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Title: SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration

Abstract

Purpose: Organ changes shape and size during radiation treatment due to both mechanical stress and radiation dose response. However, the dose response induced deformation has not been considered in conventional deformable image registration (DIR). A novel DIR approach is proposed to include both tissue elasticity and radiation dose induced organ deformation. Methods: Assuming that organ sub-volume shrinkage was proportional to the radiation dose induced cell killing/absorption, the dose induced organ volume change was simulated applying virtual temperature on each sub-volume. Hence, both stress and heterogeneity temperature induced organ deformation. Thermal stress finite element method with organ surface boundary condition was used to solve deformation. Initial boundary correspondence on organ surface was created from conventional DIR. Boundary condition was updated by an iterative optimization scheme to minimize elastic deformation energy. The registration was validated on a numerical phantom. Treatment dose was constructed applying both the conventional DIR and the proposed method using daily CBCT image obtained from HN treatment. Results: Phantom study showed 2.7% maximal discrepancy with respect to the actual displacement. Compared with conventional DIR, subvolume displacement difference in a right parotid had the mean±SD (Min, Max) to be 1.1±0.9(−0.4∼4.8), −0.1±0.9(−2.9∼2.4) and −0.1±0.9(−3.4∼1.9)mm in RL/PA/SI directions respectively. Mean parotid dosemore » and V30 constructed including the dose response induced shrinkage were 6.3% and 12.0% higher than those from the conventional DIR. Conclusion: Heterogeneous dose distribution in normal organ causes non-uniform sub-volume shrinkage. Sub-volume in high dose region has a larger shrinkage than the one in low dose region, therefore causing more sub-volumes to move into the high dose area during the treatment course. This leads to an unfavorable dose-volume relationship for the normal organ. Without including this effect in DIR, treatment dose in normal organ could be underestimated affecting treatment evaluation and planning modification. Acknowledgement: Partially Supported by Elekta Research Grant.« less

Authors:
; ; ; ;  [1]
  1. Beaumont Health Systeml, Royal Oak, MI (United States)
Publication Date:
OSTI Identifier:
22632211
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; ABSORPTION; CELL KILLING; COMPUTERIZED TOMOGRAPHY; DEFORMATION; ELASTICITY; FINANCING; FINITE ELEMENT METHOD; IMAGES; ITERATIVE METHODS; OPTIMIZATION; ORGANS; PHANTOMS; PLANNING; RADIATION DOSE DISTRIBUTIONS; RADIATION DOSES; SHRINKAGE; THERMAL STRESSES

Citation Formats

Zhu, J, Liang, J, Chen, S, Qin, A, and Yan, D. SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration. United States: N. p., 2016. Web. doi:10.1118/1.4955994.
Zhu, J, Liang, J, Chen, S, Qin, A, & Yan, D. SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration. United States. doi:10.1118/1.4955994.
Zhu, J, Liang, J, Chen, S, Qin, A, and Yan, D. 2016. "SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration". United States. doi:10.1118/1.4955994.
@article{osti_22632211,
title = {SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration},
author = {Zhu, J and Liang, J and Chen, S and Qin, A and Yan, D},
abstractNote = {Purpose: Organ changes shape and size during radiation treatment due to both mechanical stress and radiation dose response. However, the dose response induced deformation has not been considered in conventional deformable image registration (DIR). A novel DIR approach is proposed to include both tissue elasticity and radiation dose induced organ deformation. Methods: Assuming that organ sub-volume shrinkage was proportional to the radiation dose induced cell killing/absorption, the dose induced organ volume change was simulated applying virtual temperature on each sub-volume. Hence, both stress and heterogeneity temperature induced organ deformation. Thermal stress finite element method with organ surface boundary condition was used to solve deformation. Initial boundary correspondence on organ surface was created from conventional DIR. Boundary condition was updated by an iterative optimization scheme to minimize elastic deformation energy. The registration was validated on a numerical phantom. Treatment dose was constructed applying both the conventional DIR and the proposed method using daily CBCT image obtained from HN treatment. Results: Phantom study showed 2.7% maximal discrepancy with respect to the actual displacement. Compared with conventional DIR, subvolume displacement difference in a right parotid had the mean±SD (Min, Max) to be 1.1±0.9(−0.4∼4.8), −0.1±0.9(−2.9∼2.4) and −0.1±0.9(−3.4∼1.9)mm in RL/PA/SI directions respectively. Mean parotid dose and V30 constructed including the dose response induced shrinkage were 6.3% and 12.0% higher than those from the conventional DIR. Conclusion: Heterogeneous dose distribution in normal organ causes non-uniform sub-volume shrinkage. Sub-volume in high dose region has a larger shrinkage than the one in low dose region, therefore causing more sub-volumes to move into the high dose area during the treatment course. This leads to an unfavorable dose-volume relationship for the normal organ. Without including this effect in DIR, treatment dose in normal organ could be underestimated affecting treatment evaluation and planning modification. Acknowledgement: Partially Supported by Elekta Research Grant.},
doi = {10.1118/1.4955994},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of themore » errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties.« less
  • Purpose: To investigate a deformable image registration method to improve soft-tissue contrast in four-dimensional (4D) computed tomography (CT) images of the liver. Methods and Materials: Ten patients with hepatocellular carcinoma underwent 4D CT scan for radiotherapy treatment planning on a positron emission tomography/CT scanner. Four-dimensional CT images were binned into 10 equispaced phases. The exhale phase served as the reference phase, and images from the other nine phases were coregistered to the reference phase image using an intensity-based, automatic deformable image registration method. Then the coregistered images were combined to create a single, high-quality reconstructed CT image at exhale phasemore » as the new reference for target delineation. The extent of image quality enhancement was quantified relative to the original CT by calculating the signal-to-noise ratio and the contrast-to-noise ratio. Results: The soft tissue image contrast was noticeably better after deformable image registration than in the original scans. Signal-to-noise ratios inside the liver region of interest increased for all patients by a factor of 3.0 (range, 2.3-3.7). The improvement in image quality was not linearly proportionate to the number of images averaged. Using only 6 phases can achieve at least 85% of the contrast enhancement that can be achieved using all 10 phases. We also found that contrast enhancement was inversely proportional to the original image quality (p = 0.006), and the contrast enhancement is attained with little loss of spatial resolution. Conclusions: This deformable image registration method is feasible to improve soft-tissue image quality in 4D CT images.« less
  • No abstract prepared.
  • Purpose: Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different accumulated doses. The purpose of this study was to investigate the dosimetric effect of and propose a postprocessing solution to reduce inverse consistency and transitivity errors. Methods: Four MVCT images and four phases of a lung 4DCT, each with an associated calculated dose, were selected for analysis. DVFsmore » between all four images in each data set were created using the Fast Symmetric Demons algorithm. Dose was accumulated on the fourth image in each set using DIR via two different image pathways. The two accumulated doses on the fourth image were compared. The inverse consistency and transitivity errors in the DVFs were then reduced. The dose accumulation was repeated using the processed DVFs, the results of which were compared with the accumulated dose from the original DVFs. To evaluate the influence of the postprocessing technique on DVF accuracy, the original and processed DVF accuracy was evaluated on the lung 4DCT data on which anatomical landmarks had been identified by an expert. Results: Dose accumulation to the same image via different image pathways resulted in two different accumulated dose results. After the inverse consistency errors were reduced, the difference between the accumulated doses diminished. The difference was further reduced after reducing the transitivity errors. The postprocessing technique had minimal effect on the accuracy of the DVF for the lung 4DCT images. Conclusions: This study shows that inverse consistency and transitivity errors in DIR have a significant dosimetric effect in dose accumulation; Depending on the image pathway taken to accumulate the dose, different results may be obtained. A postprocessing technique that reduces inverse consistency and transitivity error is presented, which allows for consistent dose accumulation regardless of the image pathway followed.« less
  • Purpose: To propose and validate a novel and accurate deformable image registration (DIR) scheme to facilitate dose accumulation among treatment fractions of high-dose-rate (HDR) gynecological brachytherapy. Method: We have developed a method to adapt DIR algorithms to gynecologic anatomies with HDR applicators by incorporating a segmentation step and a point-matching step into an existing DIR framework. In the segmentation step, random walks algorithm is used to accurately segment and remove the applicator region (AR) in the HDR CT image. A semi-automatic seed point generation approach is developed to obtain the incremented foreground and background point sets to feed the randommore » walks algorithm. In the subsequent point-matching step, a feature-based thin-plate spline-robust point matching (TPS-RPM) algorithm is employed for AR surface point matching. With the resulting mapping, a DVF characteristic of the deformation between the two AR surfaces is generated by B-spline approximation, which serves as the initial DVF for the following Demons DIR between the two AR-free HDR CT images. Finally, the calculated DVF via Demons combined with the initial one serve as the final DVF to map doses between HDR fractions. Results: The segmentation and registration accuracy are quantitatively assessed by nine clinical HDR cases from three gynecological cancer patients. The quantitative results as well as the visual inspection of the DIR indicate that our proposed method can suppress the interference of the applicator with the DIR algorithm, and accurately register HDR CT images as well as deform and add interfractional HDR doses. Conclusions: We have developed a novel and robust DIR scheme that can perform registration between HDR gynecological CT images and yield accurate registration results. This new DIR scheme has potential for accurate interfractional HDR dose accumulation. This work is supported in part by the National Natural ScienceFoundation of China (no 30970866 and no 81301940)« less