Figure 1.

Flowchart of the PACE model. The model is first trained on a cohort of N patients, whose spatially-normalized dose maps are defined on a grid of M voxels. The training phase results in a set of M Generalized Linear Models (GLMs) and in the Maximum Likelihood Estimation (MLE) of the parameters ν, μ, and Tp₅₀. The application of PACE on a spatially-normalized test dose map exploit the M GLMs to derive a collection of global RIM predictions (P map) and weights (W map) that are finally combined according to the estimated parameters ν, μ, and Tp₅₀.