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Hegarty S, Hardcastle N, Korte J, Kron T, Everitt S, Rahim S, Hegi-Johnson F, Franich R. Please Place Your Seat in the Full Upright Position: A Technical Framework for Landing Upright Radiation Therapy in the 21 st Century. Front Oncol 2022; 12:821887. [PMID: 35311128 PMCID: PMC8929673 DOI: 10.3389/fonc.2022.821887] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 01/27/2022] [Indexed: 12/20/2022] Open
Abstract
Delivering radiotherapy to patients in an upright position can allow for increased patient comfort, reduction in normal tissue irradiation, or reduction of machine size and complexity. This paper gives an overview of the requirements for the delivery of contemporary arc and modulated radiation therapy to upright patients. We explore i) patient positioning and immobilization, ii) simulation imaging, iii) treatment planning and iv) online setup and image guidance. Treatment chairs have been designed to reproducibly position seated patients for treatment and can be augmented by several existing immobilisation systems or promising emerging technologies such as soft robotics. There are few solutions for acquiring CT images for upright patients, however, cone beam computed tomography (CBCT) scans of upright patients can be produced using the imaging capabilities of standard Linacs combined with an additional patient rotation device. While these images will require corrections to make them appropriate for treatment planning, several methods indicate the viability of this approach. Treatment planning is largely unchanged apart from translating gantry rotation to patient rotation, allowing for a fixed beam with a patient rotating relative to it. Rotation can be provided by a turntable during treatment delivery. Imaging the patient with the same machinery as used in treatment could be advantageous for online plan adaption. While the current focus is using clinical linacs in existing facilities, developments in this area could also extend to lower-cost and mobile linacs and heavy ion therapy.
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Affiliation(s)
- Sarah Hegarty
- School of Science, RMIT University, Melbourne, VIC, Australia.,Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia.,Sir Peter MacCallum Department of Oncology, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Parkville, VIC, Australia
| | - James Korte
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Department of Biomedical Engineering, School of Engineering, University of Melbourne, Melbourne, VIC, Australia
| | - Tomas Kron
- Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia.,Sir Peter MacCallum Department of Oncology, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Parkville, VIC, Australia
| | - Sarah Everitt
- Sir Peter MacCallum Department of Oncology, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Parkville, VIC, Australia.,Department of Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Sulman Rahim
- Department of Radiation Therapy, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Fiona Hegi-Johnson
- Sir Peter MacCallum Department of Oncology, Faculty of Medicine, Dentistry and Health Science, University of Melbourne, Parkville, VIC, Australia.,Department of Radiation Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Rick Franich
- School of Science, RMIT University, Melbourne, VIC, Australia.,Department of Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
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Piperdi H, Portal D, Neibart SS, Yue NJ, Jabbour SK, Reyhan M. Adaptive Radiation Therapy in the Treatment of Lung Cancer: An Overview of the Current State of the Field. Front Oncol 2021; 11:770382. [PMID: 34912715 PMCID: PMC8666420 DOI: 10.3389/fonc.2021.770382] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/09/2021] [Indexed: 12/25/2022] Open
Abstract
Lung cancer treatment is constantly evolving due to technological advances in the delivery of radiation therapy. Adaptive radiation therapy (ART) allows for modification of a treatment plan with the goal of improving the dose distribution to the patient due to anatomic or physiologic deviations from the initial simulation. The implementation of ART for lung cancer is widely varied with limited consensus on who to adapt, when to adapt, how to adapt, and what the actual benefits of adaptation are. ART for lung cancer presents significant challenges due to the nature of the moving target, tumor shrinkage, and complex dose accumulation because of plan adaptation. This article presents an overview of the current state of the field in ART for lung cancer, specifically, probing topics of: patient selection for the greatest benefit from adaptation, models which predict who and when to adapt plans, best timing for plan adaptation, optimized workflows for implementing ART including alternatives to re-simulation, the best radiation techniques for ART including magnetic resonance guided treatment, algorithms and quality assurance, and challenges and techniques for dose reconstruction. To date, the clinical workflow burden of ART is one of the major reasons limiting its widespread acceptance. However, the growing body of evidence demonstrates overwhelming support for reduced toxicity while improving tumor dose coverage by adapting plans mid-treatment, but this is offset by the limited knowledge about tumor control. Progress made in predictive modeling of on-treatment tumor shrinkage and toxicity, optimizing the timing of adaptation of the plan during the course of treatment, creating optimal workflows to minimize staffing burden, and utilizing deformable image registration represent ways the field is moving toward a more uniform implementation of ART.
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Affiliation(s)
- Huzaifa Piperdi
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
| | - Daniella Portal
- Rutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States
| | - Shane S. Neibart
- Rutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States
| | - Ning J. Yue
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
| | - Salma K. Jabbour
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
- Rutgers Robert Wood Johnson Medical School, Rutgers, The State of New Jersey University, Piscataway, NJ, United States
| | - Meral Reyhan
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
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Chen M, Yang J, Liao Z, Chen J, Xu C, He X, Zhang X, Zhu RX, Li H. Anatomic change over the course of treatment for non-small cell lung cancer patients and its impact on intensity-modulated radiation therapy and passive-scattering proton therapy deliveries. Radiat Oncol 2020; 15:55. [PMID: 32138753 PMCID: PMC7059279 DOI: 10.1186/s13014-020-01503-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 02/19/2020] [Indexed: 12/20/2022] Open
Abstract
Purpose To quantify tumor anatomic change of non-small cell lung cancer (NSCLC) patients given passive-scattering proton therapy (PSPT) and intensity-modulated radiation therapy (IMRT) through 6–7 weeks of treatment, and analyze the correlation between anatomic change and the need to adopt adaptive radiotherapy (ART). Materials and methods Weekly 4D CT sets of 32 patients (8/8 IMRT with/without ART, 8/8 PSPT with/without ART) acquired during treatment, were registered to the planning CT using an in-house developed deformable registration algorithm. The anatomic change was quantified as the mean variation of the region of interest (ROI) relative to the planning CT by averaging the magnitude of deformation vectors of all voxels within the ROI contour. Mean variations of GTV and CTV were compared between subgroups classified by ART status and treatment modality using the independent t-test. Logistic regression analysis was performed to clarify the effect of anatomic change on the probability of ART adoption. Results There was no significant difference (p = 0.679) for the time-averaged mean CTV variations from the planning CT between IMRT (7.61 ± 2.80 mm) and PSPT (7.21 ± 2.67 mm) patients. However, a significant difference (p = 0.001) was observed between ART (8.93 ± 2.19 mm) and non-ART (5.90 ± 2.33 mm) patients, when treatment modality was not considered. Mean CTV variation from the planning CT in all patients increases significantly (p < 0.001), with a changing rate of 1.77 mm per week. Findings for the GTV change was similar. The logistic regression model correctly predicted 71.9% of cases in ART adoption. The correlation is stronger in the PSPT group with a pseudo R2 value of 0.782, compared to that in the IMRT group (pseudo R2 = 0.182). Conclusion The magnitude of target volume variation over time could be greater than the usual treatment margin. Mean target volume variation from the planning position can be used to identify lung cancer patients that may need ART.
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Affiliation(s)
- Mei Chen
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.,Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Zhongxing Liao
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Jiayi Chen
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Cheng Xu
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaodong He
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaodong Zhang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ronald X Zhu
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Heng Li
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. .,Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
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