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Parisi A, Furutani KM, Sato T, Beltran CJ. LET-based approximation of the microdosimetric kinetic model for proton radiotherapy. Med Phys 2024. [PMID: 39153222 DOI: 10.1002/mp.17337] [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: 04/26/2024] [Revised: 07/19/2024] [Accepted: 07/19/2024] [Indexed: 08/19/2024] Open
Abstract
BACKGROUND Phenomenological relative biological effectiveness (RBE) models for proton therapy, based on the dose-averaged linear energy transfer (LET), have been developed to address the apparent RBE increase towards the end of the proton range. The results of these phenomenological models substantially differ due to varying empirical assumptions and fitting functions. In contrast, more theory-based approaches are used in carbon ion radiotherapy, such as the microdosimetric kinetic model (MKM). However, implementing microdosimetry-based models in LET-based proton therapy treatment planning systems poses challenges. PURPOSE This work presents a LET-based version of the MKM that is practical for clinical use in proton radiotherapy. METHODS At first, we derived an approximation of the Mayo Clinic Florida (MCF) MKM for relatively-sparsely ionizing radiation such as protons. The mathematical formalism of the proposed model is equivalent to the original MKM, but it maintains some key features of the MCF MKM, such as the determination of model parameters from measurable cell characteristics. Subsequently, we carried out Monte Carlo calculations with PHITS in different simulated scenarios to establish a heuristic correlation between microdosimetric quantities and the dose averaged LET of protons. RESULTS A simple allometric function was found able to describe the relationship between the dose-averaged LET of protons and the dose-mean lineal energy, which includes the contributions of secondary particles. The LET-based MKM was used to model the in vitro clonogenic survival RBE of five human and rodent cell lines (A549, AG01522, CHO, T98G, and U87) exposed to pristine and spread-out Bragg peak (SOBP) proton beams. The results of the LET-based MKM agree well with the biological data in a comparable or better way with respect to the other models included in the study. A sensitivity analysis on the model results was also performed. CONCLUSIONS The LET-based MKM integrates the predictive theoretical framework of the MCF MKM with a straightforward mathematical description of the RBE based on the dose-averaged LET, a physical quantity readily available in modern treatment planning systems for proton therapy.
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Affiliation(s)
- Alessio Parisi
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
| | - Keith M Furutani
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
| | - Tatsuhiko Sato
- Nuclear Science and Engineering Center, Japan Atomic Energy Agency, Tokai, Ibaraki, Japan
- Research Center for Nuclear Physics, Osaka University, Suita, Osaka, Japan
| | - Chris J Beltran
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
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Kalholm F, Toma-Dasu I, Traneus E, Bassler N. Novel radiation quality metrics accounting for proton energy spectra for RBE proton models. Med Phys 2024; 51:5773-5782. [PMID: 38852194 DOI: 10.1002/mp.17236] [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: 12/22/2023] [Revised: 05/24/2024] [Accepted: 05/25/2024] [Indexed: 06/11/2024] Open
Abstract
BACKGROUND For proton therapy, a relative biological effectiveness (RBE) of 1.1 is widely applied clinically. However, due to abundant evidence of variable RBE in vitro, and as suggested in studies of patient outcomes, RBE might increase by the end of the proton tracks, as described by several proposed variable RBE models. Typically, the dose averaged linear energy transfer (LET d $\text{LET}_d$ ) has been used as a radiation quality metric (RQM) for these models. However, the optimal choice of RQM has not been fully explored. PURPOSE This study aims to propose novel RQMs that effectively weight protons of different energies, and assess their predictive power for variable RBE in proton therapy. The overall objective is to identify an RQM that better describes the contribution of individual particles to the RBE of proton beams. METHODS High-throughput experimental set-ups of in vitro cell survival studies for proton RBE determination are simulated utilizing the SHIELD-HIT12A Monte Carlo particle transport code. For every data point, the proton energy spectra are simulated, allowing the calculation of novel RQMs by applying different power levels to the spectra of LET or effective Q $Q$ (Q eff $Q_\mathrm{eff}$ ) values. A phenomenological linear-quadratic-based RBE model is then applied to the in vitro data, using various RQMs as input variables, and the model performance is evaluated by root-mean-square-error (RMSE) for the logarithm of cell surviving fractions of each data point. RESULTS Increasing the power level, that is, putting an even higher weight on higher LET particles when constructing the RQM is generally associated with an increased model performance, with dose averagedLET 3 $\text{LET}^3$ (i.e., dose averaged cubed LET,cLET d $\mathrm{cLET}_d$ ) resulting in a RMSE value 0.31, compared to 0.45 for a model based on (linearly weighted)LET d $\text{LET}_d$ , with similar trends also observed for track averaged andQ eff $Q_\mathrm{eff}$ -based RQMs. CONCLUSIONS The results indicate that improved proton variable RBE models can be constructed assuming a non-linear RBE(LET) relationship for individual protons. If similar trends hold also for an in vitro-environment, variable RBE effects are likely better described bycLET d $\mathrm{cLET}_d$ or tracked averaged cubed LET (cLET t $\mathrm{cLET}_t$ ), or correspondingQ eff $Q_\mathrm{eff}$ -based RQM, rather than linearly weightedLET d $\text{LET}_d$ orLET t $\text{LET}_t$ which is conventionally applied today.
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Affiliation(s)
- Fredrik Kalholm
- Medical Radiation Physics, Department of Physics, Stockholm University, Stockholm, Sweden
- Department of Oncology and Pathology, Medical Radiation Physics, Karolinska Institutet, Stockholm, Sweden
| | - Iuliana Toma-Dasu
- Medical Radiation Physics, Department of Physics, Stockholm University, Stockholm, Sweden
- Department of Oncology and Pathology, Medical Radiation Physics, Karolinska Institutet, Stockholm, Sweden
| | | | - Niels Bassler
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
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Waxer JF, Wong K, Modiri A, Charpentier AM, Moiseenko V, Ronckers CM, Taddei PJ, Constine LS, Sprow G, Tamrazi B, MacDonald S, Olch AJ. Risk of Cerebrovascular Events Among Childhood and Adolescent Patients Receiving Cranial Radiation Therapy: A PENTEC Normal Tissue Outcomes Comprehensive Review. Int J Radiat Oncol Biol Phys 2024; 119:417-430. [PMID: 36057476 DOI: 10.1016/j.ijrobp.2022.06.079] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 05/19/2022] [Accepted: 06/21/2022] [Indexed: 10/14/2022]
Abstract
PURPOSE Radiation-induced cerebrovascular toxicity is a well-documented sequelae that can be both life-altering and potentially fatal. We performed a meta-analysis of the relevant literature to create practical models for predicting the risk of cerebral vasculopathy after cranial irradiation. METHODS AND MATERIALS A literature search was performed for studies reporting pediatric radiation therapy (RT) associated cerebral vasculopathy. When available, we used individual patient RT doses delivered to the Circle of Willis (CW) or optic chiasm (as a surrogate), as reported or digitized from original publications, to formulate a dose-response. A logistic fit and a Normal Tissue Complication Probability (NTCP) model was developed to predict future risk of cerebrovascular toxicity and stroke, respectively. This NTCP risk was assessed as a function of prescribed dose. RESULTS The search identified 766 abstracts, 5 of which were used for modeling. We identified 101 of 3989 pediatric patients who experienced at least one cerebrovascular toxicity: transient ischemic attack, stroke, moyamoya, or arteriopathy. For a range of shorter follow-ups, as specified in the original publications (approximate attained ages of 17 years), our logistic fit model predicted the incidence of any cerebrovascular toxicity as a function of dose to the CW, or surrogate structure: 0.2% at 30 Gy, 1.3% at 45 Gy, and 4.4% at 54 Gy. At an attained age of 35 years, our NTCP model predicted a stroke incidence of 0.9% to 1.3%, 1.8% to 2.7%, and 2.8% to 4.1%, respectively at prescribed doses of 30 Gy, 45 Gy, and 54 Gy (compared with a baseline risk of 0.2%-0.3%). At an attained age of 45 years, the predicted incidence of stroke was 2.1% to 4.2%, 4.5% to 8.6%, and 6.7% to 13.0%, respectively at prescribed doses of 30 Gy, 45 Gy, and 54 Gy (compared with a baseline risk of 0.5%-1.0%). CONCLUSIONS Risk of cerebrovascular toxicity continues to increase with longer follow-up. NTCP stroke predictions are very sensitive to model variables (baseline stroke risk and proportional stroke hazard), both of which found in the literature may be systematically erring on minimization of true risk. We hope this information will assist practitioners in counseling, screening, surveilling, and facilitating risk reduction of RT-related cerebrovascular late effects in this highly sensitive population.
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Affiliation(s)
- Jonathan F Waxer
- Department of Radiation Oncology, Southern California Permanente Medical Group, Los Angeles, California
| | - Kenneth Wong
- Radiation Oncology Program, Children's Hospital Los Angeles/Keck School of Medicine of the University of Southern California, Los Angeles, California.
| | - Arezoo Modiri
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland
| | - Anne-Marie Charpentier
- Department of Radiation Oncology, Center Hospitalier de l'Universite de Montreal, Montreal, QC, Canada
| | - Vitali Moiseenko
- Department of Radiation Medicine and Applied Science, University of California San Diego, La Jolla, California
| | - Cécile M Ronckers
- Department of Pediatric Oncology, Princess Maxima Center for Pediatric Oncology, Utretcht, Netherlands
| | - Phillip J Taddei
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, Washington
| | - Louis S Constine
- Department of Radiation Oncology and Pediatrics, University of Rochester Medical Center, Rochester, New York
| | - Grant Sprow
- Albert Einstein College of Medicine, Bronx, New York
| | - Benita Tamrazi
- Department of Radiology, Children's Hospital Los Angeles/Keck School of Medicine of the University of Southern California, Los Angeles, California
| | - Shannon MacDonald
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Arthur J Olch
- Radiation Oncology Program, Children's Hospital Los Angeles/Keck School of Medicine of the University of Southern California, Los Angeles, California
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Arce P, Bolst D, Bordage MC, Brown JMC, Cirrone P, Cortés-Giraldo MA, Cutajar D, Cuttone G, Desorgher L, Dondero P, Dotti A, Faddegon B, Fedon C, Guatelli S, Incerti S, Ivanchenko V, Konstantinov D, Kyriakou I, Latyshev G, Le A, Mancini-Terracciano C, Maire M, Mantero A, Novak M, Omachi C, Pandola L, Perales A, Perrot Y, Petringa G, Quesada JM, Ramos-Méndez J, Romano F, Rosenfeld AB, Sarmiento LG, Sakata D, Sasaki T, Sechopoulos I, Simpson EC, Toshito T, Wright DH. Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group. Med Phys 2021; 48:19-56. [PMID: 32392626 PMCID: PMC8054528 DOI: 10.1002/mp.14226] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 04/26/2020] [Accepted: 04/30/2020] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. AIMS To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics. MATERIALS AND METHODS G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. RESULTS This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data. DISCUSSION Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics. CONCLUSION The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.
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Affiliation(s)
| | - D Bolst
- Centre For Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | - M-C Bordage
- CRCT (INSERM and Paul Sabatier University), Toulouse, France
| | - J M C Brown
- Department of Radiation Science and Technology, Delft University of Technology, Delft, The Netherlands
| | | | | | - D Cutajar
- Centre For Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | | | - L Desorgher
- Institute of Radiation Physics (IRA), Lausanne University Hospital, Lausanne, Switzerland
| | | | - A Dotti
- SLAC National Accelerator Laboratory, Stanford, CA, USA
| | - B Faddegon
- University of California, San Francisco, CA, USA
| | - C Fedon
- Radboud University Medical Center, Nijmegen, The Netherlands
| | - S Guatelli
- Centre For Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | - S Incerti
- Université de Bordeaux, CNRS/IN2P3, UMR5797, Centre d'Études Nucléaires de Bordeaux Gradignan, Gradignan, France
| | - V Ivanchenko
- Tomsk State University, Tomsk, Russian Federation
- CERN, Geneva, Switzerland
| | - D Konstantinov
- NRC "Kurchatov Institute" - IHEP, Protvino, Russian Federation
| | - I Kyriakou
- Medical Physics Laboratory, University of Ioannina, Ioannina, Greece
| | - G Latyshev
- NRC "Kurchatov Institute" - IHEP, Protvino, Russian Federation
| | - A Le
- Centre For Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | | | | | | | | | - C Omachi
- Nagoya Proton Therapy Center, Nagoya, Japan
| | | | - A Perales
- Medical Physics Department of Clínica Universidad de Navarra, Pamplona, Spain
| | - Y Perrot
- IRSN, Fontenay-aux-Roses, France
| | | | | | | | - F Romano
- INFN Catania Section, Catania, Italy
- Medical Physics Department, National Physical Laboratory, Teddington, UK
| | - A B Rosenfeld
- Centre For Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | | | - D Sakata
- Centre For Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | | | - I Sechopoulos
- Radboud University Medical Center, Nijmegen, The Netherlands
- Dutch Expert Center for Screening (LRCB), Nijmegen, The Netherlands
| | - E C Simpson
- Department of Nuclear Physics, Research School of Physics, Australian National University, Canberra, Australia
| | - T Toshito
- Nagoya Proton Therapy Center, Nagoya, Japan
| | - D H Wright
- SLAC National Accelerator Laboratory, Stanford, CA, USA
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Exosomes and exosomal microRNA in non-targeted radiation bystander and abscopal effects in the central nervous system. Cancer Lett 2020; 499:73-84. [PMID: 33160002 DOI: 10.1016/j.canlet.2020.10.049] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 10/24/2020] [Accepted: 10/29/2020] [Indexed: 12/11/2022]
Abstract
Localized cranial radiotherapy is a dominant treatment for brain cancers. After being subjected to radiation, the central nervous system (CNS) exhibits targeted effects as well as non-targeted radiation bystander effects (RIBE) and abscopal effects (RIAE). Radiation-induced targeted effects in the CNS include autophagy and various changes in tumor cells due to radiation sensitivity, which can be regulated by microRNAs. Non-targeted radiation effects are mainly induced by gap junctional communication between cells, exosomes containing microRNAs can be transduced by intracellular endocytosis to regulate RIBE and RIAE. In this review, we discuss the involvement of microRNAs in radiation-induced targeted effects, as well as exosomes and/or exosomal microRNAs in non-targeted radiation effects in the CNS. As a target pathway, we also discuss the Akt pathway which is regulated by microRNAs, exosomes, and/or exosomal microRNAs in radiation-induced targeted effects and RIBE in CNS tumor cells. As the CNS-derived exosomes can cross the blood-brain-barrier (BBB) into the bloodstream and be isolated from peripheral blood, exosomes and exosomal microRNAs can emerge as promising minimally invasive biomarkers and therapeutic targets for radiation-induced targeted and non-targeted effects in the CNS.
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Abolfath R, Helo Y, Carlson DJ, Stewart R, Grosshans D, Mohan R. A new approach to modeling the microdosimetry of proton therapy beams. Med Phys 2020; 47:3184-3190. [PMID: 32249429 PMCID: PMC10019905 DOI: 10.1002/mp.14165] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 03/12/2020] [Accepted: 03/26/2020] [Indexed: 01/26/2023] Open
Abstract
INTRODUCTION To revisit the formulation of the mean chord length in microdosimetry and replace it by the particle mean free path appropriate for modelings in radiobiology. METHODS We perform a collision-by-collision followed by event-by-event Geant4 Monte Carlo simulation and calculate double-averaged stepping length, 〈〈l〉〉, for a range of target sizes from mm down to μm and depth in water. We consider 〈〈l〉〉 to represent the particle mean free path. RESULTS We show that 〈〈l〉〉 continuously drops as a function of depth and asymptotically saturates to a minimum value in low energies, where it exhibits a universal scaling behavior, independent of particle nominal beam energy. We correlate 〈〈l〉〉 to linear density of DNA damage, complexities of initial lethal lesions and illustrate a relative difference between predictive RBEs in model calculations using mean chord length vs the proposed mean free path. We demonstrate consistency between rapid increase in RBE within and beyond the Bragg peak and 〈〈l〉〉, a decreasing function of depth. DISCUSSION AND CONCLUSION An interplay between localities in imparted energy at nanometer scale and subsequent physio-chemical processes, causalities and pathways in DNA damage requires substitution of geometrical chord length of cell nuclei by mean-free path of proton and charged particles to account for a mean distance among sequential collisions in DNA materials. To this end, the event averaging over cell volume in the current microdosimetry formalism must be superseded by the collision averaging scored within the volume. The former, is fundamentally a global attribute of the cell nuclei surfaces and boundaries and is characterized by their membrane diameters, hence such global indices are not appropriate to quantitatively represent the radiobiological strength of the particles and their RBE variabilities that is associated with the sensitivities to local structure of the collisions and their spatio-temporal collective patterns in DNA materials.
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Affiliation(s)
- Ramin Abolfath
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yusuf Helo
- Imanova Centre for Imaging Sciences, Invicro LLC, London, UK
- Department of Medical Physics and Bioengineering, University College London, UK
| | - David J. Carlson
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Robert Stewart
- School of Medicine, Department of Radiation Oncology, University of Washington, Seattle, WA 98195, USA
| | - David Grosshans
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
| | - Radhe Mohan
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
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Abolfath R, Peeler C, Mirkovic D, Mohan R, Grosshans D. A DNA damage multiscale model for NTCP in proton and hadron therapy. Med Phys 2020; 47:2005-2012. [PMID: 31955444 PMCID: PMC10015418 DOI: 10.1002/mp.14034] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 12/18/2019] [Accepted: 01/03/2020] [Indexed: 12/20/2022] Open
Abstract
PURPOSE To develop a first principle and multiscale model for normal tissue complication probability (NTCP) as a function of dose and LET for proton and in general for particle therapy with a goal of incorporating nanoscale radio-chemical to macroscale cell biological pathways, spanning from initial DNA damage to tissue late effects. METHODS The method is a combination of analytical and multiscale computational steps including (a) derivation of functional dependencies of NTCP on DNA-driven cell lethality in nanometer and mapping to dose and LET in millimeter, and (b) three-dimensional-surface fitting to Monte Carlo data set generated based on postradiation image change and gathered for a cohort of 14 pediatric patients treated by scanning beam of protons for ependymoma. We categorize voxel-based dose and LET associated with development of necrosis in NTCP. RESULT Our model fits well the clinical data, generated for postradiation tissue toxicity and necrosis. The fitting procedure results in extraction of in vivo radio-biological α-β indices and their numerical values. DISCUSSION AND CONCLUSION The NTCP model, explored in this work, allows to correlate the tissue toxicities to DNA initial damage, cell lethality and the properties and qualities of radiation, dose, and LET.
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Affiliation(s)
- Ramin Abolfath
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
| | - Chris Peeler
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
| | - Dragan Mirkovic
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
| | - Radhe Mohan
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
| | - David Grosshans
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, 75031, USA
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Lu VM, Welby JP, Laack NN, Mahajan A, Daniels DJ. Pseudoprogression after radiation therapies for low grade glioma in children and adults: A systematic review and meta-analysis. Radiother Oncol 2020; 142:36-42. [DOI: 10.1016/j.radonc.2019.07.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 07/09/2019] [Indexed: 02/06/2023]
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Rørvik E, Thörnqvist S, Ytre-Hauge KS. The experimental dose ranges influence the LETd dependency of the proton minimum RBE (RBEmin). ACTA ACUST UNITED AC 2019; 64:195001. [DOI: 10.1088/1361-6560/ab369a] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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10
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Newpower M, Patel D, Bronk L, Guan F, Chaudhary P, McMahon SJ, Prise KM, Schettino G, Grosshans DR, Mohan R. Using the Proton Energy Spectrum and Microdosimetry to Model Proton Relative Biological Effectiveness. Int J Radiat Oncol Biol Phys 2019; 104:316-324. [PMID: 30731186 PMCID: PMC6499683 DOI: 10.1016/j.ijrobp.2019.01.094] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 12/28/2018] [Accepted: 01/29/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE We introduce a methodology to calculate the microdosimetric quantity dose-mean lineal energy for input into the microdosimetric kinetic model (MKM) to model the relative biological effectiveness (RBE) of proton irradiation experiments. METHODS AND MATERIALS The data from 7 individual proton RBE experiments were included in this study. In each experiment, the RBE at several points along the Bragg curve was measured. Monte Carlo simulations to calculate the lineal energy probability density function of 172 different proton energies were carried out with use of Geant4 DNA. We calculated the fluence-weighted lineal energy probability density function (fw(y)), based on the proton energy spectra calculated through Monte Carlo at each experimental depth, calculated the dose-mean lineal energy yD¯ for input into the MKM, and then computed the RBE. The radius of the domain (rd) was varied to reach the best agreement between the MKM-predicted RBE and experimental RBE. A generic RBE model as a function of dose-averaged linear energy transfer (LETD) with 1 fitting parameter was presented and fit to the experimental RBE data as well to facilitate a comparison to the MKM. RESULTS Both the MKM and LETD-based models modeled the RBE from experiments well. Values for rd were similar to those of other cell lines under proton irradiation that were modeled with the MKM. Analysis of the performance of each model revealed that neither model was clearly superior to the other. CONCLUSIONS Our 3 key accomplishments include the following: (1) We developed a method that uses the proton energy spectra and lineal energy distributions of those protons to calculate dose-mean lineal energy. (2) We demonstrated that our application of the MKM provides theoretical validation of proton irradiation experiments that show that RBE is significantly greater than 1.1. (3) We showed that there is no clear evidence that the MKM is better than LETD-based RBE models.
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Affiliation(s)
- Mark Newpower
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas; Medical Physics Program, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas.
| | - Darshana Patel
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Lawrence Bronk
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Fada Guan
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Pankaj Chaudhary
- Centre for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Stephen J McMahon
- Centre for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Kevin M Prise
- Centre for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, United Kingdom
| | - Giuseppe Schettino
- National Physical Laboratory, Hampton Road, Teddington, Middlesex, United Kingdom; University of Surrey, Department of Physics, Guilford, United Kingdom
| | - David R Grosshans
- Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Radhe Mohan
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
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Ludmir EB, Mahajan A, Paulino AC, Jones JY, Ketonen LM, Su JM, Grosshans DR, McAleer MF, McGovern SL, Lassen-Ramshad YA, Adesina AM, Dauser RC, Weinberg JS, Chintagumpala MM. Increased risk of pseudoprogression among pediatric low-grade glioma patients treated with proton versus photon radiotherapy. Neuro Oncol 2019; 21:686-695. [PMID: 30753704 PMCID: PMC6502497 DOI: 10.1093/neuonc/noz042] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Pseudoprogression (PsP) is a recognized phenomenon after radiotherapy (RT) for high-grade glioma but is poorly characterized for low-grade glioma (LGG). We sought to characterize PsP for pediatric LGG patients treated with RT, with particular focus on the role of RT modality using photon-based intensity-modulated RT (IMRT) or proton beam therapy (PBT). METHODS Serial MRI scans from 83 pediatric LGG patients managed at 2 institutions between 1998 and 2017 were evaluated. PsP was scored when a progressive lesion subsequently decreased or stabilized for at least a year without therapy. RESULTS Thirty-two patients (39%) were treated with IMRT, and 51 (61%) were treated with PBT. Median RT dose for the cohort was 50.4 Gy(RBE) (range, 45-59.4 Gy[RBE]). PsP was identified in 31 patients (37%), including 8/32 IMRT patients (25%) and 23/51 PBT patients (45%). PBT patients were significantly more likely to have post-RT enlargement (hazard ratio [HR] 2.15, 95% CI: 1.06-4.38, P = 0.048). RT dose >50.4 Gy(RBE) similarly predicted higher rates of PsP (HR 2.61, 95% CI: 1.20-5.68, P = 0.016). Multivariable analysis confirmed the independent effects of RT modality (P = 0.03) and RT dose (P = 0.01) on PsP incidence. Local progression occurred in 10 patients: 7 IMRT patients (22%) and 3 PBT patients (6%), with a trend toward improved local control for PBT patients (HR 0.34, 95% CI: 0.10-1.18, P = 0.099). CONCLUSIONS These data highlight substantial rates of PsP among pediatric LGG patients, particularly those treated with PBT. PsP should be considered when assessing response to RT in LGG patients within the first year after RT.
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Affiliation(s)
- Ethan B Ludmir
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Anita Mahajan
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Mayo Clinic, Rochester, Minnesota, USA
| | - Arnold C Paulino
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Texas Children’s Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Jeremy Y Jones
- Texas Children’s Cancer Center, Baylor College of Medicine, Houston, Texas, USA
- Nationwide Children’s Hospital, Columbus, Ohio, USA
| | - Leena M Ketonen
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jack M Su
- Texas Children’s Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - David R Grosshans
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Susan L McGovern
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Adekunle M Adesina
- Texas Children’s Cancer Center, Baylor College of Medicine, Houston, Texas, USA
| | - Robert C Dauser
- The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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12
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Abolfath R, Helo Y, Bronk L, Carabe A, Grosshans D, Mohan R. Renormalization of radiobiological response functions by energy loss fluctuations and complexities in chromosome aberration induction: deactivation theory for proton therapy from cells to tumor control. THE EUROPEAN PHYSICAL JOURNAL. D, ATOMIC, MOLECULAR, AND OPTICAL PHYSICS 2019; 73:64. [PMID: 39148557 PMCID: PMC11325099 DOI: 10.1140/epjd/e2019-90263-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2018] [Revised: 08/21/2018] [Indexed: 08/17/2024]
Abstract
We employ a multi-scale mechanistic approach built upon our recent phenomenological/computational methodologies [R. Abolfath et al., Sci. Rep. 7, 8340 (2017)] to investigate radiation induced cell toxicities and deactivation mechanisms as a function of linear energy transfer in hadron therapy. Our theoretical model consists of a system of Markov chains in microscopic and macroscopic spatio-temporal landscapes, i.e., stochastic birth-death processes of cells in millimeter-scale colonies that incorporates a coarse-grained driving force to account for microscopic radiation induced damage. The coupling, hence the driving force in this process, stems from a nano-meter scale radiation induced DNA damage that incorporates the enzymatic end-joining repair and mis-repair mechanisms. We use this model for global fitting of the high-throughput and high accuracy clonogenic cell-survival data acquired under exposure of the therapeutic scanned proton beams, the experimental design that considers γ-H2AX as the biological endpoint and exhibits maximum observed achievable dose and LET, beyond which the majority of the cells undergo collective biological deactivation processes. An estimate to optimal dose and LET calculated from tumor control probability by extension to ~106 cells per mm-size voxels is presented. We attribute the increase in degree of complexity in chromosome aberration to variabilities in the observed biological responses as the beam linear energy transfer (LET) increases, and verify consistency of the predicted cell death probability with the in vitro cell survival assay of approximately 100 non-small cell lung cancer (NSCLC) cells. The present model provides an interesting interpretation to variabilities in α and β indices via perturbative expansion of the cell survival fraction (SF) in terms of specific and lineal energies, z and y, corresponding to continuous transitions in pair-wise to ternary, quaternary and more complex recombination of broken chromosomes from the entrance to the end of the range of proton beam.
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Affiliation(s)
- Ramin Abolfath
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 75031, USA
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Yusuf Helo
- Invicro, A Konica Minolta Company, London, UK
- Centre for Medical Image Computing and Department of Computer Science, University College London, London, UK
| | - Lawrence Bronk
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 75031, USA
| | - Alejandro Carabe
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David Grosshans
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 75031, USA
| | - Radhe Mohan
- Department of Radiation Physics and Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 75031, USA
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13
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Wang W, Li C, Qiu R, Chen Y, Wu Z, Zhang H, Li J. Modelling of Cellular Survival Following Radiation-Induced DNA Double-Strand Breaks. Sci Rep 2018; 8:16202. [PMID: 30385845 PMCID: PMC6212584 DOI: 10.1038/s41598-018-34159-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Accepted: 07/24/2018] [Indexed: 12/30/2022] Open
Abstract
A mechanistic model of cellular survival following radiation-induced DNA double-strand breaks (DSBs) was proposed in this study. DSBs were assumed as the initial lesions in the DNA of the cell nucleus induced by ionizing radiation. The non-homologous end-joining (NHEJ) pathway was considered as the domain pathway of DSB repair in mammalian cells. The model was proposed to predict the relationship between radiation-induced DSBs in nucleus and probability of cell survival, which was quantitatively described by two input parameters and six fitting parameters. One input parameter was the average number of primary particles which caused DSB, the other input parameter was the average number of DSBs yielded by each primary particle that caused DSB. The fitting parameters were used to describe the biological characteristics of the irradiated cells. By determining the fitting parameters of the model with experimental data, the model is able to estimate surviving fractions for the same type of cells exposed to particles with different physical parameters. The model further revealed the mechanism of cell death induced by the DSB effect. Relative biological effectiveness (RBE) of charged particles at different survival could be calculated with the model, which would provide reference for clinical treatment.
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Affiliation(s)
- Wenjing Wang
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Chunyan Li
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Nuctech Company Limited, Beijing, China
| | - Rui Qiu
- Department of Engineering Physics, Tsinghua University, Beijing, China.
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China.
| | - Yizheng Chen
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Zhen Wu
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Nuctech Company Limited, Beijing, China
| | - Hui Zhang
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
| | - Junli Li
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education, Beijing, China
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14
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Paganetti H. Proton Relative Biological Effectiveness - Uncertainties and Opportunities. Int J Part Ther 2018; 5:2-14. [PMID: 30370315 DOI: 10.14338/ijpt-18-00011.1] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Proton therapy treatments are prescribed using a biological effectiveness relative to photon therapy of 1.1, that is, proton beams are considered to be 10% more biologically effective. Debate is ongoing as to whether this practice needs to be revised. This short review summarizes current knowledge on relative biological effectiveness variations and uncertainties in vitro and in vivo. Clinical relevance is discussed and strategies toward biologically guided treatment planning are presented.
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Affiliation(s)
- Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, USA
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