Journal
HEALTH PHYSICS
Volume 103, Issue 4, Pages 367-382Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/HP.0b013e31825f75a7
Keywords
laboratory animals; mortality; radiation dose; radiation effects
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Funding
- NIAID NIH HHS [N01AI50043] Funding Source: Medline
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The development of medical countermeasures against the hematopoietic subsyndrome of the acute radiation syndrome requires well characterized and validated animal models. The model must define the radiation dose-and time-dependent relationships for mortality and major signs of morbidity to include other organ damage that may contribute to morbidity and mortality. Herein, the authors define these parameters for a nonhuman primate exposed to total body radiation and administered medical management. A blinded, randomized study (n = 48 rhesus macaques) determined the lethal dose-response relationship using bilateral 6 MV linear accelerator photon radiation to doses in the range of 7.20 to 8.90 Gy at 0.80 Gy min(-1). Following irradiation, animals were monitored for complete bloodcounts, body weight, temperature, diarrhea, and hydration status for 60 d. Animals were administered medical management consisting of intravenous fluids, prophylactic antibiotics, blood transfusions, anti-diarrheals, analgesics, and nutrition. The primary endpoint was survival at 60 d post-irradiation; secondary endpoints included hematopoietic-related parameters, number of transfusions, incidence of documented infection, febrile neutropenia, severity of diarrhea, mean survival time of decedents, and tissue histology. The study defined an LD30/60 of 7.06 Gy, LD50/60 of 7.52 Gy, and an LD70/60 of 7.99 Gy with a relatively steep slope of 1.13 probits per linear dose. This study establishes a rhesus macaque model of the hematopoietic acute radiation syndrome and shows the marked effect of medical management on increased survival and overall mean survival time for decedents. Furthermore, following a nuclear terrorist event, medical management may be the only treatment administered at its optimal schedule. Health Phys. 103(4):367-382;2012
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