Radiation Risk Reduction Research Articles

Tap Water Shorts the Lifespan of Mice with Prolonged Exposure to Fractionated γ-Radiation

Assessing the role of social factors in the formation of radioresistance in chronic exposure and finding ways to increase it are important for understanding the mechanisms of the damaging effects of radiation and developing practical methods for reducing radiation risk in professionals exposed to ionizing radiation and patients undergoing radiation therapy. In this work, we investigated the ability to influence the lifespan of animals exposed to γ-radiation fractionally for a long time by replacing drinking water from tap water to distilled water. Female ICR mice (CD-1) were exposed to total 60Co γ radiation weekly in fractions for 33 weeks starting at 9 weeks of age. The dose of a single irradiation was 50 mGy, the average dose rate was 2 mGy/sec. The total radiation dose was 1.65 Gy. Control non-irradiated mice and irradiated animals were divided into 2 groups. The first received tap water, and the second received distilled water throughout the experiment. Non-irradiated animals kept on tap water showed a statistically insignificant (log-rank test, p = 0.483) reduction in average life expectancy compared to mice kept on distilled water. In animals after exposure to 60Co γ-radiation, a statistically significant (p = 0.0013) decrease in life expectancy was noted when kept on tap water and statistically insignificant (p = 0.1511) when kept on distilled water. Tap water and irradiation showed a clear synergy with a combined effect on the body of mice, expressed in a more than threefold decrease in the period of post-radiation shortening of life expectancy. Distilled water reduced the rate of death of irradiated animals and modified the rate of death of non-irradiated animals. Our data demonstrate that the reduction in life expectancy of mice kept on tap water caused by long-term fractionated irradiation can be reduced when animals are kept on distilled water.

Patient radiation risk reduction by controlling the tube start angle in single and dual source spiral CT scans: A simulation study.

Organ doses in spiral CT scans depend on the tube startangle. To determine the effective dose in single source CT (SSCT) and dual source CT (DSCT) scans as a function of tube start angle and spiral pitch value to identify the dose reduction potential by selecting the optimal startangle. Using Monte Carlo simulations, dose values for different tube positions with an angular increment of and a longitudinal increment of were simulated over a range of with collimations of , , and . The simulations were performed for the thorax region of six adult patients based on clinical CT data. From the resulting dose distributions, organ doses and effective dose were determined as a function of tube angle and longitudinal position. Using these per-view dose data, the individual organ doses, as well as the total effective dose, were determined for spiral scans with and without tube current modulation (TCM) with pitch values ranging from 0.5 to 1.5 for SSCT and up to 3.0 for DSCT. The dose of the best and worst tube start angle in terms of dose was determined and compared to the mean dose over all tube startangles. With increasing pitch and collimation, the dose variations from the effective dose averaged over all start angles increase. While for a collimation of , the variations from the mean dose value stay below for SSCT, we find that for a spiral scan with a pitch of 3.0 for DSCT with TCM and collimation of , the dose for the best starting angle is on average lower than the mean value and lower than the maximumvalue. Variation of the tube start angle in spiral scans exhibits substantial differences in radiation dose especially for high pitch values and for high collimations. Therefore, we suggest to control the tube start angle to minimize patientrisk.

Comprehensive risk management and safety strategies in radiation use in medical imaging

Radiation use in medical imaging, while essential for accurate diagnosis and treatment planning, poses inherent risks that require comprehensive risk management and safety strategies. This review discusses the critical aspects of managing these risks in clinical settings, focusing on patient safety, staff protection, and environmental considerations. A major challenge in medical imaging is balancing the diagnostic benefits of radiation against potential harms, particularly in sensitive populations such as children and pregnant women. Comprehensive risk management involves implementing dose optimization techniques, such as using low-dose imaging protocols and advanced technologies like iterative reconstruction and artificial intelligence (AI) algorithms, which enhance image quality while minimizing exposure. Additionally, ensuring the safety of healthcare staff is paramount. This requires adherence to strict safety protocols, including the use of personal protective equipment (PPE), regular monitoring of radiation levels, and continuous education on safe radiation practices. Institutional policies must also address the proper maintenance and calibration of imaging equipment to prevent unnecessary exposure due to equipment malfunction or improper use. Environmental safety is another critical component, necessitating the safe disposal of radioactive materials and the adoption of energy-efficient technologies to reduce the environmental footprint of medical imaging. Regulatory compliance with international safety standards, such as those set by the International Commission on Radiological Protection (ICRP) and national bodies, is essential for ensuring consistent safety practices across healthcare institutions. Future directions in radiation safety include the integration of digital health technologies to monitor and manage radiation exposure more effectively, and ongoing research into novel imaging techniques that could further reduce radiation risks. Collaboration between healthcare providers, researchers, and policymakers is crucial to advancing safety standards and improving risk management strategies in medical imaging. This review highlights the importance of a comprehensive approach to managing radiation risks in medical imaging, emphasizing the need for continuous innovation, education, and policy support to protect patients, healthcare workers, and the environment.

MAIR-Net: a sparse-view CT reconstruction network based on a combination of mixed attention and iterative optimization learning

Sparse-view computed tomography (CT) is one of the main means to reduce radiation risk. When the projection data is highly undersampled, the reconstructed CT image may suffer from serious stripe artifacts and structural information loss. In this paper, we propose a sparse-view CT reconstruction network architecture combining mixed attention (MA) and an iterative reconstruction strategy, called MAIR-Net. Firstly, the approach expands the proximal gradient descent into the neural network and uses an initial value enhancement module between the gradient descent module and the proximal mapping module. The aim is to enhance the flow of detailed information between different layers, fully retain image details, and improve the network convergence speed. Secondly, the mixed attention module (MAM) is introduced into the reconstruction process as a regularization term. It adaptively fuses local and non-local features of the image, which are used to reduce the over-smoothing of the reconstructed image and fully retain the details of the reconstructed image, respectively. Experimental results showed that the proposed method can better retain the details of the reconstructed image and improve the quality of the reconstructed image while inhibiting the sparse angle artifacts of the CT reconstructed image.

Noise-Generating and Imaging Mechanism Inspired Implicit Regularization Learning Network for Low Dose CT Reconstrution.

Low-dose computed tomography (LDCT) helps to reduce radiation risks in CT scanning while maintaining image quality, which involves a consistent pursuit of lower incident rays and higher reconstruction performance. Although deep learning approaches have achieved encouraging success in LDCT reconstruction, most of them treat the task as a general inverse problem in either the image domain or the dual (sinogram and image) domains. Such frameworks have not considered the original noise generation of the projection data and suffer from limited performance improvement for the LDCT task. In this paper, we propose a novel reconstruction model based on noise-generating and imaging mechanism in full-domain, which fully considers the statistical properties of intrinsic noises in LDCT and prior information in sinogram and image domains. To solve the model, we propose an optimization algorithm based on the proximal gradient technique. Specifically, we derive the approximate solutions of the integer programming problem on the projection data theoretically. Instead of hand-crafting the sinogram and image regularizers, we propose to unroll the optimization algorithm to be a deep network. The network implicitly learns the proximal operators of sinogram and image regularizers with two deep neural networks, providing a more interpretable and effective reconstruction procedure. Numerical results demonstrate our proposed method improvements of > 2.9 dB in peak signal to noise ratio, > 1.4% promotion in structural similarity metric, and > 9 HU decrements in root mean square error over current state-of-the-art LDCT methods.

RegFormer: A Local–Nonlocal Regularization-Based Model for Sparse-View CT Reconstruction

Sparse-view computed tomography (CT) is one of the primal means to reduce radiation risk. However, the reconstruction of sparse-view CT with classic analytical method is usually contaminated by severe artifacts. By designing the regularization terms carefully, iterative reconstruction (IR) algorithms can produce promising results. Aided by the powerful deep learning techniques, learned regularization terms with convolution neural network (CNN) have attracted much attention and can further improve performance. In this paper, to further enhance the performance of existing learnable regularization-based networks, we propose a learnable local-nonlocal regularization-based model called RegFormer for sparse-view CT reconstruction. Specifically, we unroll the iterative scheme into a neural network and replace the gradient of handcrafted regularization terms with learnable kernels. The convolution layers are used to learn gradient of local regularization, resulting in excellent denoising performance. In addition, the transformer-based encoders and decoders incorporate the learned nonlocal prior into the model, preserving the structures and details. To enhance the ability to extract deep features, we propose an iteration transmission (IT) module that further improve the efficiency of each iteration. The experimental results show that our proposed RegFormer outperforms several state-of-the-art methods in artifact reduction and detail preservation.

Low-dose CT reconstruction using dataset-free learning.

Low-Dose computer tomography (LDCT) is an ideal alternative to reduce radiation risk in clinical applications. Although supervised-deep-learning-based reconstruction methods have demonstrated superior performance compared to conventional model-driven reconstruction algorithms, they require collecting massive pairs of low-dose and norm-dose CT images for neural network training, which limits their practical application in LDCT imaging. In this paper, we propose an unsupervised and training data-free learning reconstruction method for LDCT imaging that avoids the requirement for training data. The proposed method is a post-processing technique that aims to enhance the initial low-quality reconstruction results, and it reconstructs the high-quality images by neural work training that minimizes the ℓ1-norm distance between the CT measurements and their corresponding simulated sinogram data, as well as the total variation (TV) value of the reconstructed image. Moreover, the proposed method does not require to set the weights for both the data fidelity term and the plenty term. Experimental results on the AAPM challenge data and LoDoPab-CT data demonstrate that the proposed method is able to effectively suppress the noise and preserve the tiny structures. Also, these results demonstrate the rapid convergence and low computational cost of the proposed method. The source code is available at https://github.com/linfengyu77/IRLDCT.

Reduction of Radiation Risk to Cardiologists and Patients during Coronary Angiography: Effect of Exposure Angulation and Composite Shields

Purpose: This study aimed to design an improved form of a composite shield with different materials and shapes and simultaneously reduce the radiation dose to both the patient and operator.
 Materials and Methods: A female phantom study was performed with and without bismuth belt-shaped composite shields on the breast region at different beam projections used in coronary angiography. Dose measurements were conducted using GR-200 thermo-luminescence dosimeters, dose area product (DAP), and air kerma (AK) over regular and large breast locations, with and without using bismuth shields. An electronic personal dosimeter was used for operator dose assessment. Patients received doses between 2.27 mSv and 3.38 mSv, depending on the size and strength of beam projections.
 Results: The use of the developed shields caused a dose reduction of 18%–25% of sensitive breast tissue due to breast size and shield type. During coronary angiography, the mean values of DAP and AK were 2.02 (1.24-2.80) mGy.m2 and 314.1 (202.8-500) mGy, respectively. The highest recorded dose was at the LAO/CRA and LAO/CAU beam projections for both the patient and operator. After applying a belt shield, the operator's radiation dose was decreased by approximately 32%. We found a statistically significant correlation between the radiation dose received by the operator and the patient's breast radiation exposure dose (p<0.001, r2=0.93).
 Conclusion: The designed belt shield can be a potentially promising protective device for decreasing the radiation risk to the patient's breast and the operator during coronary angiography. However, further studies will be considered before the application of this shield in standard clinical practice.

Desain Sistem Mekanik Robot SCARA untuk Internet Nuclear Instrumentation Laboratory

Radiation protection training requires a robotic arm as a radiation shield regulator that can be controlled remotely to reduce radiation risk. The required robot is a Selective Compliance Assembly Robot Arm (SCARA) type robotic arm. This research aims to design a mechanical system for the SCARA robot for the Internet Nuclear Instrumentation Laboratory (INIL). The research method for making robots begins with a 3D CAD design followed by manufacturing and assembly. Robot control using the Arduino IDE application. Robotic arm testing using stress analysis from Autodesk Inventor software and movement and accuracy testing. The results of the research have successfully designed robotic arms with dimensions of 50.8 cm high, 14 cm wide, and 56 cm long. The robot's work area is 189 cm2, with the farthest range being 30 cm. Keywords: radiation protection, mechanical design, SCARA robot, robotic arm, NPP, INIL

Determination of natural radioactivity using gamma spectrometry in used soils as construction materials in Qom province, Iran

The concentrations determination of natural radionuclides as radiation sources has an important role in reducing radiation risk and evaluating of non-nuclear activities impact. In this research, the concentrations of natural radionuclides 40K, 226Ra, and 232Th in the soil samples collected from 13 different locations in the Qom province (Delijan Cement Mine area) were measured by means of gamma-ray spectrometry using a shielded NaI (Tl) detector. For this purpose, the Nuclide master plus simulation program was used to evaluate the efficiency, and then the acquired data was validated. The activity concentrations of 40K, 226Ra, and 232Th varied within the ranges of 23.19 ± 1.95 to 287.19 ± 2.38, 3.04 ± 0.47 to 13.43 ± 0.56, 2.26 ± 0.37 to 4.63 ± 0.38 Bq.kg−1 with the mean values of 75.78, 8.69, and 3.30 Bq.kg−1, respectively. Radium equivalent activity, internal and external hazard indices were determined to assess radiological hazards. The mean Raeq was measured 19.26 Bq.kg−1 and Hex and Hin were calculated 0.052 and 0.075 which these quantities were lower than the world average. The results revealed that radiological risk due to natural radionuclides in this area was negligible and extracted soil samples as construction materials (cement) are safe.

Human Health on the Moon and Beyond and the Results of the Spaceflight for Everybody Symposium.

INTRODUCTION:In 2022, the National Aeronautics and Space Administration (NASA) began launching missions to establish a sustainable human presence on the Moon. One key to success will be maintaining human health. In preparation for longer missions with more diverse crews, the Spaceflight for Everybody Symposium was held to review currently known human spaceflight biomedical knowledge, the future of exploration space medicine, and the ability of NASA to manage the spaceflight human health risks and enable exploration. The symposium highlighted the future of precision health/personalized medicine, the possible spaceflight health acute and lifetime illnesses, and the challenge of identifying appropriate prevention, treatment, rehabilitation, and autonomous medical systems for long-duration spaceflight. The symposium was organized to look back at NASA exploration, science, and leadership successes, celebrate NASA women's leadership, and focus on future Artemis activities, including research and development that will benefit both spaceflight and terrestrial life. NASA current preparations for returning to the Moon have led to increased acknowledgment of the importance of workforce diversity, i.e., to use the best candidate in every work position, including the plan for the first woman and person of color to land on the Moon. NASA is developing plans to use commercial spaceflight research opportunities when the International Space Station is no longer available. Astronaut health decisions will consist of individualized health risk determinations and mitigation strategies and increased medical self-care. Research findings include improved exploration cardiovascular, musculoskeletal, and radiation risk reduction and improved interpersonal support for both astronaut crews and mission control personnel.Schneider V, Siegel B, Allen JR. Human health on the Moon and beyond and the results of the Spaceflight for Everybody Symposium. Aerosp Med Hum Perform. 2023; 94(8):634-643.

Appropriate Imaging Modalities in the Emergency Department for Assessment of Renal Stones

Introduction:Urolithiasis prevalence is approximately 15-20%, the third most common urological presentation to emergency departments (ED). In the ED, renal stones are usually diagnosed by clinical presentation, but imaging modalities play a role in confirmation and exclusion of hydronephrosis. 85% of stones are calcium oxalate/calcium phosphate, which are radio opaque, and 15% are radiolucent uric acid or cysteine stones. Non-contrast CT scans have 95% and 97% sensitivity and specificity rates, while x-rays have 57% and 76% respectively. In Wexford General Hospital, radiology prefers plain film x-rays prior to CT scans in assessing kidney stones.Method:The aim of this study was to assess the sensitivity of x-rays in patients undergoing low dose non-contrast CT for kidney stones and to apply this information to clinical practice. A retrospective audit was conducted using NIMIS/PACS from December 1, 2021-March 31,2022. All patients who underwent CT KUBS for evaluation of renal stones were included, and CT KUB findings were compared with initial x-ray findings.Results:A CT KUB was performed on 56 patients to assess renal stones, and 29 patients had renal stones. Among 29 patients, 21 had x-rays and CT scans performed, and 12 had x-ray findings that indicated renal stones, indicating 57% sensitivity. The study found 36 patients had x-rays for renal stones, but no CT scan was scheduled for 15 patients who might have undiagnosed radiolucent stones.Conclusion:Radiological imaging plays a central role in the management of suspected renal stones. CT KUB is a useful tool for evaluating patients with radio-opaque kidney stones as well as detecting radiolucent stones and renal pathologies that can be missed with plain radiographs. Low-dose CT KUB is recommended as a first-line investigation for renal stone patients to reduce radiation risks and unnecessary abdominal x-rays while assisting clinicians in accurately diagnosing patients and excluding other possible causes.

Radioactive Aerosol Control and Decontamination in the Decommissioning of the Fukushima Daiichi Nuclear Power Station

The recent Nuclear Regulation Authority evaluation report suggests that at the Fukushima Daiichi Nuclear Power Station, the concrete shield plugs above the primary containment vessel (PCV) have exceptionally high radiation levels in Units 2 and 3, which may increase the risk of radiation exposure during decommissioning operations. During the cleaning and disassembly of such radiation hot spots, it is expected that a large amount of submicron-sized radioactive aerosol particles will be generated, which may influence the decommissioning operation. In the present study, laser cleaning experiments were conducted at the University of Tokyo Aerosol Removal Test Facility to simulate aerosol scavenging during the laser cleaning process. The facility can reproduce multiple phenomena expected in actual plant decommissioning, such as laser decontamination and simultaneous mist and spraying operations. Through the work, we have developed effective aerosol dispersion control methods and strategies based on the joint use of water mist and water spray to reduce radiation risk in either laser cutting or other means of decontamination methods. Preliminary laser cleaning experiments on various coated samples were conducted to assess the aerosol removal efficiency using water droplets and mist. It was verified that the proposed method effectively cleans the radiation hot spots during the decommissioning process.

Dose Reduction Strategies for Pregnant Women in Emergency Settings.

In modern clinical practice, there is an increasing dependence on imaging techniques in several settings, and especially during emergencies. Consequently, there has been an increase in the frequency of imaging examinations and thus also an increased risk of radiation exposure. In this context, a critical phase is a woman's pregnancy management that requires a proper diagnostic assessment to reduce radiation risk to the fetus and mother. The risk is greatest during the first phases of pregnancy at the time of organogenesis. Therefore, the principles of radiation protection should guide the multidisciplinary team. Although diagnostic tools that do not employ ionizing radiation, such as ultrasound (US) and magnetic resonance imaging (MRI) should be preferred, in several settings as polytrauma, computed tomography (CT) nonetheless remains the examination to perform, beyond the fetus risk. In addition, protocol optimization, using dose-limiting protocols and avoiding multiple acquisitions, is a critical point that makes it possible to reduce risks. The purpose of this review is to provide a critical evaluation of emergency conditions, e.g., abdominal pain and trauma, considering the different diagnostic tools that should be used as study protocols in order to control the dose to the pregnant woman and fetus.

Impact of Image Denoising Techniques on CNN-based Liver Vessel Segmentation using Synthesis Low-dose Contrast Enhanced CT Images

Liver vessel segmentation in contrast-enhanced CT (CECT) images has a significant role in the planning stage for liver cancer treatment, such as radiofrequency ablation (RFA). Lowering the radiation dose in CECT imaging to reduce radiation risk to the patient degrades the quality of the image and potentially affects the liver vessel segmentation. In recent years, the convolutional neural network (CNN) has shown significant achievement in medical image analysis, including segmentation and denoising tasks. This paper presents a study on a new framework consisting of three well-known denoising techniques, including vessel enhancing diffusion (VED), RED-CNN, and MAP-NN, along with the state-of-theart segmentation method (nnU-Net) to segment the liver vessels in CECT images. We quantitatively evaluate the impacts of denoising techniques on the vessel segmentation on multi-level simulated low-dose CECT images of the liver. The performances of the liver vessel segmentation method combined with the denoising techniques are evaluated using Dice score, sensitivity metric, and processing time. In addition, the effect of denoising on the surface roughness of the segmented liver vessel is also investigated. The experiments show that the image denoising techniques improve the quality of liver vessel segmentation on high noisy CECT images while also reducing the segmentation accuracy on low-noise-level CECT images.

INFLUENCE OF AIRWAY GEOMETRY ON RADON RISK ASSESSMENT IN ADULTS AND CHILDREN (MICRODOSIMETRIC APPROACH).

The aim of this work was to use the microdosimetric threshold energy model to study the effects of alpha-emitting 222Rn progeny on the probability of developing lung cancer. The results suggest that the radiation risk may increase by several times as the thickness of the surface layer decreases. The thicker the protective mucus layer and the deeper the sensitive target cells are located in the tissue, the less radiation damage the same dose produces. These findings have been applied to children of various ages. As children grow older, their lungs enlarge, the mucus layer thickens and the cells sensitive to radiation damage move deeper into the lung tissue, resulting in a reduction of radiation risk. The fraction of affected target cells is not only a function of dose but also of lung tissue depth. The results indicate that children can be several times more vulnerable to radiation than adults.

Image enhancement of ultra-low dose CBCT images using a deep generative model

<h3>Objective</h3> The aim of this study was to improve the image quality of CBCT images, obtained with an ultra-low dose (ULD) protocol, using a deep generative model called pix2pix image-to-image translation technique. <h3>Study Design</h3> CBCT images of a dry skull and mandible were obtained using preset standard and ULD imaging protocols. We combined the scans into a dataset with 1,412 ULD scans and normal-dose DICOM image pairs (2,824 scans in total), and randomly selected 10% (140) image pairs as the test set. We trained a pix2pix deep generative model by first converting the DICOM images to JPG images and then feeding the training set image pairs to the network. We tested the performance of the trained model on the previously unseen test set ULD images and compared the synthesized images with the corresponding normal dose and ULD images. A preliminary blind study on the ULD, standard, and synthesized images by an oral and maxillofacial radiologist was done and image quality and edge definition were assessed. <h3>Results</h3> Preliminary results indicated that in the three datasets used for review, all synthesized images were rated as having higher image quality and better edge definition compared to ULD images. Analysis also indicated that synthesized images were equivalent to standard images in image quality and edge definition. <h3>Conclusion</h3> CBCT usage is expected to grow globally by 9.7%. With the expected growth, reducing radiation dose and improving image quality is of paramount importance to reduce the radiation burden on the population. The current study focused on image enhancement of CBCT images acquired with the ULD protocol. Initial analysis indicated a marked improvement in image quality of the synthesized images when compared to ULD images. With further research and successful implementation, we have an opportunity to reduce radiation risks to patients while improving image quality. <b>Statement of Ethical Review</b> Ethical Review or exemption was not warranted for this study.

ESTIMATION OF PEDIATRIC DOSE DESCRIPTORS ADAPTED TO INDIVIDUAL SPECIFIC SIZE FROM CT EXAMINATIONS.

Clinical challenges in pediatrics dose estimation by the displayed computed tomography (CT) dose indices may lead to inaccuracy, and thus size-specific dose estimate (SSDE) is introduced for better-personalized dose estimation. This study aims to estimate pediatric dose adapted to specific size. This retrospective study involved pediatric population aged 0-12y. SSDE was derived from scanner reported volume CT dose index (CTDIvol), based on individual effective diameter (Deff) with corresponding size correction factors. The correlations of Deff with other associated factors such as age, exposure setting, CTDIvol and SSDE were also studied. The average Deff of Malaysian pediatric was smaller than reference phantom size (confidence interval, CI=0.28, mean=14.79) and (CI=0.51, mean=16.33) for head and abdomen, respectively. These have led to underestimation of pediatric dose as SSDE was higher than displayed CTDIvol. The percentage differences were statistically significant (p<.001) ranged from 0 to 17% and 37 to 60% for head and abdominal CT, respectively. In conclusion, the clinical implementation of SSDE in pediatric CT imaging is highly relevant to reduce radiation risk.

Persistent impact of Fukushima decontamination on soil erosion and suspended sediment

In Fukushima, government-led decontamination reduced radiation risk and recovered 137Cs-contaminated soil, yet its long-term downstream impacts remain unclear. Here we provide the comprehensive decontamination impact assessment from 2013 to 2018 using governmental decontamination data, high-resolution satellite images and concurrent river monitoring results. We find that regional erosion potential intensified during decontamination (2013–2016) but decreased in the subsequent revegetation stage. Compared with 2013, suspended sediment at the 1-year-flood discharge increased by 237.1% in 2016. A mixing model suggests that the gradually increasing sediment from decontaminated regions caused a rapid particulate 137Cs decline, whereas no significant changes in downstream discharge-normalized 137Cs flux were observed after decontamination. Our findings demonstrate that upstream decontamination caused persistently excessive suspended sediment loads downstream, though with reduced 137Cs concentration, and that rapid vegetation recovery can shorten the duration of such unsustainable impacts. Future upstream remediation should thus consider pre-assessing local natural restoration and preparing appropriate revegetation measures in remediated regions for downstream sustainability.

Medical Countermeasure Requirements to Meet NASA's Space Radiation Permissible Exposure Limits for a Mars Mission Scenario.

The space radiation environment consists of a complex mixture of ionizing particles that pose significant health risks to crew members. NASA currently requires that an astronaut's career Risk of Exposure Induced Death (REID) for cancer mortality should not exceed 3% at the upper 95% confidence level. This career radiation limit is likely to be exceeded for even the shortest round-trip mission scenario to Mars. As such, NASA has begun to pursue more vigorously approaches to directly reduce radiation risks, despite the large uncertainties associated with such projections. A recent study considered cohort studies of aspirin and warfarin as possible medical countermeasures (MCMs) acting to reduce background cancer mortality rates used in astronaut risk projections. It was shown that such MCMs can reduce the REID for specific tissues in restricted time intervals over which the drugs were administered; however, the cumulative effect on total lifetime REID was minimal. As an extension, the present work addresses more general MCM requirements that would be needed to meet current NASA radiation limits for a Mars mission scenario. A sensitivity analysis is performed within the major components of the NASA cancer risk model that would likely be modified by MCM interventions. This includes the background cancer incidence and mortality rates, epidemiologically based hazard rates derived from acute terrestrial exposures, and radiation quality factors used to translate terrestrial exposures to space radiation. Relationships between possible MCMs and each of these components are discussed. Results from this study provide important information regarding MCM requirements needed to meet NASA limits for planned Mars missions. Insight into the types of countermeasures expected to yield greatest reductions in crew risk is also gained.