A PROPOSAL FOR MINIMUM DETECTABLE COMPARTMENT IN MIRD DOSIMETRY MODELING

The accuracy of radiation dose estimates from radiopharmaceutical admi nistrations has recently become more important for three main reasons: (i) clinical providers are demanding more information on diagnostic p rocedures; (ii) regulatory groups are scrutinizing dosimetry for resea rch subjects; and (iii) accurate organ doses are crucial in therapeuti c administrations. These dose estimates are a sensitive function of th e residence times. Because most clinical data acquisition protocols ar e limited to the first 24 h after dose administration, the area under the remainder of the time-activity curve (TAC) must be estimated. Esti mation methods range from assuming physical decay only (overly conserv ative) to extrapolating end point physiological kinetics (overly liber al). This study demonstrates how much the results from these two metho ds vary and develops an alternative method which more accurately estim ates this remainder term. A method, called the minimum detectable comp artment (MDC), is constructed so that an accurate dose estimate can be made with a realistic measure of the remainder term. The method for d etermining MDC uses standard hypothesis testing. Using an analogue of the traditional minimal detectable activity calculation, a model with and without constant compartments is fitted to the TAC. The size of th e constant compartment is varied until the relative likelihood of the two models meets the desired measure of power and sensitivity. Compute r simulations of a simple mono-exponential are used to demonstrate the MDC as a function of the model, the number of data points, the range of the data and the noise in the data. The MDC is a very sensitive fun ction of the data range. It falls by more than 50% when the data range is increased from two to three half-lives. In addition, the MDC is mo derately sensitive to the noise in the data and relatively insensitive to the number of data points. These findings suggest that the MDC met hod can also be uses a priori to indicate what type of data collection regimen is necessary to achieve a certain accuracy.