Radioiodine thyroid ablation therapy is a common method for treatment of felines exhibiting hyperthyroidism. Due to the high gamma-ray emission rate of radioiodine (131I), patients following treatment must be held in isolation for several days before release to prevent unnecessary dose to owners and members of the public. Dose rate measurement on the external surface of the patient of ≤ 20 μSv h−1 is maintained as the patient release criterion without regard to residual activity. However, the Texas Department of State Health Services regulatory guide recommends a release limit of 3.7 MBq to households with non-pregnant women and children over the age of 18 y, and a limit of 925 kBq to households of pregnant women and children who can be supervised. In this paper, Monte Carlo computational radiation transport techniques are employed to predict and standardize the patient isolation time at the clinic by correlating the thyroid burden and surface dose rates of felines. Measurements of patient dose rate as a function of time are used to determine the patient-specific effective half-life experimentally and to validate the model results. Results show that an average holding time of 8 to 9 d is sufficient to reduce the residual activity to 3.7 MBq levels. Additionally, contact dose rate measurements of 20 μSv h−1 or less correlate to residual activity levels of approximately 925 kBq. Based on the model and measurements, a protocol was developed for clinical use at Texas A&M University Veterinary Medical Teaching Hospital to allow estimation of residual activity following injection. This in turn confirms that the surface dose rates used as the release criteria follow the release limits recommended in the regulatory guide.
*Department of Nuclear Engineering, Texas A&M University, College Station, TX 77843‐3133; †Environmental Health and Safety, Texas A&M University, College Station, TX 77843‐4472.
The authors declare no conflicts of interest.
For correspondence contact: T. Michael Martin, 337 Zachry Engineering Center, 3133 TAMU, College Station, TX 77843‐3133, or email at email@example.com.
(Manuscript accepted 4 March 2015)