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Updated: Jan 31, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
PREDICTING BIOLOGICAL EFFECTS ALONG HADRONTHERAPY DOSE PROFILES BY THE BIANCA BIOPHYSICAL MODEL
Mario Pietro Carante1, John Tello1,2,3, Francesca Ballarini1,2
1National Institute of Nuclear Physics (INFN), INFN-Sezione di Pavia, via Bassi 6, Pavia, Italy.
Abstract:
The BIANCA biophysical model of cell death and chromosome aberrations was further refined and applied to predict the biological effectiveness along Spread-Out Bragg Peaks used in hadrontherapy. The simulation outcomes were compared with in vitro survival data on protons, He-ions and C-ions over a wide LET range, and the particle- and LET-dependence of the DNA Cluster Lesions (CLs) yields used as input parameters was investigated. For each particle type, the CL yield was found to increase with LET in a linear-quadratic fashion; fitting the CL yields allowed to predict cell death and chromosome aberrations in principle at any depth along a longitudinal proton dose profile used at CNAO. A clear increase in effectiveness was found in the SOBP distal region, supporting the idea that, in some cases, the constant proton RBE usually applied in clinics may be a sub-optimal solution.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

