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Title: TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies

Abstract

Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errors on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. Inmore » the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need for an adaptive treatment strategy.« less

Authors:
 [1];  [2]; ;  [1];  [3]
  1. RaySearch Laboratories AB, Stockholm (Sweden)
  2. (Sweden)
  3. KTH Royal Institute of Technology, Stockholm (Sweden)
Publication Date:
OSTI Identifier:
22654073
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; ERRORS; FRACTIONATION; PATIENTS; PLANNING; RADIATION DOSE DISTRIBUTIONS; RADIOTHERAPY; STOCHASTIC PROCESSES

Citation Formats

Boeck, M, KTH Royal Institute of Technology, Stockholm, Eriksson, K, Hardemark, B, and Forsgren, A. TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies. United States: N. p., 2016. Web. doi:10.1118/1.4957699.
Boeck, M, KTH Royal Institute of Technology, Stockholm, Eriksson, K, Hardemark, B, & Forsgren, A. TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies. United States. doi:10.1118/1.4957699.
Boeck, M, KTH Royal Institute of Technology, Stockholm, Eriksson, K, Hardemark, B, and Forsgren, A. 2016. "TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies". United States. doi:10.1118/1.4957699.
@article{osti_22654073,
title = {TU-H-CAMPUS-JeP3-01: Towards Robust Adaptive Radiation Therapy Strategies},
author = {Boeck, M and KTH Royal Institute of Technology, Stockholm and Eriksson, K and Hardemark, B and Forsgren, A},
abstractNote = {Purpose: To set up a framework combining robust treatment planning with adaptive reoptimization in order to maintain high treatment quality, to respond to interfractional variations and to identify those patients who will benefit the most from an adaptive fractionation schedule. Methods: We propose adaptive strategies based on stochastic minimax optimization for a series of simulated treatments on a one-dimensional patient phantom. The plan should be able to handle anticipated systematic and random errors and is applied during the first fractions. Information on the individual geometric variations is gathered at each fraction. At scheduled fractions, the impact of the measured errors on the delivered dose distribution is evaluated. For a patient that receives a dose that does not satisfy specified plan quality criteria, the plan is reoptimized based on these individual measurements using one of three different adaptive strategies. The reoptimized plan is then applied during future fractions until a new scheduled adaptation becomes necessary. In the first adaptive strategy the measured systematic and random error scenarios and their assigned probabilities are updated to guide the robust reoptimization. The focus of the second strategy lies on variation of the fraction of the worst scenarios taken into account during robust reoptimization. In the third strategy the uncertainty margins around the target are recalculated with the measured errors. Results: By studying the effect of the three adaptive strategies combined with various adaptation schedules on the same patient population, the group which benefits from adaptation is identified together with the most suitable strategy and schedule. Preliminary computational results indicate when and how best to adapt for the three different strategies. Conclusion: A workflow is presented that provides robust adaptation of the treatment plan throughout the course of treatment and useful measures to identify patients in need for an adaptive treatment strategy.},
doi = {10.1118/1.4957699},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: Ultrasound is ideal for real-time monitoring in radiotherapy with high soft tissue contrast, non-ionization, portability, and cost effectiveness. Few studies investigated clinical application of real-time ultrasound monitoring for abdominal stereotactic body radiation therapy (SBRT). This study aims to demonstrate the feasibility of real-time monitoring of 3D target motion using 4D ultrasound. Methods: An ultrasound probe holding system was designed to allow clinician to freely move and lock ultrasound probe. For phantom study, an abdominal ultrasound phantom was secured on a 2D programmable respiratory motion stage. One side of the stage was elevated than another side to generate 3D motion.more » The motion stage made periodic breath-hold movement. Phantom movement tracked by infrared camera was considered as ground truth. For volunteer study three healthy subjects underwent the same setup for abdominal SBRT with active breath control (ABC). 4D ultrasound B-mode images were acquired for both phantom and volunteers for real-time monitoring. 10 breath-hold cycles were monitored for each experiment. For phantom, the target motion tracked by ultrasound was compared with motion tracked by infrared camera. For healthy volunteers, the reproducibility of ABC breath-hold was evaluated. Results: Volunteer study showed the ultrasound system fitted well to the clinical SBRT setup. The reproducibility for 10 breath-holds is less than 2 mm in three directions for all three volunteers. For phantom study the motion between inspiration and expiration captured by camera (ground truth) is 2.35±0.02 mm, 1.28±0.04 mm, 8.85±0.03 mm in LR, AP, SI directly, respectively. The motion monitored by ultrasound is 2.21±0.07 mm, 1.32±0.12mm, 9.10±0.08mm, respectively. The motion monitoring error in any direction is less than 0.5 mm. Conclusion: The volunteer study proved the clinical feasibility of real-time ultrasound monitoring for abdominal SBRT. The phantom and volunteer ABC studies demonstrated sub-millimeter accuracy of 3D motion movement monitoring.« less
  • Purpose: With introduction of high-quality treatment imaging during radiation therapy (RT) delivery, e.g., MR-Linac, adaptive replanning of either online or offline becomes appealing. Dose accumulation of delivered fractions, a prerequisite for the adaptive replanning, can be cumbersome and inaccurate. The purpose of this work is to develop an automated process to accumulate daily doses and to assess the dose accumulation accuracy voxel-by-voxel for adaptive replanning. Methods: The process includes the following main steps: 1) reconstructing daily dose for each delivered fraction with a treatment planning system (Monaco, Elekta) based on the daily images using machine delivery log file and consideringmore » patient repositioning if applicable, 2) overlaying the daily dose to the planning image based on deformable image registering (DIR) (ADMIRE, Elekta), 3) assessing voxel dose deformation accuracy based on deformation field using predetermined criteria, and 4) outputting accumulated dose and dose-accuracy volume histograms and parameters. Daily CTs acquired using a CT-on-rails during routine CT-guided RT for sample patients with head and neck and prostate cancers were used to test the process. Results: Daily and accumulated doses (dose-volume histograms, etc) along with their accuracies (dose-accuracy volume histogram) can be robustly generated using the proposed process. The test data for a head and neck cancer case shows that the gross tumor volume decreased by 20% towards the end of treatment course, and the parotid gland mean dose increased by 10%. Such information would trigger adaptive replanning for the subsequent fractions. The voxel-based accuracy in the accumulated dose showed that errors in accumulated dose near rigid structures were small. Conclusion: A procedure as well as necessary tools to automatically accumulate daily dose and assess dose accumulation accuracy is developed and is useful for adaptive replanning. Partially supported by Elekta, Inc.« less
  • Purpose: To develop a new method which adaptively determines the optimal needle insertion sequence for HDR prostate brachytherapy involving divergent needle-by-needle dose delivery by e.g. a robotic device. A needle insertion sequence is calculated at the beginning of the intervention and updated after each needle insertion with feedback on needle positioning errors. Methods: Needle positioning errors and anatomy changes may occur during HDR brachytherapy which can lead to errors in the delivered dose. A novel strategy was developed to calculate and update the needle sequence and the dose plan after each needle insertion with feedback on needle positioning errors. Themore » dose plan optimization was performed by numerical simulations. The proposed needle sequence determination optimizes the final dose distribution based on the dose coverage impact of each needle. This impact is predicted stochastically by needle insertion simulations. HDR procedures were simulated with varying number of needle insertions (4 to 12) using 11 patient MR data-sets with PTV, prostate, urethra, bladder and rectum delineated. Needle positioning errors were modeled by random normally distributed angulation errors (standard deviation of 3 mm at the needle’s tip). The final dose parameters were compared in the situations where the needle with the largest vs. the smallest dose coverage impact was selected at each insertion. Results: Over all scenarios, the percentage of clinically acceptable final dose distribution improved when the needle selected had the largest dose coverage impact (91%) compared to the smallest (88%). The differences were larger for few (4 to 6) needle insertions (maximum difference scenario: 79% vs. 60%). The computation time of the needle sequence optimization was below 60s. Conclusion: A new adaptive needle sequence determination for HDR prostate brachytherapy was developed. Coupled to adaptive planning, the selection of the needle with the largest dose coverage impact increases chances of reaching the clinical constraints. M. Borot de Battisti is funded by Philips Medical Systems Nederland B.V.; M. Moerland is principal investigator on a contract funded by Philips Medical Systems Nederland B.V.; G. Hautvast and D. Binnekamp are fulltime employees of Philips Medical Systems Nederland B.V.« less
  • Purpose: To examine a range of scenarios for image-guided adaptive radiation therapy of prostate cancer, including different schedules for megavoltage CT imaging, patient repositioning, and dose replanning. Methods and Materials: We simulated multifraction dose distributions with deformable registration using 35 sets of megavoltage CT scans of 13 patients. We computed cumulative dose–volume histograms, from which tumor control probabilities and normal tissue complication probabilities (NTCPs) for rectum were calculated. Five-field intensity modulated radiation therapy (IMRT) with 18-MV x-rays was planned to achieve an isocentric dose of 76 Gy to the clinical target volume (CTV). The differences between D{sub 95}, tumor controlmore » probability, V{sub 70Gy}, and NTCP for rectum, for accumulated versus planned dose distributions, were compared for different target volume sizes, margins, and adaptive strategies. Results: The CTV D{sub 95} for IMRT treatment plans, averaged over 13 patients, was 75.2 Gy. Using the largest CTV margins (10/7 mm), the D{sub 95} values accumulated over 35 fractions were within 2% of the planned value, regardless of the adaptive strategy used. For tighter margins (5 mm), the average D{sub 95} values dropped to approximately 73.0 Gy even with frequent repositioning, and daily replanning was necessary to correct this deficit. When personalized margins were applied to an adaptive CTV derived from the first 6 treatment fractions using the STAPLE (Simultaneous Truth and Performance Level Estimation) algorithm, target coverage could be maintained using a single replan 1 week into therapy. For all approaches, normal tissue parameters (rectum V{sub 70Gy} and NTCP) remained within acceptable limits. Conclusions: The frequency of adaptive interventions depends on the size of the CTV combined with target margins used during IMRT optimization. The application of adaptive target margins (<5 mm) to an adaptive CTV determined 1 week into therapy minimizes the need for subsequent dose replanning.« less
  • Purpose: To evaluate the potential impact of several setup error correction strategies on a proposed image-guided adaptive radiotherapy strategy for locally advanced lung cancer. Methods: Daily 4D cone-beam CT and weekly 4D fan-beam CT images were acquired from 9 lung cancer patients undergoing concurrent chemoradiation therapy. Initial planning CT was deformably registered to daily CBCT images to generate synthetic treatment courses. An adaptive radiation therapy course was simulated using the weekly CT images with replanning twice and a hypofractionated, simultaneous integrated boost to a total dose of 66 Gy to the original PTV and either a 66 Gy (no boost)more » or 82 Gy (boost) dose to the boost PTV (ITV + 3mm) in 33 fractions with IMRT or VMAT. Lymph nodes (LN) were not boosted (prescribed to 66 Gy in both plans). Synthetic images were rigidly, bony (BN) or tumor and carina (TC), registered to the corresponding plan CT, dose was computed on these from adaptive replans (PLAN) and deformably accumulated back to the original planning CT. Cumulative D98% of CTV of PT (ITV for 82Gy) and LN, and normal tissue dose changes were analyzed. Results: Two patients were removed from the study due to large registration errors. For the remaining 7 patients, D98% for CTV-PT (ITV-PT for 82 Gy) and CTV-LN was within 1 Gy of PLAN for both 66 Gy and 82 Gy plans with both setup techniques. Overall, TC based setup provided better results, especially for LN coverage (p = 0.1 for 66Gy plan and p = 0.2 for 82 Gy plan, comparison of BN and TC), though not significant. Normal tissue dose constraints violated for some patients if constraint was barely achieved in PLAN. Conclusion: The hypofractionated adaptive strategy appears to be deliverable with soft tissue alignment for the evaluated margins and planning parameters. Research was supported by NIH P01CA116602.« less