1
|
Chang C, Bohannon D, Tian Z, Wang Y, Mcdonald MW, Yu DS, Liu T, Zhou J, Yang X. A retrospective study on the investigation of potential dosimetric benefits of online adaptive proton therapy for head and neck cancer. J Appl Clin Med Phys 2024; 25:e14308. [PMID: 38368614 PMCID: PMC11087169 DOI: 10.1002/acm2.14308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 10/28/2023] [Accepted: 02/06/2024] [Indexed: 02/20/2024] Open
Abstract
PURPOSE Proton therapy is sensitive to anatomical changes, often occurring in head-and-neck (HN) cancer patients. Although multiple studies have proposed online adaptive proton therapy (APT), there is still a concern in the radiotherapy community about the necessity of online APT. We have performed a retrospective study to investigate the potential dosimetric benefits of online APT for HN patients relative to the current offline APT. METHODS Our retrospective study has a patient cohort of 10 cases. To mimic online APT, we re-evaluated the dose of the in-use treatment plan on patients' actual treatment anatomy captured by cone-beam CT (CBCT) for each fraction and performed a templated-based automatic replanning if needed, assuming that these were performed online before treatment delivery. Cumulative dose of the simulated online APT course was calculated and compared with that of the actual offline APT course and the designed plan dose of the initial treatment plan (referred to as nominal plan). The ProKnow scoring system was employed and adapted for our study to quantify the actual quality of both courses against our planning goals. RESULTS The average score of the nominal plans over the 10 cases is 41.0, while those of the actual offline APT course and our simulated online course is 25.8 and 37.5, respectively. Compared to the offline APT course, our online course improved dose quality for all cases, with the score improvement ranging from 0.4 to 26.9 and an average improvement of 11.7. CONCLUSION The results of our retrospective study have demonstrated that online APT can better address anatomical changes for HN cancer patients than the current offline replanning practice. The advanced artificial intelligence based automatic replanning technology presents a promising avenue for extending potential benefits of online APT.
Collapse
Affiliation(s)
- Chih‐Wei Chang
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Duncan Bohannon
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Zhen Tian
- Department of Radiation and Cellular OncologyUniversity of ChicagoChicagoIllinoisUSA
| | - Yinan Wang
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Mark W. Mcdonald
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - David S. Yu
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Tian Liu
- Department of Radiation OncologyMount Sinai Medical CenterNew YorkNew YorkUSA
| | - Jun Zhou
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer InstituteEmory UniversityAtlantaGeorgiaUSA
| |
Collapse
|
2
|
Oud M, Breedveld S, Rojo-Santiago J, Giżyńska MK, Kroesen M, Habraken S, Perkó Z, Heijmen B, Hoogeman M. A fast and robust constraint-based online re-optimization approach for automated online adaptive intensity modulated proton therapy in head and neck cancer. Phys Med Biol 2024; 69:075007. [PMID: 38373350 DOI: 10.1088/1361-6560/ad2a98] [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: 09/21/2023] [Accepted: 02/19/2024] [Indexed: 02/21/2024]
Abstract
Objective. In head-and-neck cancer intensity modulated proton therapy, adaptive radiotherapy is currently restricted to offline re-planning, mitigating the effect of slow changes in patient anatomies. Daily online adaptations can potentially improve dosimetry. Here, a new, fully automated online re-optimization strategy is presented. In a retrospective study, this online re-optimization approach was compared to our trigger-based offline re-planning (offlineTBre-planning) schedule, including extensive robustness analyses.Approach. The online re-optimization method employs automated multi-criterial re-optimization, using robust optimization with 1 mm setup-robustness settings (in contrast to 3 mm for offlineTBre-planning). Hard planning constraints and spot addition are used to enforce adequate target coverage, avoid prohibitively large maximum doses and minimize organ-at-risk doses. For 67 repeat-CTs from 15 patients, fraction doses of the two strategies were compared for the CTVs and organs-at-risk. Per repeat-CT, 10.000 fractions with different setup and range robustness settings were simulated using polynomial chaos expansion for fast and accurate dose calculations.Main results. For 14/67 repeat-CTs, offlineTBre-planning resulted in <50% probability ofD98%≥ 95% of the prescribed dose (Dpres) in one or both CTVs, which never happened with online re-optimization. With offlineTBre-planning, eight repeat-CTs had zero probability of obtainingD98%≥ 95%Dpresfor CTV7000, while the minimum probability with online re-optimization was 81%. Risks of xerostomia and dysphagia grade ≥ II were reduced by 3.5 ± 1.7 and 3.9 ± 2.8 percentage point [mean ± SD] (p< 10-5for both). In online re-optimization, adjustment of spot configuration followed by spot-intensity re-optimization took 3.4 min on average.Significance. The fast online re-optimization strategy always prevented substantial losses of target coverage caused by day-to-day anatomical variations, as opposed to the clinical trigger-based offline re-planning schedule. On top of this, online re-optimization could be performed with smaller setup robustness settings, contributing to improved organs-at-risk sparing.
Collapse
Affiliation(s)
- Michelle Oud
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| | - Sebastiaan Breedveld
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
| | - Jesús Rojo-Santiago
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| | | | - Michiel Kroesen
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Radiation Oncology, Delft, The Netherlands
| | - Steven Habraken
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| | - Zoltán Perkó
- Delft University of Technology, Faculty of Applied Sciences, Department of Radiation Science and Technology, The Netherlands
| | - Ben Heijmen
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
| | - Mischa Hoogeman
- Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, The Netherlands
- HollandPTC, Department of Medical Physics & Informatics, Delft, The Netherlands
| |
Collapse
|
3
|
Lundberg M, Meijers A, Souris K, Deffet S, Weber DC, Lomax A, Knopf A. Technical note: development of a simulation framework, enabling the investigation of locally tuned single energy proton radiography. Biomed Phys Eng Express 2024; 10:027002. [PMID: 38241732 DOI: 10.1088/2057-1976/ad20a8] [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: 09/27/2023] [Accepted: 01/19/2024] [Indexed: 01/21/2024]
Abstract
Range uncertainties remain a limitation for the confined dose distribution that proton therapy can offer. The uncertainty stems from the ambiguity when translating CT Hounsfield Units (HU) into proton stopping powers. Proton Radiography (PR) can be used to verify the proton range. Specifically, PR can be used as a quality-control tool for CBCT-based synthetic CTs. An essential part of the work illustrating the potential of PR has been conducted using multi-layer ionization chamber (MLIC) detectors and mono-energetic PR. Due to the dimensions of commercially available MLICs, clinical adoption is cumbersome. Here, we present a simulation framework exploring locally-tuned single energy (LTSE) proton radiography and corresponding potential compact PR detector designs. Based on a planning CT data set, the presented framework models the water equivalent thickness. Subsequently, it analyses the proton energies required to pass through the geometry within a defined ROI. In the final step, an LTSE PR is simulated using the MCsquare Monte Carlo code. In an anatomical head phantom, we illustrate that LTSE PR allows for a significantly shorter longitudinal dimension of MLICs. We compared PR simulations for two exemplary 30 × 30 mm2proton fields passing the phantom at a 90° angle at an anterior and a posterior location in an iso-centric setup. The longitudinal distance over which all spots per field range out is significantly reduced for LTSE PR compared to mono-energetic PR. In addition, we illustrate the difference in shape of integral depth dose (IDD) when using constrained PR energies. Finally, we demonstrate the accordance of simulated and experimentally acquired IDDs for an LTSE PR acquisition. As the next steps, the framework will be used to investigate the sensitivity of LTSE PR to various sources of errors. Furthermore, we will use the framework to systematically explore the dimensions of an optimized MLIC design for daily clinical use.
Collapse
Affiliation(s)
- Måns Lundberg
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Arturs Meijers
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Kevin Souris
- Ion Beam Applications SA, Louvain-La-Neuve, Belgium
| | | | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Department of Radiation Oncology, University Hospital of Zürich, Zürich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Antony Lomax
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
- Department of Physics, ETH Zurich, Zurich, Switzerland
| | - Antje Knopf
- Institute for Medical Engineering and Medical Informatics, School of Life Science FHNW, Muttenz, Switzerland
| |
Collapse
|
4
|
Bobić M, Christensen JB, Lee H, Choulilitsa E, Czerska K, Togno M, Safai S, Yukihara EG, Winey BA, Lomax AJ, Paganetti H, Albertini F, Nesteruk KP. Optically stimulated luminescence dosimeters for simultaneous measurement of point dose and dose-weighted LET in an adaptive proton therapy workflow. Front Oncol 2024; 13:1333039. [PMID: 38510267 PMCID: PMC10951997 DOI: 10.3389/fonc.2023.1333039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 12/18/2023] [Indexed: 03/22/2024] Open
Abstract
Purpose To demonstrate the suitability of optically stimulated luminescence detectors (OSLDs) for accurate simultaneous measurement of the absolute point dose and dose-weighted linear energy transfer (LETD) in an anthropomorphic phantom for experimental validation of daily adaptive proton therapy. Methods A clinically realistic intensity-modulated proton therapy (IMPT) treatment plan was created based on a CT of an anthropomorphic head-and-neck phantom made of tissue-equivalent material. The IMPT plan was optimized with three fields to deliver a uniform dose to the target volume covering the OSLDs. Different scenarios representing inter-fractional anatomical changes were created by modifying the phantom. An online adaptive proton therapy workflow was used to recover the daily dose distribution and account for the applied geometry changes. To validate the adaptive workflow, measurements were performed by irradiating Al2O3:C OSLDs inside the phantom. In addition to the measurements, retrospective Monte Carlo simulations were performed to compare the absolute dose and dose-averaged LET (LETD) delivered to the OSLDs. Results The online adaptive proton therapy workflow was shown to recover significant degradation in dose conformity resulting from large anatomical and positioning deviations from the reference plan. The Monte Carlo simulations were in close agreement with the OSLD measurements, with an average relative error of 1.4% for doses and 3.2% for LETD. The use of OSLDs for LET determination allowed for a correction for the ionization quenched response. Conclusion The OSLDs appear to be an excellent detector for simultaneously assessing dose and LET distributions in proton irradiation of an anthropomorphic phantom. The OSLDs can be cut to almost any size and shape, making them ideal for in-phantom measurements to probe the radiation quality and dose in a predefined region of interest. Although we have presented the results obtained in the experimental validation of an adaptive proton therapy workflow, the same approach can be generalized and used for a variety of clinical innovations and workflow developments that require accurate assessment of point dose and/or average LET.
Collapse
Affiliation(s)
- Mislav Bobić
- Department of Physics, ETH Zurich, Zurich, Switzerland
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Hoyeon Lee
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Evangelia Choulilitsa
- Department of Physics, ETH Zurich, Zurich, Switzerland
- Paul Scherrer Institute, Villigen, Switzerland
| | | | | | | | | | - Brian A. Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Antony J. Lomax
- Department of Physics, ETH Zurich, Zurich, Switzerland
- Paul Scherrer Institute, Villigen, Switzerland
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | | | - Konrad P. Nesteruk
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| |
Collapse
|
5
|
Duetschler A, Winterhalter C, Meier G, Safai S, Weber DC, Lomax AJ, Zhang Y. A fast analytical dose calculation approach for MRI-guided proton therapy. Phys Med Biol 2023; 68:195020. [PMID: 37750045 DOI: 10.1088/1361-6560/acf90d] [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: 05/08/2023] [Accepted: 09/12/2023] [Indexed: 09/27/2023]
Abstract
Objective.Magnetic resonance (MR) is an innovative technology for online image guidance in conventional radiotherapy and is also starting to be considered for proton therapy as well. For MR-guided therapy, particularly for online plan adaptations, fast dose calculation is essential. Monte Carlo (MC) simulations, however, which are considered the gold standard for proton dose calculations, are very time-consuming. To address the need for an efficient dose calculation approach for MRI-guided proton therapy, we have developed a fast GPU-based modification of an analytical dose calculation algorithm incorporating beam deflections caused by magnetic fields.Approach.Proton beams (70-229 MeV) in orthogonal magnetic fields (0.5/1.5 T) were simulated using TOPAS-MC and central beam trajectories were extracted to generate look-up tables (LUTs) of incremental rotation angles as a function of water-equivalent depth. Beam trajectories are then reconstructed using these LUTs for the modified ray casting dose calculation. The algorithm was validated against MC in water, different materials and for four example patient cases, whereby it has also been fully incorporated into a treatment plan optimisation regime.Main results.Excellent agreement between analytical and MC dose distributions could be observed with sub-millimetre range deviations and differences in lateral shifts <2 mm even for high densities (1000 HU). 2%/2 mm gamma pass rates were comparable to the 0 T scenario and above 94.5% apart for the lung case. Further, comparable treatment plan quality could be achieved regardless of magnetic field strength.Significance.A new method for accurate and fast proton dose calculation in magnetic fields has been developed and successfully implemented for treatment plan optimisation.
Collapse
Affiliation(s)
- Alisha Duetschler
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
- Department of Physics, ETH Zürich, 8092 Zürich, CH, Switzerland
| | - Carla Winterhalter
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
| | - Gabriel Meier
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
| | - Sairos Safai
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
| | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
- Department of Radiation Oncology, University Hospital of Zürich, 8091 Zürich, CH, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, CH, Switzerland
| | - Antony J Lomax
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
- Department of Physics, ETH Zürich, 8092 Zürich, CH, Switzerland
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, 5232 Villigen PSI, CH, Switzerland
| |
Collapse
|
6
|
Smolders A, Choulilitsa E, Czerska K, Bizzocchi N, Krcek R, Lomax A, Weber DC, Albertini F. Dosimetric comparison of autocontouring techniques for online adaptive proton therapy. Phys Med Biol 2023; 68:175006. [PMID: 37385266 DOI: 10.1088/1361-6560/ace307] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 06/29/2023] [Indexed: 07/01/2023]
Abstract
Objective.Anatomical and daily set-up uncertainties impede high precision delivery of proton therapy. With online adaptation, the daily plan is reoptimized on an image taken shortly before the treatment, reducing these uncertainties and, hence, allowing a more accurate delivery. This reoptimization requires target and organs-at-risk (OAR) contours on the daily image, which need to be delineated automatically since manual contouring is too slow. Whereas multiple methods for autocontouring exist, none of them are fully accurate, which affects the daily dose. This work aims to quantify the magnitude of this dosimetric effect for four contouring techniques.Approach.Plans reoptimized on automatic contours are compared with plans reoptimized on manual contours. The methods include rigid and deformable registration (DIR), deep-learning based segmentation and patient-specific segmentation.Main results.It was found that independently of the contouring method, the dosimetric influence of usingautomaticOARcontoursis small (<5% prescribed dose in most cases), with DIR yielding the best results. Contrarily, the dosimetric effect of using theautomatic target contourwas larger (>5% prescribed dose in most cases), indicating that manual verification of that contour remains necessary. However, when compared to non-adaptive therapy, the dose differences caused by automatically contouring the target were small and target coverage was improved, especially for DIR.Significance.The results show that manual adjustment of OARs is rarely necessary and that several autocontouring techniques are directly usable. Contrarily, manual adjustment of the target is important. This allows prioritizing tasks during time-critical online adaptive proton therapy and therefore supports its further clinical implementation.
Collapse
Affiliation(s)
- A Smolders
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - E Choulilitsa
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - K Czerska
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| | - N Bizzocchi
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| | - R Krcek
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - A Lomax
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Physics, ETH Zurich, Switzerland
| | - D C Weber
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
- Department of Radiation Oncology, University Hospital Zurich, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Switzerland
| | - F Albertini
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
| |
Collapse
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
Bertschi S, Stützer K, Berthold J, Pietsch J, Smeets J, Janssens G, Richter C. Potential margin reduction in prostate cancer proton therapy with prompt gamma imaging for online treatment verification. Phys Imaging Radiat Oncol 2023; 26:100447. [PMID: 37287850 PMCID: PMC10242552 DOI: 10.1016/j.phro.2023.100447] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/06/2023] [Accepted: 05/09/2023] [Indexed: 06/09/2023] Open
Abstract
The potential of proton therapy is currently limited due to large safety margins. We estimated the potential reduction of clinical margins when using prompt gamma imaging (PGI) for online treatment verification of prostate cancer. For two adaptive scenarios a potential reduction relative to clinical practice was evaluated. The use of a trolley-mounted PGI system for online treatment verification to trigger an adaptation reduced the current range margins from 7 mm to 3 mm. In a case example, the dose reduction due to reduced range margins was substantially larger compared to reduced setup margins when using pre-treatment volumetric imaging.
Collapse
Affiliation(s)
- Stefanie Bertschi
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Fetscherstr. 74, PF41, 01307 Dresden, 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, Fetscherstr. 74, PF41, 01307 Dresden, Germany
| | - Jonathan Berthold
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Fetscherstr. 74, PF41, 01307 Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Bautzner Landstr. 400, 01328 Dresden, Germany
| | - Julian Pietsch
- OncoRay – National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden – Rossendorf, Fetscherstr. 74, PF41, 01307 Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Bautzner Landstr. 400, 01328 Dresden, Germany
| | - Julien Smeets
- Ion Beam Applications SA, Chemin du Cyclotron 3, 1348 Louvain-la-Neuve, Belgium
| | - Guillaume Janssens
- Ion Beam Applications SA, Chemin du Cyclotron 3, 1348 Louvain-la-Neuve, Belgium
| | - 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, Fetscherstr. 74, PF41, 01307 Dresden, Germany
- Helmholtz-Zentrum Dresden – Rossendorf, Institute of Radiooncology – OncoRay, Bautzner Landstr. 400, 01328 Dresden, Germany
- German Cancer Consortium (DKTK), Partner Site Dresden, and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69192 Heidelberg, Germany
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, PF 50, 01307 Dresden, Germany
| |
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Bobić M, Lalonde A, Nesteruk KP, Lee H, Nenoff L, Gorissen BL, Bertolet A, Busse PM, Chan AW, Winey BA, Sharp GC, Verburg JM, Lomax AJ, Paganetti H. Large anatomical changes in head-and-neck cancers – a dosimetric comparison of online and offline adaptive proton therapy. Clin Transl Radiat Oncol 2023; 40:100625. [PMID: 37090849 PMCID: PMC10120292 DOI: 10.1016/j.ctro.2023.100625] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 04/03/2023] Open
Abstract
Purpose This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.
Collapse
|
11
|
Nesteruk KP, Bobić M, Sharp GC, Lalonde A, Winey BA, Nenoff L, Lomax AJ, Paganetti H. Low-Dose Computed Tomography Scanning Protocols for Online Adaptive Proton Therapy of Head-and-Neck Cancers. Cancers (Basel) 2022; 14:cancers14205155. [PMID: 36291939 PMCID: PMC9600085 DOI: 10.3390/cancers14205155] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/15/2022] [Accepted: 10/19/2022] [Indexed: 01/11/2023] Open
Abstract
PURPOSE To evaluate the suitability of low-dose CT protocols for online plan adaptation of head-and-neck patients. METHODS We acquired CT scans of a head phantom with protocols corresponding to CT dose index volume CTDIvol in the range of 4.2-165.9 mGy. The highest value corresponds to the standard protocol used for CT simulations of 10 head-and-neck patients included in the study. The minimum value corresponds to the lowest achievable tube current of the GE Discovery RT scanner used for the study. For each patient and each low-dose protocol, the noise relative to the standard protocol, derived from phantom images, was applied to a virtual CT (vCT). The vCT was obtained from a daily CBCT scan corresponding to the fraction with the largest anatomical changes. We ran an established adaptive workflow twice for each low-dose protocol using a high-quality daily vCT and the corresponding low-dose synthetic vCT. For a relative comparison of the adaptation efficacy, two adapted plans were recalculated in the high-quality vCT and evaluated with the contours obtained through deformable registration of the planning CT. We also evaluated the accuracy of dose calculation in low-dose CT volumes using the standard CT protocol as reference. RESULTS The maximum differences in D98 between low-dose protocols and the standard protocol for the high-risk and low-risk CTV were found to be 0.6% and 0.3%, respectively. The difference in OAR sparing was up to 3%. The Dice similarity coefficient between propagated contours obtained with low-dose and standard protocols was above 0.982. The mean 2%/2 mm gamma pass rate for the lowest-dose image, using the standard protocol as reference, was found to be 99.99%. CONCLUSION The differences between low-dose protocols and the standard scanning protocol were marginal. Thus, low-dose CT protocols are suitable for online adaptive proton therapy of head-and-neck cancers. As such, considering scanning protocols used in our clinic, the imaging dose associated with online adaption of head-and-neck cancers treated with protons can be reduced by a factor of 40.
Collapse
Affiliation(s)
- Konrad P. Nesteruk
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Correspondence:
| | - Mislav Bobić
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland
| | - Gregory C. Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Arthur Lalonde
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Brian A. Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Lena Nenoff
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Antony J. Lomax
- Department of Physics, ETH Zurich, CH-8093 Zurich, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, CH-5232 Villigen, Switzerland
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| |
Collapse
|
12
|
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.
Collapse
|
13
|
Nenoff L, Buti G, Bobić M, Lalonde A, Nesteruk KP, Winey B, Sharp GC, Sudhyadhom A, Paganetti H. Integrating Structure Propagation Uncertainties in the Optimization of Online Adaptive Proton Therapy Plans. Cancers (Basel) 2022; 14:cancers14163926. [PMID: 36010919 PMCID: PMC9406068 DOI: 10.3390/cancers14163926] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 08/10/2022] [Accepted: 08/12/2022] [Indexed: 01/11/2023] Open
Abstract
Currently, adaptive strategies require time- and resource-intensive manual structure corrections. This study compares different strategies: optimization without manual structure correction, adaptation with physician-drawn structures, and no adaptation. Strategies were compared for 16 patients with pancreas, liver, and head and neck (HN) cancer with 1-5 repeated images during treatment: 'reference adaptation', with structures drawn by a physician; 'single-DIR adaptation', using a single set of deformably propagated structures; 'multi-DIR adaptation', using robust planning with multiple deformed structure sets; 'conservative adaptation', using the intersection and union of all deformed structures; 'probabilistic adaptation', using the probability of a voxel belonging to the structure in the optimization weight; and 'no adaptation'. Plans were evaluated using reference structures and compared using a scoring system. The reference adaptation with physician-drawn structures performed best, and no adaptation performed the worst. For pancreas and liver patients, adaptation with a single DIR improved the plan quality over no adaptation. For HN patients, integrating structure uncertainties brought an additional benefit. If resources for manual structure corrections would prevent online adaptation, manual correction could be replaced by a fast 'plausibility check', and plans could be adapted with correction-free adaptation strategies. Including structure uncertainties in the optimization has the potential to make online adaptation more automatable.
Collapse
Affiliation(s)
- Lena Nenoff
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
- Correspondence:
| | - Gregory Buti
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
- Center of Molecular Imaging, Radiotherapy and Oncology (MIRO), Institute of Experimental and Clinical Research (IREC), Université Catholique de Louvain, 1200 Brussels, Belgium
| | - Mislav Bobić
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Physics, ETH Zurich, 8092 Zurich, Switzerland
| | - Arthur Lalonde
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Konrad P. Nesteruk
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Brian Winey
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Gregory Charles Sharp
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Atchar Sudhyadhom
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Harald Paganetti
- Harvard Medical School, Boston, MA 02115, USA
- Department of Radiation Oncology, Physics Division, Massachusetts General Hospital, Boston, MA 02114, USA
| |
Collapse
|
14
|
Feng H, Patel SH, Wong WW, Younkin JE, Penoncello GP, Morales DH, Stoker JB, Robertson DG, Fatyga M, Bues M, Schild SE, Foote RL, Liu W. GPU-accelerated Monte Carlo-based online adaptive proton therapy - a feasibility study. Med Phys 2022; 49:3550-3563. [PMID: 35443080 DOI: 10.1002/mp.15678] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/21/2022] [Accepted: 04/12/2022] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To develop an online Graphic-Processing-Unit (GPU)-accelerated Monte-Carlo-based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address inter-fraction anatomical changes in patients treated with PBS. METHODS AND MATERIALS A four-step workflow was developed using our in-house developed GPU-accelerated Monte-Carlo-based treatment planning system to implement online Monte-Carlo-based ART for PBS. The first step conducts diffeomorphic demon-based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a re-optimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the re-opotimized plan in the third step. The fourth step involves a two-stage (before and after delivery) patient specific quality assurance (PSQA) of the re-optimized plan. The before-delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open-source Monte Carlo code, MCsquare. The after-delivery PSQA is to compare the plan dose to the dose re-calculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), Dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from re-optimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS. RESULTS For all three patients, the propagated contours were found to have good volume conformance [JI (lowest-highest: 0.833-0.983) and DSC (0.909-0.992)] but sub-optimal boundary coincidence [HD (2.37-20.76 mm)] for organs at risk (OARs). The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the inter-fractional anatomical changes. Re-optimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 seconds, excluding the time for manual intervention. CONCLUSION The proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a re-optimized plan that significantly improved the plan quality. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Hongying Feng
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - Samir H Patel
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - William W Wong
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - James E Younkin
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | | | | | - Joshua B Stoker
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | | | - Mirek Fatyga
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - Martin Bues
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - Steven E Schild
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - Robert L Foote
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Wei Liu
- Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, 85054, USA
| |
Collapse
|