Nonlinear elastic registration of brain images with tumor pathology using a biomechanical model [MRI]

• Published in: IEEE transactions on medical imaging 1999-07, Vol.18 (7), p.580-592
• Main Authors: Kyriacou, S.K., Davatzikos, C., Zinreich, S.J., Bryan, R.N.
• Format: Article
• Language: English
• Subjects: Anatomy; Biological and medical sciences; Biological tissues; Biomechanical Phenomena; Biomechanics; Boundary conditions; Brain; Brain - diagnostic imaging; Brain - pathology; Brain - physiopathology; Brain modeling; Brain Neoplasms - diagnosis; Brain Neoplasms - physiopathology; Computer Simulation; Computerized, statistical medical data processing and models in biomedicine; Deformable models; Deformation; Disease Progression; Finite element method; Finite element methods; Humans; Magnetic Resonance Imaging; Medical management aid. Diagnosis aid; Medical sciences; Neoplasms; Neurology; Oncology; Pathology; Reproducibility of Results; Skull; Tomography, X-Ray Computed; Tumors of the nervous system. Phacomatoses
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/42.790458

A biomechanical model of the brain is presented, using a finite-element formulation. Emphasis is given to the modeling of the soft-tissue deformations induced by the growth of tumors and its application to the registration of anatomical atlases, with images from patients presenting such pathologies. First, an estimate of the anatomy prior to the tumor growth is obtained through a simulated biomechanical contraction of the tumor region. Then a normal-to-normal atlas registration to this estimated pre-tumor anatomy is applied. Finally, the deformation from the tumor-growth model is applied to the resultant registered atlas, producing an atlas that has been deformed to fully register to the patient images. The process of tumor growth is simulated in a nonlinear optimization framework, which is driven by anatomical features such as boundaries of brain structures. The deformation of the surrounding tissue is estimated using a nonlinear elastic model of soft tissue under the boundary conditions imposed by the skull, ventricles, and the falx and tentorium. A preliminary two-dimensional (2-D) implementation is presented in this paper, and tested on both simulated and patient data. One of the long-term goals of this work is to use anatomical brain atlases to estimate the locations of important brain structures in the brain and to use these estimates in pre-surgical and radiosurgical planning systems.