A Review of Numerical Models of Radiation Injury and Repair Considering Subcellular Targets and the Extracellular Microenvironment.

Astronauts in space are subject to continuous exposure to ionizing radiation. There is concern about the acute and late-occurring adverse health effects that astronauts could incur following a protracted exposure to the space radiation environment. Therefore, it is vital to consider the current tools and models used to describe and study the organic consequences of ionizing radiation exposure. It is equally important to see where these models could be improved. Historically, radiobiological models focused on how radiation damages nuclear deoxyribonucleic acid (DNA) and the role DNA repair mechanisms play in resulting biological effects, building on the hypotheses of Crowther and Lea from the 1940s and 1960s, and they neglected other subcellular targets outside of nuclear DNA. The development of these models and the current state of knowledge about radiation effects impacting astronauts in orbit, as well as how the radiation environment and cellular microenvironment are incorporated into these radiobiological models, aid our understanding of the influence space travel may have on astronaut health. It is vital to consider the current tools and models used to describe the organic consequences of ionizing radiation exposure and identify where they can be further improved.

Medical workforce in the United States.

This section focuses on the professional workforce comprised of the primary medical specialties that utilize ionizing radiation in their practices. Those discussed include the specialties of radiology and radiation oncology, as well as the subspecialties of radiology, namely diagnostic radiology, interventional radiology, nuclear radiology, and nuclear medicine. These professionals provide essential health care services, for example, the interpretation of imaging studies, the provision of interventional procedures, radionuclide therapeutic treatments, and radiation therapy. In addition, they may be called on to function as part of a radiologic emergency response team to care for potentially exposed persons following radiation events, for example, detonation of a nuclear weapon, nuclear power plant accidents, and transportation incidents. For these reasons, maintenance of an adequate workforce in each of these professions is essential to meeting the nation's future needs. Currently, there is a shortage for all physicians in the medical radiology workforce.

Proton therapy for adults with mediastinal lymphomas: the International Lymphoma Radiation Oncology Group guidelines.

Among adult lymphoma survivors, radiation treatment techniques that increase the excess radiation dose to organs at risk (OARs) put patients at risk for increased side effects, especially late toxicities. Minimizing radiation to OARs in adults patients with Hodgkin and non-Hodgkin lymphomas involving the mediastinum is the deciding factor for the choice of treatment modality. Proton therapy may help to reduce the radiation dose to the OARs and reduce toxicities, especially the risks for cardiac morbidity and second cancers. Because proton therapy may have some disadvantages, identifying the patients and the circumstances that may benefit the most from proton therapy is important. We present modern guidelines to identify adult lymphoma patients who may derive the greatest benefit from proton therapy, along with an analysis of the advantages and disadvantages of proton treatment.

Justification and optimization of radiation exposures: a new framework to aggregate arbitrary detriments and benefits.

Myriad radiation effects, including benefits and detriments, complicate justifying and optimizing radiation exposures. The purpose of this study was to develop a comprehensive conceptual framework and corresponding quantitative methods to aggregate the detriments and benefits of radiation exposures to individuals, groups, and populations. In this study, concepts from the ICRP for low dose were integrated with clinical techniques focused on high dose to develop a comprehensive figure of merit (FOM) that takes into account arbitrary host- and exposure-related factors, endpoints, and time points. The study built on existing methods with three new capabilities: application to individuals, groups, and populations; extension to arbitrary numbers and types of endpoints; and inclusion of limitation, where relevant. The FOM was applied to three illustrative exposure situations: emergency response, diagnostic imaging, and cancer radiotherapy, to evaluate its utility in diverse settings. The example application to radiation protection revealed the FOM's utility in optimizing the benefits and risks to a population while keeping individual exposures below applicable regulatory limits. Examples in diagnostic imaging and cancer radiotherapy demonstrated the FOM's utility for guiding population- and patient-specific decisions in medical applications. The major finding of this work is that it is possible to quantitatively combine the benefits and detriments of any radiation exposure situation involving an individual or population to perform cost-effectiveness analyses using the ICRP key principles of radiation protection. This FOM fills a chronic gap in the application of radiation-protection theory, i.e., limitations of generalized frameworks to algorithmically justify and optimize radiation exposures. This new framework potentially enhances objective optimization and justification, especially in complex exposure situations.

Tumour size can have an impact on the outcomes of epidemiological studies on second cancers after radiotherapy.

Obtaining a correct dose-response relationship for radiation-induced cancer after radiotherapy presents a major challenge for epidemiological studies. The purpose of this paper is to gain a better understanding of the associated uncertainties. To accomplish this goal, some aspects of an epidemiological study on breast cancer following radiotherapy of Hodgkin's disease were simulated with Monte Carlo methods. It is demonstrated that although the doses to the breast volume are calculated by one treatment plan, the locations and sizes of the induced secondary breast tumours can be simulated and, based on these simulated locations and sizes, the absorbed doses at the site of tumour incidence can also be simulated. For the simulations of point dose at tumour site, linear and non-linear mechanistic models which predict risk of cancer induction as a function of dose were applied randomly to the treatment plan. These simulations provided for each second tumour and each simulated tumour size the predicted dose. The predicted-dose-response-characteristic from the analysis of the simulated epidemiological study was analysed. If a linear dose-response relationship for cancer induction was applied to calculate the theoretical doses at the simulated tumour sites, all Monte-Carlo realizations of the epidemiological study yielded strong evidence for a resulting linear risk to predicted-dose-response. However, if a non-linear dose-response of cancer induction was applied to calculate the theoretical doses, the Monte Carlo simulated epidemiological study resulted in a non-linear risk to predicted-dose-response relationship only if the tumour size was small (< 1.5 cm). If the diagnosed breast tumours exceeded an average diameter of 1.5 cm, an applied non-linear theoretical-dose-response relationship for second cancer falsely resulted in strong evidence for a linear predicted-dose relationship from the epidemiological study realizations. For a typical distribution of breast cancer sizes, the model selection probability for a resulting predicted-dose linear model was 61% although a non-linear theoretical-dose-response relationship for cancer induction had been applied. The results of this study, therefore, provide evidence that the shapes of epidemiologically obtained dose-response relationships for cancer induction can be biased by the finite size of the diagnosed second tumour, even though the epidemiological study was done correctly.

Benchmark measurements and simulations of dose perturbations due to metallic spheres in proton beams.

Monte Carlo simulations are increasingly used for dose calculations in proton therapy due to its inherent accuracy. However, dosimetric deviations have been found using Monte Carlo code when high density materials are present in the proton beam line. The purpose of this work was to quantify the magnitude of dose perturbation caused by metal objects. We did this by comparing measurements and Monte Carlo predictions of dose perturbations caused by the presence of small metal spheres in several clinical proton therapy beams as functions of proton beam range, spread-out Bragg peak width and drift space. Monte Carlo codes MCNPX, GEANT4 and Fast Dose Calculator (FDC) were used. Generally good agreement was found between measurements and Monte Carlo predictions, with the average difference within 5% and maximum difference within 17%. The modification of multiple Coulomb scattering model in MCNPX code yielded improvement in accuracy and provided the best overall agreement with measurements. Our results confirmed that Monte Carlo codes are well suited for predicting multiple Coulomb scattering in proton therapy beams when short drift spaces are involved.

ADVANTAGES OF MCNPX-BASED LATTICE TALLY OVER MESH TALLY IN HIGH-SPEED MONTE CARLO DOSE RECONSTRUCTION FOR PROTON RADIOTHERAPY.

Monte Carlo simulations are increasingly used to reconstruct dose distributions in radiotherapy research studies. Many studies have used the MCNPX Monte Carlo code with a mesh tally for dose reconstructions. However, when the number of voxels in the simulated patient anatomy is large, the computation time for a mesh tally can become prohibitively long. The purpose of this work was to test the feasibility of using lattice tally instead of mesh tally for whole-body dose reconstructions. We did this by comparing the dosimetric accuracy and computation time of lattice tallies with those of mesh tallies for craniospinal proton irradiation. The two tally methods generated nearly identical dosimetric results, within 1% in dose and within 1 mm distance-to-agreement for 99% of the voxels. For a typical craniospinal proton treatment field, simulation speed was 4 to 17 times faster using the lattice tally than using the mesh tally, depending on the numbers of proton histories and voxels. We conclude that the lattice tally is an acceptable substitute for the mesh tally in dose reconstruction, making it a suitable potential candidate for clinical treatment planning.

The future workforce in cancer prevention: advancing discovery, research, and technology.

As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.

Stray neutron radiation exposures from proton therapy: physics-based analytical models of neutron spectral fluence, kerma and absorbed dose.

Objective. Patients who receive proton beam therapy are exposed to unwanted stray neutrons. Stray radiations increase the risk of late effects in normal tissues, such as second cancers and cataracts, and may cause implanted devices such as pacemakers to malfunction. Compared to therapeutic beams, little attention has been paid to modeling stray neutron exposures. In the past decade, substantial progress was made to develop semiempirical models of stray neutron dose equivalent, but models to routinely calculate neutron absorbed dose and kerma are still lacking. The objective of this work was to develop a new physics based analytical model to calculate neutron spectral fluence, kerma, and absorbed dose in a water phantom.Approach. We developed the model using dosimetric data from Monte Carlo simulations and neutron kerma coefficients from the literature. The model explicitly considers the production, divergence, scattering, and attenuation of neutrons. Neutron production was modeled for 120-250 MeV proton beams impinging on a variety of materials. Fluence, kerma and dose calculations were performed in a 30 × 180 × 44 cm3phantom at points up to 43 cm in depth and 80 cm laterally.Main Results. Predictions of the analytical model agreed reasonably with corresponding values from Monte Carlo simulations, with a mean difference in average energy deposited of 20%, average kerma coefficient of 21%, and absorbed dose to water of 49%.Significance. The analytical model is simple to implement and use, requires less configuration data that previously reported models, and is computationally fast. This model appears potentially suitable for integration in treatment planning system, which would enable risk calculations in prospective and retrospective cases, providing a powerful tool for epidemiological studies and clinical trials.

A patient-specific hybrid phantom for calculating radiation dose and equivalent dose to the whole body.

Objective. As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical computed tomography (CT) scans.Approach. A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code.Main results. The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively.Significance. The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.

Applications of a patient-specific whole-body CT-mesh hybrid computational phantom in second cancer risk prediction.

Objective.CT-mesh hybrid phantoms (or 'hybrid(s)') made from integrated patient CT data and mesh-type reference computational phantoms (MRCPs) can be beneficial for patient-specific whole-body dose evaluation, but this benefit has yet to be evaluated for second cancer risk prediction. The purpose of this study is to compare the hybrid's ability to predict risk throughout the body with a patient-scaled MRCP against ground truth whole-body CTs (WBCTs).Approach.Head and neck active scanning proton treatment plans were created for and simulated on seven hybrids and the corresponding scaled MRCPs and WBCTs. Equivalent dose throughout the body was calculated and input into five second cancer risk models for both excess absolute and excess relative risk (EAR and ERR). The hybrid phantom was evaluated by comparing equivalent dose and risk predictions against the WBCT.Main results.The hybrid most frequently provides whole-body second cancer risk predictions which are closer to the ground truth when compared to a scaled MRCP alone. The performance of the hybrid relative to the scaled MRCP was consistent across ERR, EAR, and all risk models. For all in-field organs, where the hybrid shares the WBCT anatomy, the hybrid was better than or equal to the scaled MRCP for both equivalent dose and risk prediction. For out-of-field organs across all patients, the hybrid's equivalent dose prediction was superior than the scaled MRCP in 48% of all comparisons, equivalent for 34%, and inferior for 18%. For risk assessment in the same organs, the hybrid's prediction was superior than the scaled MRCP in 51.8% of all comparisons, equivalent in 28.6%, and inferior in 19.6%.Significance.Whole-body risk predictions from the CT-mesh hybrid have shown to be more accurate than those from a reference phantom alone. These hybrids could aid in risk-optimized treatment planning and individual risk assessment to minimize second cancer incidence.