The 4D computational patient specic of the respiratory system could be potentially
used in various medical contexts; for diagnosis, treatment planning, laparoscopic,
dose computation or the registration between online imaging systems such as positron emission
tomography (PET), computed-tomography (CT) as well as high delity and precise
computer-based training simulators. The main novelty of this PhD project lies in the context
of radiation therapy; we have developed a patient-specic biomechanical model of the
respiratory system enabling the correlation of the internal organs motion with respiratory
surrogate signal(s) during the treatment. This permits to take into account the respiratory
motion variabilities. The deformation of the dierent structures is controlled and driven by
simulated rib cage (mimic the external intercostal muscles) and diaphragm actions. For the
diaphragm, we have applied the radial direction of muscle forces, and simple homogeneous
dirichlet boundary condition is applied to the lower part of the diaphragm, which is attached
to the rib cage. For each rib a rigid transformation is calculated automatically by nite helical
axis method (rigid translation and rotation) and used to dene displacement boundary
conditions. The resulting widening of the thoracic cavity forces the lungs to expand due
to an applied negative pressure in the pleural cavity. Other novelty of the PhD project,
that the amplitude of the lung pressure and diaphragm force are patient-specic, and determined
at dierent respiratory states by an optimization framework based on inverse FE
analysis methodology, by minimizing the volume lungs errors, between the respiratory volume
(calculated from CT scan images at each state) and the simulated volume (calculated
by biomechanical simulation). All other structures are linked to each other, but feature
dierent deformation behavior due to the assigned material properties. Our results are
quite realistic compared to the 4D CT scan images and the proposed physically-based FE
model is able to predict correctly the respiratory motion.