  Concerns have been raised about possible cancer risks after exposure to
computed tomography (CT) scans in childhood. The health effects of ionizing
radiation are then estimated from the absorbed dose to the organs of interest
which is calculated, for each CT scan, from dosimetric numerical models, like
the one proposed in the NCICT software. Given that a dosimetric model depends
on input parameters which are most often uncertain, the calculation of absorbed
doses is inherently uncertain. A current methodological challenge in radiation
epidemiology is thus to be able to account for dose uncertainty in risk
estimation. A preliminary important step can be to identify the most
influential input parameters implied in dose estimation, before modelling and
accounting for their related uncertainty in radiation-induced health risks
estimates. In this work, a variance-based global sensitivity analysis was
performed to rank by influence the uncertain input parameters of the NCICT
software implied in brain and red bone marrow doses estimation, for four
classes of CT examinations. Two recent sensitivity indices, especially adapted
to the case of dependent input parameters, were estimated, namely: the Shapley
effects and the Proportional Marginal Effects (PME). This provides a first
comparison of the respective behavior and usefulness of these two indices on a
real medical application case. The conclusion is that Shapley effects and PME
are intrinsically different, but complementary. Interestingly, we also observed
that the proportional redistribution property of the PME allowed for a clearer
importance hierarchy between the input parameters.
