4D positron emission tomography image reconstruction based on biomechanical respiratory motion

Respiratory-induced organ motion is a technical challenge to nuclear imaging and to particle therapy dose calculations for lung cancer treatment in particular. Internal organ tissue displacements and deformations induced by breathing need to be taken into account when calculating Monte Carlo dose distributions or when performing tomographic reconstructions for PET imaging. This paper proposes a method to reconstruct PET activities over tetrahedral meshes which are deformed based on biomechanical patient specific model of the respiratory system to tackle the non reproductibility of the breathing. We also describe the adaptation of the popular List-Mode Maximum Likelihood Estimation (LM-MLEM) reconstruction algorithm to motion estimation model using the finite element method (FEM). Our simulations demonstrate the accuracy of the proposed 4D LM-MLEM reconstruction algorithm based on biomechanical model and its capability to correct motion artifacts due to the breathing.