Speaker
Description
Muon scattering tomography (MST) leverages the multiple Coulomb scattering of cosmic-ray muons to reconstruct the internal structure of dense objects. While extensively studied in security and geophysics, its application to medical imaging remains an open question. We report on a simulation-based study evaluating the feasibility of MST for imaging biological tissues, with a focus on spine monitoring. Using GEANT4, we implement voxelized anatomical phantoms based on ICRP reference models and introduce controlled deformations to simulate scoliosis curvature. We quantify the detectability of bone structures (ρ ≈ 1.85 g/cm³) against surrounding soft tissues (ρ ≈ 0.95–1.05 g/cm³) and assess reconstruction performance in terms of spatial resolution and contrast-to-noise ratio. We investigate the impact of acquisition time and compare scenarios based on natural cosmic muon flux. The results provide insight into the physical limits of MST in low-contrast biological environments and help define the parameter space in which clinically relevant measurements, such as Cobb angle estimation, may be achievable.