Epilepsy is a debilitating brain disorder and surgery is the key treatment modality for those patients whose seizures cannot be controlled medically. Epilepsy surgery is complex, requiring multimodal imaging data for planning and execution, and image analysis software is essential for this process. The overall goal of this application is to develop a robust commercial software platform for multimodal image analysis for epilepsy surgery that can obtain regulatory approval for clinical use in both academic and non- academic hospitals. These software tools were developed in part for the needs of our epilepsy research at Yale over the last 10 years under NIH/NIBIB funding and in part internally at Electrical Geodesics Inc. for the brain segmentation, source analysis, and display parts of the forthcoming GeoSource 3.0 software package. The innovation in this proposal lies (i) the development of innovative image analysis methodology that addresses specific needs in epilepsy image analysis and (ii) the translation of tested research software to a new design that will enable its successful transition via regulatory approval to clinical use. The significance of this proposal is that it aims to provide clinically usable epilepsy surgical planning software with explicit support for multimodal image integration and intracranial electrode localization that can be integrated with the image-guided navigation systems used for neurosurgery. This tool would have a major impact on both surgical planning and image-guided epilepsy neurosurgery.
In the US, the lifetime cost of epilepsy for an estimated 181,000 people with an onset in 1995 is projected at $11.1B and the annual cost for an estimated 2.3 million prevalent cases is estimated at $12.5B. In many of these cases, the treatment procedure requires identifying the abnormal brain region involved and removing it via neurosurgery. Epilepsy surgery costs over $100,000 per case and since the surgery is complex and often involves two phases, image analysis software is critical to integrate multimodal imaging and EEG recording for pre- and intra-operative decision support.
|Onofrey, John A; Staib, Lawrence H; Papademetris, Xenophon (2015) Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration. Inf Process Med Imaging 24:662-74|