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Huiskes M, Kong W, Oud M, Crama K, Rasch C, Breedveld S, Heijmen B, Astreinidou E. Validation of Fully Automated Robust Multicriterial Treatment Planning for Head and Neck Cancer IMPT. Int J Radiat Oncol Biol Phys 2024; 119:968-977. [PMID: 38284961 DOI: 10.1016/j.ijrobp.2023.12.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 12/10/2023] [Accepted: 12/23/2023] [Indexed: 01/30/2024]
Abstract
PURPOSE Our purpose was to compare robust intensity modulated proton therapy (IMPT) plans, automatically generated with wish-list-based multicriterial optimization as implemented in Erasmus-iCycle, with manually created robust clinical IMPT plans for patients with head and neck cancer. METHODS AND MATERIALS Thirty-three patients with head and neck cancer were retrospectively included. All patients were previously treated with a manually created IMPT plan with 7000 cGy dose prescription to the primary tumor (clinical target volume [CTV]7000) and 5425 cGy dose prescription to the bilateral elective volumes (CTV5425). Plans had a 4-beam field configuration and were generated with scenario-based robust optimization (21 scenarios, 3-mm setup error, and ±3% density uncertainty for the CTVs). Three clinical plans were used to configure the Erasmus-iCycle wish-list for automated generation of robust IMPT plans for the other 30 included patients, in line with clinical planning requirements. Automatically and manually generated IMPT plans were compared for (robust) target coverage, organ-at-risk (OAR) doses, and normal tissue complication probabilities (NTCP). No manual fine-tuning of automatically generated plans was performed. RESULTS For all automatically generated plans, voxel-wise minimum D98% values for the CTVs were within clinical constraints and similar to manual plans. All investigated OAR parameters were favorable in the automatically generated plans (all P < .001). Median reductions in mean dose to OARs went up to 667 cGy for the inferior pharyngeal constrictor muscle, and median reductions in D0.03cm3 in serial OARs ranged up to 1795 cGy for the spinal cord surface. The observed lower mean dose in parallel OARs resulted in statistically significant lower NTCP for xerostomia (grade ≥2: 34.4% vs 38.0%; grade ≥3: 9.0% vs 10.2%) and dysphagia (grade ≥2: 11.8% vs 15.0%; grade ≥3: 1.8% vs 2.8%). CONCLUSIONS Erasmus-iCycle was able to produce IMPT dose distributions fully automatically with similar (robust) target coverage and improved OAR doses and NTCPs compared with clinical manual planning, with negligible hands-on planning workload.
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Affiliation(s)
- Merle Huiskes
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands.
| | - Wens Kong
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Michelle Oud
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Koen Crama
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands; HollandPTC, Delft, The Netherlands
| | - Coen Rasch
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands; HollandPTC, Delft, The Netherlands
| | - Sebastiaan Breedveld
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Ben Heijmen
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Eleftheria Astreinidou
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, The Netherlands
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Chong IY, Chau I. Is there still a place for radiotherapy in gastric cancer? Curr Opin Pharmacol 2023; 68:102325. [PMID: 36610101 DOI: 10.1016/j.coph.2022.102325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 01/07/2023]
Abstract
Stomach cancer is an aggressive disease and represents a global health problem. The majority of patients with localised disease present with locally advanced cancer that requires multimodality treatment. Chemoradiotherapy delivered after D2 gastrectomy has been evaluated in a number of clinical studies and best evidence, thus far, does not support its use in the post-operative setting. Data from currently recruiting and ongoing trials with exploratory translational endpoints are eagerly awaited to direct the use of chemoradiotherapy in the neoadjuvant setting. Radiotherapy can be effective in the palliation of symptoms associated with advanced gastric cancer. Furthermore, Stereotactic Body Radiotherapy has the potential to provide long term disease control in a proportion of gastric cancer patients with oligometastatic liver disease.
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Affiliation(s)
- Irene Y Chong
- Consultant Clinical Oncologist, The Royal Marsden NHS Foundation Trust, London, UK.
| | - Ian Chau
- Consultant Medical Oncologist, The Royal Marsden Hospital NHS Foundation Trust, London, UK
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Mazonakis M, Tzanis E, Lyraraki E, Damilakis J. Automatic Radiobiological Comparison of Radiation Therapy Plans: An Application to Gastric Cancer. Cancers (Basel) 2022; 14:cancers14246098. [PMID: 36551582 PMCID: PMC9776876 DOI: 10.3390/cancers14246098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/08/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
(1) Aim: This study was conducted to radiobiologically compare radiotherapy plans for gastric cancer with a newly developed software tool. (2) Methods: Treatment planning was performed on two computational phantoms simulating adult male and female patients. Three-dimensional conformal radiotherapy (3D-CRT), intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans for gastric cancer were generated with three-photon beam energies. The equivalent uniform dose (EUD), tumor control probability (TCP) of the target and normal tissue control probability (NTCP) of eight different critical organs were calculated. A new software was employed for these calculations using the EUD-based model and dose-volume-histogram data. (3) Results: The IMRT and VMAT plan led to TCPs of 51.3-51.5%, whereas 3D-CRT gave values up to 50.2%. The intensity-modulated techniques resulted in NTCPs of (5.3 × 10-6-3.3 × 10-1)%. The corresponding NTCPs from 3D-CRT were (3.4 × 10-7-7.4 × 10-1)%. The above biological indices were automatically calculated in less than 40 s with the software. (4) Conclusions: The direct and quick radiobiological evaluation of radiotherapy plans is feasible using the new software tool. The IMRT and VMAT reduced the probability of the appearance of late effects in most of the surrounding critical organs and slightly increased the TCP compared to 3D-CRT.
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Affiliation(s)
- Michalis Mazonakis
- Department of Medical Physics, Faculty of Medicine, University of Crete, 71003 Iraklion, Greece
- Correspondence:
| | - Eleftherios Tzanis
- Department of Medical Physics, Faculty of Medicine, University of Crete, 71003 Iraklion, Greece
| | - Efrossyni Lyraraki
- Department of Radiation Oncology, University Hospital of Iraklion, 71110 Iraklion, Greece
| | - John Damilakis
- Department of Medical Physics, Faculty of Medicine, University of Crete, 71003 Iraklion, Greece
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Leitão J, Bijman R, Wahab Sharfo A, Brus Y, Rossi L, Breedveld S, Heijmen B. Automated multi-criterial planning with beam angle optimization to establish non-coplanar VMAT class solutions for nasopharyngeal carcinoma. Phys Med 2022; 101:20-27. [PMID: 35853387 DOI: 10.1016/j.ejmp.2022.06.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 06/07/2022] [Accepted: 06/29/2022] [Indexed: 10/17/2022] Open
Abstract
PURPOSE Complexity in selecting optimal non-coplanar beam setups and prolonged delivery times may hamper the use of non-coplanar treatments for nasopharyngeal carcinoma (NPC). Automated multi-criterial planning with integrated beam angle optimization was used to define non-coplanar VMAT class solutions (CSs), each consisting of a coplanar arc and additional 1 or 2 fixed, non-coplanar partial arcs. METHODS Automated planning was used to generate a coplanar VMAT plan with 5 complementary computer-optimized non-coplanar IMRT beams (VMAT+5) for each of the 20 included patients. Subsequently, the frequency distribution of the 100 patient-specific non-coplanar IMRT beam directions was used to select non-coplanar arcs for supplementing coplanar VMAT. A second investigated CS with only one non-coplanar arc consisted of coplanar VMAT plus a partial arc at 90° couch angle (VMATCS90). Plans generated with the two VMATCSs were compared to coplanar VMAT. RESULTS VMAT+5 analysis resulted in VMATCS60: two partial non-coplanar arcs at couch angles 60° and -60° to complement coplanar VMAT. Compared to coplanar VMAT, the non-coplanar VMATCS60 and VMATCS90 yielded substantial average dose reductions in OARs associated with xerostomia and dysphagia, i.e., parotids, submandibular glands, oral cavity and swallowing muscles (p < 0.05) for the same PTV coverage and without violating hard constraints. Impact of non-coplanar treatment and superiority of either VMACS60 and VMATCS90 was highly patient dependent. CONCLUSIONS Compared to coplanar VMAT, dose to OARs was substantially reduced with a CS with one or two non-coplanar arcs. Preferences for coplanar or one or two additional arcs are highly patient-specific, balancing plan quality and treatment time.
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Affiliation(s)
- Joana Leitão
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
| | - Rik Bijman
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Abdul Wahab Sharfo
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Yori Brus
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Linda Rossi
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Sebastiaan Breedveld
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Ben Heijmen
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
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Evaluation of an automated template-based treatment planning system for radiotherapy of anal, rectal and prostate cancer. Tech Innov Patient Support Radiat Oncol 2022; 22:30-36. [PMID: 35464888 PMCID: PMC9020095 DOI: 10.1016/j.tipsro.2022.04.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/11/2022] [Accepted: 04/05/2022] [Indexed: 11/21/2022] Open
Abstract
Automated treatment planning system compared to manual planning. Equivalent plan quality between VMAT manually generated- and IMRT automatically generated plans. Evaluation of anal, prostate and rectum treatment plans. Generation of highly consistent IMRT automated plan within 2 to 3.5 min.
Background and purpose The Ethos system has enabled online adaptive radiotherapy (oART) by implementing an automated treatment planning system (aTPS) for both intensity-modulated radiotherapy (IMRT) and volumetric modulated arc radiotherapy (VMAT) plan creation. The purpose of this study is to evaluate the quality of aTPS plans in the pelvic region. Material and Methods Sixty patients with anal (n = 20), rectal (n = 20) or prostate (n = 20) cancer were retrospectively re-planned with the aTPS. Three IMRT (7-, 9- and 12-field) and two VMAT (2 and 3 arc) automatically generated plans (APs) were created per patient. The duration of the automated plan generation was registered. The best IMRT-AP and VMAT-AP for each patient were selected based on target coverage and dose to organs at risk (OARs). The AP quality was analyzed and compared to corresponding clinically accepted and manually generated VMAT plans (MPs) using several clinically relevant dose metrics. Calculation-based pre-treatment plan quality assurance (QA) was performed for all plans. Results The median total duration to generate the five APs with the aTPS was 55 min, 39 min and 35 min for anal, prostate and rectal plans, respectively. The target coverage and the OAR sparing were equivalent for IMRT-APs and VMAT-MPs, while VMAT-Aps. demonstrated lower target dose homogeneity and higher dose to some OARs. Both conformity and homogeneity index were equivalent (rectal) or better (anal and prostate) for IMRT-APs compared to VMAT-MPs. All plans passed the patient-specific QA tolerance limit. Conclusions The aTPS generates plans comparable to MPs within a short time-frame which is highly relevant for oART treatments.
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Key Words
- AP, automatically generated plan
- Automated treatment planning
- CN, conformity number
- CT, computed tomography
- CTV, clinical target volume
- DVH, dose volume histogram
- FFF, flattening filter free
- GTV, gross tumor volume
- HI, homogeneity index
- IMRT, intensity modulated radiotherapy
- Intelligent optimization engine
- KPB, knowledge-based planning
- Linac, Linear accelerators
- MCO, multi-criteria optimization
- MLC, multileaf collimator
- MP, manually-generated plan
- MR, magnetic resonance
- MU, Monitor Unit
- OAR, Organ at risk
- Online adaptive radiotherapy
- PTV, planning target volume
- Pelvic cancer
- Plan quality
- QA, Quality assurance
- SD, standard deviation
- Template-based Ethos TPS
- VMAT, volumetric arc radiotherapy
- aTPS, automated treatment planning system
- oART, online adaptive radiotherapy
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Fu Y, Zhang H, Morris ED, Glide-Hurst CK, Pai S, Traverso A, Wee L, Hadzic I, Lønne PI, Shen C, Liu T, Yang X. Artificial Intelligence in Radiation Therapy. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022; 6:158-181. [PMID: 35992632 PMCID: PMC9385128 DOI: 10.1109/trpms.2021.3107454] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Artificial intelligence (AI) has great potential to transform the clinical workflow of radiotherapy. Since the introduction of deep neural networks, many AI-based methods have been proposed to address challenges in different aspects of radiotherapy. Commercial vendors have started to release AI-based tools that can be readily integrated to the established clinical workflow. To show the recent progress in AI-aided radiotherapy, we have reviewed AI-based studies in five major aspects of radiotherapy including image reconstruction, image registration, image segmentation, image synthesis, and automatic treatment planning. In each section, we summarized and categorized the recently published methods, followed by a discussion of the challenges, concerns, and future development. Given the rapid development of AI-aided radiotherapy, the efficiency and effectiveness of radiotherapy in the future could be substantially improved through intelligent automation of various aspects of radiotherapy.
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Affiliation(s)
- Yabo Fu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Hao Zhang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Eric D. Morris
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, CA 90095, USA
| | - Carri K. Glide-Hurst
- Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Suraj Pai
- Maastricht University Medical Centre, Netherlands
| | | | - Leonard Wee
- Maastricht University Medical Centre, Netherlands
| | | | - Per-Ivar Lønne
- Department of Medical Physics, Oslo University Hospital, PO Box 4953 Nydalen, 0424 Oslo, Norway
| | - Chenyang Shen
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75002, USA
| | - Tian Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
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Schipaanboord BWK, Heijmen BJM, Breedveld S. TBS-BAO: fully automated beam angle optimization for IMRT guided by a total-beam-space reference plan. Phys Med Biol 2022; 67. [PMID: 35026742 DOI: 10.1088/1361-6560/ac4b37] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 01/13/2022] [Indexed: 11/11/2022]
Abstract
Properly selected beam angles contribute to the quality of radiotherapy treatment plans. However, the beam angle optimization (BAO) problem is difficult to solve to optimality due to its non-convex discrete nature with many local minima. In this study, we propose TBS-BAO, a novel approach for solving the BAO problem, and test it for non-coplanar robotic CyberKnife radiotherapy for prostate cancer. First, an ideal Pareto-optimal reference dose distribution is automatically generated usinga priorimulti-criterial fluence map optimization (FMO) to generate a plan that includes all candidate beams (total-beam-space, TBS). Then, this ideal dose distribution is reproduced as closely as possible in a subsequent segmentation/beam angle optimization step (SEG/BAO), while limiting the number of allowed beams to a user-selectable preset value. SEG/BAO aims at a close reproduction of the ideal dose distribution. For each of 33 prostate SBRT patients, 18 treatment plans with different pre-set numbers of allowed beams were automatically generated with the proposed TBS-BAO. For each patient, the TBS-BAO plans were then compared to a plan that was automatically generated with an alternative BAO method (Erasmus-iCycle) and to a high-quality manually generated plan. TBS-BAO was able to automatically generate plans with clinically feasible numbers of beams (∼25), with a quality highly similar to corresponding 91-beam ideal reference plans. Compared to the alternative Erasmus-iCycle BAO approach, similar plan quality was obtained for 25-beam segmented plans, while computation times were reduced from 10.7 hours to 4.8/1.5 hours, depending on the applied pencil-beam resolution in TBS-BAO. 25-beam TBS-BAO plans had similar quality as manually generated plans with on average 48 beams, while delivery times reduced from 22.3 to 18.4/18.1 min. TBS reference plans could effectively steer the discrete non-convex BAO.
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Affiliation(s)
- B W K Schipaanboord
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - B J M Heijmen
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - S Breedveld
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
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Wang R, Shen J, Yan H, Gao X, Dong T, Li S, Wang P, Zhou J. Dosimetric comparison between intensity-modulated radiotherapy and volumetric-modulated arc therapy in patients of left-sided breast cancer treated with modified radical mastectomy: CONSORT. Medicine (Baltimore) 2022; 101:e28427. [PMID: 35029181 PMCID: PMC8757972 DOI: 10.1097/md.0000000000028427] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 12/06/2021] [Indexed: 01/05/2023] Open
Abstract
Volumetric-modulated arc therapy (VMAT) is a novel treatment strategy that protects normal tissues and enhances target volume coverage during radiotherapy.This study aimed to clarify whether VMAT is superior to intensity-modulated radiotherapy (IMRT) in treatment planning for left-sided breast cancer patients after modified radical mastectomy.Left-sided breast cancer patients treated with modified radical mastectomy were eligible for analysis. The dose distribution of both planning target volume and organs at risk were analyzed by using dose volume histograms.Twenty-four patients were eligible for analysis. Both VMAT and IMRT plans were sufficient in planning target volume coverage. In terms of conformity, VMAT was superior to IMRT (P = .034). Dmean, V5, and V10 of the heart were significantly decreased in VMAT plans when compared with IMRT plans. VMAT was as effective as IMRT plans in sparing of other normal tissues. In addition, both the mean number of monitor units and treatment time were significantly reduced when VMAT was compared with IMRT.VMAT plans was equivalent or superior to IMRT plans in dose distribution, and was associated with slightly advantage in sparing of the heart and coronary arteries. Our analyses suggested VMAT as a preferred option in left-sided breast cancer patients treated with modified radical mastectomy.
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Wang X, Wang WH, Wang SL, Song YW, Liu YP, Tang Y, Li N, Liu WY, Fang H, Li YX, Zhao DB, Chi Y, Yang L, Jin J. Efficacy and toxicity of capecitabine combined with intensity-modulated radiotherapy after D1/D2 lymph node dissection in patients with gastric cancer. World J Gastrointest Oncol 2021; 13:1532-1543. [PMID: 34721783 PMCID: PMC8529930 DOI: 10.4251/wjgo.v13.i10.1532] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/14/2021] [Accepted: 08/16/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Adjuvant chemoradiotherapy (ACRT) with oral capecitabine and intensity-modulated radiotherapy (IMRT) were well tolerated in a phase I study in patients who had undergone partial or total gastrectomy for locally advanced gastric cancer (GC). This phase II study aimed to further determine the efficacy and toxicity of this combination after radical resection and D1/D2 lymph node dissection (LND) for patients with locally advanced GC.
AIM To further determine the efficacy and toxicity of this combination after radical resection and D1/D2 LND for patients with locally advanced GC.
METHODS Forty patients (median age, 53 years; range, 24-71 years) with pathologically confirmed adenocarcinoma who underwent D1/D2 LND were included in this study. The patients received ACRT comprising IMRT (total irradiation dose: 45 Gy delivered in daily 1.8-Gy fractions on 5 d a week over 5 wk) and capecitabine chemotherapy (dose: 800 mg/m² twice daily throughout the duration of radiotherapy). The primary study endpoint was disease-free survival (DFS), and the secondary endpoints were overall survival (OS), toxic effects, and treatment compliance.
RESULTS The 3-year DFS and OS were 66.2% and 75%, respectively. The median time to recurrence was 19.5 mo (range, 6.1-68 mo). Peritoneal implantation (n = 10) was the most common recurrence pattern, and the lung was the most common site of extra-abdominal metastases (n = 5). Nine patients developed grade 3 or 4 toxicities during ACRT. Two patients discontinued ACRT, while eleven underwent ACRT without receiving the entire course of capecitabine. There were no treatment-related deaths.
CONCLUSION The ACRT protocol described herein showed acceptable safety and efficacy for patients with locally advanced GC who received radical gastrectomy and D1/2 LND.
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Affiliation(s)
- Xin Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Wei-Hu Wang
- Department of Radiation Oncology, Peking University Cancer Hospital and Institute, Beijing 100001, China
| | - Shu-Lian Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yong-Wen Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yue-Ping Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yuan Tang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Ning Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, Guangdong Province, China
| | - Wen-Yang Liu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Hui Fang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Ye-Xiong Li
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Dong-Bing Zhao
- Department of Pancreatic and Gastric Surgery, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yihebali Chi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Lin Yang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Jing Jin
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, Guangdong Province, China
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Bijman R, Sharfo AW, Rossi L, Breedveld S, Heijmen B. Pre-clinical validation of a novel system for fully-automated treatment planning. Radiother Oncol 2021; 158:253-261. [DOI: 10.1016/j.radonc.2021.03.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 02/24/2021] [Accepted: 03/02/2021] [Indexed: 12/17/2022]
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Bijman R, Rossi L, Janssen T, de Ruiter P, Carbaat C, van Triest B, Breedveld S, Sonke JJ, Heijmen B. First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer. Acta Oncol 2020; 59:926-932. [PMID: 32436450 DOI: 10.1080/0284186x.2020.1766697] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Background and purpose: In this study we developed a workflow for fully-automated generation of deliverable IMRT plans for a 1.5 T MR-Linac (MRL) based on contoured CT scans, and we evaluated automated MRL planning for rectal cancer.Methods: The Monte Carlo dose calculation engine used in the clinical MRL TPS (Monaco, Elekta AB, Stockholm, Sweden), suited for high accuracy dose calculations in a 1.5 T magnetic field, was coupled to our in-house developed Erasmus-iCycle optimizer. Clinically deliverable plans for 23 rectal cancer patients were automatically generated in a two-step process, i.e., multi-criterial fluence map optimization with Erasmus-iCycle followed by a conversion into a deliverable IMRT plan in the clinical TPS. Automatically generated plans (AUTOplans) were compared to plans that were manually generated with the clinical TPS (MANplans).Results: With AUTOplanning large reductions in planning time and workload were obtained; 4-6 h mainly hands-on planning for MANplans vs ∼1 h of mainly computer computation time for AUTOplans. For equal target coverage, the bladder and bowel bag Dmean was reduced in the AUTOplans by 1.3 Gy (6.9%) on average with a maximum reduction of 4.5 Gy (23.8%). Dosimetric measurements at the MRL demonstrated clinically acceptable delivery accuracy for the AUTOplans.Conclusions: A system for fully automated multi-criterial planning for a 1.5 T MR-Linac was developed and tested for rectal cancer patients. Automated planning resulted in major reductions in planning workload and time, while plan quality improved. Negative impact of the high magnetic field on the dose distributions could be avoided.
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Affiliation(s)
- Rik Bijman
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Linda Rossi
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Tomas Janssen
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Peter de Ruiter
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Casper Carbaat
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Baukelien van Triest
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Sebastiaan Breedveld
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Jan-Jakob Sonke
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Ben Heijmen
- Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
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12
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Wang C, Zhu X, Hong JC, Zheng D. Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future. Technol Cancer Res Treat 2020; 18:1533033819873922. [PMID: 31495281 PMCID: PMC6732844 DOI: 10.1177/1533033819873922] [Citation(s) in RCA: 99] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Treatment planning is an essential step of the radiotherapy workflow. It has become more sophisticated over the past couple of decades with the help of computer science, enabling planners to design highly complex radiotherapy plans to minimize the normal tissue damage while persevering sufficient tumor control. As a result, treatment planning has become more labor intensive, requiring hours or even days of planner effort to optimize an individual patient case in a trial-and-error fashion. More recently, artificial intelligence has been utilized to automate and improve various aspects of medical science. For radiotherapy treatment planning, many algorithms have been developed to better support planners. These algorithms focus on automating the planning process and/or optimizing dosimetric trade-offs, and they have already made great impact on improving treatment planning efficiency and plan quality consistency. In this review, the smart planning tools in current clinical use are summarized in 3 main categories: automated rule implementation and reasoning, modeling of prior knowledge in clinical practice, and multicriteria optimization. Novel artificial intelligence-based treatment planning applications, such as deep learning-based algorithms and emerging research directions, are also reviewed. Finally, the challenges of artificial intelligence-based treatment planning are discussed for future works.
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Affiliation(s)
- Chunhao Wang
- 1 Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Xiaofeng Zhu
- 2 Department of Radiation Oncology, Georgetown University Hospital, Rockville, MD, USA
| | - Julian C Hong
- 1 Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA.,3 Department of Radiation Oncology, University of California, San Francisco, CA, USA
| | - Dandan Zheng
- 4 Department of Radiation Oncology, University of Nebraska Medical Center, Omaha, NE, USA
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13
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Künzel LA, Leibfarth S, Dohm OS, Müller AC, Zips D, Thorwarth D. Automatic VMAT planning for post-operative prostate cancer cases using particle swarm optimization: A proof of concept study. Phys Med 2019; 69:101-109. [PMID: 31862575 DOI: 10.1016/j.ejmp.2019.12.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 11/20/2019] [Accepted: 12/05/2019] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE To investigate the potential of Particle Swarm Optimization (PSO) for fully automatic VMAT radiotherapy (RT) treatment planning. MATERIAL AND METHODS In PSO a solution space of planning constraints is searched for the best possible RT plan in an iterative, statistical method, optimizing a population of candidate solutions. To identify the best candidate solution and for final evaluation a plan quality score (PQS), based on dose volume histogram (DVH) parameters, was introduced. Automatic PSO-based RT planning was used for N = 10 postoperative prostate cancer cases, retrospectively taken from our clinical database, with a prescribed dose of EUD = 66 Gy in addition to two constraints for rectum and one for bladder. Resulting PSO-based plans were compared dosimetrically to manually generated VMAT plans. RESULTS PSO successfully proposed treatment plans comparable to manually optimized ones in 9/10 cases. The median (range) PTV EUD was 65.4 Gy (64.7-66.0) for manual and 65.3 Gy (62.5-65.5) for PSO plans, respectively. However PSO plans achieved significantly lower doses in rectum D2% 67.0 Gy (66.5-67.5) vs. 66.1 Gy (64.7-66.5, p = 0.016). All other evaluated parameters (PTV D98% and D2%, rectum V40Gy and V60Gy, bladder D2% and V60Gy) were comparable in both plans. Manual plans had lower PQS compared to PSO plans with -0.82 (-16.43-1.08) vs. 0.91 (-5.98-6.25). CONCLUSION PSO allows for fully automatic generation of VMAT plans with plan quality comparable to manually optimized plans. However, before clinical implementation further research is needed concerning further adaptation of PSO-specific parameters and the refinement of the PQS.
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Affiliation(s)
- Luise A Künzel
- Section for Biomedical Physic, Department for Radiation Oncology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Sara Leibfarth
- Section for Biomedical Physic, Department for Radiation Oncology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany
| | - Oliver S Dohm
- Department for Radiation Oncology, University Hospital Tübingen, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany
| | - Arndt-Christian Müller
- Department for Radiation Oncology, University Hospital Tübingen, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany
| | - Daniel Zips
- Department for Radiation Oncology, University Hospital Tübingen, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany; German Cancer Consortium (DKTK), Partner Site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Thorwarth
- Section for Biomedical Physic, Department for Radiation Oncology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany; German Cancer Consortium (DKTK), Partner Site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
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14
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Breedveld S, Bennan ABA, Aluwini S, Schaart DR, Kolkman-Deurloo IKK, Heijmen BJM. Fast automated multi-criteria planning for HDR brachytherapy explored for prostate cancer. ACTA ACUST UNITED AC 2019; 64:205002. [DOI: 10.1088/1361-6560/ab44ff] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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15
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Wheeler PA, Chu M, Holmes R, Woodley OW, Jones CS, Maggs R, Staffurth J, Palaniappan N, Spezi E, Lewis DG, Campbell S, Fitzgibbon J, Millin AE. Evaluating the application of Pareto navigation guided automated radiotherapy treatment planning to prostate cancer. Radiother Oncol 2019; 141:220-226. [PMID: 31526670 DOI: 10.1016/j.radonc.2019.08.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 07/19/2019] [Accepted: 08/12/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND AND PURPOSE Current automated planning methods do not allow for the intuitive exploration of clinical trade-offs during calibration. Recently a novel automated planning solution, which is calibrated using Pareto navigation principles, has been developed to address this issue. The purpose of this work was to clinically validate the solution for prostate cancer patients with and without elective nodal irradiation. MATERIALS AND METHODS For 40 randomly selected patients (20 prostate and seminal vesicles (PSV) and 20 prostate and pelvic nodes (PPN)) automatically generated volumetric modulated arc therapy plans (VMATAuto) were compared against plans created by expert dosimetrists under clinical conditions (VMATClinical) and no time pressures (VMATIdeal). Plans were compared through quantitative comparison of dosimetric parameters and blind review by an oncologist. RESULTS Upon blind review 39/40 and 33/40 VMATAuto plans were considered preferable or equal to VMATClinical and VMATIdeal respectively, with all deemed clinically acceptable. Dosimetrically, VMATAuto, VMATClinical and VMATIdeal were similar, with observed differences generally of low clinical significance. Compared to VMATClinical, VMATAuto reduced hands-on planning time by 94% and 79% for PSV and PPN respectively. Total planning time was significantly reduced from 22.2 mins to 14.0 mins for PSV, with no significant reduction observed for PPN. CONCLUSIONS A novel automated planning solution has been evaluated, whose Pareto navigation based calibration enabled clinical decision-making on trade-off balancing to be intuitively incorporated into automated protocols. It was successfully applied to two sites of differing complexity and robustly generated high quality plans in an efficient manner.
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Affiliation(s)
- Philip A Wheeler
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom.
| | - Michael Chu
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
| | - Rosemary Holmes
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
| | - Owain W Woodley
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
| | - Ceri S Jones
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
| | - Rhydian Maggs
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
| | - John Staffurth
- School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Nachi Palaniappan
- Department of Oncology, Velindre Cancer Centre, Cardiff, United Kingdom
| | - Emiliano Spezi
- School of Engineering, Cardiff University, Cardiff, United Kingdom
| | - David G Lewis
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
| | | | | | - Anthony E Millin
- Department of Medical Physics, Velindre Cancer Centre, Cardiff, United Kingdom
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16
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Wheeler PA, Chu M, Holmes R, Smyth M, Maggs R, Spezi E, Staffurth J, Lewis DG, Millin AE. Utilisation of Pareto navigation techniques to calibrate a fully automated radiotherapy treatment planning solution. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2019; 10:41-48. [PMID: 33458267 PMCID: PMC7807535 DOI: 10.1016/j.phro.2019.04.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 04/10/2019] [Accepted: 04/14/2019] [Indexed: 12/19/2022]
Abstract
Background and purpose Current automated radiotherapy planning solutions do not allow for the intuitive exploration of different treatment options during protocol calibration. This work introduces an automated planning solution, which aims to address this problem through incorporating Pareto navigation techniques into the calibration process. Materials and methods For each tumour site a set of planning goals is defined. Utilising Pareto navigation techniques an operator calibrates the solution through intuitively exploring different treatment options: selecting the optimum balancing of competing planning goals for the given site. Once calibrated, fully automated plan generation is possible, with specific algorithms implemented to ensure trade-off balancing of new patients is consistent with that during calibration. Using the proposed methodology the system was calibrated for prostate and seminal vesicle treatments. The resultant solution was validated through quantitatively comparing the dose distribution of automatically generated plans (VMATAuto) against the previous clinical plan, for ten randomly selected patients. Results VMATAuto yielded statistically significant improvements in: PTV conformity indices, high dose bladder metrics, mean bowel dose, and the majority of rectum dose metrics. Of particular note was the reduction in mean rectum dose (median 25.1 Gy vs. 27.5 Gy), rectum V24.3Gy (median 41.1% vs. 46.4%), and improvement in the conformity index for the primary PTV (median 0.86 vs. 0.79). Dosimetric improvements were not at the cost of other dose metrics. Conclusions An automated planning methodology with a Pareto navigation based calibration has been developed, which enables the complex balancing of competing trade-offs to be intuitively incorporated into automated protocols.
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Affiliation(s)
- Philip A Wheeler
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Michael Chu
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Rosemary Holmes
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Maeve Smyth
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Rhydian Maggs
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Emiliano Spezi
- Cardiff University, School of Engineering, Cardiff, United Kingdom
| | - John Staffurth
- Cardiff University, School of Medicine, Cardiff, United Kingdom
| | - David G Lewis
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
| | - Anthony E Millin
- Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom
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17
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Hussein M, Heijmen BJM, Verellen D, Nisbet A. Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations. Br J Radiol 2018; 91:20180270. [PMID: 30074813 DOI: 10.1259/bjr.20180270] [Citation(s) in RCA: 142] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Radiotherapy treatment planning of complex radiotherapy techniques, such as intensity modulated radiotherapy and volumetric modulated arc therapy, is a resource-intensive process requiring a high level of treatment planner intervention to ensure high plan quality. This can lead to variability in the quality of treatment plans and the efficiency in which plans are produced, depending on the skills and experience of the operator and available planning time. Within the last few years, there has been significant progress in the research and development of intensity modulated radiotherapy treatment planning approaches with automation support, with most commercial manufacturers now offering some form of solution. There is a rapidly growing number of research articles published in the scientific literature on the topic. This paper critically reviews the body of publications up to April 2018. The review describes the different types of automation algorithms, including the advantages and current limitations. Also included is a discussion on the potential issues with routine clinical implementation of such software, and highlights areas for future research.
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Affiliation(s)
- Mohammad Hussein
- 1 Metrology for Medical Physics Centre, National Physical Laboratory , Teddington , UK
| | - Ben J M Heijmen
- 2 Division of Medical Physics, Erasmus MC Cancer Institute , Rotterdam , The Netherlands
| | - Dirk Verellen
- 3 Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB) , Brussels , Belgium.,4 Radiotherapy Department, Iridium Kankernetwerk , Antwerp , Belgium
| | - Andrew Nisbet
- 5 Department of Medical Physics, Royal Surrey County Hospital NHS Foundation Trust , Guildford , UK.,6 Department of Physics, University of Surrey , Guildford , UK
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