title: A personalized biomechanical model for respiratory motion prediction.
abstract: Time-resolved imaging of the thorax or abdominal area is affected by respiratory motion. Nowadays, one-dimensional respiratory surrogates are used to estimate the current state of the lung during its cycle, but with rather poor results. This paper presents a framework to predict the 3D lung motion based on a patient-specific finite element model of respiratory mechanics estimated from two CT images at end of inspiration (EI) and end of expiration (EE). We first segment the lung, thorax and sub-diaphragm organs automatically using a machine-learning algorithm. Then, a biomechanical model of the lung, thorax and sub-diaphragm is employed to compute the 3D respiratory motion. Our model is driven by thoracic pressures, estimated automatically from the EE and EI images using a trust-region approach. Finally, lung motion is predicted by modulating the thoracic pressures. The effectiveness of our approach is evaluated by predicting lung deformation during exhale on five DIR-Lab datasets. Several personalization strategies are tested, showing that an average error of 3.88 +/- 1.54 mm in predicted landmark positions can be achieved. Since our approach is generative, it may constitute a 3D surrogate information for more accurate medical image reconstruction and patient respiratory analysis.
authors.affiliation: Siemens Corporation, Corporate Research and Technology, Princeton, NJ, USA.
authors.forename: B
authors.initials: B
authors.lastname: Fuerst
authors.forename: T
authors.initials: T
authors.lastname: Mansi
authors.forename: Jianwen
authors.initials: J
authors.lastname: Zhang
authors.forename: P
authors.initials: P
authors.lastname: Khurd
authors.forename: J
authors.initials: J
authors.lastname: Declerck
authors.forename: T
authors.initials: T
authors.lastname: Boettger
authors.forename: Nassir
authors.initials: N
authors.lastname: Navab
authors.forename: J
authors.initials: J
authors.lastname: Bayouth
authors.forename: Dorin
authors.initials: D
authors.lastname: Comaniciu
authors.forename: A
authors.initials: A
authors.lastname: Kamen
mesh_terms: D016477:Artifacts; D003198:Computer Simulation; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging* / Q000502:physiology*; D008954:Models, Biological; D009038:Motion; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D015656:Respiratory Mechanics / Q000502:physiology*; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods*; D012680:Sensitivity and Specificity