1
|
Besuglow J, Tessonnier T, Mein S, Eichkorn T, Haberer T, Herfarth K, Abdollahi A, Debus J, Mairani A. Understanding Relative Biological Effectiveness and Clinical Outcome of Prostate Cancer Therapy Using Particle Irradiation: Analysis of Tumor Control Probability With the Modified Microdosimetric Kinetic Model. Int J Radiat Oncol Biol Phys 2024; 119:1545-1556. [PMID: 38423224 DOI: 10.1016/j.ijrobp.2024.02.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 12/22/2023] [Accepted: 02/10/2024] [Indexed: 03/02/2024]
Abstract
PURPOSE Recent experimental studies and clinical trial results might indicate that-at least for some indications-continued use of the mechanistic model for relative biological effectiveness (RBE) applied at carbon ion therapy facilities in Europe for several decades (LEM-I) may be unwarranted. We present a novel clinical framework for prostate cancer treatment planning and tumor control probability (TCP) prediction based on the modified microdosimetric kinetic model (mMKM) for particle therapy. METHODS AND MATERIALS Treatment plans of 91 patients with prostate tumors (proton: 46, carbon ions: 45) applying 66 GyRBE [RBE = 1.1 for protons and LEM-I, (α/β)x = 2.0 Gy, for carbon ions] in 20 fractions were recalculated using mMKM [(α/β)x = 3.1 Gy]). Based solely on the response data of photon-irradiated patient groups stratified according to risk and usage of androgen deprivation therapy, we derived parameters for an mMKM-based Poisson-TCP model. Subsequently, new carbon and helium ion plans, adhering to prescribed biological dose criteria, were generated. These were systematically compared with the clinical experience of Japanese centers employing an analogous fractionation scheme and existing proton plans. RESULTS mMKM predictions suggested significant biological dose deviation between the proton and carbon ion arms. Patients irradiated with protons received (3.25 ± 0.08) GyRBEmMKM/Fx, whereas patients treated with carbon ions received(2.51 ± 0.05) GyRBEmMKM/Fx. TCP predictions were (86 ± 3)% for protons and (52 ± 4)% for carbon ions, matching the clinical outcome of 85% and 50%. Newly optimized carbon ion plans, guided by the mMKM/TCP model, effectively replicated clinical data from Japanese centers. Using mMKM, helium ions exhibited similar target coverage as proton and carbon ions and improved rectum and bladder sparing compared with proton. CONCLUSIONS Our mMKM-based model for prostate cancer treatment planning and TCP prediction was validated against clinical data for proton and carbon ion therapy, and its application was extended to helium ion therapy. Based on the data presented in this work, mMKM seems to be a good candidate for clinical biological calculations in carbon ion therapy for prostate cancer.
Collapse
Affiliation(s)
- Judith Besuglow
- Clinical Cooperation Unit Translational Radiation Oncology (E210), National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; German Cancer Consortium (DKTK) Core-Center Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Thomas Tessonnier
- Clinical Cooperation Unit Translational Radiation Oncology (E210), National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany
| | - Stewart Mein
- Clinical Cooperation Unit Translational Radiation Oncology (E210), National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; German Cancer Consortium (DKTK) Core-Center Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Tanja Eichkorn
- National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Department of Radiation Oncology, Heidelberg University Hospital (UKHD), Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Thomas Haberer
- National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany
| | - Klaus Herfarth
- National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Department of Radiation Oncology, Heidelberg University Hospital (UKHD), Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Amir Abdollahi
- Clinical Cooperation Unit Translational Radiation Oncology (E210), National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine (MFHD) and Heidelberg University Hospital (UKHD), Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; German Cancer Consortium (DKTK) Core-Center Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jürgen Debus
- German Cancer Consortium (DKTK) Core-Center Heidelberg, German Cancer Research Center (DKFZ), Heidelberg, Germany; National Center for Radiation Oncology (NCRO), Heidelberg Institute of Radiation Oncology (HIRO), Heidelberg University and German Cancer Research Center (DKFZ), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Department of Radiation Oncology, Heidelberg University Hospital (UKHD), Heidelberg, Germany; National Center for Tumor Diseases (NCT), Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology (E050), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrea Mairani
- Clinical Cooperation Unit Translational Radiation Oncology (E210), National Center for Tumor Diseases (NCT), Heidelberg University Hospital (UKHD) and German Cancer Research Center (DKFZ), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Medical Physics, National Centre of Oncological Hadrontherapy (CNAO), Pavia, Italy.
| |
Collapse
|
2
|
Iyer A, Apte AP, Bendau E, Thor M, Chen I, Shin J, Wu A, Gomez D, Rimner A, Yorke E, Deasy JO, Jackson A. ROE (Radiotherapy Outcomes Estimator): An open-source tool for optimizing radiotherapy prescriptions. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107833. [PMID: 37863013 PMCID: PMC10872836 DOI: 10.1016/j.cmpb.2023.107833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 09/16/2023] [Accepted: 09/25/2023] [Indexed: 10/22/2023]
Abstract
BACKGROUND AND OBJECTIVES Radiotherapy prescriptions currently derive from population-wide guidelines established through large clinical trials. We provide an open-source software tool for patient-specific prescription determination using personalized dose-response curves. METHODS We developed ROE, a plugin to the Computational Environment for Radiotherapy Research to visualize predicted tumor control and normal tissue complication simultaneously, as a function of prescription dose. ROE can be used natively with MATLAB and is additionally made accessible in GNU Octave and Python, eliminating the need for commercial licenses. It provides a curated library of published and validated predictive models and incorporates clinical restrictions on normal tissue outcomes. ROE additionally provides batch-mode tools to evaluate and select among different fractionation schemes and analyze radiotherapy outcomes across patient cohorts. CONCLUSION ROE is an open-source, GPL-copyrighted tool for interactive exploration of the dose-response relationship to aid in radiotherapy planning. We demonstrate its potential clinical relevance in (1) improving patient awareness by quantifying the risks and benefits of a given treatment protocol (2) assessing the potential for dose escalation across patient cohorts and (3) estimating accrual rates of new protocols.
Collapse
Affiliation(s)
- Aditi Iyer
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States.
| | - Aditya P Apte
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States
| | - Ethan Bendau
- Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Maria Thor
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States
| | - Ishita Chen
- Department of Radiation Oncology, Tennessee Oncology, Nashville, TN, United States
| | - Jacob Shin
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Abraham Wu
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Daniel Gomez
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Andreas Rimner
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Ellen Yorke
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States
| | - Joseph O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States
| | - Andrew Jackson
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, United States
| |
Collapse
|
3
|
Wakisaka Y, Minami K, Okada N, Tsubouchi T, Hamatani N, Yagi M, Takashina M, Kanai T. Treatment planning of carbon ion radiotherapy for prostate cancer based on cellular experiments with PC3 human prostate cancer cells. Phys Med 2023; 107:102537. [PMID: 36780791 DOI: 10.1016/j.ejmp.2023.102537] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 01/10/2023] [Accepted: 01/31/2023] [Indexed: 02/13/2023] Open
Abstract
[Purpose] Treatment plans for carbon ion radiotherapy (CIRT) in Japan are designed to uniformly deliver the prescribed clinical dose based on the radiosensitivity of human salivary gland (HSG) cells to the planning target volume (PTV). However, sensitivity to carbon beams varies between cell lines, that is, it should be checked that the clinical dose distribution based on the cell radiosensitivity of the treatment site is uniform within the PTV. [Methods] We modeled the linear energy transfer (LET) dependence of the linear-quadratic (LQ) coefficients specific to prostate cancer, which accounts for the majority of CIRT. This was achieved by irradiating prostate cancer cells (PC3) with X-rays from a 4 MV-Linac and carbon beams with different LETs of 11.1-214.3 keV/μm. By using the radiosensitivity of PC3 cells derived from cellular experiments, we reconstructed prostate-cancer-specific clinical dose distributions on patient computed tomography (CT). [Results] The LQ coefficient, α, of PC3 cells was larger than that of HSG cells at low (<50 keV/μm) LET and smaller at high (>50 keV/μm) LET, which was validated by cellular experiments performed on rectangular SOBPs. The reconstructed dose distribution on patient CT was sloped when 1 fraction incident from the one side of the patient was considered, but remained uniform from the sum of 12 fractions of the left-right opposing beams (as is used in clinical practice). [Conclusion] Our study reveals the inhomogeneity of clinical doses in single-field plans calculated using the PC3 radiosensitivity data. However, this inhomogeneity is compensated by using the combination of left-right opposing beams.
Collapse
Affiliation(s)
- Yushi Wakisaka
- Osaka Heavy Ion Therapy Center, Osaka City, Osaka, Japan; Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Osaka City, Osaka, Japan.
| | - Kazumasa Minami
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Osaka City, Osaka, Japan
| | - Nao Okada
- Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Osaka City, Osaka, Japan
| | | | | | - Masashi Yagi
- Osaka Heavy Ion Therapy Center, Osaka City, Osaka, Japan; Department of Carbon Ion Radiotherapy, Osaka University Graduate School of Medicine, Osaka City, Osaka, Japan
| | | | - Tatsuaki Kanai
- Osaka Heavy Ion Therapy Center, Osaka City, Osaka, Japan; Department of Medical Physics and Engineering, Osaka University Graduate School of Medicine, Osaka City, Osaka, Japan
| |
Collapse
|
4
|
Marignol L. Generation of Radioresistant Prostate Cancer Cells. Methods Mol Biol 2023; 2645:129-138. [PMID: 37202614 DOI: 10.1007/978-1-0716-3056-3_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The development of in vitro isogenic models of radioresistance through exposure to fractionated radiation is an increasingly used approach to investigate the mechanisms of radioresistance in cancer cells. Owing to the complex nature of the biological effect of ionizing radiation, the generation and validation of these models requires the careful consideration of radiation exposure protocols and cellular endpoints. This chapter presents a protocol we used to derive and characterize an isogenic model of radioresistant prostate cancer cells. This protocol may be applicable to other cancer cell lines.
Collapse
Affiliation(s)
- Laure Marignol
- Translational Radiobiology and Oncology Group, Applied Radiation Therapy Trinity Research Group, Trinity College Dublin, Dublin, Ireland.
| |
Collapse
|
5
|
Open Source Repository and Online Calculator of Prediction Models for Diagnosis and Prognosis in Oncology. Biomedicines 2022; 10:biomedicines10112679. [DOI: 10.3390/biomedicines10112679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/18/2022] [Accepted: 10/20/2022] [Indexed: 11/16/2022] Open
Abstract
(1) Background: The main aim was to develop a prototype application that would serve as an open-source repository for a curated subset of predictive and prognostic models regarding oncology, and provide a user-friendly interface for the included models to allow online calculation. The focus of the application is on providing physicians and health professionals with patient-specific information regarding treatment plans, survival rates, and side effects for different expected treatments. (2) Methods: The primarily used models were the ones developed by our research group in the past. This selection was completed by a number of models, addressing the same cancer types but focusing on other outcomes that were selected based on a literature search in PubMed and Medline databases. All selected models were publicly available and had been validated TRIPOD (Transparent Reporting of studies on prediction models for Individual Prognosis Or Diagnosis) type 3 or 2b. (3) Results: The open source repository currently incorporates 18 models from different research groups, evaluated on datasets from different countries. Model types included logistic regression, Cox regression, and recursive partition analysis (decision trees). (4) Conclusions: An application was developed to enable physicians to complement their clinical judgment with user-friendly patient-specific predictions using models that have received internal/external validation. Additionally, this platform enables researchers to display their work, enhancing the use and exposure of their models.
Collapse
|
6
|
Mein S, Klein C, Kopp B, Magro G, Harrabi S, Karger CP, Haberer T, Debus J, Abdollahi A, Dokic I, Mairani A. Assessment of RBE-Weighted Dose Models for Carbon Ion Therapy Toward Modernization of Clinical Practice at HIT: In Vitro, in Vivo, and in Patients. Int J Radiat Oncol Biol Phys 2020; 108:779-791. [PMID: 32504659 DOI: 10.1016/j.ijrobp.2020.05.041] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 04/02/2020] [Accepted: 05/21/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE Present-day treatment planning in carbon ion therapy is conducted with assumptions for a limited number of tissue types and models for effective dose. Here, we comprehensively assess relative biological effectiveness (RBE) in carbon ion therapy and associated models toward the modernization of current clinical practice in effective dose calculation. METHODS Using 2 human (A549, H460) and 2 mouse (B16, Renca) tumor cell lines, clonogenic cell survival assay was performed for examination of changes in RBE along the full range of clinical-like spread-out Bragg peak (SOBP) fields. Prediction power of the local effect model (LEM1 and LEM4) and the modified microdosimetric kinetic model (mMKM) was assessed. Experimentation and analysis were carried out in the frame of a multidimensional end point study for clinically relevant ranges of physical dose (D), dose-averaged linear energy transfer (LETd), and base-line photon radio-sensitivity (α/β)x. Additionally, predictions were compared against previously reported RBE measurements in vivo and surveyed in patient cases. RESULTS RBE model prediction performance varied among the investigated perspectives, with mMKM prediction exhibiting superior agreement with measurements both in vitro and in vivo across the 3 investigated end points. LEM1 and LEM4 performed their best in the highest LET conditions but yielded overestimations and underestimations in low/midrange LET conditions, respectively, as demonstrated by comparison with measurements. Additionally, the analysis of patient treatment plans revealed substantial variability across the investigated models (±20%-30% uncertainty), largely dependent on the selected model and absolute values for input tissue parameters αx and βx. CONCLUSION RBE dependencies in vitro, in vivo, and in silico were investigated with respect to various clinically relevant end points in the context of tumor-specific tissue radio-sensitivity assignment and accurate RBE modeling. Discovered model trends and performances advocate upgrading current treatment planning schemes in carbon ion therapy and call for verification via clinical outcome analysis with large patient cohorts.
Collapse
Affiliation(s)
- Stewart Mein
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine and Heidelberg University Hospital, Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany; German Cancer Consortium Core-Center Heidelberg, German Cancer Research Center, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Germany
| | - Carmen Klein
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine and Heidelberg University Hospital, Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany; German Cancer Consortium Core-Center Heidelberg, German Cancer Research Center, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany; Faculty of Biosciences, Heidelberg University, Germany
| | - Benedikt Kopp
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine and Heidelberg University Hospital, Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany; German Cancer Consortium Core-Center Heidelberg, German Cancer Research Center, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Germany
| | - Giuseppe Magro
- National Centre of Oncological Hadrontherapy, Medical Physics, Pavia, Italy
| | - Semi Harrabi
- Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany; National Center for Tumor Diseases, Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Christian P Karger
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Thomas Haberer
- Heidelberg Ion-Beam Therapy Center, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen Debus
- German Cancer Consortium Core-Center Heidelberg, German Cancer Research Center, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Germany; National Center for Tumor Diseases, Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Amir Abdollahi
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine and Heidelberg University Hospital, Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany; German Cancer Consortium Core-Center Heidelberg, German Cancer Research Center, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany
| | - Ivana Dokic
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, Department of Radiation Oncology, Heidelberg Faculty of Medicine and Heidelberg University Hospital, Heidelberg Ion-Beam Therapy Center, Heidelberg, Germany; German Cancer Consortium Core-Center Heidelberg, German Cancer Research Center, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, Heidelberg Institute of Radiation Oncology, National Center for Radiation Oncology, Heidelberg University and German Cancer Research Center, Heidelberg, Germany.
| | - Andrea Mairani
- Clinical Cooperation Unit Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany; National Centre of Oncological Hadrontherapy, Medical Physics, Pavia, Italy; Heidelberg Ion-Beam Therapy Center, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
| |
Collapse
|
7
|
Alaswad M, Kleefeld C, Foley M. Optimal tumour control for early-stage non-small-cell lung cancer: A radiobiological modelling perspective. Phys Med 2019; 66:55-65. [DOI: 10.1016/j.ejmp.2019.09.074] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 09/06/2019] [Accepted: 09/08/2019] [Indexed: 12/25/2022] Open
|
8
|
Takei H, Inaniwa T. Effect of Irradiation Time on Biological Effectiveness and Tumor Control Probability in Proton Therapy. Int J Radiat Oncol Biol Phys 2019; 105:222-229. [PMID: 31085286 DOI: 10.1016/j.ijrobp.2019.05.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 03/16/2019] [Accepted: 05/01/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE The biological effectiveness of proton beams may decrease with irradiation time because of sublethal damage repair (SLDR). The purpose of this study is to systematically evaluate this effect in hypofractionated proton therapy for various target sizes, depths, and prescribed doses per fraction. METHODS AND MATERIALS Plans with a single spread-out Bragg peak beam were created using a constant relative biological effectiveness (RBE) of 1.1 to cover targets of 6 different sizes located at 3 different depths in water. Biological doses of 2, 3, 5, 10, and 20 Gy (RBE) were prescribed to the targets. First, to investigate the depth variation of the biological effectiveness, the biological dose in instantaneous irradiation was recalculated based on the microdosimetric kinetic model. SLDR was then taken into account in the microdosimetric kinetic model during treatments to obtain the irradiation time-dependent biological effectiveness for irradiation time T of 5 to 60 minutes and beam interruption time τ of 0 to 60 minutes. The tumor control probabilities were calculated for single-fraction proton therapy fields of different Ts and τs, and the curative doses were evaluated at a tumor control probability of 90%. RESULTS The biological effectiveness decreased with longer T and τ and higher prescribed dose. The maximum decrease in the biological effectiveness was 21% with a 20 Gy (RBE) prescribed dose. In single-fraction proton therapy, the curative dose increased linearly by approximately 33% to 35% with the increase of T from 0 to 60 minutes. CONCLUSIONS The biological effectiveness varies largely with T and τ because of SLDR during treatments. This effect was pronounced for high prescribed doses per fraction. Thus, the effect of SLDR needs to be considered in hypofractionated and single-fraction proton therapies in relation to size and depth of the target.
Collapse
Affiliation(s)
- Hideyuki Takei
- Faculty of Medicine, University of Tsukuba, Ibaraki, Japan.
| | - Taku Inaniwa
- Department of Accelerator and Medical Physics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| |
Collapse
|
9
|
Buizza G, Molinelli S, D'Ippolito E, Fontana G, Pella A, Valvo F, Preda L, Orecchia R, Baroni G, Paganelli C. MRI-based tumour control probability in skull-base chordomas treated with carbon-ion therapy. Radiother Oncol 2019; 137:32-37. [PMID: 31051372 DOI: 10.1016/j.radonc.2019.04.018] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 03/30/2019] [Accepted: 04/18/2019] [Indexed: 12/22/2022]
Abstract
PURPOSE To derive personalized tumour control probability (TCP) models, using diffusion-weighted (DW-) MRI for defining initial tumour cellular density in skull-base chordoma patients undergoing carbon-ion radiotherapy (CIRT). MATERIALS AND METHODS 67 patients affected by skull-base chordoma were enrolled for a standardized CIRT treatment (70.4 Gy (RBE) prescription dose). Local control information was clinically assessed. For 20 of them, apparent diffusion coefficient (ADC) maps were computed from DW-MRI and then converted into cellular density. Radiosensitivity parameters (α, β) were estimated from the available data through an optimization procedure, taking advantage of a relationship observed between local control and the dose received by at least the 98% of the gross tumour volume. These parameters were fed into two poissonian TCP models, based on the LQ model, being the first (TCPLIT) computed from literature parameters and the second (TCPADC) enriched by a personalized initial cellular density derived from ADC maps. RESULTS The inclusion of the cellular density derived from ADC into TCPADC yielded slightly higher dose values at which TCP = 0.5 (D50 = 38.91 Gy (RBE)) with respect to TCPLIT (D5034.16 Gy (RBE)). This suggested a more conservative approach, even if the prognostic power of TCPADC and TCPLIT, tested with respect to local control, was equivalent in terms of sensitivity (0.867) and specificity (0.600). CONCLUSIONS Both TCPADC and TCPLIT exhibited good agreement with a clinically validated information of local control, the former providing more conservative predictions.
Collapse
Affiliation(s)
- Giulia Buizza
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy.
| | - Silvia Molinelli
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Emma D'Ippolito
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Giulia Fontana
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Andrea Pella
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Francesca Valvo
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Lorenzo Preda
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy; Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Italy
| | - Roberto Orecchia
- National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Guido Baroni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy; National Center of Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy
| |
Collapse
|
10
|
Her EJ, Reynolds HM, Mears C, Williams S, Moorehouse C, Millar JL, Ebert MA, Haworth A. Radiobiological parameters in a tumour control probability model for prostate cancer LDR brachytherapy. Phys Med Biol 2018; 63:135011. [PMID: 29799812 DOI: 10.1088/1361-6560/aac814] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
To provide recommendations for the selection of radiobiological parameters for prostate cancer treatment planning. Recommendations were based on validation of the previously published values, parameter estimation and a consideration of their sensitivity within a tumour control probability (TCP) model using clinical outcomes data from low-dose-rate (LDR) brachytherapy. The proposed TCP model incorporated radiosensitivity (α) heterogeneity and a non-uniform distribution of clonogens. The clinical outcomes data included 849 prostate cancer patients treated with LDR brachytherapy at four Australian centres between 1995 and 2012. Phoenix definition of biochemical failure was used. Validation of the published values from four selected literature and parameter estimation was performed with a maximum likelihood estimation method. Each parameter was varied to evaluate the change in calculated TCP to quantify the sensitivity of the model to its radiobiological parameters. Using a previously published parameter set and a total clonogen number of 196 000 provided TCP estimates that best described the patient cohort. Fitting of all parameters with a maximum likelihood estimation was not possible. Variations in prostate TCP ranged from 0.004% to 0.67% per 1% change in each parameter. The largest variation was caused by the log-normal distribution parameters for α (mean, [Formula: see text], and standard deviation, σ α ). Based on the results using the clinical cohort data, we recommend a previously published dataset is used for future application of the TCP model with inclusion of a patient-specific, non-uniform clonogen density distribution which could be derived from multiparametric imaging. The reduction in uncertainties in these parameters will improve the confidence in using biological models for clinical radiotherapy planning.
Collapse
Affiliation(s)
- E J Her
- School of Physics and Astrophysics, University of Western Australia, Perth, Australia
| | | | | | | | | | | | | | | |
Collapse
|
11
|
Towards a Clinical Decision Support System for External Beam Radiation Oncology Prostate Cancer Patients: Proton vs. Photon Radiotherapy? A Radiobiological Study of Robustness and Stability. Cancers (Basel) 2018; 10:cancers10020055. [PMID: 29463018 PMCID: PMC5836087 DOI: 10.3390/cancers10020055] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 01/19/2018] [Accepted: 02/14/2018] [Indexed: 12/25/2022] Open
Abstract
We present a methodology which can be utilized to select proton or photon radiotherapy in prostate cancer patients. Four state-of-the-art competing treatment modalities were compared (by way of an in silico trial) for a cohort of 25 prostate cancer patients, with and without correction strategies for prostate displacements. Metrics measured from clinical image guidance systems were used. Three correction strategies were investigated; no-correction, extended-no-action-limit, and online-correction. Clinical efficacy was estimated via radiobiological models incorporating robustness (how probable a given treatment plan was delivered) and stability (the consistency between the probable best and worst delivered treatments at the 95% confidence limit). The results obtained at the cohort level enabled the determination of a threshold for likely clinical benefit at the individual level. Depending on the imaging system and correction strategy; 24%, 32% and 44% of patients were identified as suitable candidates for proton therapy. For the constraints of this study: Intensity-modulated proton therapy with online-correction was on average the most effective modality. Irrespective of the imaging system, each treatment modality is similar in terms of robustness, with and without the correction strategies. Conversely, there is substantial variation in stability between the treatment modalities, which is greatly reduced by correction strategies. This study provides a ‘proof-of-concept’ methodology to enable the prospective identification of individual patients that will most likely (above a certain threshold) benefit from proton therapy.
Collapse
|
12
|
Prostate Cancer Radiation Therapy: What Do Clinicians Have to Know? BIOMED RESEARCH INTERNATIONAL 2016; 2016:6829875. [PMID: 28116302 PMCID: PMC5225325 DOI: 10.1155/2016/6829875] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 10/18/2016] [Accepted: 10/31/2016] [Indexed: 12/11/2022]
Abstract
Radiotherapy (RT) for prostate cancer (PC) has steadily evolved over the last decades, with improving biochemical disease-free survival. Recently population based research also revealed an association between overall survival and doses ≥ 75.6 Gray (Gy) in men with intermediate- and high-risk PC. Examples of improved RT techniques are image-guided RT, intensity-modulated RT, volumetric modulated arc therapy, and stereotactic ablative body RT, which could facilitate further dose escalation. Brachytherapy is an internal form of RT that also developed substantially. New devices such as rectum spacers and balloons have been developed to spare rectal structures. Newer techniques like protons and carbon ions have the intrinsic characteristics maximising the dose on the tumour while minimising the effect on the surrounding healthy tissue, but clinical data are needed for confirmation in randomised phase III trials. Furthermore, it provides an overview of an important discussion issue in PC treatment between urologists and radiation oncologists: the comparison between radical prostatectomy and RT. Current literature reveals that all possible treatment modalities have the same cure rate, but a different toxicity pattern. We recommend proposing the possible different treatment modalities with their own advantages and side-effects to the individual patient. Clinicians and patients should make treatment decisions together (shared decision-making) while using patient decision aids.
Collapse
|
13
|
Walsh S. Erratum: “A validated tumor control probability model based on a meta-analysis of low, intermediate, and high-risk prostate cancer patients treated by photon, proton, or carbon-ion radiotherapy” [Med. Phys. 43, 734-747 (2016)]. Med Phys 2016; 43:5263. [DOI: 10.1118/1.4960371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
|