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Title: SU-F-J-58: Evaluation of RayStation Hybrid Deformable Image Registration for Accurate Contour Propagation in Adaptive Planning

Abstract

Purpose: Adaptive radiotherapy requires complete new sets of regions of interests (ROIs) delineation on the mid-treatment CT images. This work aims at evaluating the accuracy of the RayStation hybrid deformable image registration (DIR) algorithm for its overall integrity and accuracy in contour propagation for adaptive planning. Methods: The hybrid DIR is based on the combination of intensity-based algorithm and anatomical information provided by contours. Patients who received mid-treatment CT scans were identified for the study, including six lung patients (two mid-treatment CTs) and six head-and-neck (HN) patients (one mid-treatment CT). DIRpropagated ROIs were compared with physician-drawn ROIs for 8 ITVs and 7 critical organs (lungs, heart, esophagus, and etc.) for the lung patients, as well as 14 GTVs and 20 critical organs (mandible, eyes, parotids, and etc.) for the HN patients. Volume difference, center of mass (COM) difference, and Dice index were used for evaluation. Clinical-relevance of each propagated ROI was scored by two physicians, and correlated with the Dice index. Results: For critical organs, good agreement (Dice>0.9) were seen on all 7 for lung patients and 13 out of 20 for HN patients, with the rest requiring minimal edits. For targets, COM differences were within 5 mm on averagemore » for all patients. For Lung, 5 out of 8 ITVs required minimal edits (Dice 0.8–0.9), with the rest 2 needed re-drawn due to their small volumes (<10 cc). However, the propagated HN GTVs resulted in relatively low Dice values (0.5–0.8) due to their small volumes (3–40 cc) and high variability, among which 2 required re-drawn due to new nodal target identified on the mid-treatment CT scans. Conclusion: The hybrid DIR algorithm was found to be clinically useful and efficient for lung and HN patients, especially for propagated critical organ ROIs. It has potential to significantly improve the workflow in adaptive planning.« less

Authors:
; ; ; ; ;  [1]
  1. University of California Davis Medical Center, Sacramento, CA (United States)
Publication Date:
OSTI Identifier:
22632190
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; ACCURACY; ALGORITHMS; COMPARATIVE EVALUATIONS; COMPUTERIZED TOMOGRAPHY; CRITICAL ORGANS; ESOPHAGUS; EYES; HEART; IMAGE PROCESSING; IMAGES; JAW; LUNGS; NECK; PATIENTS; PLANNING; RADIOTHERAPY

Citation Formats

Rong, Y, Rao, S, Daly, M, Wright, C, Benedict, S, and Yamamoto, T. SU-F-J-58: Evaluation of RayStation Hybrid Deformable Image Registration for Accurate Contour Propagation in Adaptive Planning. United States: N. p., 2016. Web. doi:10.1118/1.4955966.
Rong, Y, Rao, S, Daly, M, Wright, C, Benedict, S, & Yamamoto, T. SU-F-J-58: Evaluation of RayStation Hybrid Deformable Image Registration for Accurate Contour Propagation in Adaptive Planning. United States. doi:10.1118/1.4955966.
Rong, Y, Rao, S, Daly, M, Wright, C, Benedict, S, and Yamamoto, T. 2016. "SU-F-J-58: Evaluation of RayStation Hybrid Deformable Image Registration for Accurate Contour Propagation in Adaptive Planning". United States. doi:10.1118/1.4955966.
@article{osti_22632190,
title = {SU-F-J-58: Evaluation of RayStation Hybrid Deformable Image Registration for Accurate Contour Propagation in Adaptive Planning},
author = {Rong, Y and Rao, S and Daly, M and Wright, C and Benedict, S and Yamamoto, T},
abstractNote = {Purpose: Adaptive radiotherapy requires complete new sets of regions of interests (ROIs) delineation on the mid-treatment CT images. This work aims at evaluating the accuracy of the RayStation hybrid deformable image registration (DIR) algorithm for its overall integrity and accuracy in contour propagation for adaptive planning. Methods: The hybrid DIR is based on the combination of intensity-based algorithm and anatomical information provided by contours. Patients who received mid-treatment CT scans were identified for the study, including six lung patients (two mid-treatment CTs) and six head-and-neck (HN) patients (one mid-treatment CT). DIRpropagated ROIs were compared with physician-drawn ROIs for 8 ITVs and 7 critical organs (lungs, heart, esophagus, and etc.) for the lung patients, as well as 14 GTVs and 20 critical organs (mandible, eyes, parotids, and etc.) for the HN patients. Volume difference, center of mass (COM) difference, and Dice index were used for evaluation. Clinical-relevance of each propagated ROI was scored by two physicians, and correlated with the Dice index. Results: For critical organs, good agreement (Dice>0.9) were seen on all 7 for lung patients and 13 out of 20 for HN patients, with the rest requiring minimal edits. For targets, COM differences were within 5 mm on average for all patients. For Lung, 5 out of 8 ITVs required minimal edits (Dice 0.8–0.9), with the rest 2 needed re-drawn due to their small volumes (<10 cc). However, the propagated HN GTVs resulted in relatively low Dice values (0.5–0.8) due to their small volumes (3–40 cc) and high variability, among which 2 required re-drawn due to new nodal target identified on the mid-treatment CT scans. Conclusion: The hybrid DIR algorithm was found to be clinically useful and efficient for lung and HN patients, especially for propagated critical organ ROIs. It has potential to significantly improve the workflow in adaptive planning.},
doi = {10.1118/1.4955966},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To evaluate the clinical potential of deformable image registration (DIR)-based automatic propagation of physician-drawn contours from a planning CT to midtreatment CT images for head and neck (H and N) adaptive radiotherapy. Methods: Ten H and N patients, each with a planning CT (CT1) and a subsequent CT (CT2) taken approximately 3–4 week into treatment, were considered retrospectively. Clinically relevant organs and targets were manually delineated by a radiation oncologist on both sets of images. Four commercial DIR algorithms, two B-spline-based and two Demons-based, were used to deform CT1 and the relevant contour sets onto corresponding CT2 images. Agreementmore » of the propagated contours with manually drawn contours on CT2 was visually rated by four radiation oncologists in a scale from 1 to 5, the volume overlap was quantified using Dice coefficients, and a distance analysis was done using center of mass (CoM) displacements and Hausdorff distances (HDs). Performance of these four commercial algorithms was validated using a parameter-optimized Elastix DIR algorithm. Results: All algorithms attained Dice coefficients of >0.85 for organs with clear boundaries and those with volumes >9 cm{sup 3}. Organs with volumes <3 cm{sup 3} and/or those with poorly defined boundaries showed Dice coefficients of ∼0.5–0.6. For the propagation of small organs (<3 cm{sup 3}), the B-spline-based algorithms showed higher mean Dice values (Dice = 0.60) than the Demons-based algorithms (Dice = 0.54). For the gross and planning target volumes, the respective mean Dice coefficients were 0.8 and 0.9. There was no statistically significant difference in the Dice coefficients, CoM, or HD among investigated DIR algorithms. The mean radiation oncologist visual scores of the four algorithms ranged from 3.2 to 3.8, which indicated that the quality of transferred contours was “clinically acceptable with minor modification or major modification in a small number of contours.” Conclusions: Use of DIR-based contour propagation in the routine clinical setting is expected to increase the efficiency of H and N replanning, reducing the amount of time needed for manual target and organ delineations.« less
  • Deformable image registration, contour propagation and dose mapping have become common, possibly essential tools for modern image-guided radiation therapy. Historically, these tools have been largely developed at academic medical centers and used in a rather limited and well controlled fashion. Today these tools are now available to the radiotherapy community at large, both as stand-alone applications and as integrated components of both treatment planning and treatment delivery systems. Unfortunately, the details of how these tools work and their limitations are not generally documented or described by the vendors that provide them. Although “it looks right”, determining that unphysical deformations maymore » have occurred is crucial. Because of this, understanding how and when to use, and not use these tools to support everyday clinical decisions is far from straight forward. The goal of this session will be to present both the theory (basic and advanced) and practical clinical use of deformable image registration, contour propagation and dose mapping. To the extent possible, the “secret sauce” that different vendor use to produce reasonable/acceptable results will be described. A detailed explanation of the possible sources of errors and actual examples of these will be presented. Knowing the underlying principles of the process and understanding the confounding factors will help the practicing medical physicist be better able to make decisions (about making decisions) using these tools available. Learning Objectives: Understand the basic (101) and advanced (201) principles of deformable image registration, contour propagation and dose mapping data mapping. Understand the sources and impact of errors in registration and data mapping and the methods for evaluating the performance of these tools. Understand the clinical use and value of these tools, especially when used as a “black box”.« less
  • Brachytherapy devices and software are designed to last for a certain period of time. Due to a number of considerations, such as material factors, wear-and-tear, backwards compatibility, and others, they all reach a date when they are no longer supported by the manufacturer. Most of these products have a limited duration for their use, and the information is provided to the user at time of purchase. Because of issues or concerns determined by the manufacturer, certain products are retired sooner than the anticipated date, and the user is immediately notified. In these situations, the institution is facing some difficult choices:more » remove these products from the clinic or perform tests and continue their usage. Both of these choices come with a financial burden: replacing the product or assuming a potential medicolegal liability. This session will provide attendees with the knowledge and tools to make better decisions when facing these issues. Learning Objectives: Understand the meaning of “end-of-life or “life expectancy” for brachytherapy devices and software Review items (devices and software) affected by “end-of-life” restrictions Learn how to effectively formulate “end-of-life” policies at your institution Learn about possible implications of “end-of-life” policy Review other possible approaches to “end-of-life” issue.« less
  • Brachytherapy devices and software are designed to last for a certain period of time. Due to a number of considerations, such as material factors, wear-and-tear, backwards compatibility, and others, they all reach a date when they are no longer supported by the manufacturer. Most of these products have a limited duration for their use, and the information is provided to the user at time of purchase. Because of issues or concerns determined by the manufacturer, certain products are retired sooner than the anticipated date, and the user is immediately notified. In these situations, the institution is facing some difficult choices:more » remove these products from the clinic or perform tests and continue their usage. Both of these choices come with a financial burden: replacing the product or assuming a potential medicolegal liability. This session will provide attendees with the knowledge and tools to make better decisions when facing these issues. Learning Objectives: Understand the meaning of “end-of-life or “life expectancy” for brachytherapy devices and software Review items (devices and software) affected by “end-of-life” restrictions Learn how to effectively formulate “end-of-life” policies at your institution Learn about possible implications of “end-of-life” policy Review other possible approaches to “end-of-life” issue.« less
  • Purpose: To compare the contour propagation accuracy of two deformable image registration (DIR) algorithms in the Raystation treatment planning system – the “Hybrid” algorithm based on image intensities and anatomical information; and the “Biomechanical” algorithm based on linear anatomical elasticity and finite element modeling. Methods: Both DIR algorithms were used for CT-to-CT deformation for 20 lung radiation therapy patients that underwent treatment plan revisions. Deformation accuracy was evaluated using landmark tracking to measure the target registration error (TRE) and inverse consistency error (ICE). The deformed contours were also evaluated against physician drawn contours using Dice similarity coefficients (DSC). Contour propagationmore » was qualitatively assessed using a visual quality score assigned by physicians, and a refinement quality score (0 0.9 for lungs, > 0.85 for heart, > 0.8 for liver) and similar qualitative assessments (VQS < 0.35, RQS > 0.75 for lungs). When anatomical structures were used to control the deformation, the DSC improved more significantly for the biomechanical DIR compared to the hybrid DIR, while the VQS and RQS improved only for the controlling structures. However, while the inclusion of controlling structures improved the TRE for the hybrid DIR, it increased the TRE for the biomechanical DIR. Conclusion: The hybrid DIR was found to perform slightly better than the biomechanical DIR based on lower TRE while the DSC, VQS, and RQS studies yielded comparable results for both. The use of controlling structures showed considerable improvement in the hybrid DIR results and is recommended for clinical use in contour propagation.« less