• Humans
• Neoplasms/radiotherapy
• Models, Theoretical
• Radiotherapy Planning, Computer-Assisted/methods
• Radiosurgery/methods
• Precision Medicine
• Radiotherapy/methods

• glioblastoma
• high-grade glioma
• modeling
• radiobiological modeling
• radiotherapy
• tumor invasion
• tumor modeling

• Humans
• Disease Progression
• Neoplasm Invasiveness
• Cell Survival/radiation effects
• Brain Neoplasms/pathology
• Brain Neoplasms/radiotherapy
• Glioma/pathology
• Glioma/radiotherapy
• Neoplasm Grading
• Female
• Male
• Middle Aged
• Models, Biological
• Adult
• Tumor Burden/radiation effects
• Glioblastoma/radiotherapy
• Glioblastoma/pathology
• Aged

• BNCT
• Equivalent uniform dose
• Normal tissue complication probability
• Photon isoeffective dose
• Radiotoxic effects
• Somnolence syndrome

• Boron Neutron Capture Therapy/adverse effects
• Boron Neutron Capture Therapy/methods
• Brain Neoplasms/radiotherapy
• Rats
• Radiotherapy Dosage
• Animals
• Humans
• Photons/therapeutic use
• Photons/adverse effects
• Radiotherapy Planning, Computer-Assisted
• Radiation Dosage
• Brain/radiation effects
• Models, Biological
• Dose-Response Relationship, Radiation

• Head and Neck Neoplasms/radiotherapy
• Head and Neck Neoplasms/pathology
• Humans
• Tumor Burden
• Models, Biological
• Cell Proliferation
• Oxygen
• Linear Models
• Tumor Hypoxia

• Biologically Effective Dose (BED)
• Gamma Knife
• Stereotactic Radiosurgery

• Radiosurgery/methods
• Humans
• Radiotherapy Planning, Computer-Assisted/methods
• Radiotherapy Dosage
• Relative Biological Effectiveness
• Tumor Burden
• Neuroma, Acoustic/radiotherapy
• Neuroma, Acoustic/surgery

• biologically effective dose
• metastatic castration-resistant prostate cancer
• physiologically based pharmacokinetic model
• radiobiological response
• radiopharmaceutical therapy

• PJT-180251 and RGPIN-2019-06467. This work was supported by the Canadian Institutes of Health Research (CIHR) Project Grant PJT-180251, Networking Health Ltd., Mitacs Elevate, as well as the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2019-06

• Animals
• Humans
• DNA/radiation effects
• DNA/chemistry
• DNA Damage
• DNA Repair
• History, 20th Century
• History, 21st Century
• Monte Carlo Method
• Radiation, Ionizing
• Radiobiology/history

• Humans
• Radiobiology
• Cytogenetics
• Chromosome Aberrations/radiation effects
• Animals
• DNA Repair/radiation effects
• Radiation, Ionizing
• History, 20th Century
• DNA Breaks, Double-Stranded/radiation effects

• Dose painting
• Hypoxia
• Image registration

• Humans
• Head and Neck Neoplasms/radiotherapy
• Head and Neck Neoplasms/diagnostic imaging
• Radiotherapy Dosage
• Radiotherapy Planning, Computer-Assisted/methods
• Positron Emission Tomography Computed Tomography
• Image Processing, Computer-Assisted/methods
• Misonidazole/analogs & derivatives
• Radiation Dosage

• biophysical modeling
• brachytherapy
• radiobiology

• Brachytherapy/methods
• Humans
• Radiotherapy Planning, Computer-Assisted/methods
• Models, Biological
• Radiotherapy Dosage
• Research Report
• Biophysical Phenomena
• Biophysics

• carbon ion radiotherapy
• cell survival model
• tumor control probability

• Carcinoma, Non-Small-Cell Lung/radiotherapy
• Humans
• Lung Neoplasms/radiotherapy
• Heavy Ion Radiotherapy
• Neoplasm Staging
• Models, Biological
• Radiation Tolerance

• Artificial intelligence
• Zap-X
• cyberknife
• gamma knife
• history
• radiosurgery
• radiotherapy
• stereotactic body radiation therapy
• stereotactic radiosurgery
• stereotactic radiotherapy

• anticancer therapies
• lung cancer
• mathematical modeling
• metastasis

• Humans
• Lung Neoplasms/drug therapy
• Models, Theoretical
• Signal Transduction

• DEC-2020/37/B/ST6/01959 National Science Center

• Biodose Tools
• R
• biodosimetry
• data analysis
• dose assessment
• graphical user interface

• Radiation Monitoring/methods
• Bayes Theorem
• Retrospective Studies
• Radiometry
• Software

• dosimetry
• microspheres
• radiobiology
• radioembolisation
• yttrium 90

• ABT-263
• AG-1478
• Breast cancer
• Cervical cancer
• Inhibitor therapy
• Lung cancer
• NVP-BEZ235
• Radiotherapy

• SPECT
• dosimetry
• radiopharmaceutical therapy

• Humans
• Radiometry
• Radiopharmaceuticals/therapeutic use
• Software

• Biodosimetry
• Chromosomal translocation
• Dose-response curve
• Fluorescent in-situ hybridization
• Radiation

• Dicentric chromosome
• EURADOS
• RENEB
• biological dosimetry
• inter-laboratory comparison

• Humans
• Chromosome Aberrations/radiation effects
• Radiation Dosage
• Phantoms, Imaging
• Radiometry/methods

Radiotherapy can effectively kill malignant cells, but the doses required to cure cancer patients may inflict severe collateral damage to adjacent healthy tissues. Recent technological advances in the clinical application has revitalized hyperthermia treatment (HT) as an option to improve radiotherapy (RT) outcomes. Understanding the synergistic effect of simultaneous thermoradiotherapy via mathematical modelling is essential for treatment planning. We here propose a theoretical model in which the thermal enhancement ratio (TER) relates to the cell fraction being radiosensitised by the infliction of sublethal damage through HT. Further damage finally kills the cell or abrogates its proliferative capacity in a non-reversible process. We suggest the TER to be proportional to the energy invested in the sensitisation, which is modelled as a simple rate process. Assuming protein denaturation as the main driver of HT-induced sublethal damage and considering the temperature dependence of the heat capacity of cellular proteins, the sensitisation rates were found to depend exponentially on temperature; in agreement with previous empirical observations. Our findings point towards an improved definition of thermal dose in concordance with the thermodynamics of protein denaturation. Our predictions well reproduce experimental in vitro and in vivo data, explaining the thermal modulation of cellular radioresponse for simultaneous thermoradiotherapy.

• Fractionation
• Radiation-induced cell proliferation
• Radiobiology
• Repopulation
• TCP
• Tumor control probability
• Weekend

To evaluate the effect of interruption in radiotherapy due to machine failure in patients and medical institutions using machine failure risk analysis (MFRA).

The risk of machine failure during treatment is assigned to three scores (biological effect, B; occurrence, O; and cost of labor and repair parts, C) for each type of machine failure. The biological patient risk (BPR) and the economic institution risk (EIR) are calculated as the product of B and O (B×O) and C and O (C×O), respectively. The MFRA is performed in two linear accelerators (linacs).

The multileaf collimator (MLC) fault has the highest BPR and second highest EIR. In particular, TrueBeam has a higher BPR and EIR for MLC failures. The total EIR in TrueBeam was significantly higher than that in Clinac iX. The minor interlock had the second highest BPR, whereas a smaller EIR. Meanwhile, the EIR for the LaserGuard fault was the highest, and that for the monitor chamber fault was the second highest. These machine failures occurred in TrueBeam. The BPR and EIR should be evaluated for each linac. Further, the sensitivity of the BPR, it decreased with higher T1/2 and α/β values. No relative difference is observed in the BPR for each machine failure when T1/2 and α/β were varied.

The risk faced by patients and institutions in machine failure may be reduced using MFRA.

For clinical radiotherapy, interruption can occur from unscheduled downtime with machine failures. Interruption causes sublethal damage repair. The current study evaluated the effect of interruption in radiotherapy owing to machine failure on patients and medical institutions using a new method, that is, machine failure risk analysis.

• biological dose calculation
• downtime
• machine failure

With new advancements in technology, it is now possible to collect data for a variety of different metrics describing tumor growth, including tumor volume, composition, and vascularity, among others. For any proposed model of tumor growth and treatment, we observe large variability among individual patients’ parameter values, particularly those relating to treatment response; thus, exploiting the use of these various metrics for model calibration can be helpful to infer such patient-specific parameters both accurately and early, so that treatment protocols can be adjusted mid-course for maximum efficacy. However, taking measurements can be costly and invasive, limiting clinicians to a sparse collection schedule. As such, the determination of optimal times and metrics for which to collect data in order to best inform proper treatment protocols could be of great assistance to clinicians. In this investigation, we employ a Bayesian information-theoretic calibration protocol for experimental design in order to identify the optimal times at which to collect data for informing treatment parameters. Within this procedure, data collection times are chosen sequentially to maximize the reduction in parameter uncertainty with each added measurement, ensuring that a budget of n high-fidelity experimental measurements results in maximum information gain about the low-fidelity model parameter values. In addition to investigating the optimal temporal pattern for data collection, we also develop a framework for deciding which metrics should be utilized at each data collection point. We illustrate this framework with a variety of toy examples, each utilizing a radiotherapy treatment regimen. For each scenario, we analyze the dependence of the predictive power of the low-fidelity model upon the measurement budget.

• Multiquadric radial function
• Numerical simulations
• Radial basis function-generated finite difference scheme
• Reaction-diffusion models of radiation therapy
• brain tumor

• Algorithms
• Brain/diagnostic imaging
• Brain Neoplasms/diagnostic imaging
• Brain Neoplasms/radiotherapy
• Diffusion
• Humans
• Models, Theoretical

• LQ model
• RBE
• SLD repair
• proton therapy

• biological optimisation
• precision medicine
• prostate cancer

• Biologically effective dose
• Dose rate
• Hypofractionation
• Radiation protraction

• Humans
• Practice Guidelines as Topic
• Radiation Exposure/prevention & control
• Radiation Protection/standards
• Radiopharmaceuticals/therapeutic use

• 16464 Cancer Research UK

• Chromosomal aberrations
• ionizing radiation
• micronuclei
• radiobiological assays

• Cell Survival/radiation effects
• DNA Breaks, Double-Stranded/radiation effects
• Dose-Response Relationship, Radiation
• Models, Biological
• Poisson Distribution
• Probability
• Radiation Dosage
• Radiobiology
• Radiometry/methods
• Relative Biological Effectiveness

• cancer
• combination therapy
• computational modeling
• immunotherapy
• mathematical oncology
• photodynamic therapy
• photomedicine

• K22 CA181611 NCI NIH HHS
• R00 CA175292 NCI NIH HHS
• R01 CA124515 NCI NIH HHS
• R01 CA157664 NCI NIH HHS

• brachytherapy
• rotating shield brachytherapy
• intensity modulated brachytherapy
• prostate cancer
• multisource brachytherapy
• brachytherapy dose protraction

• Brachytherapy/adverse effects
• Feasibility Studies
• Humans
• Male
• Organs at Risk/radiation effects
• Prostatic Neoplasms/radiotherapy
• Radiation Dosage
• Radiation Protection
• Radiotherapy Dosage
• Radiotherapy Planning, Computer-Assisted
• Rotation
• Urethra/radiation effects

• P30 CA086862 NCI NIH HHS
• R01 EB020665 NIBIB NIH HHS
• R41 CA210737 NCI NIH HHS

• Chromosome Aberrations/radiation effects
• DNA Breaks/radiation effects
• DNA Repair
• Radiation Exposure
• Recombination, Genetic

Dose rate variation is a critical factor affecting radionuclide therapy (RNT) efficacy. Relatively few studies to date have investigated the dose rate effect in RNT. Therefore, the aim of this study was to benchmark ⁹⁰Y RNT (at different dose rates) against external beam radiotherapy (EBRT) in vitro and compare cell kill responses between the two irradiation processes.

Three human colorectal carcinoma (CRC) cell lines (HT29, HCT116, SW48) were exposed to ⁹⁰Y doses in the ranges 1–10.4 and 6.2–62.3 Gy with initial dose rates of 0.013–0.13 Gy/hr (low dose rate, LDR) and 0.077–0.77 Gy/hr (high dose rate, HDR), respectively. Results were compared to a 6-MV photon beam doses in the range from 1–9 Gy with constant dose rate of 277 Gy/hr. The cell survival parameters from the linear quadratic (LQ) model were determined. Additionally, Monte Carlo simulations were performed to calculate the average dose, dose rate and the number of hits in the cell nucleus.

For the HT29 cell line, which was the most radioresistant, the α/β ratio was found to be ≈ 31 for HDR–⁹⁰Y and ≈ 3.5 for EBRT. LDR–⁹⁰Y resulting in insignificant cell death compared to HDR–⁹⁰Y and EBRT. Simulation results also showed for LDR–⁹⁰Y, for doses ≲ 3 Gy, the average number of hits per cell nucleus is ≲ 2 indicating insufficiently delivered lethal dose. For ⁹⁰Y doses \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\gtrsim $\end{document}≳ 3 Gy the number of hits per nucleus decreases rapidly and falls below ≈ 2 after ≈ 5 days of incubation time. Therefore, our results demonstrate that LDR–⁹⁰Y is radiobiologically less effective than EBRT. However, HDR–⁹⁰Y at ≈ 56 Gy was found to be radiobiologically as effective as acute ≈ 8 Gy EBRT.

These results demonstrate that the efficacy of RNT is dependent on the initial dose rate at which radiation is delivered. Therefore, for a relatively long half-life radionuclide such as ⁹⁰Y, a higher initial activity is required to achieve an outcome as effective as EBRT.

• External beam radiotherapy (EBRT)
• Radionuclide therapy (RNT)
• Yttrium-90

• Cell Line
• Cytogenetic Analysis
• Fibroblasts/metabolism
• Fibroblasts/radiation effects
• High-Throughput Nucleotide Sequencing
• Humans
• Translocation, Genetic/radiation effects

• R01 AI080486 NIAID NIH HHS

• Chromosome aberrations
• F-ratio
• Inversions
• Ionizing radiation

Recent technological advances allow precise radiation delivery to tumor targets. As opposed to more conventional radiotherapy—where multiple small fractions are given—in some cases, the preferred course of treatment may involve only a few (or even one) large dose(s) per fraction. Under these conditions, the choice of appropriate radiobiological model complicates the tasks of predicting radiotherapy outcomes and designing new treatment regimens. The most commonly used model for this purpose is the venerable linear-quadratic (LQ) formalism as it applies to cell survival. However, predictions based on the LQ model are frequently at odds with data following very high acute doses. In particular, although the LQ predicts a continuously bending dose–response relationship for the logarithm of cell survival, empirical evidence over the high-dose region suggests that the survival response is instead log-linear with dose. Here, we show that the distribution of lethal chromosomal lesions among individual human cells (lymphocytes and fibroblasts) exposed to gamma rays and X rays is somewhat overdispersed, compared with the Poisson distribution. Further, we show that such overdispersion affects the predicted dose response for cell survival (the fraction of cells with zero lethal lesions). This causes the dose response to approximate log-linear behavior at high doses, even when the mean number of lethal lesions per cell is well fitted by the continuously curving LQ model. Accounting for overdispersion of lethal lesions provides a novel, mechanistically based explanation for the observed shapes of cell survival dose responses that, in principle, may offer a tractable and clinically useful approach for modeling the effects of high doses per fraction.

• chromosomal aberrations
• lethal lesions
• linear-quadratic model
• overdispersion
• radiation
• stereotactic radiotherapy
• survival curve