Variation of normal tissue complication probability (NTCP) estimates of radiation-induced XXXX in relation to changes in delineation of the thyroid gland.

@entity1 @entity1375 @entity135 @entity213
UNASSIGNED: Background. To examine the variations of risk-estimates of radiation-induced @entity1375 ( @entity1375 ) from our previously developed normal tissue complication probability (NTCP) model in @entity1 with @entity213 ( @entity213 ) in relation to variability of delineation of the thyroid gland. @entity1 and methods. In a previous study for development of an NTCP model for @entity1375 , the thyroid gland was delineated in 246 treatment plans of @entity1 with @entity213 . Fifty of these plans were randomly chosen for re-delineation for a study of the intra- and inter-observer variability of thyroid volume, Dmean and estimated risk of @entity1375 . Bland-Altman plots were used for assessment of the systematic (mean) and random [standard deviation (SD)] variability of the three parameters, and a method for displaying the spatial variation in delineation differences was developed. Results. Intra-observer variability resulted in a mean difference in thyroid volume and Dmean of 0.4 cm(3) (SD    1.6) and -0.5 Gy (SD    1.0), respectively, and 0.3 cm(3) (SD    1.8) and 0.0 Gy (SD    1.3) for inter-observer variability. The corresponding mean differences of NTCP values for radiation-induced @entity1375 due to intra- and inter-observer variations were insignificantly small, -0.4% (SD    6.0) and -0.7% (SD    4.8), respectively, but as the SDs show, for some @entity1 the difference in estimated NTCP was large. Conclusion. For the entire study population, the variation in predicted risk of radiation-induced @entity1375 in @entity135 was small and our NTCP model was robust against observer variations in delineation of the thyroid gland. However, for the individual @entity1 , there may be large differences in estimated risk which calls for precise delineation of the thyroid gland to obtain correct dose and NTCP estimates for optimized treatment planning in the individual @entity1 .
