Radiobiological Data Research Articles

International horizon-style exercise (HSE): advancing the use of adverse outcome pathway (AOP) in radiation protection

The Adverse Outcome Pathway (AOP) framework provides a means to integrate radiobiological and epidemiological data across different levels of biological organisation for an adverse outcome of interest to regulatory decision-making. The AOP approach is envisioned to improve understanding of radiation-induced effects at low doses and dose-rates and decrease the uncertainty in radiation health risk assessment. To explore the challenges in the use of AOPs, an international horizon-style exercise (HSE) was initiated through the Nuclear Energy Agency (NEA) High-Level Group on Low Dose Research (HLG-LDR) Radiation/Chemical (Rad/Chem) AOP joint topical group. The HSE was completed in three phases. First, candidate research questions were solicited from radiation risk professionals via a dedicated website. Second, the over 250 questions submitted were refined by a dedicated steering committee using a best-worst scaling method. During a virtual 3-day workshop, the list of questions was further refined to the top 25 priority questions. Lastly, an internet-based survey of the broader radiation risk community lead to an orderly ranking of the 25 priority questions, again using a best-worst scaling method. Major themes from the survey included the ability of AOPs to address different levels of biological organisation, radiation quality, dose or dose rate, time patterns, and confounding variables. Broadly, these efforts will help advance the use of AOP in radiation research and regulation.

Seventy Years of Dose-response Models: From the Target Theory to the Use of Big Databases Involving Cell Survival and DNA Repair.

Radiobiological data, whether obtained at the clinical, biological or molecular level has significantly contributed to a better description and prediction of the individual dose-response to ionizing radiation and a better estimation of the radiation-induced risks. Particularly, over the last seventy years, the amount of radiobiological data has considerably increased, and permitted the mathematical formulas describing dose-response to become less empirical. A better understanding of the basic radiobiological mechanisms has also contributed to establish quantitative inter-correlations between clinical, biological and molecular biomarkers, refining again the mathematical models of description. Today, big data approaches and, more recently, artificial intelligence may finally complete and secure this long process of thinking from the multi-scale description of radiation-induced events to their prediction. Here, we reviewed the major dose-response models applied in radiobiology for quantifying molecular and cellular radiosensitivity and aimed to explain their evolution: Specifically, we highlighted the advances concerning the target theory with the cell survival models and the progressive introduction of the DNA repair process in the mathematical models. Furthermore, we described how the technological advances have changed the description of DNA double-strand break (DSB) repair kinetics by introducing the important notion of DSB recognition, independent of that of DSB repair. Initially developed separately, target theory on one hand and, DSB recognition and repair, on the other hand may be now fused into a unified model involving the cascade of phosphorylations mediated by the ATM kinase in response to any genotoxic stress.

Ionization Detail Parameters for DNA Damage Evaluation in Charged Particle Radiotherapy: Simulation Study Based on Cell Survival Database.

Details of excitation and ionization acts hide a description of the biological effects of charged particle traversal through living tissue. Nanodosimetry enables the introduction of novel quantities that characterize and quantify the particle track structure while also serving as a foundation for assessing biological effects based on this quantification. This presents an opportunity to enhance the planning of charged particle radiotherapy by taking into account the ionization detail. This work uses Monte Carlo simulations with Geant4-DNA code for a wide variety of charged particles and their radiation qualities to analyze the distribution of ionization cluster sizes within nanometer-scale volumes, similar to DNA diameter. By correlating these results with biological parameters extracted from the PIDE database for the V79 cell line, a novel parameter R2 based on ionization details is proposed for the evaluation of radiation quality in terms of biological consequences, i.e., radiobiological cross section for inactivation. By incorporating the probability p of sub-lethal damage caused by a single ionization, we address limitations associated with the usually proposed nanodosimetric parameter Fk for characterizing the biological effects of radiation. We show that the new parameter R2 correlates well with radiobiological data and can be used to predict biological outcomes.

Radiobiological analysis of VMAT treatment plan with flattened and flattening filter free photon beam: an EUD and TCP based comparative study.

This study aimed to evaluate the dosimetric and radiobiological differences between 6MV flattened filter (FF) and flattening filter free (FFF) using volumetric modulated arc (VMAT) technique for head and neck (H&N) cancer patients. Fifteen patients with H&N carcinoma were selected and treated with VMAT with FF (VMATFF) treatment plan. Retrospectively, additional VMAT treatment plans were developed using FFF beams (VMATFFF). Radiobiological parameters, such as equivalent uniform dose (EUD), tumor cure probability (TCP), and normal tissue complication probability (NTCP), were calculated using Niemierko's model for both VMATFF and VMATFFF. Correlation between dosimetric and radiobiological data were analyzed and compared. The conformity index (CI) was 0.975 ± 0.014 (VMATFF) and 0.964 ± 0. 019 (VMATFFF) with p ≥ 0.05. Statistically, there was an insignificant difference in the planning target volume (PTV) results for TCP (%) values, with values of 81.20 ± 0.88% (VMATFF) and 81.01 ± 0.92 (%) (VMATFF). Similarly, there was an insignificant difference in the EUD (Gy) values, which were 71.53 ± 0.33 Gy (VMATFF) and 71.46 ± 0.34 Gy (VMATFFF). The NTCP values for the spinal cord, left parotid, and right parotid were 6.54 × 10-07%, 8.04%, and 7.69%, respectively, in the case of VMATFF. For VMATFFF, the corresponding NTCP values for the spinal cord, parotids left, and parotid right were 3.09 × 10-07%, 6.57%, and 6.73%, respectively. The EUD and Mean Dose to PTV were strongly correlated for VMATFFF. An increased mean dose to the PTV and greater TCP were reported for the VMATFF, which can enhance the delivery of the therapeutic dose to the target.

Sensitivity of a mini-TEPC to radiation quality variations in clinical proton beams

PurposeThis work aims at studying the sensitivity of a miniaturized Tissue-Equivalent Proportional Counter to variations of beam quality in clinical radiation fields, to further investigate its performances as radiation quality monitor. MethodsMeasurements were taken at the CATANA facility (INFN-LNS, Catania, Italy), in a monoenergetic and an energy-modulated proton beam with the same initial energy of 62 MeV. PMMA layers were placed in front of the detector to measure at different depths along the depth-dose profile. The frequency- and dose-mean lineal energy were compared to the track- and dose-averaged LET calculated by Monte Carlo simulations. A microdosimetric evaluation of the Relative Biological Effectiveness (RBE) was performed and compared with cell survival experiments. ResultsMicrodosimetric distributions measured at identical depths in the two beams show spectral differences reflecting their different radiation quality. Discrepancies are most evident at depths corresponding to the Spread-Out Bragg Peak, while spectra at the entrance and in the dose fall-off regions are similar. This can be explained by the different energy components that compose the pristine and spread-out peaks at each depth. The trend of microdosimetric mean values matches that of calculated LET averages along the entire penetration depth, and the microdosimetric estimation of RBE is consistent with radiobiological data not only at 2 Gy but also at lower dose levels, such as those absorbed by healthy tissues. ConclusionsThe mini-TEPC is sensitive to differences in radiation quality resulting from different modulations of the proton beam, confirming its potential for beam quality monitoring in proton therapy.

Linear energy transfer (LET) distribution outside small radiotherapy field edges produced by 6 MV X-rays

In modern radiotherapy with photons, the absorbed dose outside the radiation field is generally investigated. But it is well known that the biological damage depends not only on the absorbed dose but also on LET. This work investigated the dose-average LET (LΔ,D) outside several small radiotherapy fields to provide information that can help for better evaluating the biological effect in organs at risk close to the tumour volume. The electron fluences produced in liquid water by a 6 MV X-rays Varian iX linac were calculated using the EGSnrc Monte Carlo code. With the electron spectra, LΔ,D calculations were made for eight open small square fields and the reference field at water depths of 0.15 cm, 1.35 cm, 9.85 cm and 19.85 cm and several off-axis distances. The variation of LΔ,D from the centre of the beam to 2 cm outside the field’s edge depends on the field size and water depth. Using radiobiological data reported in the literature for chromosomal aberrations as an endpoint for the induction of dicentrics determined in Human Lymphocytes, we estimated the maximum low-dose relative biological effectiveness, (RBEM) finding an increase of up to 100% from the centre of the beam to 2 cm from the field's edge.

Radiobiological Characterization of Pancreatic Cancer Patient-Derived Organoids

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive and lethal tumors with a 5-year survival rate of less than 10%. Neoadjuvant radio(chemo)therapy aiming tumor downsizing fails in about 70% due to high heterogeneity, strong desmoplastic stroma and intrinsic radioresistance. In this project, pancreatic cancer patient-derived organoids (PDOs) are characterized regarding radioresponse, DNA-damage, proliferation and hypoxia, and clinical patients' outcome is correlated with the preclinical radiobiological data. In contrast to 2D monolayer cultures, PDOs maintain similar appearance, organization and functionality as the original tissue and therefore might have the potential as advanced preclinical model in radiation oncology. The radiation response of nine different pancreatic cancer PDO lines was determined by 3D cell viability assay. PDOs were irradiated with 0, 2, 4, 6, and 8 Gy (CellRad, Precision, USA) 24h after seeding and the ATP-dependent viability assay was performed 72h and 7d after irradiation (RT). Changes in morphology, number, and size were investigated by microscopy at different time points after RT. PDOs were characterized immunohistochemically by y-H2AX (DNA damage), and Ki-67 (proliferation) staining. RNA sequencing data of treatment-naive PDOs were analyzed by gene set enrichment analyses (GSEA) regarding radioresistance. Preclinical results were correlated with corresponding clinical data of PDAC patients. After optimization of the experimental set-up, PDOs showed a dose-dependent decrease in viability 7d after RT and heterogeneity in radioresponse. PDO lines were classified into radiosensitive, -intermediate, and -resistant subclasses. Immunohisto-chemical staining showed a significant increase in DNA double-strand breaks after RT. A correlation between radiosensitivity and enhanced proliferation index Ki67 was observed. Based on RNA sequencing data, OXPHOS- and hypoxia-dependent genes, amongst others, were identified as pathways significantly differentially regulated between the subclasses by GSEA. Preclinical radioresistance was associated with worse survival and poor clinical outcome. The results of the preclinical experiments demonstrate the heterogeneity among PDOs in response to RT reflecting the clinical situation of patients with PDAC. The findings from the GSEA show promising aspects for further experiments to understand the role of hypoxia in PDAC and its effect on radioresistance. PDOs have the potential as a novel translational research platform in radiation oncology. Prospectively, we aim to implement the screening of the radiosensitivity of PDOs in clinical practice for the realization of truly personalized radiotherapy in PDAC patients.

Non-targeted effects and space radiation risks for astronauts on multiple International Space Station and lunar missions

Future space travel to the earth's moon or the planet Mars will likely lead to the selection of experienced International Space Station (ISS) or lunar crew persons for subsequent lunar or mars missions. Major concerns for space travel are galactic cosmic ray (GCR) risks of cancer and circulatory diseases. However large uncertainties in risk prediction occur due to the quantitative and qualitative differences in heavy ion microscopic energy deposition leading to differences in biological effects compared to low LET radiation. In addition, there are sparse radiobiology data and absence of epidemiology data for heavy ions and other high LET radiation. Non-targeted effects (NTEs) are found in radiobiology studies to increase the biological effectiveness of high LET radiation at low dose for cancer related endpoints. In this paper the most recent version of the NASA Space Cancer Risk model (NSCR-2022) is used to predict mission risks while considering NTEs in solid cancer risk predictions. I discuss predictions of space radiation risks of cancer and circulatory disease mortality for US Whites and US Asian-Pacific Islander (API) populations for 6-month ISS, 80-day lunar missions, and combined ISS-lunar mission. Model predictions suggest NTE increase cancer risks by about ∼2.3 fold over a model that ignores NTEs. US API are predicted to have a lower cancer risks of about 30% compared to US Whites. Cancer risks are slightly less than additive for multiple missions, which is due to the decease of risk with age of exposure and the increased competition with background risks as radiation risks increase. The inclusion of circulatory risks increases mortality estimates about 25% and 37% for females and males, respectively in the model ignoring NTEs, and 20% and 30% when NTEs are assumed to modify solid cancer risk. The predictions made here for combined ISS and lunar missions suggest risks are within risk limit recommendations by the National Council on Radiation Protection and Measurements (NCRP) for such missions.

Ionization detail parameters and cluster dose: a mathematical model for selection of nanodosimetric quantities for use in treatment planning in charged particle radiotherapy

Objective. To propose a mathematical model for applying ionization detail (ID), the detailed spatial distribution of ionization along a particle track, to proton and ion beam radiotherapy treatment planning (RTP). Approach. Our model provides for selection of preferred ID parameters (I p ) for RTP, that associate closest to biological effects. Cluster dose is proposed to bridge the large gap between nanoscopic I p and macroscopic RTP. Selection of I p is demonstrated using published cell survival measurements for protons through argon, comparing results for nineteen I p : N k , k = 2, 3, …, 10, the number of ionizations in clusters of k or more per particle, and F k , k = 1, 2, …, 10, the number of clusters of k or more per particle. We then describe application of the model to ID-based RTP and propose a path to clinical translation. Main results. The preferred I p were N 4 and F 5 for aerobic cells, N 5 and F 7 for hypoxic cells. Significant differences were found in cell survival for beams having the same LET or the preferred N k . Conversely, there was no significant difference for F 5 for aerobic cells and F 7 for hypoxic cells, regardless of ion beam atomic number or energy. Further, cells irradiated with the same cluster dose for these I p had the same cell survival. Based on these preliminary results and other compelling results in nanodosimetry, it is reasonable to assert that I p exist that are more closely associated with biological effects than current LET-based approaches and microdosimetric RBE-based models used in particle RTP. However, more biological variables such as cell line and cycle phase, as well as ion beam pulse structure and rate still need investigation. Significance. Our model provides a practical means to select preferred I p from radiobiological data, and to convert I p to the macroscopic cluster dose for particle RTP.

Reassessing lead protective garment assessment using ICRP 103 tissue weighting factors

Lead protective garments worn by medical staff in the presence of x-rays develop defects over time. This work proposes a novel method of assessing the protective efficacy of the garments as defects develop. The proposed method applies updated radiobiology data from ICRP 103. This work applied the as low as reasonably achievable principle to devise a formula through which a maximum allowed defect area in lead protective garments can be calculated. This formula depends on the cross-sectional areas () and ICRP 103 tissue weighting factors () of the most radiosensitive and overlapping organs protected by the garment, the maximum allowed additional effective dose to the garment wearer due to the defects (), and the unattenuated absorbed dose at the surface of the garment (). The maximum allowed defect areas are separated into three regions: above the waist, below the waist, and thyroid. To be conservative, it was assumed that = 50 mGy yr−1, and = 0.3 mSv yr−1. Also conservatively, transmission was assumed to be 0%, as employing a non-zero transmission factor would increase the maximum allowed defect area. Maximum allowed defect areas were as follows: 370 mm2 for above the waist, 37 mm2 for below the waist, and 279 mm2 for the thyroid. These values can be compared to commonly published values which are 670 mm2 for an apron, 15 mm2 over the gonads, and 11–20 mm2 for the thyroid. The proposed method for lead protective garment assessment is highly adaptable as values can be adjusted as radiobiology data are updated, and as values such as radiation dose limits vary across jurisdictions. Future works will include collection of data for unattenuated dose to apron () as it varies across professions, so that garments may be allowed different defect areas if relegated to individuals of specific professions.

Gold Nanorods as Radiopharmaceutical Carriers: Preparation and Preliminary Radiobiological In Vitro Tests

Low-energy electrons (Auger electrons) can be produced via the interaction of photons with gold atoms in gold nanorods (AuNRs). These electrons are similar to those emitted during the decay of technetium-99m (99mTc), a radioactive nuclide widely used for diagnostics in nuclear medicine. Auger and internal conversion (IC) electron emitters appropriately targeted to the DNA of tumors cells may, therefore, represent a new radiotherapeutic approach. 99mTc radiopharmaceuticals, which are used for diagnosis, could indeed be used in theragnostic fields when loaded on AuNRs and delivered to a tumor site. This work aims to provide a proof of concept (i) to evaluate AuNRs as carriers of 99mTc-based radiopharmaceuticals, and (ii) to evaluate the efficacy of Auger electrons emitted by photon-irradiated AuNRs in inducing radio-induced damage in T98G cells, thus mimicking the effect of Auger electrons emitted during the decay of 99mTc used in clinical settings. Data are presented on AuNRs’ chemical characterization (with an aspect ratio of 3.2 and Surface Plasmon Resonance bands at 520 and 680 nm) and the loading of pharmaceuticals (after 99mTc decay) on their surface. Spectroscopic characterizations, such as UV-Vis and synchrotron radiation-induced X-ray photoelectron (SR-XPS) spectroscopies, were performed to investigate the drug–AuNR interaction. Finally, preliminary radiobiological data on cell killing with AuNRs are presented.

Characterization of Intrinsic Radiation Sensitivity in a Diverse Panel of Normal, Cancerous and CRISPR-Modified Cell Lines.

Intrinsic radiosensitivity is a major determinant of radiation response. Despite the extensive amount of radiobiological data available, variability among different studies makes it very difficult to produce high-quality radiosensitivity biomarkers or predictive models. Here, we characterize a panel of 27 human cell lines, including those derived from lung cancer, prostate cancer, and normal tissues. In addition, we used CRISPR-Cas9 to generate a panel of lines with known DNA repair defects. These cells were characterised by measuring a range of biological features, including the induction and repair of DNA double-strand breaks (DSBs), cell cycle distribution, ploidy, and clonogenic survival following X-ray irradiation. These results offer a robust dataset without inter-experimental variabilities for model development. In addition, we used these results to explore correlations between potential determinants of radiosensitivity. There was a wide variation in the intrinsic radiosensitivity of cell lines, with cell line Mean Inactivation Doses (MID) ranging from 1.3 to 3.4 Gy for cell lines, and as low as 0.65 Gy in Lig4-/- cells. Similar substantial variability was seen in the other parameters, including baseline DNA damage, plating efficiency, and ploidy. In the CRISPR-modified cell lines, residual DSBs were good predictors of cell survival (R2 = 0.78, p = 0.009), as were induced levels of DSBs (R2 = 0.61, p = 0.01). However, amongst the normal and cancerous cells, none of the measured parameters correlated strongly with MID (R2 < 0.45), and the only metrics with statistically significant associations are plating efficiency (R2 = 0.31, p = 0.01) and percentage of cell in S phase (R2 = 0.37, p = 0.005). While these data provide a valuable dataset for the modelling of radiobiological responses, the differences in the predictive power of residual DSBs between CRISPR-modified and other subgroups suggest that genetic alterations in other pathways, such as proliferation and metabolism, may have a greater impact on cellular radiation response. These pathways are often neglected in response modelling and should be considered in the future.

Investigation of In-Field and Out-of-Field Radiation Quality With Microdosimetry and Its Impact on Relative Biological Effectiveness in Proton Therapy

Using microdosimetry, this study investigated the relative biological effectiveness (RBE) and quality factor (Q¯) variations in field and out of field as a function of radiation quality for clinical protons. A water phantom with a spread-out Bragg peak (SOBP) was irradiated to acquire microdosimetric spectra at several distal and lateral depths with a tissue equivalent proportional counter. The measurements were used as inputs to microdosimetric kinetic and Loncol models to determine the RBE spatial distribution and compare it with predictions from the dose-averaged linear energy transfer-based McNamara model. Q¯ values and biological and dose equivalent values were also calculated. The data demonstrated that radiation quality changed more rapidly with depth than lateral distance from the SOBP. In beam, yD ranged from approximately 4 keV/μm at the entrance to 8 keV/μm at the SOBP far end, reaching approximately 15 keV/μm at the penumbra. Out of field, the overall highest value of 23 ± 2 keV/μm was observed at the beam-edge penumbra. Radiation quality changes caused RBE deviations from the clinical value of 1.1, whose extent depends on the approach used for assessing radiation quality as well as on the radiobiological model. For RBE10, microdosimetry-based models appeared to better reproduce the radiobiological data than the dose-averaged linear energy transfer model. Out of field, both the RBE and Q¯ values appeared to have limitations in describing the radiation biological effectiveness. This research also presents a first comprehensive benchmark of TOPAS code against in-field and out-of-field microdosimetric spectra of therapeutic protons. Further investigation will be necessary to evaluate the quantitative effects of RBE variations on treatment planning and assess the clinical consequences in terms of both tumor control and normal-tissue toxicity. The achievement of this goal calls for accurate radiobiological data to validate the RBE models.

1419P Radiobiological parameters for the assessment of 177Lu-PSMA-617 radioligand therapy in patients with metastatic castration-resistant prostate cancer

The lack of robust radiobiological data hampers the further optimization of emerging 177Lu-PSMA-directed radioligand therapy (RLT). This study aims to explore several conventional radiobiological parameters in the assessment of outcomes in tumor and normal organs at risk (OARs) for castration-resistant prostate cancer (CRPC) patients. 20 patients received a median of 3 (range 1–6, a totally of 86 cycles) 177Lu-PSMA-617 RLT were retrospectively included. Hematological status, renal and liver function, and serum PSA test before and within two weeks post-therapy were documented. Pre-therapy PSMA-PET/CT image dates were collected to establish CT-based organ segmentation. The post-therapy dosimetry of each patient was measured using at least 3-time-points SPECT/CT imaging. PSA was used to determine therapy response, and the related adverse events were documented. Dose parameters including conventional radiobiological such as absorbed dose, integral dose (D10/50/90), biologically effective doses (BED) and cumulated BEDs (cBED) were tested. All patients are well-tolerated and 19/20 patients received a partial response post-therapy. The dosimetry evaluation demonstrated a high absorbed dose in tumors compared to OARs (p<.0001). The Dosemean/max/sum of target organs decreases as the treatment cycle increases. The absorbed dose in non-tumor-bearing bones is significantly correlated with hematological AEs (G2-4) (p<.05). The patients with larger PET-based tumor volumes present higher absorbed doses in tumor and OARs (also when normalized to the administered activity). The highest D10/50/90 was received by tumor-bearing bone, the whole-body tumor and lymph/visceral regions respectively compared to OARs. BED1.5 (AUROC: 0.633) and cBED1.5 (AUROC: 0.714) demonstrated aggregable diagnostic accuracy in detecting better post-treatment PSA outcomes. Despite the limited number of patients in this study, the preliminary results encourage the exploration of radiobiological models in the assessment of PSMA-RLT. In-depth analysis and interpretation of these radiobiological parameters are still ongoing.

Inadvertent Radiation Exposures in Combat Zones: Risk of Contamination and Radiobiologic Consequences.

On February 24, 2022, Russia began a military invasion of Ukraine. Missile and air strikes were reported throughout the country, shortly followed by a large ground invasion from multiple directions. Four major theaters developed: the Kyiv offensive, the Northeastern Ukraine offensive, the Eastern Ukraine offensive, and the Southern Ukraine offensive, with continued missile and air strikes far into Western Ukraine. Advancing Russian military units launched an attack and captured the Chernobyl nuclear station. Russian troops dug trenches into the area commonly known as the "Red Forest," violating the established radiation safety measures and threatening security within the Chernobyl Exclusion Zone. The placement of military units in such close proximity to the station also sparked concerns of possible damage occurring to the containment vessel constructed around the station's wrecked fourth reactor. There are 15 operating nuclear reactors in Ukraine. Each is vulnerable to an attack or sabotage that could precipitate a malfunction and possible release of radioactive isotopes. In this short commentary, we will discuss radiobiologic data obtained after the analysis of historical nuclear power plant (NPP) accidents and emphasize new challenges for nuclear security when NPPs are found and are possible targets within a conflict zone.

Comparison of Photon Isoeffective Dose Models Based on In Vitro and In Vivo Radiobiological Experiments for Head and Neck Cancer Treated with BNCT.

Boron neutron capture therapy (BNCT) is a treatment modality for cancer that involves radiations of different qualities. A formalism that proved suitable to compute doses in photon-equivalent units is the photon isoeffective dose model. This study addresses the question whether considering in vitro or in vivo radiobiological studies to determine the parameters involved in photon isoeffective dose calculations affects the consistency of the model predictions. The analysis is focused on head and neck squamous cell carcinomas (HNSCC), a main target that proved to respond to BNCT. The photon isoeffective dose model for HNSCC with parameters from in vitro studies using the primary human cell line UT-SCC-16A was introduced and compared to the one previously reported with parameters from an in vivo oral cancer model in rodents. Both models were first compared in a simple scenario by means of tumor dose and control probability calculations. Then, the clinical impact of the different dose models was assessed from the analysis of a group of squamous cell carcinomas (SCC) patients treated with BNCT. Traditional dose calculations using the relative biological effectiveness factors derived from the SCC cell line were also analyzed. Predictions of tumor control from the evaluated models were compared to the patients' outcome. The quantification of the biological effectiveness of the different radiations revealed that relative biological effectiveness/compound biological effectiveness (RBE/CBE) factors for the SCC cell line are up to 20% higher than those assumed in clinical BNCT, highlighting the importance of using experimental data intimately linked to the tumor type to derive the model's parameters. The comparison of the different models showed that photon isoeffective doses based on in vitro data are generally greater than those from in vivo data (∼8-16% for total tumor absorbed doses of 10-15 Gy). However, the predictive power of the two models was not affected by these differences: both models fulfilled conditions to guarantee a good predictive performance and gave predictions statistically compatible with the clinical outcome. On the other hand, doses computed with the traditional model were substantially larger than those obtained with both photon isoeffective models. Moreover, the traditional model is statistically rejected, which reinforces the assertion that its inconsistencies are intrinsic and not due to the use of RBE/CBE factors obtained for a tumor type different from HN cancer. The results suggest that the nature of the radiobiological data would not affect the consistency of the photon isoeffective dose model in the studied cases of SCC head and neck cancer treated with BPA-based BNCT.

The Unified Approach of Ionizing Radiation on Biological Matter: Action of Heavy Charged Particles on Mammalian Cells

Damaging effects to mammalian cells by heavy charged particles have been realized in terms of the mean free path for linear primary ionization (the spacing of ionizing events along the charged particle tracks) using in vitro radiobiological experimentation data. Damage is found to be optimum when the mean free path for linear primary ionization along the tracks in the cell nucleus matches the mean chord length of approximately 1.8 nm through a DNA segment. A simple semi-theoretical model is proposed to define absolute biological effectiveness based on effect inactivation cross section s (mm2) which is interrelated to the mean free path for linear primary ionization l. For heavy charged particles, the model shows a saturation region for the effect cross section, ss = 60 mm2 for l ≤ 1.8 nm. The model explains the mechanisms leading to cell death via DNA strand scissions. In the saturation region, double strand breaks of the DNA are predominant, unrepaired or mismatched repair processes lead to maximum damage. At higher mean free path; l &gt; 1.8 nm, single strand breaks of the DNA is the main basic mechanism and thus repairable processes are possible.

Education in Radiation Oncology-Current Challenges and Difficulties.

The evolution and development of radiotherapy in the last two decades has meant that postgraduate medical training has not kept up with this rapid progress both in terms of multidisciplinary clinical approaches and especially in terms of technological advances. Education in radiation oncology is a major priority in the context of the rapid development of radiotherapy, including advanced knowledge of radiobiology, radiation physics and clinical oncology, anatomy, tumor biology and advanced medical imaging. In this context, the lack of training in radiation oncology in the curricula of medical faculties may have detrimental consequences for the training of residents in radiotherapy but also in their choice of specialty after completing their university studies. There is a clear gap between resident physicians’ actual and required knowledge of radiotherapy, and this requires urgent remediation. In the context of technical advances in imaging-guided radiotherapy (IGRT) and new radiobiology data, a balanced approach divided equally between general oncology, clinical radiation oncology, radiation oncology technology, medical physics and radiobiology, anatomy and multimodal imaging, including mentorship could bring educational and career choice benefits for students of radiation oncology.

Radiobiological approach to treatment gaps in locally advanced head and neck cancers radical radiotherapy arising from the COVID-19 pandemic.

Gaps of radiotherapy treatment are one of the factors recognized as unfavorable in terms of tumor control and disease prognosis. All strategies for compensating the negative effect of radiotherapy treatment gaps are based on radiobiological models. Using the modified square linear formalism (Dale`s equation) it is possible to calculate the additional dose in order to compensate the accelerated tumor repopulation effect. SARS-CoV-2 infection is an important factor that can lead to an interruption of irradiation for medium and long- term intervals. We aim to present the radiobiological data underlying the recalculation of radiotherapy treatment and exemplification for different clinical scenarios in the case of head and neck cancers (Ref. 17). Keywords: adiobiology, treatment gaps, locally advanced head and neck cancers, radical radiotherapy, COVID-19 pandemic.

Радиобиологическая модель расчёта вероятности гибели клеток млекопитающих при облучении их ионизирующим излучением с разной линейной потерей энергии

One of the fundamental problems of radiobiology is to predict a quantitative relationship between the onset of a specified radiation-induced effect on a biological object and the dose of exposure to ionizing radiation under different conditions (for ionizing radiation of different quality and different time of exposure). The purpose of this article is to solve a particular part of the general problem: the development of a mathematical model for the probability of death of mammalian cells depending on the radiation dose with arbitrarily specified linear energy transfer (LET), with a single irradiation of these cells in vitro. To solve this problem, microdosimetric approaches based on the theory of the dual action of radiation were used. When developing the model, the following assumptions were used: 1) there are sensitive volumes (SVs) in the cell, damage to the volumes can lead to cell death; 2) the probability of cell death depends on the number of damaged SVs; 3) the probability of damage to the SVs depends on the energy absorbed in it; 4) to calculate the energy absorbed in the SVs, a simple model for the interaction of ionizing particles with matter was used: the particles move in a straight line, the LET of the particles coincide with the linear energy absorbed in the matter. The developed mathematical model for estimating relationship of the probability of cell death on the dose explicitly contains LET. Thus, the use of the proposed model makes possible separation of biological parameters responsible for the onset of radiation-induced effect from radiation characteristics of the irradiation conditions., Classical radiobiological data, underlying the IAEA ionizing radiation recommendations for determining the relative biological effectiveness (RBE) of different types present an argument for the model validation. Experimental data on irradiation of human kidney T1 cells present an example. The article demonstrates that the developed model makes it possible to calculate the probability of cell death depending on the dose of ionizing radiation with an arbitrarily set LET for photons, electrons, and -particles with a LET from 0.4 to 200 keV/ µm. It follows from the proposed model that a linear-quadratic dependence can occur not only in DNA damage, but also in other biologically important molecules. The use of this model can be extended to predict other radiation-induced effects, as well as the probability of occurrence of radiation-induced effects under various time exposure regimes.