IEEE Transactions on Medical Imaging · 1999 · 165 citations · 25 references
MedicineNeurosurgerySurgeryBiomedical ImagingFinite Element AnalysisHuman AnatomyImage RegistrationIntraoperative NavigationSurgical AnatomyThree-dimensional ReconstructionAnatomical Deformation ModelingDeformation ModelsImage-guided NeurosurgeryIntraoperative GuidanceIntraoperative RegistrationMedical Image RegistrationOrgan Shape DeterminationPatient-to-image Registration
Brain deformations during surgery cause significant changes in anatomy, making navigation based on preoperative images error‑prone. The study develops a finite‑element biomechanical model of the human head to correct preoperative images for intraoperative brain deformations, aiming to improve navigation accuracy. The model is a 2‑D finite‑element framework with two material types (extendable to 3‑D and multiple materials) that incorporates user‑specified homologous landmarks as correspondences, and has been applied to synthetic and real MR image pairs for deformation correction. Material parameters were derived from literature, and the model produced physically plausible deformations on synthetic data and accurately predicted intraoperative changes in real MR images, even when landmarks were limited to a small region.
The accuracy of image-guided neurosurgery generally suffers from brain deformations due to intraoperative changes. These deformations cause significant changes of the anatomical geometry (organ shape and spatial interorgan relations), thus making intraoperative navigation based on preoperative images error prone. In order to improve the navigation accuracy, we developed a biomechanical model of the human head based on the finite element method, which can be employed for the correction of preoperative images to cope with the deformations occurring during surgical interventions. At the current stage of development, the two-dimensional (2-D) implementation of the model comprises two different materials, though the theory holds for the three-dimensional (3-D) case and is capable of dealing with an arbitrary number of different materials. For the correction of a preoperative image, a set of homologous landmarks must be specified which determine correspondences. These correspondences can be easily integrated into the model and are maintained throughout the computation of the deformation of the preoperative image. The necessary material parameter values have been determined through a comprehensive literature study. Our approach has been tested for the case of synthetic images and yields physically plausible deformation results. Additionally, we carried out registration experiments with a preoperative MR image of the human head and a corresponding postoperative image simulating an intraoperative image. We found that our approach yields good prediction results, even in the case when correspondences are given in a relatively small area of the image only.
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