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Ianik Plante

Publications and source records attributed to Ianik Plante.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

A Computationally Efficient Algorithm for Sampling the Rudd Differential Cross Section

Monte Carlo radiation transport codes such as RITRACKS or Geant4 are used to simulate the interaction of ions with matter. These codes rely on sampling algorithms to determine interactions and various physical properties of particles involved in the simulations. It is crucial to develop efficient sampling algorithms since Monte Carlo radiation transport simulations can be time consuming. This work presents an efficient sampling algorithm to determine the energy of secondary electrons following ion-water interactions. The applicability and intended use of the algorithm are discussed in detail, and it is shown that the new algorithm is up to 6X10 4 times faster than the method currently used in Geant4-DNA.

Floriane Poignant↗
NASA NTRS2024

DNA Break Clustering as a Predictor of Cell Death across Various Radiation Qualities: Influence of Cell Size, Cell Asymmetry, and Beam Orientation

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ∼0.2keV/μmto∼3000keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area either because of a smaller size or a change in beam orientation have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects.

cell survival↗
NASA NTRS2024

Comparison of Geant4-DNA and RITRACKS/RITCARD: Microdosimetry, Nanodosimetry and DNA Damage Predictions for Low to High LET Ions

Low linear energy transfer (LET) ionizing radiations induce homogeneously distributed DNA damage at the cellular scale, while high LET ionizing radiations are well known to create complex biological damage including clustered double strand breaks (DSB). Clustered DSB are critical events that are difficult to repair, leading to increased biological outcomes compared to low LET radiation exposure. Recent studies have shown that DNA compaction, which can be actively modified by the cell to allow DNA repair, influences the yield of DSB [1]. The goal of this work is to determine the impact of DNA compaction on chromosome aberration formation, a biomarker of radiation-induced cancer risk. The RITRACKS track structure code [2], together with the RITCARD code [3], allow one to simulate the transport of high LET ions, calculate DNA damage and repair, and chromosome aberration formation, but does not include detailed geometrical models of DNA. The Geant4-DNA toolkit provides such detailed models with different levels of DNA compaction [1,4], but does not model chromosome aberration formation. In this work, these highly detailed DNA geometries are used to compute DNA breaks with Geant4-DNA and combine the results with the RITCARD tool to compute chromosome aberrations. As a first step, we compared the transport models used in RITRACKS and Geant4-DNA and newly released heavy ion model transport (G4DNARuddIonisationExtendedModel Geant4 v11.2) to ensure consistency between the physical stage of the two radiation transport codes. We compared energy deposition at the micrometric and nanometric scales for different ions (H 250 MeV, H 150 Me, He 250 MeV/n, C 290 MeV/n, O 350 MeV/n, O 55 MeV/n, Si 170MeV/n, Ti 300 MeV/n, Ti 300 MeV/n, Fe 600 MeV/n, Fe 450 MeV/n and Fe 300 MeV/n) with LET ranging from ~0.4 keV/μm up to 235 keV/μm. Excellent agreement is found for both microdosimetric and nanodosimetric spectra for all ion types and energies. The calculation of DNA breaks and their complexity with the Geant4-DNA is an ongoing work, and comparison with RITCARD will be presented based on result availability at the time of the conference. [1] Tang et al. (2019). Med. Phys., 46(3), 1501-1511. [2] Plante et al. (2008). NJP, 10(12), 125020. [3] Plante et al. (2019). Rad. Res., 192(3), 282-298. [4] Incerti et al. (2018). Med. Phys., 45(8), e722-e739.

Floriane Poignant↗
NASA NTRS2024

Integration of the Cardiovascular Risk Model Astro-CHARM in the NASA Radiation Risk Model

Space radiation poses an increased risk for cardiovascular diseases (CVD) during and after spaceflight, that should be quantified to plan future space missions such as the flight to Mars. The radiation-induced CVD risk is evaluated using a linear no-threshold dose response excess relative risk (ERR) model, so that the risk is function of the radiation dose and of the background (i.e., non-exposed) incidence rate. The background CVD risk can be evaluated using clinical prediction models (CPMs). The first CPMs developed in the 1960’s have identified CVD risk factors such as blood pressure, diabetes, cholesterol, and smoking. In this work, the steps used to integrate the CVD risk provided by a CPM into the NASA Radiation Risk Model are described. Simulation results calculated using available data for relevant mission scenarios are also shown, and the challenges in CVD risk predictions are discussed.

Space radiation↗
NASA NTRS2021

PolyFit: A C++ code for Polynomial Curve Fit with Calculation of Error Bars

In radiobiology, many dose-response results are modeled using the so-called linear-quadratic(LQ)model, which means that results are modeled as a function of dose Das 𝑅(𝐷)=𝛽0+𝛽1𝐷+𝛽2𝐷2. The coefficients 𝛽0, 𝛽1and 𝛽2are obtained from fitting a series of data points (𝑥𝑖,𝑦𝑖), which is usually done using a least-square method. The LQ and more generally the polynomial fit capability is implemented in many software that analyzes data. However, it is often convenient to do the fitting programmatically, especially when a large number of datasets should be analyzed. Furthermore, depending on the software used, some features may not be implemented. In this mini-review, I discuss the basis of polynomial fitting, including the calculation of errors on the coefficients and results, use of weighting and fixing the intercept value (the coefficient 𝛽0). A simple C++ code to perform the polynomial curve fitting is also provided. This code should be useful not only in radiobiology but in other fields of science as well.

Ianik Plante↗
NASA NTRS2021

PolyFit: A C++ code for Polynomial Curve Fit with Calculation of Error Bars

In radiobiology, many dose-response results are modeled using the so-called linear-quadratic (LQ)model, which means that results are modeled as a function of dose Das 𝑅(𝐷)=𝛽0+𝛽1𝐷+𝛽2𝐷2. The coefficients 𝛽0, 𝛽1and 𝛽2are obtained from fitting a series of data points (𝑥𝑖, 𝑦𝑖), which is usually done using a least-square method. The LQ and more generally the polynomial fit capability is implemented in many software that analyzes data. However, there are some instances where the fitting needs to be done programmatically. Furthermore, depending on the software used, some features may not be implemented. In this mini-review, I discuss the basis of polynomial fitting, including the calculation of errors on the coefficients and results, use of weighting and fixing the intercept value (the coefficient 𝛽0). A simple C++ code to perform the polynomial curve fitting is also provided. This code should be useful not only in radiobiology but in other fields of science as well.

Ianik Plante↗
NASA NTRSDate not supplied

Track Structure Components: Characterizing Energy Deposition from Direct and Peripheral Hits in Spherical Cells

Energy deposition by ionizing radiation in micrometric targets (microdosimetry), representative of cells, is very important to understand the effect of radiation and the cellular and biological response. Microdosimetry is used to estimate quality factors for risk assessment in radiation protection and quantify Relative Biological Effectiveness (RBE) for treatment planning of hadron radiation therapy. Radiation physics has shown that ionizing radiation deposit their energy in a complex manner, the track structure. Consequently, energy deposited in a target is a function of factors like the ion type, its energy and the irradiated volume.

Ianik Plante↗
NASA NTRSDate not supplied

Predicting cell death and mutation frequency for a wide spectrum of LET and across cell lines from DNA break clustering inside repair domains

Cosmic radiation, which is composed of high charged and energy (HZE) particles, is responsible for cell death and mutation, which may be involved in cancer induction. Mutations are consequences of mis-repaired DNA breaks – especially double-strand breaks (DSBs) – that induce inter- and intra-chromosomal rearrangements (translocations, deletions, inversion). In this study, a computer simulation model is used to investigate the clustering of DSBs in repair domains, previously evidenced by our group in human breast cells. This model is calibrated with experimental data measuring persistent 53BP1 radiation-induced foci (RIF) and is used to explain the high relative biological effectiveness (RBE) of HZE for both cell death and DNA mutation frequencies. We first validate our DSB cluster model using a new track structure model deployed on a simple geometrical configuration for repair domains in the nucleus; then we extend the scope from cell death to mutation induction. This work suggests that mechanism based on DSB repair process can explain several biological effects induced by HZE particles on different type of living cells.

Ianik Plante↗
NASA NTRSDate not supplied

Utility of Terrestrial Cardiovascular Disease Data in Astronaut Radiation Risk Assessment – A Case Study Showing Increased Risk with Clonal Hematopoiesis of Indeterminate Potential

Cardiovascular disease (CVD) is associated with high doses of radiation and is are cognized health risk for astronauts on multiple or long duration exploration missions to the Moon or Mars. Currently, radiation risk assessment is based on background population disease rates and does not consider individual risk factors that may modify analysis, especially at lower radiation doses.

Zarana S Patel↗
NASA NTRSDate not supplied

Modeling Space-Radiation Induced Chromosome Aberrations

Exposure to ionizing radiation is identified as one of the main hazards of space flight. Galactic cosmic rays (GCRs) are composed of energetic protons (87%), helium nuclei (12%) and high-charge and energy (HZE) ions. At the cellular scale, HZE ions have a pattern of energy deposition that depends on the ion linear energy transfer (LET), with high LET ions favoring the formation of complex DNA damages that induce chromosome aberrations (CAs). Understanding how physical (e.g., ion type and energy) and biological (e.g., cell type) parameters impact CA formation is required to assess space radiation risks such as carcinogenesis. The Monte Carlo tool RITCARD/RITRACKS [1,2] developed by NASA allows simulation of the transport of HZE ions and subsequent energy deposition at the cellular scale and models the creation of DNA double strand breaks (DSBs), DNA repair and formation of CAs. We used this radiation transport code to further understand how radiation quality and cell size affects CA formation.

Floriane Poignant↗