.12–0.43), 0.29 (0.22–0.45) and 0.33 (0.25–0.39). Conclusion: The maximum principal stress maps showed a stronger correlation with the ventilation images than the previously proposed Jacobian or change in HU maps. This metric thus appears promising for CT-ventilation imaging. This work was funded in part by NIH P01CA059827.« less
  • Purpose: To demonstrate the efficacy of a novel functional lung imaging method that utilizes single-inhalation, single-energy xenon CT (Xe-CT) lung ventilation scans, and to compare it against the current clinical standard, ventilation single-photon emission CT (V-SPECT). Methods: In an IRB-approved clinical study, 14 patients undergoing thoracic radiotherapy received two successive single inhalation, single energy (80keV) CT images of the entire lung using 100% oxygen and a 70%/30% xenon-oxygen mixture. A subset of ten patients also received concurrent SPECT ventilation scans. Anatomic reproducibility between the two scans was achieved using a custom video biofeedback apparatus. The CT images were registered tomore » each other by deformable registration, and a calculated difference image served as surrogate xenon ventilation map. Both lungs were partitioned into twelve sectors, and a sector-wise correlation was performed between the xenon and V-SPECT scans. A linear regression model was developed with forced expiratory volume (FEV) as a predictor and the coefficient of variation (CoV) as the outcome. Results: The ventilation comparison for five of the patients had either moderate to strong Pearson correlation coefficients (0.47 to 0.69, p<0.05). Of these, four also had moderate to strong Spearman correlation coefficients (0.46 to 0.80, p<0.03). The patients with the strongest correlation had clear regional ventilation deficits. The patient comparisons with the weakest correlations had more homogeneous ventilation distributions, and those patients also had diminished lung function as assessed by spirometry. Analysis of the relationship between CoV and FEV yielded a non-significant trend toward negative correlation (Pearson coefficient −0.60, p<0.15). Conclusion: Significant correlations were found between the Xe-CT and V-SPECT ventilation imagery. The results from this small cohort of patients indicate that single inhalation, single energy Xe-CT has the potential to quantify regional lung ventilation volumetrically with high resolution using widely accessible radiologic equipment. Bill Loo and Peter Maxim are founders of TibaRay, Inc. Bill Loo is also a board member. Bill Loo and Peter Maxim have received research grants from Varian Medical Systems, Inc. and RaySearch Laboratory.« less
  • Purpose: To investigate the incorporation of pre-therapy regional ventilation function in predicting radiation fibrosis (RF) in stage III non-small-cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy. Methods: 37 stage III NSCLC patients were retrospectively studied. Patients received one cycle of cisplatin-gemcitabine, followed by two to three cycles of cisplatin-etoposide concurrently with involved-field thoracic radiotherapy between 46 and 66 Gy (2 Gy per fraction). Pre-therapy regional ventilation images of the lung were derived from 4DCT via a density-change-based image registration algorithm with mass correction. RF was evaluated at 6-months post-treatment using radiographic scoring based on airway dilation and volumemore » loss. Three types of ipsilateral lung metrics were studied: (1) conventional dose-volume metrics (V20, V30, V40, and mean-lung-dose (MLD)), (2) dose-function metrics (fV20, fV30, fV40, and functional mean-lung-dose (fMLD) generated by combining regional ventilation and dose), and (3) dose-subvolume metrics (sV20, sV30, sV40, and subvolume mean-lung-dose (sMLD) defined as the dose-volume metrics computed on the sub-volume of the lung with at least 60% of the quantified maximum ventilation status). Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were used to evaluate the predictability of these metrics for RF. Results: In predicting airway dilation, the area under the ROC curve (AUC) values for (V20, MLD), (fV20, fMLD), and (sV20, and sMLD) were (0.76, 0.70), (0.80, 0.74) and (0.82, 0.80), respectively. The logistic regression p-values were (0.09, 0.18), (0.02, 0.05) and (0.004, 0.006), respectively. With regard to volume loss, the corresponding AUC values for these metrics were (0.66, 0.57), (0.67, 0.61) and (0.71, 0.69), and p-values were (0.95, 0.90), (0.43, 0.64) and (0.08, 0.12), respectively. Conclusion: The inclusion of regional ventilation function improved predictability of radiation fibrosis. Dose-subvolume metrics provided a promising method for incorporating functional information into the conventional dose-volume parameters for outcome assessment.« less