Experimental Validation of an Analytical Program and a Monte Carlo Simulation for the Computation of the Far Out-of-Field Dose in External Beam Photon Therapy Applied to Pediatric Patients.

Background: The out-of-the-field absorbed dose affects the probability of primary second radiation-induced cancers. This is particularly relevant in the case of pediatric treatments. There are currently no methods employed in the clinical routine for the computation of dose distributions from stray radiation in radiotherapy. To overcome this limitation in the framework of conventional teletherapy with photon beams, two computational tools have been developed-one based on an analytical approach and another depending on a fast Monte Carlo algorithm. The purpose of this work is to evaluate the accuracy of these approaches by comparison with experimental data obtained from anthropomorphic phantom irradiations. Materials and Methods: An anthropomorphic phantom representing a 5-year-old child (ATOM, CIRS) was irradiated considering a brain tumor using a Varian TrueBeam linac. Two treatments for the same planned target volume (PTV) were considered, namely, intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). In all cases, the irradiation was conducted with a 6-MV energy beam using the flattening filter for a prescribed dose of 3.6 Gy to the PTV. The phantom had natLiF : Mg, Cu, P (MCP-N) thermoluminescent dosimeters (TLDs) in its 180 holes. The uncertainty of the experimental data was around 20%, which was mostly attributed to the MCP-N energy dependence. To calculate the out-of-field dose, an analytical algorithm was implemented to be run from a Varian Eclipse TPS. This algorithm considers that all anatomical structures are filled with water, with the exception of the lungs which are made of air. The fast Monte Carlo code dose planning method was also used for computing the out-of-field dose. It was executed from the dose verification system PRIMO using a phase-space file containing 3x109 histories, reaching an average standard statistical uncertainty of less than 0.2% (coverage factor k = 1 ) on all voxels scoring more than 50% of the maximum dose. The standard statistical uncertainty of out-of-field voxels in the Monte Carlo simulation did not exceed 5%. For the Monte Carlo simulation the actual chemical composition of the materials used in ATOM, as provided by the manufacturer, was employed. Results: In the out-of-the-field region, the absorbed dose was on average four orders of magnitude lower than the dose at the PTV. For the two modalities employed, the discrepancy between the central values of the TLDs located in the out-of-the-field region and the corresponding positions in the analytic model were in general less than 40%. The discrepancy in the lung doses was more pronounced for IMRT. The same comparison between the experimental and the Monte Carlo data yielded differences which are, in general, smaller than 20%. It was observed that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT. Conclusions: The proposed computational methods for the routine calculation of the out-of-the-field dose produce results that are similar, in most cases, with the experimental data. It has been experimentally found that the VMAT irradiation produces the smallest out-of-the-field dose when compared to IMRT for a given PTV.

Validation of a Monte Carlo Framework for Out-of-Field Dose Calculations in Proton Therapy.

Proton therapy enables to deliver highly conformed dose distributions owing to the characteristic Bragg peak and the finite range of protons. However, during proton therapy, secondary neutrons are created, which can travel long distances and deposit dose in out-of-field volumes. This out-of-field absorbed dose needs to be considered for radiation-induced secondary cancers, which are particularly relevant in the case of pediatric treatments. Unfortunately, no method exists in clinics for the computation of the out-of-field dose distributions in proton therapy. To help overcome this limitation, a computational tool has been developed based on the Monte Carlo code TOPAS. The purpose of this work is to evaluate the accuracy of this tool in comparison to experimental data obtained from an anthropomorphic phantom irradiation. An anthropomorphic phantom of a 5-year-old child (ATOM, CIRS) was irradiated for a brain tumor treatment in an IBA Proteus Plus facility using a pencil beam dedicated nozzle. The treatment consisted of three pencil beam scanning fields employing a lucite range shifter. Proton energies ranged from 100 to 165 MeV. A median dose of 50.4 Gy(RBE) with 1.8 Gy(RBE) per fraction was prescribed to the initial planning target volume (PTV), which was located in the cerebellum. Thermoluminescent detectors (TLDs), namely, Li-7-enriched LiF : Mg, Ti (MTS-7) type, were used to detect gamma radiation, which is produced by nuclear reactions, and secondary as well as recoil protons created out-of-field by secondary neutrons. Li-6-enriched LiF : Mg,Cu,P (MCP-6) was combined with Li-7-enriched MCP-7 to measure thermal neutrons. TLDs were calibrated in Co-60 and reported on absorbed dose in water per target dose (µGy/Gy) as well as thermal neutron dose equivalent per target dose (µSv/Gy). Additionally, bubble detectors for personal neutron dosimetry (BD-PND) were used for measuring neutrons (>50 keV), which were calibrated in a Cf-252 neutron beam to report on neutron dose equivalent dose data. The Monte Carlo code TOPAS (version 3.6) was run using a phase-space file containing 1010 histories reaching an average standard statistical uncertainty of less than 0.2% (coverage factor k = 1) on all voxels scoring more than 50% of the maximum dose. The primary beam was modeled following a Fermi-Eyges description of the spot envelope fitted to measurements. For the Monte Carlo simulation, the chemical composition of the tissues represented in ATOM was employed. The dose was tallied as dose-to-water, and data were normalized to the target dose (physical dose) to report on absorbed doses per target dose (mSv/Gy) or neutron dose equivalent per target dose (µSv/Gy), while also an estimate of the total organ dose was provided for a target dose of 50.4 Gy(RBE). Out-of-field doses showed absorbed doses that were 5 to 6 orders of magnitude lower than the target dose. The discrepancy between TLD data and the corresponding scored values in the Monte Carlo calculations involving proton and gamma contributions was on average 18%. The comparison between the neutron equivalent doses between the Monte Carlo simulation and the measured neutron doses was on average 8%. Organ dose calculations revealed the highest dose for the thyroid, which was 120 mSv, while other organ doses ranged from 18 mSv in the lungs to 0.6 mSv in the testes. The proposed computational method for routine calculation of the out-of-the-field dose in proton therapy produces results that are compatible with the experimental data and allow to calculate out-of-field organ doses during proton therapy.

Epidemiological Studies of Low-Dose Ionizing Radiation and Cancer: Summary Bias Assessment and Meta-Analysis.

BACKGROUND: Ionizing radiation is an established carcinogen, but risks from low-dose exposures are controversial. Since the Biological Effects of Ionizing Radiation VII review of the epidemiological data in 2006, many subsequent publications have reported excess cancer risks from low-dose exposures. Our aim was to systematically review these studies to assess the magnitude of the risk and whether the positive findings could be explained by biases. METHODS: Eligible studies had mean cumulative doses of less than 100 mGy, individualized dose estimates, risk estimates, and confidence intervals (CI) for the dose-response and were published in 2006-2017. We summarized the evidence for bias (dose error, confounding, outcome ascertainment) and its likely direction for each study. We tested whether the median excess relative risk (ERR) per unit dose equals zero and assessed the impact of excluding positive studies with potential bias away from the null. We performed a meta-analysis to quantify the ERR and assess consistency across studies for all solid cancers and leukemia. RESULTS: Of the 26 eligible studies, 8 concerned environmental, 4 medical, and 14 occupational exposure. For solid cancers, 16 of 22 studies reported positive ERRs per unit dose, and we rejected the hypothesis that the median ERR equals zero (P = .03). After exclusion of 4 positive studies with potential positive bias, 12 of 18 studies reported positive ERRs per unit dose (P = .12). For leukemia, 17 of 20 studies were positive, and we rejected the hypothesis that the median ERR per unit dose equals zero (P = .001), also after exclusion of 5 positive studies with potential positive bias (P = .02). For adulthood exposure, the meta-ERR at 100 mGy was 0.029 (95% CI = 0.011 to 0.047) for solid cancers and 0.16 (95% CI = 0.07 to 0.25) for leukemia. For childhood exposure, the meta-ERR at 100 mGy for leukemia was 2.84 (95% CI = 0.37 to 5.32); there were only two eligible studies of all solid cancers. CONCLUSIONS: Our systematic assessments in this monograph showed that these new epidemiological studies are characterized by several limitations, but only a few positive studies were potentially biased away from the null. After exclusion of these studies, the majority of studies still reported positive risk estimates. We therefore conclude that these new epidemiological studies directly support excess cancer risks from low-dose ionizing radiation. Furthermore, the magnitude of the cancer risks from these low-dose radiation exposures was statistically compatible with the radiation dose-related cancer risks of the atomic bomb survivors.

The HARMONIC project: study design for the assessment of radiation doses and associated cancer risks following cardiac fluoroscopy in childhood.

The HARMONIC project (Health Effects of Cardiac Fluoroscopy and Modern Radiotherapy in Paediatrics) is a European study aiming to improve our understanding of the long-term health risks from radiation exposures in childhood and early adulthood. Here, we present the study design for the cardiac fluoroscopy component of HARMONIC. A pooled cohort of approximately 100 000 patients who underwent cardiac fluoroscopy procedures in Belgium, France, Germany, Italy, Norway, Spain or the UK, while aged under 22 years, will be established from hospital records and/or insurance claims data. Doses to individual organs will be estimated from dose indicators recorded at the time of examination, using a lookup-table-based dosimetry system produced using Monte Carlo radiation transport simulations and anatomically realistic computational phantom models. Information on beam geometry and x-ray energy spectra will be obtained from a representative sample of radiation dose structured reports. Uncertainties in dose estimates will be modelled using 2D Monte Carlo methods. The cohort will be followed up using national registries and insurance records to determine vital status and cancer incidence. Information on organ transplantation (a major risk factor for cancer development in this patient group) and/or other conditions predisposing to cancer will be obtained from national or local registries and health insurance data, depending on country. The relationship between estimated radiation dose and cancer risk will be investigated using regression modelling. Results will improve information for patients and parents and aid clinicians in managing and implementing changes to reduce radiation risks without compromising medical benefits.

Site-specific Solid Cancer Mortality After Exposure to Ionizing Radiation: A Cohort Study of Workers (INWORKS).

BACKGROUND: There is considerable scientific interest in associations between protracted low-dose exposure to ionizing radiation and the occurrence of specific types of cancer. METHODS: Associations between ionizing radiation and site-specific solid cancer mortality were examined among 308,297 nuclear workers employed in France, the United Kingdom, and the United States. Workers were monitored for external radiation exposure and follow-up encompassed 8.2 million person-years. Radiation-mortality associations were estimated using a maximum-likelihood method and using a Markov chain Monte Carlo method, the latter used to fit a hierarchical regression model to stabilize estimates of association. RESULTS: The analysis included 17,957 deaths attributable to solid cancer, the most common being lung, prostate, and colon cancer. Using a maximum-likelihood method to quantify associations between radiation dose- and site-specific cancer, we obtained positive point estimates for oral, esophagus, stomach, colon, rectum, pancreas, peritoneum, larynx, lung, pleura, bone and connective tissue, skin, ovary, testis, and thyroid cancer; in addition, we obtained negative point estimates for cancer of the liver and gallbladder, prostate, bladder, kidney, and brain. Most of these estimated coefficients exhibited substantial imprecision. Employing a hierarchical model for stabilization had little impact on the estimated associations for the most commonly observed outcomes, but for less frequent cancer types, the stabilized estimates tended to take less extreme values and have greater precision than estimates obtained without such stabilization. CONCLUSIONS: The results provide further evidence regarding associations between low-dose radiation exposure and cancer.

Assessing organ doses from paediatric CT scans--a novel approach for an epidemiology study (the EPI-CT study).

The increasing worldwide use of paediatric computed tomography (CT) has led to increasing concerns regarding the subsequent effects of exposure to radiation. In response to this concern, the international EPI-CT project was developed to study the risk of cancer in a large multi-country cohort. In radiation epidemiology, accurate estimates of organ-specific doses are essential. In EPI-CT, data collection is split into two time periods--before and after introduction of the Picture Archiving Communication System (PACS) introduced in the 1990s. Prior to PACS, only sparse information about scanner settings is available from radiology departments. Hence, a multi-level approach was developed to retrieve information from a questionnaire, surveys, scientific publications, and expert interviews. For the years after PACS was introduced, scanner settings will be extracted from Digital Imaging and Communications in Medicine (DICOM) headers, a protocol for storing medical imaging data. Radiation fields and X-ray interactions within the body will be simulated using phantoms of various ages and Monte-Carlo-based radiation transport calculations. Individual organ doses will be estimated for each child using an accepted calculation strategy, scanner settings, and the radiation transport calculations. Comprehensive analyses of missing and uncertain dosimetry data will be conducted to provide uncertainty distributions of doses.