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Rechner LA, Modiri A, Stick LB, Maraldo MV, Aznar MC, Rice SR, Sawant A, Bentzen SM, Vogelius IR, Specht L. Biological optimization for mediastinal lymphoma radiotherapy - a preliminary study. Acta Oncol 2020; 59:879-887. [PMID: 32216586 PMCID: PMC7446040 DOI: 10.1080/0284186x.2020.1733654] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 02/18/2020] [Indexed: 11/30/2022]
Abstract
Purpose: In current radiotherapy (RT) planning and delivery, population-based dose-volume constraints are used to limit the risk of toxicity from incidental irradiation of organs at risks (OARs). However, weighing tradeoffs between target coverage and doses to OARs (or prioritizing different OARs) in a quantitative way for each patient is challenging. We introduce a novel RT planning approach for patients with mediastinal Hodgkin lymphoma (HL) that aims to maximize overall outcome for each patient by optimizing on tumor control and mortality from late effects simultaneously.Material and Methods: We retrospectively analyzed 34 HL patients treated with conformal RT (3DCRT). We used published data to model recurrence and radiation-induced mortality from coronary heart disease and secondary lung and breast cancers. Patient-specific doses to the heart, lung, breast, and target were incorporated in the models as well as age, sex, and cardiac risk factors (CRFs). A preliminary plan of candidate beams was created for each patient in a commercial treatment planning system. From these candidate beams, outcome-optimized (O-OPT) plans for each patient were created with an in-house optimization code that minimized the individual risk of recurrence and mortality from late effects. O-OPT plans were compared to VMAT plans and clinical 3DCRT plans.Results: O-OPT plans generally had the lowest risk, followed by the clinical 3DCRT plans, then the VMAT plans with the highest risk with median (maximum) total risk values of 4.9 (11.1), 5.1 (17.7), and 7.6 (20.3)%, respectively (no CRFs). Compared to clinical 3DCRT plans, O-OPT planning reduced the total risk by at least 1% for 9/34 cases assuming no CRFs and 11/34 cases assuming presence of CRFs.Conclusions: We developed an individualized, outcome-optimized planning technique for HL. Some of the resulting plans were substantially different from clinical plans. The results varied depending on how risk models were defined or prioritized.
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Affiliation(s)
- Laura Ann Rechner
- Department of Oncology, Section of Radiotherapy, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Niels Bohr Institute, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Arezoo Modiri
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Line Bjerregaard Stick
- Department of Oncology, Section of Radiotherapy, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Niels Bohr Institute, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Maja V. Maraldo
- Department of Oncology, Section of Radiotherapy, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Marianne C. Aznar
- Manchester Cancer Research Centre, Division of Cancer Sciences, The University of Manchester, Manchester, UK
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, UK
| | | | - Amit Sawant
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Søren M. Bentzen
- Greenebaum Comprehensive Cancer Center, Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ivan Richter Vogelius
- Department of Oncology, Section of Radiotherapy, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Lena Specht
- Department of Oncology, Section of Radiotherapy, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
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Sparing of the Neural Stem Cell Compartment During Whole-Brain Radiation Therapy: A Dosimetric Study Using Helical Tomotherapy. Int J Radiat Oncol Biol Phys 2010; 78:946-54. [DOI: 10.1016/j.ijrobp.2009.12.012] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2009] [Revised: 11/05/2009] [Accepted: 12/02/2009] [Indexed: 11/17/2022]
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Kupchak C, Battista J, Van Dyk J. Experience-driven dose-volume histogram maps of NTCP risk as an aid for radiation treatment plan selection and optimization. Med Phys 2007; 35:333-43. [DOI: 10.1118/1.2815943] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Schinkel C, Stavrev P, Stavreva N, Fallone BG. A theoretical approach to the problem of dose-volume constraint estimation and their impact on the dose-volume histogram selection. Med Phys 2006; 33:3444-59. [PMID: 17022241 DOI: 10.1118/1.2237453] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
This paper outlines a theoretical approach to the problem of estimating and choosing dose-volume constraints. Following this approach, a method of choosing dose-volume constraints based on biological criteria is proposed. This method is called "reverse normal tissue complication probability (NTCP) mapping into dose-volume space" and may be used as a general guidance to the problem of dose-volume constraint estimation. Dose-volume histograms (DVHs) are randomly simulated, and those resulting in clinically acceptable levels of complication, such as NTCP of 5 +/- 0.5%, are selected and averaged producing a mean DVH that is proven to result in the same level of NTCP. The points from the averaged DVH are proposed to serve as physical dose-volume constraints. The population-based critical volume and Lyman NTCP models with parameter sets taken from literature sources were used for the NTCP estimation. The impact of the prescribed value of the maximum dose to the organ, D(max), on the averaged DVH and the dose-volume constraint points is investigated. Constraint points for 16 organs are calculated. The impact of the number of constraints to be fulfilled based on the likelihood that a DVH satisfying them will result in an acceptable NTCP is also investigated. It is theoretically proven that the radiation treatment optimization based on physical objective functions can sufficiently well restrict the dose to the organs at risk, resulting in sufficiently low NTCP values through the employment of several appropriate dose-volume constraints. At the same time, the pure physical approach to optimization is self-restrictive due to the preassignment of acceptable NTCP levels thus excluding possible better solutions to the problem.
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Affiliation(s)
- Colleen Schinkel
- Department of Physics, University of Alberta, and Department of Medical Physics, Cross Cancer Institute, 11560 University Avenue, Edmonton, Alberta, T6G1Z2, Canada
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