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Title: Generation of Composite Dose and Biological Effective Dose (BED) Over Multiple Treatment Modalities and Multistage Planning Using Deformable Image Registration

Abstract

Currently there are no commercially available tools to generate composite plans across different treatment modalities and/or different planning image sets. Without a composite plan, it may be difficult to perform a meaningful dosimetric evaluation of the overall treatment course. In this paper, we introduce a method to generate composite biological effective dose (BED) plans over multiple radiotherapy treatment modalities and/or multistage plans, using deformable image registration. Two cases were used to demonstrate the method. Case I was prostate cancer treated with intensity-modulated radiation therapy (IMRT) and a permanent seed implant. Case II involved lung cancer treated with two treatment plans generated on two separate computed tomography image sets. Thin-plate spline or optical flow methods were used as appropriate to generate deformation matrices. The deformation matrices were then applied to the dose matrices and the resulting physical doses were converted to BED and added to yield the composite plan. Cell proliferation and sublethal repair were considered in the BED calculations. The difference in BED between normal tissues and tumor volumes was accounted for by using different BED models, {alpha}/{beta} values, and cell potential doubling times. The method to generate composite BED plans presented in this paper provides information not available withmore » the traditional simple dose summation or physical dose summation. With the understanding of limitations and uncertainties of the algorithms involved, it may be valuable for the overall treatment plan evaluation.« less

Authors:
 [1]; ; ; ;  [2]
  1. Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL (United States) and Department of Medical Radiological Technology, China Medical University, Taiwan (China), E-mail: geoffrey.zhang@moffitt.org
  2. Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL (United States) and Department of Medical Radiological Technology, China Medical University, Taiwan (China)
Publication Date:
OSTI Identifier:
21333982
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Dosimetry; Journal Volume: 35; Journal Issue: 2; Other Information: DOI: 10.1016/j.meddos.2009.05.001; PII: S0958-3947(09)00048-X; Copyright (c) 2010 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; BIOLOGICAL REPAIR; CELL PROLIFERATION; COMPUTERIZED TOMOGRAPHY; IMAGES; LUNGS; NEOPLASMS; PLANNING; PROSTATE; RADIATION DOSES; RADIOTHERAPY

Citation Formats

Zhang, Geoffrey, Huang, T-C, Feygelman, Vladimir, Stevens, Craig, and Forster, Kenneth. Generation of Composite Dose and Biological Effective Dose (BED) Over Multiple Treatment Modalities and Multistage Planning Using Deformable Image Registration. United States: N. p., 2010. Web. doi:10.1016/j.meddos.2009.05.001.
Zhang, Geoffrey, Huang, T-C, Feygelman, Vladimir, Stevens, Craig, & Forster, Kenneth. Generation of Composite Dose and Biological Effective Dose (BED) Over Multiple Treatment Modalities and Multistage Planning Using Deformable Image Registration. United States. doi:10.1016/j.meddos.2009.05.001.
Zhang, Geoffrey, Huang, T-C, Feygelman, Vladimir, Stevens, Craig, and Forster, Kenneth. 2010. "Generation of Composite Dose and Biological Effective Dose (BED) Over Multiple Treatment Modalities and Multistage Planning Using Deformable Image Registration". United States. doi:10.1016/j.meddos.2009.05.001.
@article{osti_21333982,
title = {Generation of Composite Dose and Biological Effective Dose (BED) Over Multiple Treatment Modalities and Multistage Planning Using Deformable Image Registration},
author = {Zhang, Geoffrey and Huang, T-C and Feygelman, Vladimir and Stevens, Craig and Forster, Kenneth},
abstractNote = {Currently there are no commercially available tools to generate composite plans across different treatment modalities and/or different planning image sets. Without a composite plan, it may be difficult to perform a meaningful dosimetric evaluation of the overall treatment course. In this paper, we introduce a method to generate composite biological effective dose (BED) plans over multiple radiotherapy treatment modalities and/or multistage plans, using deformable image registration. Two cases were used to demonstrate the method. Case I was prostate cancer treated with intensity-modulated radiation therapy (IMRT) and a permanent seed implant. Case II involved lung cancer treated with two treatment plans generated on two separate computed tomography image sets. Thin-plate spline or optical flow methods were used as appropriate to generate deformation matrices. The deformation matrices were then applied to the dose matrices and the resulting physical doses were converted to BED and added to yield the composite plan. Cell proliferation and sublethal repair were considered in the BED calculations. The difference in BED between normal tissues and tumor volumes was accounted for by using different BED models, {alpha}/{beta} values, and cell potential doubling times. The method to generate composite BED plans presented in this paper provides information not available with the traditional simple dose summation or physical dose summation. With the understanding of limitations and uncertainties of the algorithms involved, it may be valuable for the overall treatment plan evaluation.},
doi = {10.1016/j.meddos.2009.05.001},
journal = {Medical Dosimetry},
number = 2,
volume = 35,
place = {United States},
year = 2010,
month = 7
}
  • Purpose: To compare the performance of two deformable image registration (DIR) algorithms for contour propagation and to evaluate the accuracy of DIR for use with high dose rate (HDR) brachytherapy planning for cervical cancer. Methods: Five patients undergoing HDR ring and tandem brachytherapy were included in this retrospective study. All patients underwent CT simulation and replanning prior to each fraction (3–5 fractions total). CT-to-CT DIR was performed using two commercially available software platforms: SmartAdapt, Varian Medical Systems (Demons) and Velocity AI, Velocity Medical Solutions (B-spline). Fraction 1 contours were deformed and propagated to each subsequent image set and compared tomore » contours manually drawn by an expert clinician. Dice similarity coefficients (DSC), defined as, DSC(A,B)=2(AandB)/(A+B) were calculated to quantify spatial overlap between manual (A) and deformed (B) contours. Additionally, clinician-assigned visual scores were used to describe and compare the performance of each DIR method and ultimately evaluate which was more clinically acceptable. Scoring was based on a 1–5 scale—with 1 meaning, “clinically acceptable with no contour changes” and 5 meaning, “clinically unacceptable”. Results: Statistically significant differences were not observed between the two DIR algorithms. The average DSC for the bladder, rectum and rectosigmoid were 0.82±0.08, 0.67±0.13 and 0.48±0.18, respectively. The poorest contour agreement was observed for the rectosigmoid due to limited soft tissue contrast and drastic anatomical changes, i.e., organ shape/filling. Two clinicians gave nearly equivalent average scores of 2.75±0.91 for SmartAdapt and 2.75±0.94 for Velocity AI—indicating that for a majority of the cases, more than one of the three contours evaluated required major modifications. Conclusion: Limitations of both DIR algorithms resulted in inaccuracies in contour propagation in the pelvic region, thus hampering the clinical utility of this technology. Further work is required to optimize these algorithms and take advantage of the potential of DIR for HDR brachytherapy planning.« less
  • Purpose: Radiotherapy plans for patients with cervical cancer treated with EBRT followed by HDR brachytherapy are optimized by constraining dose to organs at risk (OARs). Risk of treatment related toxicities is estimated based on the dose received to the hottest 2cc (D2cc) of the bladder, bowel, rectum, and sigmoid. To account for intrafractional variation in OAR volume and positioning, a dose deformation method is proposed for more accurate evaluation of dose distribution for these patients. Methods: Radiotherapy plans from five patients who received 50.4Gy pelvic EBRT followed by 30Gy in five fractions of HDR brachytherapy, using split-ring and tandem applicators,more » were retrospectively evaluated using MIM Software version 6.0. Dose accumulation workflows were used for initial deformation of EBRT and HDR planning CTs onto a common HDR planning CT. The Reg Refine tool was applied with user-specified local alignments to refine the deformation. Doses from the deformed images were transferred to the common planning CT. Deformed doses were scaled to the EQD2, following the linear-quadratic BED model (considered α/β ratio for tumor as 10, and 3 for rest of the tissues), and then combined to create the dose composite. MIM composite doses were compared to the clinically-reported plan assessments based upon the American Brachytherapy Society (ABS) guidelines for cervical HDR brachytherapy treatment. Results: Bladder D2cc exhibited significant reduction (−11.4%±3.85%, p< 0.02) when evaluated using MIM deformable dose composition. Differences observed for bowel, rectum, and sigmoid D2cc were not significant (−0.58±7.37%, −4.13%±13.7%, and 8.58%±4.71%, respectively and p>0.05 for all) relative to the calculated values used clinically. Conclusion: Application of deformable dose composite techniques may lead to more accurate total dose reporting and can allow for elevated dose to target structures with the assurance of not exceeding dose to OARs. Further study into deformable dose composition and correlation with clinical outcomes is warranted.« less
  • Purpose: To evaluate the implications of differences between contours drawn manually and contours generated automatically by deformable image registration for four-dimensional (4D) treatment planning. Methods and Materials: In 12 lung cancer patients intensity-modulated radiotherapy (IMRT) planning was performed for both manual contours and automatically generated ('auto') contours in mid and peak expiration of 4D computed tomography scans, with the manual contours in peak inspiration serving as the reference for the displacement vector fields. Manual and auto plans were analyzed with respect to their coverage of the manual contours, which were assumed to represent the anatomically correct volumes. Results: Auto contoursmore » were on average larger than manual contours by up to 9%. Objective scores, D{sub 2%} and D{sub 98%} of the planning target volume, homogeneity and conformity indices, and coverage of normal tissue structures (lungs, heart, esophagus, spinal cord) at defined dose levels were not significantly different between plans (p = 0.22-0.94). Differences were statistically insignificant for the generalized equivalent uniform dose of the planning target volume (p = 0.19-0.94) and normal tissue complication probabilities for lung and esophagus (p = 0.13-0.47). Dosimetric differences >2% or >1 Gy were more frequent in patients with auto/manual volume differences {>=}10% (p = 0.04). Conclusions: The applied deformable image registration algorithm produces clinically plausible auto contours in the majority of structures. At this stage clinical supervision of the auto contouring process is required, and manual interventions may become necessary. Before routine use, further investigations are required, particularly to reduce imaging artifacts.« less
  • Purpose: Late complications (cardiac toxicities, secondary lung, and breast cancer) remain a significant concern in the radiation treatment of Hodgkin's lymphoma (HL). To address this issue, predictive dose-risk models could potentially be used to estimate radiotherapy-related late toxicities. This study investigates the use of deformable image registration (DIR) and navigator channels (NCs) to reconstruct 3D lung models from 2D radiographic planning images, in order to retrospectively calculate the treatment dose exposure to HL patients treated with 2D planning, which are now experiencing late effects. Methods: Three-dimensional planning CT images of 52 current HL patients were acquired. 12 image sets weremore » used to construct a male and a female population lung model. 23 ''Reference'' images were used to generate lung deformation adaptation templates, constructed by deforming the population model into each patient-specific lung geometry using a biomechanical-based DIR algorithm, MORFEUS. 17 ''Test'' patients were used to test the accuracy of the reconstruction technique by adapting existing templates using 2D digitally reconstructed radiographs. The adaptation process included three steps. First, a Reference patient was matched to a Test patient by thorax measurements. Second, four NCs (small regions of interest) were placed on the lung boundary to calculate 1D differences in lung edges. Third, the Reference lung model was adapted to the Test patient's lung using the 1D edge differences. The Reference-adapted Test model was then compared to the 3D lung contours of the actual Test patient by computing their percentage volume overlap (POL) and Dice coefficient. Results: The average percentage overlapping volumes and Dice coefficient expressed as a percentage between the adapted and actual Test models were found to be 89.2{+-}3.9% (Right lung=88.8%; Left lung=89.6%) and 89.3{+-}2.7% (Right=88.5%; Left=90.2%), respectively. Paired T-tests demonstrated that the volumetric reconstruction method made a statistically significant improvement to the population lung model shape (p<0.05). The error in the results were also comparable to the volume overlap difference observed between inhale and exhale lung volumes during free-breathing respiratory motion (POL:p=0.43; Dice:p=0.20), which implies that the accuracies of the reconstruction method are within breathing constraints and would not be the confining factor in estimating normal tissue dose exposure. Conclusions: The result findings show that the DIR-NC technique can achieve a high degree of reconstruction accuracy, and could be useful in approximating 3D dosimetric representations of historical 2D treatment. In turn, this could provide a better understanding of the biophysical relationship between dose-volume exposure and late term radiotherapy effects.« less
  • Purpose: To investigate the effectiveness of employing abdominal compression (AC) in reducing motion for the target region and sub-regions of the lung as part of the planning process for radiation therapy. Methods: Fourteen patients with early lung cancer were scanned with 4DCT and it was determined that target motion exceeded our institutional limit of > 8 mm motion and received a repeat 4DCT with AC. For each 4DCT, deformable image registration (DIR) was used to map the max inhale to the max exhale phase to determine the deformation vector fields (DVF). DIR was performed with Morphons and Demons algorithms. Themore » mean DVF was used to represent that sub-region for each patient. The magnitudes of the mean DVF were quantified for the target and 12 sub-regions in the AP, LR SI directions. The sub-regions were contoured on each lung as (add prefix R or L for lung): Upper-Anterior (UA), Upper-Posterior (UP), Mid-Anterior (MA), Mid-Posterior (MP), Lower-Anterior (LA) and Lower-Posterior (LP). Results: The min/max SI motion for the target on the uncompressed 4DCT was 8mm/24.5 mm. The magnitude of decrease in SI was greatest in the RLP region (3.7±4.0mm) followed by target region (3.3±2.2mm) and finally the LLP region (3.0±3.5mm). The magnitude of decrease in 3D vector followed the same trend; RLP (3.5±2.2mm) then GTV (3.5±2.6mm) then LLP (2.7±3.8mm). 79% of the cases had a SI decrease of >12.5%, 43% had a SI decrease of >25% and 21% had a SI decrease of >50% as compared to the motion on the uncompressed 4DCT. Conclusion: AC is useful in reducing motion with the largest decreases observed in the lower posterior regions of the lungs. However, it should be noted that AC will not greatly decrease motion for all cases as 21% of cases did not reduce SI motion more than 12.5% of initial motion.« less