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.

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.

Personalized 3D-printed anthropomorphic whole-body phantom irradiated by protons, photons, and neutrons.

The objective of this study was to confirm the feasibility of three-dimensionally-printed (3D-printed), personalized whole-body anthropomorphic phantoms for radiation dose measurements in a variety of charged and uncharged particle radiation fields. We 3D-printed a personalized whole-body phantom of an adult female with a height of 154.8 cm, mass of 90.7 kg, and body mass index of 37.8 kg/m2. The phantom comprised of a hollow plastic shell filled with water and included a watertight access conduit for positioning dosimeters. It is compatible with a wide variety of radiation dosimeters, including ionization chambers that are suitable for uncharged and charged particles. Its mass was 6.8 kg empty and 98 kg when filled with water. Watertightness and mechanical robustness were confirmed after multiple experiments and transportations between institutions. The phantom was irradiated to the cranium with therapeutic beams of 170-MeV protons, 6-MV photons, and fast neutrons. Radiation absorbed dose was measured from the cranium to the pelvis along the longitudinal central axis of the phantom. The dose measurements were made using established dosimetry protocols and well-characterized instruments. For the therapeutic environments considered in this study, stray radiation from intracranial treatment beams was the lowest for proton therapy, intermediate for photon therapy, and highest for neutron therapy. An illustrative example set of measurements at the location of the thyroid for a square field of 5.3 cm per side resulted in 0.09, 0.59, and 1.93 cGy/Gy from proton, photon, and neutron beams, respectively. In this study, we found that 3D-printed personalized phantoms are feasible, inherently reproducible, and well-suited for therapeutic radiation measurements. The measurement methodologies we developed enabled the direct comparison of radiation exposures from neutron, proton, and photon beam irradiations.

Generalized approach for radiotherapy treatment planning by optimizing projected health outcome: preliminary results for prostate radiotherapy patients.

Research in cancer care increasingly focuses on survivorship issues, e.g. managing disease- and treatment-related morbidity and mortality occurring during and after treatment. This necessitates innovative approaches that consider treatment side effects in addition to tumor cure. Current treatment-planning methods rely on constrained iterative optimization of dose distributions as a surrogate for health outcomes. The goal of this study was to develop a generally applicable method to directly optimize projected health outcomes. We developed an outcome-based objective function to guide selection of the number, angle, and relative fluence weight of photon and proton radiotherapy beams in a sample of ten prostate-cancer patients by optimizing the projected health outcome. We tested whether outcome-optimized radiotherapy (OORT) improved the projected longitudinal outcome compared to dose-optimized radiotherapy (DORT) first for a statistically significant majority of patients, then for each individual patient. We assessed whether the results were influenced by the selection of treatment modality, late-risk model, or host factors. The results of this study revealed that OORT was superior to DORT. Namely, OORT maintained or improved the projected health outcome of photon- and proton-therapy treatment plans for all ten patients compared to DORT. Furthermore, the results were qualitatively similar across three treatment modalities, six late-risk models, and 10 patients. The major finding of this work was that it is feasible to directly optimize the longitudinal (i.e. long- and short-term) health outcomes associated with the total (i.e. therapeutic and stray) absorbed dose in all of the tissues (i.e. healthy and diseased) in individual patients. This approach enables consideration of arbitrary treatment factors, host factors, health endpoints, and times of relevance to cancer survivorship. It also provides a simpler, more direct approach to realizing the full beneficial potential of cancer radiotherapy.

Clinical commissioning of intensity-modulated proton therapy systems: Report of AAPM Task Group 185.

Proton therapy is an expanding radiotherapy modality in the United States and worldwide. With the number of proton therapy centers treating patients increasing, so does the need for consistent, high-quality clinical commissioning practices. Clinical commissioning encompasses the entire proton therapy system's multiple components, including the treatment delivery system, the patient positioning system, and the image-guided radiotherapy components. Also included in the commissioning process are the x-ray computed tomography scanner calibration for proton stopping power, the radiotherapy treatment planning system, and corresponding portions of the treatment management system. This commissioning report focuses exclusively on intensity-modulated scanning systems, presenting details of how to perform the commissioning of the proton therapy and ancillary systems, including the required proton beam measurements, treatment planning system dose modeling, and the equipment needed.

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.

Method to quickly and accurately calculate absorbed dose from therapeutic and stray photon exposures throughout the entire body in individual patients.

PURPOSE: Photon radiotherapy techniques typically devote considerable attention to limiting the exposure of healthy tissues outside of the target volume. Numerous studies have shown, however, that commercial treatment planning systems (TPSs) significantly underestimate the absorbed dose outside of the treatment field. The purpose of this study was to test the feasibility of quickly and accurately calculating the total absorbed dose to the whole body from photon radiotherapy in individual patients. METHODS: We created an extended TPS by implementing a physics-based analytical model for the absorbed dose from stray photons during photon therapy into a research TPS. We configured and validated the extended TPS using measurements of 6- and 15-MV photon beams in water-box and anthropomorphic phantoms. We characterized the additional computation time required for therapeutic and stray dose calculations in a 44 × 30 × 180 cm3 water-box phantom. RESULTS: The extended TPS achieved superior dosimetric accuracy compared to the research TPS in both water and anthropomorphic phantoms, especially outside of the primary treatment field. In the anthropomorphic phantom, the extended TPS increased the generalized gamma index passing rate by a factor of 10 and decreased the median dosimetric discrepancy in the out-of-field region by a factor of 26. The extended TPS achieved an average discrepancy <1% in and near the treatment field and <1 mGy/Gy far from the treatment field in the anthropomorphic phantom. Characterization of computation time revealed that on average, the extended TPS only required 7% longer than the research TPS to calculate the total absorbed dose. CONCLUSIONS: The results of this work suggest that it is feasible to quickly and accurately calculate whole-body doses inside and outside of the therapeutic treatment field in individual patients on a routine basis using physics-based analytical dose models. This additional capability enables a more personalized approach to minimizing the risk of radiogenic late effects, such as second cancer and cardiac toxicity, as part of the treatment planning process.

Computational feasibility of calculating the steady-state blood flow rate through the vasculature of the entire human body.

The human body contains approximately 20 billion individual blood vessels that deliver nutrients and oxygen to tissues. While blood flow is a well-developed field of research, no previous studies have calculated the blood flow rates through more than 5 million connected vessels. The goal of this study was to test if it is computationally feasible to calculate the blood flow rates through a vasculature equal in size to that of the human body. We designed and implemented a two-step algorithm to calculate the blood flow rates using principles of steady-state fluid dynamics. Steady-state fluid dynamics is an accurate approximation for the microvascular and venous structures in the human body. To determine the computational feasibility, we measured and evaluated the execution time, scalability, and memory usage to quantify the computational requirements. We demonstrated that it is computationally feasible to calculate the blood flow rate through 17 billion vessels in 6.5 hours using 256 compute nodes. The computational modeling of blood flow rate in entire organisms may find application in research on drug delivery, treatment of cancer metastases, and modulation of physiological performance.

Computational feasibility of simulating changes in blood flow through whole-organ vascular networks from radiation injury.

Vasculature is necessary to the healthy function of most tissues. In radiation therapy, injury of the vasculature can have both beneficial and detrimental effects, such as tumor starvation, cardiac fibrosis, and white-matter necrosis. These effects are caused by changes in blood flow due to the vascular injury. Previously, research has focused on simulating the radiation injury of vasculature in small volumes of tissue, ignoring the systemic effects of local damage on blood flow. Little is known about the computational feasibility of simulating the radiation injury to whole-organ vascular networks. The goal of this study was to test the computational feasibility of simulating the dose deposition to a whole-organ vascular network and the resulting change in blood flow. To do this, we developed an amorphous track-structure model to transport radiation and combined this with existing methods to model the vasculature and blood flow rates. We assessed the algorithm's computational scalability, execution time, and memory usage. The data demonstrated it is computationally feasible to calculate the radiation dose and resulting changes in blood flow from 2 million protons to a network comprising 8.5 billion blood vessels (approximately the number in the human brain) in 87 hours using a 128-node cluster. Furthermore, the algorithm demonstrated both strong and weak scalability, meaning that additional computational resources can reduce the execution time further. These results demonstrate, for the first time, that it is computationally feasible to calculate radiation dose deposition in whole-organ vascular networks. These findings provide key insights into the computational aspects of modeling whole-organ radiation damage. Modeling the effects radiation has on vasculature could prove useful in the study of radiation effects on tissues, organs, and organisms.

Computational feasibility of simulating whole-organ vascular networks.

The human body contains approximately 20 billion blood vessels, which transport nutrients, oxygen, immune cells, and signals throughout the body. The brain's vasculature includes up to 9 billion of these vessels to support cognition, motor processes, and myriad other vital functions. To model blood flowing through a vasculature, a geometric description of the vessels is required. Previously reported attempts to model vascular geometries have produced highly-detailed models. These models, however, are limited to a small fraction of the human brain, and little was known about the feasibility of computationally modeling whole-organ-sized networks. We implemented a fractal-based algorithm to construct a vasculature the size of the human brain and evaluated the algorithm's speed and memory requirements. Using high-performance computing systems, the algorithm constructed a vasculature comprising 17 billion vessels in 1960 core-hours, or 49 minutes of wall-clock time, and required less than 32 GB of memory per node. We demonstrated strong scalability that was limited mainly by input/output operations. The results of this study demonstrated, for the first time, that it is feasible to computationally model the vasculature of the whole human brain. These findings provide key insights into the computational aspects of modeling whole-organ vasculature.

A physics-based analytical model of absorbed dose from primary, leakage, and scattered photons from megavoltage radiotherapy with MLCs.

A burgeoning population of cancer survivors is at risk of late health effects following radiation therapy including second cancers, with the majority of these cancers occurring outside of the treatment volume of the primary cancer. Commercial radiotherapy treatment planning systems underestimate the out-of-field dose. Previous analytical models of out-of-field dose have assumed radial symmetry and/or approximated the dimensions of collimators as semi-infinite planes. The purpose of this work was to develop a physics-based analytical model of total absorbed dose from primary, scattered, and leakage radiation for square fields from a 6 MV beam at any arbitrary point in a phantom, including in-plane, cross-plane, and out-of-plane locations. The model includes the essential physics of radiation transport through beam-limiting-devices including rounded edges of MLC leaves. The model agreed well with measurements and Monte Carlo simulations of absorbed dose in a water-box phantom and was validated for field-sizes ranging from 2 [Formula: see text] 2 to 20 [Formula: see text] 20 cm2. The signed and unsigned average percent differences were [Formula: see text] and 15.9%, respectively, for all points and field-sizes considered. An extended gamma index analysis reveals a 92% pass rate with criteria of 3 mm distance-to-agreement, 3% relative dose difference in-field, and 3 mGy Gy-1 absolute dose difference out-of-field. The average wall-clock time to calculate dose to one million points was 3.3 min. These results suggest that it is feasible to calculate absorbed dose from both therapeutic and stray radiation using physics-based analytical models with good accuracy, thus overcoming a major obstacle to routinely assessing exposures. Additionally, this work demonstrates the importance of relaxing certain simplifications such as assuming a radially symmetric stray-dose distribution. Because the model is physics-based and may be reconfigured according to the dimensions of beam-limiting-devices, adapting it to other treatment units should be straight forward. Uses for such a model include clinical and research applications, such as clinical trials and epidemiological studies.

An objective method to evaluate radiation dose distributions varying by three orders of magnitude.

PURPOSE: Modern radiotherapy practices typically report the absorbed dose (D) within the 5% relative isodose volume (i.e., the therapeutic dose region) to an accuracy of 3%-5%. Gamma-index analysis, the most commonly used method to evaluate dosimetric accuracy, has low sensitivity to discrepancies that occur outside of this region. The objective of this study was to develop an evaluation method with high sensitivity across dose distributions spanning three orders of magnitude. METHODS: We generalized the gamma index to include an additional criterion, the absolute absorbed dose difference, specifically for the low-dose region (i.e., D ≤ 5%). We also proposed a method to objectively select the appropriate magnitudes for relative-dose-difference, absolute-dose-difference, and distance-to-agreement criteria. We demonstrated the generalized gamma-index method by first finding the appropriate generalized gamma-index agreement criteria at an interval of specified passing rates. Next, we used the generalized gamma index to evaluate one-, two-, and three-dimensional absorbed dose distributions in a water-box phantom and voxelized patient geometry. RESULTS: Generalized gamma-index passing rates for one-, two-, and three-dimensional dose distributions were 55.4%, 44.5%, and 8.9%, respectively. Traditional gamma-index passing rates were 100%, 97.8%, and 96.4%, respectively. These results reveal that the generalized method has adequate sensitivity in all regions (i.e., therapeutic and low dose). Additionally, the algorithmic determination of triplets of agreement criteria revealed that they are strong functions of the specified passing rate. CONCLUSIONS: The major finding of this work is that the proposed method provides an objective evaluation of the agreement of dose distributions spanning three orders of magnitude. In particular, this generalized method correctly characterized dosimetric agreement in the low-dose region, which was not possible by traditional methods. The proposed algorithmic selection of agreement criteria decreased subjectivity and requirements of user judgment and skill. This method could find utility in a variety of applications including dose-algorithm development and translation.

Low- and middle-income countries can reduce risks of subsequent neoplasms by referring pediatric craniospinal cases to centralized proton treatment centers.

Few children with cancer in low- and middle-income countries (LMICs) have access to proton therapy. Evidence exists to support replacing photon therapy with proton therapy to reduce the incidence of secondary malignant neoplasms (SMNs) in childhood cancer survivors. The purpose of this study was to estimate the potential reduction in SMN incidence and in SMN mortality for pediatric medulloblastoma patients in LMICs if proton therapy were made available to them. For nine children of ages 2 to 14 years, we calculated the equivalent dose in organs or tissues at risk for radiogenic SMNs from therapeutic and stray radiation for photon craniospinal irradiation (CSI) in a LMIC and proton CSI in a high-income country. We projected the lifetime risks of SMN incidence and SMN mortality for every SMN site with a widely-used model from the literature. We found that the average total lifetime attributable risks of incidence and mortality were very high for both photon CSI (168% and 41%, respectively) and proton CSI (88% and 26%, respectively). SMNs having the highest risk of mortality were lung cancer (16%), non-site-specific solid tumors (16%), colon cancer (5.9%), leukemia (5.4%), and for girls breast cancer (5.0%) after photon CSI and non-site-specific solid tumors (12%), lung cancer (11%), and leukemia (4.8%) after proton CSI. The risks were higher for younger children than for older children and higher for girls than for boys. The ratios of proton CSI to photon CSI of total risks of SMN incidence and mortality were 0.56 (95% CI, 0.37 to 0.75) and 0.64 (95% CI, 0.45 to 0.82), respectively, averaged over this sample group. In conclusion, proton therapy has the potential to lessen markedly subsequent SMNs and SMN fatalities in survivors of childhood medulloblastoma in LMICs, for example, through regional centralized care. Additional methods should be explored urgently to reduce therapeutic-field doses in organs and tissues at risk for SMN, especially in the lungs, colon, and breast tissues.