Improving Mass Casualty Management: the Role of Radiation Biodosimetry
How would you test patients for radiational exposure in a crisis?
Updated July 13, 2018
The topic of nuclear and radiological bombs is something we’ve heard more about in the past year than in the past decade, but what does this mean for health care clinicians? Mary Sproull, PhD, and Kevin Camphausen, MD, from the National Institutes of Health (NIH) gave a presentation to answer that question at the Biodefense World Summit 2018 in June.
Drs. Sproull and Camphausen are working to make the medical management process more efficient and effective in the event of a mass casualty radiation exposure. Specifically, they are developing a dosimetry dose prediction model to determine how radiation biodosimetry diagnostics can help physicians estimate just how much radiation exposure a patient has experienced. (Radiation biodosimetry diagnostics estimate a person’s radiation exposure by measuring changes in biological markers that include cytogenic assays like dicentric chromosome assay.)
Research into medical countermeasures for chemical, biological, radiological, and nuclear (CBRN) attacks have been brought to the forefront since the post-9/11 Bioshield Act of 2004, which supports the Biomedical Advanced Research and Development Authority (BARDA) and the NIH to work with the Public Health Emergency Medicine Countermeasures Enterprise (PHEMCE) to develop and procure medical countermeasures for radiation exposure. This test measures changes in biological markers and works to move beyond the current methods (cytogenetic assays, lymphocyte depletion kinetics, etc) towards proteomic, genomic, metabolomic, and transcriptomic diagnostics.
Although the scenario in which these tests would need to be used seems unlikely, the truth is that in the case of a nuclear radiological event, testing a large group of people is exceedingly difficult. Drs. Sproull and Camphausen discussed an example of an incident in Goiania, Brazil in 1987, in which a radiological incident required testing of 125,000 people. Of those people, 250 were contaminated, 46 received medical countermeasures, and 14 developed acute radiation syndrome. The lack of point-of-care (POC) biodosimetry diagnostic tests and limited testing in a mass triage situation makes medical response efforts that much more stressful and challenging. Fortunately, their work focuses on developing prediction models of radiation exposure and identifying new proteomic biomarkers of radiation exposure which could be utilized between 24 and 72 hours postexposure and possibly extended to 1 to 3 weeks following an exposure.
Nuclear power is still being used within the United States.1 In fact, there are 61 commercially operating nuclear power plants with 99 nuclear reactors across 30 states. Imagine an incident like that of the Fukushima nuclear accident in 2011, which is considered the second worst nuclear accident in the history of nuclear power,2 happening in the United States. In Japan, 47,000 residents were forced to leave their homes, as the government established an 18-mile no-fly zone around the area.
Thankfully, there have been no deaths or incidents of radiation sickness,3 but what if this happened in the United States and medical providers needed to be able to establish radiation exposure quickly and efficiently? Imagine walking into an emergency department in any US hospital—do you think they would have the capacity to perform diagnostics to establish exposure? Even if the answer is yes, it’s doubtful that it would be possible in large volumes and to also determine just how much radiation the patient had been exposed to. Fundamentally, the gaps in preparedness are not just about how ready we are to respond to an event, but also whether we have the diagnostic skills to manage it. Drs. Sproull and Camphausen’s work seeks to close these gaps. Knowing if a patient has been exposed to radiation is 1 piece of the puzzle and radiation dosimetry answers that, but it also provides critical information regarding a patient’s degree of radiation exposure.
Even if you think radiological events are unlikely, here is a gentle reminder; on July 3, a drone (decked out to resemble Superman, ironically) crashed into a French nuclear plant to highlight security failures around the facility.4 Although the drone was intentionally crashed by an environmental group, such an incident highlights that accidents and failures are an unfortunate reality. Attention regarding advancing diagnostics typically falls on that their capabilities during an infectious disease outbreak, which is undoubtedly important, but it’s critical that medical management of mass exposures or casualties, extends to all CBRN avenues. This work on radiation biodosimetry is a clear example of our efforts to close these gaps, but it is critical that medical providers, whether they are in a large hospital system or critical-access hospital, have knowledge of these advancements and access.
I was fortunate to chat with Dr. Sproull* regarding her research, its application to medical providers, and why we would be having these conversations during health care preparedness exercises. She noted that “The most critical gap in emergency preparedness and response for medical management of radiological/nuclear events is the lack of a screening tool to determine whether a radiation exposure has occurred. It is expected that following a radiological/nuclear event, a large number of the uninjured population or ‘worried well’ will self-mobilize and overwhelm triage systems wanting to know if they have received a radiation exposure. Current efforts in research and late-stage development of new POC radiation biodosimetry diagnostics are aimed at meeting this critical need. Biodosimetry diagnostics are arguably the most critical countermeasure for radiation exposure as they are needed firstly, to confirm that an exposure has occurred, and secondly, to estimate the severity of the radiation exposure and which organ systems will be affected.”
Although there’s more work to be done, the expression levels of radiation in their work reveal a greater need for diagnostic methods to have a wider range of expression values for dose prediction. Further studies will look to selected biomarkers like the FMS-like tyrosine kinase 3 ligand (FLT3L), Pentraxin 3 (ptx3), Matrix metallopeptidase 9 (MMP-9), and ETC, but the investigators found that a single FL biomarker was most efficient at the prediction of a dose at 24 hours post body irradiation. Dr. Sproull further noted that “Future operational challenges for POC biodosimetry diagnostics include translating these biological assays from animal models to application in a more heterogeneous human population. Development of the technology for use under field conditions by First Responders and their integration into existing triage systems are some of the final hurdles which are being addressed to make this diagnostic fully deployable.”
Their research will continue to establish such relevant biomarkers for radiation biodosimetry and how testing can be improved for those on the ground during an event.
*Editor's note: Dr. Sproull's statements are not on behalf of the NIH, but as statements of personal opinion.
- How many nuclear power plants are in the United States, and where are they located? U.S. Energy Information Administration website. https://www.eia.gov/tools/faqs/faq.php?id=207&t=3. Updated August 15, 2017. Accessed July 11, 2018.
- The Editors of Encyclopaedia Britannica. Fukushima accident. Encyclopedia Brittanica website. https://www.britannica.com/event/Fukushima-accident. Published March 13, 2018. Accessed July 11, 2018.
- Fukushima Accident. World Nuclear Association website. http://www.world-nuclear.org/information-library/safety-and-security/safety-of-plants/fukushima-accident.aspx. Updated June 2018. Accessed July 11, 2018.
- Associated Press. Drone in Superman Garb Crashes Into French Nuclear Plant. US News & World Report website. https://www.usnews.com/news/business/articles/2018-07-03/drone-in-superman-garb-crashes-into-french-nuclear-plant. Published July 3, 2018. Accessed July 11, 2018.