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Sterpin E, Widesott L, Poels K, Hoogeman M, Korevaar EW, Lowe M, Molinelli S, Fracchiolla F. Robustness evaluation of pencil beam scanning proton therapy treatment planning: A systematic review. Radiother Oncol 2024; 197:110365. [PMID: 38830538 DOI: 10.1016/j.radonc.2024.110365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 04/30/2024] [Accepted: 05/29/2024] [Indexed: 06/05/2024]
Abstract
Compared to conventional radiotherapy using X-rays, proton therapy, in principle, allows better conformity of the dose distribution to target volumes, at the cost of greater sensitivity to physical, anatomical, and positioning uncertainties. Robust planning, both in terms of plan optimization and evaluation, has gained high visibility in publications on the subject and is part of clinical practice in many centers. However, there is currently no consensus on the methods and parameters to be used for robust optimization or robustness evaluation. We propose to overcome this deficiency by following the modified Delphi consensus method. This method first requires a systematic review of the literature. We performed this review using the PubMed and Web Of Science databases, via two different experts. Potential conflicts were resolved by a third expert. We then explored the different methods before focusing on clinical studies that evaluate robustness on a significant number of patients. Many robustness assessment methods are proposed in the literature. Some are more successful than others and their implementation varies between centers. Moreover, they are not all statistically or mathematically equivalent. The most sophisticated and rigorous methods have seen more limited application due to the difficulty of their implementation and their lack of widespread availability.
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Affiliation(s)
- E Sterpin
- KU Leuven - Department of Oncology, Laboratory of Experimental Radiotherapy, Leuven, Belgium; UCLouvain - Institution de Recherche Expérimentale et Clinique, Center of Molecular Imaging Radiotherapy and Oncology (MIRO), Brussels, Belgium; Particle Therapy Interuniversity Center Leuven - PARTICLE, Leuven, Belgium.
| | - L Widesott
- Proton Therapy Center - UO Fisica Sanitaria, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
| | - K Poels
- Particle Therapy Interuniversity Center Leuven - PARTICLE, Leuven, Belgium; UZ Leuven, Department of Radiation Oncology, Leuven, Belgium
| | - M Hoogeman
- Erasmus Medical Center, Cancer Institute, Department of Radiotherapy, Rotterdam, the Netherlands; HollandPTC, Delft, the Netherlands
| | - E W Korevaar
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, the Netherlands
| | - M Lowe
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - S Molinelli
- Fondazione CNAO - Medical Physics Unit, Pavia, Italy
| | - F Fracchiolla
- Proton Therapy Center - UO Fisica Sanitaria, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
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Borderías-Villarroel E, Barragán-Montero A, Sterpin E. Time is NTCP: Should we maximize patient throughput or perform online adaptation on proton therapy systems? Radiother Oncol 2024; 198:110389. [PMID: 38885906 DOI: 10.1016/j.radonc.2024.110389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 06/12/2024] [Accepted: 06/14/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Compared to conventional radiotherapy (XT), proton therapy (PT) may improve normal tissue complication probabilities (NTCP). However, PT typically requires higher adaptation rates due to an increased sensitivity to anatomical changes. Systematic online adaptation may address this issue, but it requires additional replanning time, decreasing patient throughput. Therefore, less patients would benefit in such case from PT for a given machine capacity, with results in worse NTCP. AIM To investigate the trade-off between PT patient throughput and NTCP gain as a function of the time needed for adaptation. METHODS A retrospective database of 14 lung patients with two repeated 4DCTs was used to compare NTCP values between XT and PT for NTCP2ym (2-year mortality), NTCPdysphagia and NTCPpneumonitis. Four scenarios were considered for PT: no adaptation using clinical robustness parameters (4D robust optimization, 3 % range error and PTV-equivalent setup errors); systematic online adaptation with clinical robustness parameters; setup errors reduced to 4 mm and to 2 mm. Dose was accumulated on the planning CT. The number of patients treated with PT depended on the extra time needed for adaptation, assuming an 8-hours capacity (assuming 14 patients a day; thus minimum 34.2 min per treatment session if there is no or instantaneous adaptation). RESULTS Baseline NTCP gains (PT against XT without adaptation) equaled 6.9 %, 6.1 %, and 7.7 % for NTCP2ym, NTCPdysphagia and NTCPpneumonitis, respectively. Using instantaneous online adaptation and setup errors of 2 mm, the overall gains were then 10.7 %, 13.6 % and 12.4 %. Taking into account loss of capacity, 13.7 min was the maximum extra-time allowed to complete adaptation and maintain an advantage on all three metrics for the 2-mm setup error scenario. CONCLUSION This study highlights the critical importance of keeping short online adaptation times when using systems with limited capacity like PT.
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Affiliation(s)
- E Borderías-Villarroel
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology (MIRO) Laboratory, Brussels, Belgium
| | - A Barragán-Montero
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology (MIRO) Laboratory, Brussels, Belgium
| | - E Sterpin
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology (MIRO) Laboratory, Brussels, Belgium; KU Leuven, Department of Oncology, Laboratory of external radiotherapy, Leuven, Belgium; Particle Therapy Interuniversity Center Leuven - PARTICLE, Leuven, Belgium.
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3
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Knäusl B, Belotti G, Bertholet J, Daartz J, Flampouri S, Hoogeman M, Knopf AC, Lin H, Moerman A, Paganelli C, Rucinski A, Schulte R, Shimizu S, Stützer K, Zhang X, Zhang Y, Czerska K. A review of the clinical introduction of 4D particle therapy research concepts. Phys Imaging Radiat Oncol 2024; 29:100535. [PMID: 38298885 PMCID: PMC10828898 DOI: 10.1016/j.phro.2024.100535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/12/2023] [Accepted: 01/04/2024] [Indexed: 02/02/2024] Open
Abstract
Background and purpose Many 4D particle therapy research concepts have been recently translated into clinics, however, remaining substantial differences depend on the indication and institute-related aspects. This work aims to summarise current state-of-the-art 4D particle therapy technology and outline a roadmap for future research and developments. Material and methods This review focused on the clinical implementation of 4D approaches for imaging, treatment planning, delivery and evaluation based on the 2021 and 2022 4D Treatment Workshops for Particle Therapy as well as a review of the most recent surveys, guidelines and scientific papers dedicated to this topic. Results Available technological capabilities for motion surveillance and compensation determined the course of each 4D particle treatment. 4D motion management, delivery techniques and strategies including imaging were diverse and depended on many factors. These included aspects of motion amplitude, tumour location, as well as accelerator technology driving the necessity of centre-specific dosimetric validation. Novel methodologies for X-ray based image processing and MRI for real-time tumour tracking and motion management were shown to have a large potential for online and offline adaptation schemes compensating for potential anatomical changes over the treatment course. The latest research developments were dominated by particle imaging, artificial intelligence methods and FLASH adding another level of complexity but also opportunities in the context of 4D treatments. Conclusion This review showed that the rapid technological advances in radiation oncology together with the available intrafractional motion management and adaptive strategies paved the way towards clinical implementation.
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Affiliation(s)
- Barbara Knäusl
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Gabriele Belotti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Jenny Bertholet
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Juliane Daartz
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Mischa Hoogeman
- Department of Medical Physics & Informatics, HollandPTC, Delft, The Netherlands
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
| | - Antje C Knopf
- Institut für Medizintechnik und Medizininformatik Hochschule für Life Sciences FHNW, Muttenz, Switzerland
| | - Haibo Lin
- New York Proton Center, New York, NY, USA
| | - Astrid Moerman
- Department of Medical Physics & Informatics, HollandPTC, Delft, The Netherlands
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Antoni Rucinski
- Institute of Nuclear Physics Polish Academy of Sciences, PL-31342 Krakow, Poland
| | - Reinhard Schulte
- Division of Biomedical Engineering Sciences, School of Medicine, Loma Linda University
| | - Shing Shimizu
- Department of Carbon Ion Radiotherapy, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Kristin Stützer
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Dresden, Germany
| | - Xiaodong Zhang
- Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Katarzyna Czerska
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
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Roberfroid B, Barragán-Montero AM, Dechambre D, Sterpin E, Lee JA, Geets X. Comparison of Ethos template-based planning and AI-based dose prediction: General performance, patient optimality, and limitations. Phys Med 2023; 116:103178. [PMID: 38000099 DOI: 10.1016/j.ejmp.2023.103178] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 10/19/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
PURPOSE Ethos proposes a template-based automatic dose planning (Etb) for online adaptive radiotherapy. This study evaluates the general performance of Etb for prostate cancer, as well as the ability to generate patient-optimal plans, by comparing it with another state-of-the-art automatic planning method, i.e., deep learning dose prediction followed by dose mimicking (DP + DM). MATERIALS General performances and capability to produce patient-optimal plan were investigated through two studies: Study-S1 generated plans for 45 patients using our initial Ethos clinical goals template (EG_init), and compared them to manually generated plans (MG). For study-S2, 10 patients which showed poor performances at study-S1 were selected. S2 compared the quality of plans generated with four different methods: 1) Ethos initial template (EG_init_selected), 2) Ethos updated template-based on S1 results (EG_upd_selected), 3) DP + DM, and 4) MG plans. RESULTS EG_init plans showed satisfactory performance for dose level above 50 Gy: reported mean metrics differences (EG_init minus MG) never exceeded 0.6 %. However, lower dose levels showed loosely optimized metrics, mean differences for V30Gy to rectum and V20Gy to anal canal were of 6.6 % and 13.0 %. EG_init_selected showed amplified differences in V30Gy to rectum and V20Gy to anal canal: 8.5 % and 16.9 %, respectively. These dropped to 5.7 % and 11.5 % for EG_upd_selected plans but strongly increased V60Gy to rectum for 2 patients. DP + DM plans achieved differences of 3.4 % and 4.6 % without compromising any V60Gy. CONCLUSION General performances of Etb were satisfactory. However, optimizing with template of goals might be limiting for some complex cases. Over our test patients, DP + DM outperformed the Etb approach.
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Affiliation(s)
- Benjamin Roberfroid
- Université catholique de Louvain - Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium.
| | - Ana M Barragán-Montero
- Université catholique de Louvain - Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium
| | - David Dechambre
- Cliniques universitaires Saint-Luc, Department of Radiation Oncology, Brussels, Belgium
| | - Edmond Sterpin
- Université catholique de Louvain - Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium; Particle Therapy Interuniversity Center Leuven - PARTICLE, Leuven, Belgium; KU Leuven - Department of Oncology, Laboratory of Experimental Radiotherapy, Leuven, Belgium
| | - John A Lee
- Université catholique de Louvain - Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium
| | - Xavier Geets
- Université catholique de Louvain - Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium; Cliniques universitaires Saint-Luc, Department of Radiation Oncology, Brussels, Belgium
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Huet-Dastarac M, Michiels S, Rivas ST, Ozan H, Sterpin E, Lee JA, Barragan-Montero A. Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer. Med Phys 2023; 50:6201-6214. [PMID: 37140481 DOI: 10.1002/mp.16431] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 03/07/2023] [Accepted: 04/01/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND In cancer care, determining the most beneficial treatment technique is a key decision affecting the patient's survival and quality of life. Patient selection for proton therapy (PT) over conventional radiotherapy (XT) currently entails comparing manually generated treatment plans, which requires time and expertise. PURPOSE We developed an automatic and fast tool, AI-PROTIPP (Artificial Intelligence Predictive Radiation Oncology Treatment Indication to Photons/Protons), that assesses quantitatively the benefits of each therapeutic option. Our method uses deep learning (DL) models to directly predict the dose distributions for a given patient for both XT and PT. By using models that estimate the Normal Tissue Complication Probability (NTCP), namely the likelihood of side effects to occur for a specific patient, AI-PROTIPP can propose a treatment selection quickly and automatically. METHODS A database of 60 patients presenting oropharyngeal cancer, obtained from the Cliniques Universitaires Saint Luc in Belgium, was used in this study. For every patient, a PT plan and an XT plan were generated. The dose distributions were used to train the two dose DL prediction models (one for each modality). The model is based on U-Net architecture, a type of convolutional neural network currently considered as the state of the art for dose prediction models. A NTCP protocol used in the Dutch model-based approach, including grades II and III xerostomia and grades II and III dysphagia, was later applied in order to perform automatic treatment selection for each patient. The networks were trained using a nested cross-validation approach with 11-folds. We set aside three patients in an outer set and each fold consists of 47 patients in training, five in validation and five for testing. This method allowed us to assess our method on 55 patients (five patients per test times the number of folds). RESULTS The treatment selection based on the DL-predicted doses reached an accuracy of 87.4% for the threshold parameters set by the Health Council of the Netherlands. The selected treatment is directly linked with these threshold parameters as they express the minimal gain brought by the PT treatment for a patient to be indicated to PT. To validate the performance of AI-PROTIPP in other conditions, we modulated these thresholds, and the accuracy was above 81% for all the considered cases. The difference in average cumulative NTCP per patient of predicted and clinical dose distributions is very similar (less than 1% difference). CONCLUSIONS AI-PROTIPP shows that using DL dose prediction in combination with NTCP models to select PT for patients is feasible and can help to save time by avoiding the generation of treatment plans only used for the comparison. Moreover, DL models are transferable, allowing, in the future, experience to be shared with centers that would not have PT planning expertise.
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Affiliation(s)
| | - Steven Michiels
- Molecular Imaging, Radiotherapy and Oncology (MIRO), IREC, UCLouvain, Brussels, Belgium
| | - Sara Teruel Rivas
- Molecular Imaging, Radiotherapy and Oncology (MIRO), IREC, UCLouvain, Brussels, Belgium
| | - Hamdiye Ozan
- Molecular Imaging, Radiotherapy and Oncology (MIRO), IREC, UCLouvain, Brussels, Belgium
| | - Edmond Sterpin
- Molecular Imaging, Radiotherapy and Oncology (MIRO), IREC, UCLouvain, Brussels, Belgium
- Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven, Leuven, Belgium
| | - John A Lee
- Molecular Imaging, Radiotherapy and Oncology (MIRO), IREC, UCLouvain, Brussels, Belgium
| | - Ana Barragan-Montero
- Molecular Imaging, Radiotherapy and Oncology (MIRO), IREC, UCLouvain, Brussels, Belgium
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Schmitz H, Rabe M, Janssens G, Rit S, Parodi K, Belka C, Kamp F, Landry G, Kurz C. Scatter correction of 4D cone beam computed tomography to detect dosimetric effects due to anatomical changes in proton therapy for lung cancer. Med Phys 2023; 50:4981-4992. [PMID: 36847184 DOI: 10.1002/mp.16335] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 02/01/2023] [Accepted: 02/14/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND The treatment of moving tumor entities is expected to have superior clinical outcomes, using image-guided adaptive intensity-modulated proton therapy (IMPT). PURPOSE For 21 lung cancer patients, IMPT dose calculations were performed on scatter-corrected 4D cone beam CTs (4DCBCTcor ) to evaluate their potential for triggering treatment adaptation. Additional dose calculations were performed on corresponding planning 4DCTs and day-of-treatment 4D virtual CTs (4DvCTs). METHODS A 4DCBCT correction workflow, previously validated on a phantom, generates 4DvCT (CT-to-CBCT deformable registration) and 4DCBCTcor images (projection-based correction using 4DvCT as a prior) with 10 phase bins, using day-of-treatment free-breathing CBCT projections and planning 4DCT images as input. Using a research planning system, robust IMPT plans administering eight fractions of 7.5 Gy were created on a free-breathing planning CT (pCT) contoured by a physician. The internal target volume (ITV) was overridden with muscle tissue. Robustness settings for range and setup uncertainties were 3% and 6 mm, and a Monte Carlo dose engine was used. On every phase of planning 4DCT, day-of-treatment 4DvCT, and 4DCBCTcor , the dose was recalculated. For evaluation, image analysis as well as dose analysis were performed using mean error (ME) and mean absolute error (MAE) analysis, dose-volume histogram (DVH) parameters, and 2%/2-mm gamma pass rate analysis. Action levels (1.6% ITV D98 and 90% gamma pass rate) based on our previous phantom validation study were set to determine which patients had a loss of dosimetric coverage. RESULTS Quality enhancements of 4DvCT and 4DCBCTcor over 4DCBCT were observed. ITV D98% and bronchi D2% had its largest agreement for 4DCBCTcor -4DvCT, and the largest gamma pass rates (>94%, median 98%) were found for 4DCBCTcor -4DvCT. Deviations were larger and gamma pass rates were smaller for 4DvCT-4DCT and 4DCBCTcor -4DCT. For five patients, deviations were larger than the action levels, suggesting substantial anatomical changes between pCT and CBCT projections acquisition. CONCLUSIONS This retrospective study shows the feasibility of daily proton dose calculation on 4DCBCTcor for lung tumor patients. The applied method is of clinical interest as it generates up-to-date in-room images, accounting for breathing motion and anatomical changes. This information could be used to trigger replanning.
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Affiliation(s)
- Henning Schmitz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Bavaria, Germany
| | - Moritz Rabe
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Bavaria, Germany
| | | | - Simon Rit
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69373, Lyon, France
| | - Katia Parodi
- Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Bavaria, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Bavaria, Germany
- Department of Radiation Oncology, University Hospital Cologne, Cologne, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Bavaria, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Bavaria, Germany
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Spautz S, Haase L, Tschiche M, Makocki S, Richter C, Troost EG, Stützer K. Comparison of 3D and 4D robustly optimized proton treatment plans for non-small cell lung cancer patients with tumour motion amplitudes larger than 5 mm. Phys Imaging Radiat Oncol 2023; 27:100465. [PMID: 37449022 PMCID: PMC10338142 DOI: 10.1016/j.phro.2023.100465] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 06/22/2023] [Accepted: 06/23/2023] [Indexed: 07/18/2023] Open
Abstract
Background and purpose There is no consensus about an ideal robust optimization (RO) strategy for proton therapy of targets with large intrafractional motion. We investigated the plan robustness of 3D and different 4D RO strategies. Materials and methods For eight non-small cell lung cancer patients with clinical target volume (CTV) motion >5 mm, different RO approaches were investigated: 3DRO considering the average CT (AvgCT) with a target density override, 4DRO considering three/all 4DCT phases, and 4DRO considering the AvgCT and three/all 4DCT phases. Robustness against setup/range errors, interplay effects based on breathing and machine log file data for deliveries with/without rescanning, and interfractional anatomical changes were analyzed for target coverage and OAR sparing. Results All nominal plans fulfilled the clinical requirements with individual CTV coverage differences <2pp; 4DRO without AvgCT generated the most conformal dose distributions. Robustness against setup/range errors was best for 4DRO with AvgCT (18% more passed error scenarios than 3DRO). Interplay effects caused fraction-wise median CTV coverage loss of 3pp and missed maximum dose constraints for heart and esophagus in 18% of scenarios. CTV coverage and OAR sparing fulfilled requirements in all cases when accumulating four interplay scenarios. Interfractional changes caused less target misses for RO with AvgCT compared to 4DRO without AvgCT (≤42%/33% vs. ≥56%/44% failed single/accumulated scenarios). Conclusions All RO strategies provided acceptable plans with equally low robustness against interplay effects demanding other mitigation than rescanning to ensure fraction-wise target coverage. 4DRO considering three phases and the AvgCT provided best compromise on planning effort and robustness.
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Affiliation(s)
- Saskia Spautz
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden, Rossendorf, Fetscherstraße 74, PF 41, 01307 Dresden, Germany
| | - Leon Haase
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden, Rossendorf, Fetscherstraße 74, PF 41, 01307 Dresden, Germany
| | - Maria Tschiche
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, PF 50, 01307 Dresden, Germany
| | - Sebastian Makocki
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, PF 50, 01307 Dresden, Germany
| | - Christian Richter
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden, Rossendorf, Fetscherstraße 74, PF 41, 01307 Dresden, Germany
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, PF 50, 01307 Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Bautzner Landstraße 400, 01328 Dresden, Germany
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69192 Heidelberg, Germany
| | - Esther G.C. Troost
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden, Rossendorf, Fetscherstraße 74, PF 41, 01307 Dresden, Germany
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstraße 74, PF 50, 01307 Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Bautzner Landstraße 400, 01328 Dresden, Germany
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69192 Heidelberg, Germany
- National Center for Tumor Diseases (NCT), Partner Site Dresden, Germany: German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany, and; Helmholtz Association / Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany; Im Neuenheimer Feld 280, 69192 Heidelberg, Germany
| | - Kristin Stützer
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden, Rossendorf, Fetscherstraße 74, PF 41, 01307 Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Bautzner Landstraße 400, 01328 Dresden, Germany
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Knäusl B, Taasti VT, Poulsen P, Muren LP. Surveying the clinical practice of treatment adaptation and motion management in particle therapy. Phys Imaging Radiat Oncol 2023; 27:100457. [PMID: 37361612 PMCID: PMC10285555 DOI: 10.1016/j.phro.2023.100457] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/28/2023] Open
Affiliation(s)
- Barbara Knäusl
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Vicki T Taasti
- Department of Radiation Oncology (Maastro), GROW - School for Oncology and Reproduction, Maastricht, University Medical Centre+, Maastricht, The Netherlands
| | - Per Poulsen
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
- Department of Oncology, Aarhus University, Aarhus, Denmark
| | - Ludvig P Muren
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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Taylor S, Lim P, Cantwell J, D’Souza D, Moinuddin S, Chang YC, Gaze MN, Gains J, Veiga C. Image guidance and interfractional anatomical variation in paediatric abdominal radiotherapy. Br J Radiol 2023; 96:20230058. [PMID: 37102707 PMCID: PMC10230397 DOI: 10.1259/bjr.20230058] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 04/28/2023] Open
Abstract
OBJECTIVES To identify variables predicting interfractional anatomical variations measured with cone-beam CT (CBCT) throughout abdominal paediatric radiotherapy, and to assess the potential of surface-guided radiotherapy (SGRT) to monitor these changes. METHODS Metrics of variation in gastrointestinal (GI) gas volume and separation of the body contour and abdominal wall were calculated from 21 planning CTs and 77 weekly CBCTs for 21 abdominal neuroblastoma patients (median 4 years, range: 2 - 19 years). Age, sex, feeding tubes, and general anaesthesia (GA) were explored as predictive variables for anatomical variation. Furthermore, GI gas variation was correlated with changes in body and abdominal wall separation, as well as simulated SGRT metrics of translational and rotational corrections between CT/CBCT. RESULTS GI gas volumes varied 74 ± 54 ml across all scans, while body and abdominal wall separation varied 2.0 ± 0.7 mm and 4.1 ± 1.5 mm from planning, respectively. Patients < 3.5 years (p = 0.04) and treated under GA (p < 0.01) experienced greater GI gas variation; GA was the strongest predictor in multivariate analysis (p < 0.01). Absence of feeding tubes was linked to greater body contour variation (p = 0.03). GI gas variation correlated with body (R = 0.53) and abdominal wall (R = 0.63) changes. The strongest correlations with SGRT metrics were found for anterior-posterior translation (R = 0.65) and rotation of the left-right axis (R = -0.36). CONCLUSIONS Young age, GA, and absence of feeding tubes were linked to stronger interfractional anatomical variation and are likely indicative of patients benefiting from adaptive/robust planning pathways. Our data suggest a role for SGRT to inform the need for CBCT at each treatment fraction in this patient group. ADVANCES IN KNOWLEDGE This is the first study to suggest the potential role of SGRT for the management of internal interfractional anatomical variation in paediatric abdominal radiotherapy.
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Affiliation(s)
- Sabrina Taylor
- University College London, Centre for Medical Image Computing, London, United Kingdom
| | - Pei Lim
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Jessica Cantwell
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Derek D’Souza
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Syed Moinuddin
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Yen-Ching Chang
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Mark N Gaze
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Jennifer Gains
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Catarina Veiga
- University College London, Centre for Medical Image Computing, London, United Kingdom
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10
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Qiu Z, Olberg S, den Hertog D, Ajdari A, Bortfeld T, Pursley J. Online adaptive planning methods for intensity-modulated radiotherapy. Phys Med Biol 2023; 68:10.1088/1361-6560/accdb2. [PMID: 37068488 PMCID: PMC10637515 DOI: 10.1088/1361-6560/accdb2] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/17/2023] [Indexed: 04/19/2023]
Abstract
Online adaptive radiation therapy aims at adapting a patient's treatment plan to their current anatomy to account for inter-fraction variations before daily treatment delivery. As this process needs to be accomplished while the patient is immobilized on the treatment couch, it requires time-efficient adaptive planning methods to generate a quality daily treatment plan rapidly. The conventional planning methods do not meet the time requirement of online adaptive radiation therapy because they often involve excessive human intervention, significantly prolonging the planning phase. This article reviews the planning strategies employed by current commercial online adaptive radiation therapy systems, research on online adaptive planning, and artificial intelligence's potential application to online adaptive planning.
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Affiliation(s)
- Zihang Qiu
- Department of Business Analytics, University of Amsterdam, The Netherlands
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Sven Olberg
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Dick den Hertog
- Department of Business Analytics, University of Amsterdam, The Netherlands
| | - Ali Ajdari
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Thomas Bortfeld
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
| | - Jennifer Pursley
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, United States of America
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11
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Trnkova P, Zhang Y, Toshito T, Heijmen B, Richter C, Aznar MC, Albertini F, Bolsi A, Daartz J, Knopf AC, Bertholet J. A survey of practice patterns for adaptive particle therapy for interfractional changes. Phys Imaging Radiat Oncol 2023; 26:100442. [PMID: 37197154 PMCID: PMC10183663 DOI: 10.1016/j.phro.2023.100442] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/22/2023] [Accepted: 04/24/2023] [Indexed: 05/19/2023] Open
Abstract
Background and purpose Anatomical changes may compromise the planned target coverage and organs-at-risk dose in particle therapy. This study reports on the practice patterns for adaptive particle therapy (APT) to evaluate current clinical practice and wishes and barriers to further implementation. Materials and methods An institutional questionnaire was distributed to PT centres worldwide (7/2020-6/2021) asking which type of APT was used, details of the workflow, and what the wishes and barriers to implementation were. Seventy centres from 17 countries participated. A three-round Delphi consensus analysis (10/2022) among the authors followed to define recommendations on required actions and future vision. Results Out of the 68 clinically operational centres, 84% were users of APT for at least one treatment site with head and neck being most common. APT was mostly performed offline with only two online APT users (plan-library). No centre used online daily re-planning. Daily 3D imaging was used for APT by 19% of users. Sixty-eight percent of users had plans to increase their use or change their technique for APT. The main barrier was "lack of integrated and efficient workflows". Automation and speed, reliable dose deformation for dose accumulation and higher quality of in-room volumetric imaging were identified as the most urgent task for clinical implementation of online daily APT. Conclusion Offline APT was implemented by the majority of PT centres. Joint efforts between industry research and clinics are needed to translate innovations into efficient and clinically feasible workflows for broad-scale implementation of online APT.
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Affiliation(s)
- Petra Trnkova
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
- Corresponding author.
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Toshiyuki Toshito
- Nagoya Proton Therapy Center, Nagoya City University West Medical Center, Nagoya, Japan
| | - Ben Heijmen
- Department of Radiotherapy, Erasmus University Medical Center (Erasmus MC), Rotterdam, the Netherlands
| | - Christian Richter
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Dresden, Germany
| | - Marianne C. Aznar
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | | | - Alessandra Bolsi
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Juliane Daartz
- Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, MA 02114, United States of America
| | - Antje C. Knopf
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
| | - Jenny Bertholet
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, Bern, Switzerland
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Miyazaki K, Fujii Y, Yamada T, Kanehira T, Miyamoto N, Matsuura T, Yasuda K, Uchinami Y, Otsuka M, Aoyama H, Takao S. Deformed dose restoration to account for tumor deformation and position changes for adaptive proton therapy. Med Phys 2023; 50:675-687. [PMID: 36502527 DOI: 10.1002/mp.16149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/10/2022] [Accepted: 11/25/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Online adaptation during intensity-modulated proton therapy (IMPT) can minimize the effect of inter-fractional anatomical changes, but remains challenging because of the complex workflow. One approach for fast and automated online IMPT adaptation is dose restoration, which restores the initial dose distribution on the updated anatomy. However, this method may fail in cases where tumor deformation or position changes occur. PURPOSE To develop a fast and robust IMPT online adaptation method named "deformed dose restoration (DDR)" that can adjust for inter-fractional tumor deformation and position changes. METHODS The DDR method comprises two steps: (1) calculation of the deformed dose distribution, and (2) restoration of the deformed dose distribution. First, the deformable image registration (DIR) between the initial clinical target volume (CTV) and the new CTV were performed to calculate the vector field. To ensure robustness for setup and range uncertainty and the ability to restore the deformed dose distribution, an expanded CTV-based registration to maintain the dose gradient outside the CTV was developed. The deformed dose distribution was obtained by applying the vector field to the initial dose distribution. Then, the voxel-by-voxel dose difference optimization was performed to calculate beam parameters that restore the deformed dose distribution on the updated anatomy. The optimization function was the sum of total dose differences and dose differences of each field to restore the initial dose overlap of each field. This method only requires target contouring, which eliminates the need for organs at risk (OARs) contouring. Six clinical cases wherein the tumor deformation and/or position changed on repeated CTs were selected. DDR feasibility was evaluated by comparing the results with those from three other strategies, namely, not adapted (continuing the initial plan), adapted by previous dose restoration, and fully optimized. RESULTS In all cases, continuing the initial plan was largely distorted on the repeated CTs and the dose-volume histogram (DVH) metrics for the target were reduced due to the tumor deformation or position changes. On the other hand, DDR improved DVH metrics for the target to the same level as the initial dose distribution. Dose increase was seen for some OARs because tumor growth had reduced the relative distance between CTVs and OARs. Robustness evaluation for setup and range uncertainty (3 mm/3.5%) showed that deviation in DVH-bandwidth for CTV D95% from the initial plan was 0.4% ± 0.5% (Mean ± S.D.) for DDR. The calculation time was 8.1 ± 6.4 min. CONCLUSIONS An online adaptation algorithm was developed that improved the treatment quality for inter-fractional anatomical changes and retained robustness for intra-fractional setup and range uncertainty. The main advantage of this method is that it only requires target contouring alone and saves the time for OARs contouring. The fast and robust adaptation method for tumor deformation and position changes described here can reduce the need for offline adaptation and improve treatment efficiency.
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Affiliation(s)
- Koichi Miyazaki
- Graduate School of Biomedical Science and Engineering, Hokkaido University, Sapporo, Hokkaido, Japan.,Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Research and Development Group, Hitachi Ltd, Hitachi, Ibaraki, Japan
| | - Yusuke Fujii
- Research and Development Group, Hitachi Ltd, Hitachi, Ibaraki, Japan
| | - Takahiro Yamada
- Research and Development Group, Hitachi Ltd, Hitachi, Ibaraki, Japan
| | - Takahiro Kanehira
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan
| | - Naoki Miyamoto
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Taeko Matsuura
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Koichi Yasuda
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Yusuke Uchinami
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Manami Otsuka
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Hidefumi Aoyama
- Department of Radiation Oncology, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
| | - Seishin Takao
- Department of Medical Physics, Hokkaido University Hospital, Sapporo, Hokkaido, Japan.,Division of Quantum Science and Engineering, Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan.,Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Hokkaido, Japan
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13
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Elhamiasl M, Salvo K, Poels K, Defraene G, Lambrecht M, Geets X, Sterpin E, Nuyts J. Low-dose CT allows for accurate proton therapy dose calculation and plan optimization. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac8dde] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 08/30/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective. Protons offer a more conformal dose delivery compared to photons, yet they are sensitive to anatomical changes over the course of treatment. To minimize range uncertainties due to anatomical variations, a new CT acquisition at every treatment session would be paramount to enable daily dose calculation and subsequent plan adaptation. However, the series of CT scans results in an additional accumulated patient dose. Reducing CT radiation dose and thereby decreasing the potential risk of radiation exposure to patients is desirable, however, lowering the CT dose results in a lower signal-to-noise ratio and therefore in a reduced quality image. We hypothesized that the signal-to-noise ratio provided by conventional CT protocols is higher than needed for proton dose distribution estimation. In this study, we aim to investigate the effect of CT imaging dose reduction on proton therapy dose calculations and plan optimization. Approach. To verify our hypothesis, a CT dose reduction simulation tool has been developed and validated to simulate lower-dose CT scans from an existing standard-dose scan. The simulated lower-dose CTs were then used for proton dose calculation and plan optimization and the results were compared with those of the standard-dose scan. The same strategy was adopted to investigate the effect of CT dose reduction on water equivalent thickness (WET) calculation to quantify CT noise accumulation during integration along the beam. Main results. The similarity between the dose distributions acquired from the low-dose and standard-dose CTs was evaluated by the dose-volume histogram and the 3D Gamma analysis. The results on an anthropomorphic head phantom and three patient cases indicate that CT imaging dose reduction up to 90% does not have a significant effect on proton dose calculation and plan optimization. The relative error was employed to evaluate the similarity between WET maps and was found to be less than 1% after reducing the CT imaging dose by 90%. Significance. The results suggest the possibility of using low-dose CT for proton therapy dose estimation, since the dose distributions acquired from the standard-dose and low-dose CTs are clinically equivalent.
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14
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Badiu V, Souris K, Buti G, Villarroel EB, Lambrecht M, Sterpin E. Improved healthy tissue sparing in proton therapy of lung tumors using statistically sound robust optimization and evaluation. Phys Med 2022; 96:62-69. [DOI: 10.1016/j.ejmp.2022.02.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 02/12/2022] [Accepted: 02/20/2022] [Indexed: 12/25/2022] Open
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15
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Borderías-Villarroel E, Taasti V, Van Elmpt W, Teruel-Rivas S, Geets X, Sterpin E. Evaluation of the clinical value of automatic online dose restoration for adaptive proton therapy of head and neck cancer. Radiother Oncol 2022; 170:190-197. [PMID: 35346754 DOI: 10.1016/j.radonc.2022.03.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 03/21/2022] [Accepted: 03/21/2022] [Indexed: 10/18/2022]
Abstract
INTRODUCTION Intensity modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. This study compares not-adapted (NA) robust plans to two adaptive IMPT methods - a fully-offline adaptive (FOA) and a simplified automatic online adaptive strategy (dose restoration (DR)) to determine the benefit of DR, in head and neck cancer (HNC). MATERIAL/METHODS Robustly optimized clinical IMPT doses in planning-CTs (pCTs) were available for a cohort of 10 HNC patients. During robust re-optimization, DR used isodose contours, generated from the clinical dose on pCTs, and patient specific objectives to reproduce the clinical dose in every repeated-CT(rCT). For each rCT(n=50), NA, DR and FOA plans were robustly evaluated. RESULTS An improvement in DVH-metrics and robustness was seen for DR and FOA plans compared to NA plans. For NA plans, 74%(37/50) of rCTs did not fulfill the CTV coverage criteria (D98%>95%Dprescription). DR improved target coverage, target homogeneity and variability on critical risk organs such as the spinal cord. After DR, 52%(26/50) of rCTs met all clinical goals. Because of large anatomical changes and/or inaccurate patient repositioning, 48%(24/50) of rCTs still needed full offline adaptation to ensure an optimal treatment since dose restoration was not able to re-establish the initial plan quality. CONCLUSION Robust optimization together with fully-automatized DR avoided offline adaptation in 52% of the cases. Implementation of dose restoration in clinical routine could ensure treatment plan optimality while saving valuable human and material resources to radiotherapy departments.
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Affiliation(s)
- Elena Borderías-Villarroel
- Molecular Imaging, Radiotherapy and Oncology (MIRO), UCLouvain, Brussels, Belgium. Avenue Hippocrate 54, Bte B1.54.07, 1200 Brussels, (Belgium).
| | - Vicki Taasti
- Department of Radiation Oncology (MAASTRO), GROW - School for Oncology, Maastricht University Medical Centre+, Doctor Tanslaan 12, 6229 ET Maastricht, (Netherlands).
| | - Wouter Van Elmpt
- Department of Radiation Oncology (MAASTRO), GROW - School for Oncology, Maastricht University Medical Centre+, Doctor Tanslaan 12, 6229 ET Maastricht, (Netherlands).
| | - S Teruel-Rivas
- Molecular Imaging, Radiotherapy and Oncology (MIRO), UCLouvain, Brussels, Belgium. Avenue Hippocrate 54, Bte B1.54.07, 1200 Brussels, (Belgium)
| | - X Geets
- Molecular Imaging, Radiotherapy and Oncology (MIRO), UCLouvain, Brussels, Belgium. Avenue Hippocrate 54, Bte B1.54.07, 1200 Brussels, (Belgium); Department of Radiation Oncology, Cliniques Universitaires Saint-Luc, Brussels, Belgium. Avenue Hippocrate 10, 1200 Brussels, (Belgium).
| | - E Sterpin
- Molecular Imaging, Radiotherapy and Oncology (MIRO), UCLouvain, Brussels, Belgium. Avenue Hippocrate 54, Bte B1.54.07, 1200 Brussels, (Belgium); Department of Oncology, Laboratory of Experimental Radiotherapy, KULeuven, Herestraat 49, 3000 Leuven, (Belgium).
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Choi MG, Law M, Djeng SK, Kim MS, Shin HB, Choe BY, Yoon DK, Suh TS. Daily adaptive proton therapy: Feasibility study of detection of tumor variations based on tomographic imaging of prompt gamma emission from proton–boron fusion reaction. NUCLEAR ENGINEERING AND TECHNOLOGY 2022. [DOI: 10.1016/j.net.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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17
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Jagt TZ, Breedveld S, Hoogeman MS. Evaluation of alternative parameter settings for dose restoration and full plan adaptation in IMPT for prostate cancer. Phys Med 2021; 92:15-23. [PMID: 34826710 DOI: 10.1016/j.ejmp.2021.11.003] [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: 05/06/2021] [Revised: 11/11/2021] [Accepted: 11/13/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND/PURPOSE Intensity-modulated proton therapy is highly sensitive to anatomical variations. A dose restoration method and a full plan adaptation method have been developed earlier, both requiring several parameter settings. This study evaluates the validity of the previously selected settings by systematically comparing them to alternatives. MATERIALS/METHODS The dose restoration method takes a prior plan and uses an energy-adaptation followed by a spot-intensity re-optimization to restore the plan to its initial state. The full adaptation method uses an energy-adaptation followed by the addition of new spots and a spot-intensity optimization to fit the new anatomy. We varied: 1) The margins and robustness settings of the prior plan, 2) the spot-addition sample size, i.e. the number of added spots, 3) the spot-addition stopping criterion, and 4) the spot-intensity optimization approach. The last three were evaluated only for the full plan adaptation. Evaluations were done on 88 CT scans of 11 prostate cancer patients. Dose was prescribed as 55 Gy(RBE) to the lymph nodes and seminal vesicles with a boost to 74 Gy(RBE) to the prostate. RESULTS For the dose restoration method, changing the applied CTV-to-PTV margins and plan robustness in the prior plans yielded insufficient target coverage or increased OAR doses. For the full plan adaptation, more spot-addition iterations and using a different optimization approach resulted in lower OAR doses compared to the default settings while maintaining target coverage. However, the calculation times increased by up to 20 times, making these variations infeasible for online-adaptation. CONCLUSION We recommend maintaining the default setting for the dose restoration approach. For the full plan adaptation we recommend to focus on fine-tuning the optimization-parameters, and apart from this using the default settings.
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Affiliation(s)
- Thyrza Z Jagt
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
| | - Sebastiaan Breedveld
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
| | - Mischa S Hoogeman
- Department of Radiotherapy, Erasmus MC Cancer Institute, Rotterdam, The Netherlands; Department of Medical Physics & Informatics, HollandPTC, Delft, The Netherlands.
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