This study proposes the development of minimally-invasive microscopy for image guided deep brain optical biopsy and accurate placement of electrodes for deep brain stimulation. This system will allow real-time tissue evaluation and accurate placement for interventions. Minimally-invasive multiphoton fluorescence microscopy using gradient index (GRIN) lenses can provide high quality images with subcellular resolution for the evaluation of pathology below the brain surface. The overall objective of this work is to develop a microscope system with accurate positioning, and to test and validate the system in phantoms. In order to make this technology useful for neurosurgical intervention, conventional intraoperative computed tomography (CT) is needed in order to position and localize the microscope in the neurosurgical environment. In addition, precise localization requires compensation for brain deformation due to brain shift and the insertion of the microscope. This work therefore requires the development of the microscope, image analysis methods for registration of intraoperative images, biomechanical modeling for brain deformation computation and integration into an image-guided neurosurgical system. The microscopy system must be designed with a sufficiently narrow and long GRIN lens to reach potential target regions with minimal tissue damage. The registration methods must be robust to the lower image quality and coverage afforded by intra-operative CT imaging. The deformation methods must provide accurate biomechanical models without excessive computation. Studies of gel phantoms with implanted particles will demonstrate the feasibility of the system, the quality of the microscopy, and the accuracy of placement and deformation. In the next phase of this work, patient studies will be designed for optical biopsy and for precise biosensor or therapeutics delivery placement. to Public Health The development of deep brain microscopy has the potential to revolutionize neurosurgical interventions such as biopsy and electrode placement, making them more accurate and efficient with the goal of improving the efficacy of treatments for diseases such as cancer, Parkinson disease and epilepsy. This development will address key limitations of current imaging techniques such as the lack of resolution or specificity to distinguish normal tissue from cancerous tissue, or to precisely determine the location of different cell layers as needed in electrode implantation for Parkinson disease. ? ? ?
| Joshi, A; Scheinost, D; Globinsky, R et al. (2011) AUGMENTED INLINE-BASED NAVIGATION FOR STEREOTACTIC IMAGE GUIDED NEUROSURGERY. Proc IEEE Int Symp Biomed Imaging :1869-1872 |
| Papademetris, Xenophon; DeLorenzo, Christine; Flossmann, Sven et al. (2009) From medical image computing to computer-aided intervention: development of a research interface for image-guided navigation. Int J Med Robot 5:147-57 |
| Tokuda, Junichi; Fischer, Gregory S; Papademetris, Xenophon et al. (2009) OpenIGTLink: an open network protocol for image-guided therapy environment. Int J Med Robot 5:423-34 |
| Joshi, Alark; Scheinost, Dustin; Vives, Kenneth P et al. (2008) Novel interaction techniques for neurosurgical planning and stereotactic navigation. IEEE Trans Vis Comput Graph 14:1587-94 |
