Data-guided brain deformation modeling: evaluation of a 3-D adjoint inversion method in porcine studies.

Biomechanical models of brain deformation are useful tools for estimating parenchymal shift that results during open cranial procedures. Intraoperative data is likely to improve model estimates, but incorporation of such data into the model is not trivial. This study tests the adjoint equations method (AEM) for data assimilation as a viable approach for integrating displacement data into a brain deformation model.

Stereopsis-guided brain shift compensation.

Brain deformation models have proven to be a powerful tool in compensating for soft tissue deformation during image-guided neurosurgery. The accuracy of these models can be improved by incorporating intraoperative measurements of brain motion. We have designed and implemented a passive intraoperative stereo vision system capable of estimating the three-dimensional shape of the surgical scene in near real-time.

Assimilating intraoperative data with brain shift modeling using the adjoint equations.

Biomechanical models of brain deformation are increasingly being used to nonrigidly register preoperative MR (pMR) images of the brain to the surgical scene. These model estimates can potentially be improved by incorporating sparse displacement data available in the operating room (OR), but integrating the intraoperative information with model calculations is a nontrivial problem. We present an inverse method to estimate the unknown boundary and volumetric forces necessary to achieve a least-squares fit between the model and the data that is formulated in terms of the adjoint equations, which are solved directly by the method of representers.

Displacement estimation with co-registered ultrasound for image guided neurosurgery: a quantitative in vivo porcine study.

Brain shift during open cranial surgery presents a challenge for maintaining registration with image-guidance systems. Ultrasound (US) is a convenient intraoperative imaging modality that may be a useful tool in detecting tissue shift and updating preoperative images based on intraoperative measurements of brain deformation. We have quantitatively evaluated the ability of spatially tracked freehand US to detect displacement of implanted markers in a series of three in vivo porcine experiments, where both US and computed tomography (CT) image acquisitions were obtained before and after deforming the brain.

In vivo quantification of retraction deformation modeling for updated image-guidance during neurosurgery.

The use of coregistered preoperative anatomical scans to provide navigational information in the operating room has greatly benefited the field of neurosurgery. Nonetheless, it has been widely acknowledged that significant errors between the operating field and the preoperative images are generated as surgery progresses. Quantification of tissue shift can be accomplished with volumetric intraoperative imaging; however, more functional, lower cost alternative solutions to this challenge are desirable.

Model-Updated Image-Guided Neurosurgery: Preliminary Analysis Using Intraoperative MR.

In this paper, initial clinical data from an intraoperative MR system are compared to calculations made by a three-dimensional finite element model of brain deformation. The preoperative and intraoperative MR data was collected on a patient undergoing a resection of an astrocytoma, grade 3 with non-enhancing and enhancing regions. The image volumes were co-registered and cortical displacements as well as subsurface structure movements were measured retrospectively.