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Title: TU-H-CAMPUS-JeP3-05: Adaptive Determination of Needle Sequence HDR Prostate Brachytherapy with Divergent Needle-By-Needle Delivery

Abstract

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. The 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 smallestmore » 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

Authors:
; ; ; ;  [1];  [2];  [3]; ;  [4]
  1. University Medical Center Utrecht, Department of Radiotherapy, Utrecht (Netherlands)
  2. IMB, UMR 5251 CNRS/University of Bordeaux, Talence (France)
  3. (Netherlands)
  4. Philips Group Innovation, Biomedical Systems, Eindhoven (Netherlands)
Publication Date:
OSTI Identifier:
22654076
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:
61 RADIATION PROTECTION AND DOSIMETRY; 60 APPLIED LIFE SCIENCES; BRACHYTHERAPY; CALCULATION METHODS; COMPUTERIZED SIMULATION; DELIVERY; ERRORS; OPTIMIZATION; PLANNING; POSITIONING; PROSTATE; RADIATION DOSE DISTRIBUTIONS

Citation Formats

Borot de Battisti, M, Maenhout, M, Lagendijk, J J W, Van Vulpen, M, Moerland, M A, Denis de Senneville, B, University Medical Center Utrecht, Imaging Division, Utrecht, Hautvast, G, and Binnekamp, D. TU-H-CAMPUS-JeP3-05: Adaptive Determination of Needle Sequence HDR Prostate Brachytherapy with Divergent Needle-By-Needle Delivery. United States: N. p., 2016. Web. doi:10.1118/1.4957703.
Borot de Battisti, M, Maenhout, M, Lagendijk, J J W, Van Vulpen, M, Moerland, M A, Denis de Senneville, B, University Medical Center Utrecht, Imaging Division, Utrecht, Hautvast, G, & Binnekamp, D. TU-H-CAMPUS-JeP3-05: Adaptive Determination of Needle Sequence HDR Prostate Brachytherapy with Divergent Needle-By-Needle Delivery. United States. doi:10.1118/1.4957703.
Borot de Battisti, M, Maenhout, M, Lagendijk, J J W, Van Vulpen, M, Moerland, M A, Denis de Senneville, B, University Medical Center Utrecht, Imaging Division, Utrecht, Hautvast, G, and Binnekamp, D. Wed . "TU-H-CAMPUS-JeP3-05: Adaptive Determination of Needle Sequence HDR Prostate Brachytherapy with Divergent Needle-By-Needle Delivery". United States. doi:10.1118/1.4957703.
@article{osti_22654076,
title = {TU-H-CAMPUS-JeP3-05: Adaptive Determination of Needle Sequence HDR Prostate Brachytherapy with Divergent Needle-By-Needle Delivery},
author = {Borot de Battisti, M and Maenhout, M and Lagendijk, J J W and Van Vulpen, M and Moerland, M A and Denis de Senneville, B and University Medical Center Utrecht, Imaging Division, Utrecht and Hautvast, G and Binnekamp, D},
abstractNote = {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. The 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.},
doi = {10.1118/1.4957703},
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: To develop adaptive planning with feedback for MRI-guided focal HDR prostate brachytherapy with a single divergent needle robotic implant device. After each needle insertion, the dwell positions for that needle are calculated and the positioning of remaining needles and dosimetry are both updated based on MR imaging. Methods: Errors in needle positioning may occur due to inaccurate needle insertion (caused by e.g. the needle’s bending) and unpredictable changes in patient anatomy. Consequently, the dose plan quality might dramatically decrease compared to the preplan. In this study, a procedure was developed to re-optimize, after each needle insertion, the remaining needlemore » angulations, source positions and dwell times in order to obtain an optimal coverage (D95% PTV>19 Gy) without exceeding the constraints of the organs at risk (OAR) (D10% urethra<21 Gy, D1cc bladder<12 Gy and D1cc rectum<12 Gy). Complete HDR procedures with 6 needle insertions were simulated for a patient MR-image set with PTV, prostate, urethra, bladder and rectum delineated. Random angulation errors, modeled by a Gaussian distribution (standard deviation of 3 mm at the needle’s tip), were generated for each needle insertion. We compared the final dose parameters for the situations (I) without re-optimization and (II) with the automatic feedback. Results: The computation time of replanning was below 100 seconds on a current desk computer. For the patient tested, a clinically acceptable dose plan was achieved while applying the automatic feedback (median(range) in Gy, D95% PTV: 19.9(19.3–20.3), D10% urethra: 13.4(11.9–18.0), D1cc rectum: 11.0(10.7–11.6), D1cc bladder: 4.9(3.6–6.8)). This was not the case without re-optimization (median(range) in Gy, D95% PTV: 19.4(14.9–21.3), D10% urethra: 12.6(11.0–15.7), D1cc rectum: 10.9(8.9–14.1), D1cc bladder: 4.8(4.4–5.2)). Conclusion: An automatic guidance strategy for HDR prostate brachytherapy was developed to compensate errors in needle positioning and improve the dose distribution. Without re-optimization, target coverage and OAR constraints may not be achieved. 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 full-time employees of Philips Medical Systems Nederland B.V.« less
  • 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 errorsmore » 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.« 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 retrospectively quantify the intra-fraction prostate motion during stereotactic body radiation therapy (SBRT) treatment using CyberKnife’s target tracking system, which may provide insight into expansion margins from GTV to PTV used in gantry-based treatments. CyberKnife is equipped with an active tracking system (InTempo) that tracks the four fiducials placed in the prostate gland. The system acquires intra-fraction orthogonal kV images at 45° and 315° in a sequential fashion. Methods: A total of 38 patients treated with SBRT using CyberKnife between 2011 and 2013 were studied. Dose-regime was 36.25 Gy in 5 fractions (7.25 Gy/fraction, twice per week) as permore » RTOG 0938 guidelines. The CyberKnife image tracking logs for all SBRT treatments using InTempo were examined. A total of 13663 images were examined for the superior/inferior (SI), anterior/posterior (AP) and left/right (LR) translation as well as roll, pitch and yaw rotations for the target position relative to the last known model position. Results: The mean ± 2 SD of intra-fraction motion was contained within 3 mm for SI and LR and 4.5 mm for AP directions at 5 minutes into the treatment delivery. It was contained within 4 mm for SI and LR and 5 mm for AP at 10 minutes. At 15 minutes into delivery, all translations were contained within 5 mm. The mean ± 2 SD of prostate roll, pitch and yaw increased with time but were contained within 5 degree at 5, 10 and 15 minutes into treatment. Additionally, target translations and rotations were within ± 1 mm and ± 1 degree for 90% and 78% of the time. Conclusion: The organ motion component of PTV margin for 10 minute VMAT delivery is contained within 4 mm in SI and LR direction and within 5 mm in the AP direction.« less
  • Purpose: Proton dose distribution is sensitive to tumor regression and tissue and normal anatomy changes. Replanning is sometimes necessary during treatment to ensure continue tumor coverage or avoid overtreatment of organs at risk (OARs). We investigated action thresholds for replanning and identified both dosimetric and non-dosimetric metrics that would predict a need for replan. Methods: All consecutive lung cancer patients (n = 188) who received definitive proton radiotherapy and had more than two evaluation CT scans at the Roberts Proton Therapy Center (Philadelphia, USA) from 2011 to 2015 were included in this study. The cohort included a variety of tumormore » sizes, locations, histology, beam angles, as well as radiation-induced tumor and lung change. Dosimetric changes during therapy were characterized by changes in the dose volume distribution of PTV, ITV, and OARs (heart, cord, esophagus, brachial plexus and lungs). Tumor and lung change were characterized by changes in sizes, and in the distribution of Hounsfield numbers and water equivalent thickness (WET) along the beam path. We applied machine learning tools to identify both dosimetric and non-dosimetric metrics that predicted a replan. Results: Preliminary data showed that clinical indicators (n = 54) were highly correlated; thus, a simple indicator may be derived to guide the action threshold for replanning. Additionally, tumor regression alone could not predict dosimetric changes in OARs; it required further information about beam angles and tumor locations. Conclusion: Both dosimetric and non-dosimetric factors are predictive of the need for replanning during proton treatment.« less