Deep-brain stimulation (DBS) procedures, which are increasingly used to treat a spectrum of movement, mood and behavioral disorders, are complex. Effective electrode implantation requires a painstaking procedure that begins with the challenging task of correlating anatomical target selection with physiological correction to account for patient variance and intraoperative brain shift. Following implantation, stimulation parameters that reduce symptoms while minimizing side effects need to be selected through a test-and-observe process that can be lengthy and spread over several visits. Over the last two funding periods of this project we have developed a system that provides assistance for all phases of the procedure. This system is the first one that permits the capture, storage, and spatial normalization of all data pertaining to DBS cases. This permits the creation of population-derived statistical atlases, customization of this information to individual patients, ad access to this information at the time and point of care. This system has been integrated into the clinical flow at our institution and contains data from more than 1400 subjects acquired at multiple institutions. We have shown that this system has a positive impact on the planning, placement, and programming phases of the procedure and, thanks to commercial partnerships we have established, components of our system are already available for routine clinical use. In this funding period, we will build on our previous efforts to continue the clinical evaluation of or system, expand its functionality, and deploy it at collaborating sites. Our long term goals are to develop and field (1) the first integrated DBS solution that will permit seamless exchange of information between all phases of the procedure and (2) a shared and global resource that will allow rapid dissemination of discovery and outcomes related to specific brain targets. It will thus be a catalyst that can both speed up discoveries in neurological sciences and improve clinical processes.
Deep brain stimulation (DBS) implant requires precise placement of electrodes deep within the brain. Surgical implantation is difficult and the device can be challenging to program once it is implanted. In this project, we will build on eight years o research efforts to continue the development and clinical deployment of a system that provides assistance to clinical teams for the planning, implantation, and programing phases of the procedure.
Huo, Yuankai; Bao, Shunxing; Parvathaneni, Prasanna et al. (2018) Improved Stability of Whole Brain Surface Parcellation with Multi-Atlas Segmentation. Proc SPIE Int Soc Opt Eng 10574: |
Chakravorti, Srijata; Morgan, Victoria L; Trujillo-Diaz, Paula et al. (2018) A Structural Connectivity Approach to Validate a Model-based Technique for the Segmentation of the Pulvinar Complex. Proc SPIE Int Soc Opt Eng 10578: |
Gao, Yurui; Schilling, Kurt G; Stepniewska, Iwona et al. (2018) Tests of clustering thalamic nuclei based on various dMRI models in the squirrel monkey brain. Proc SPIE Int Soc Opt Eng 10578: |
Bermudez, Camilo; Plassard, Andrew J; Davis, Taylor L et al. (2018) Learning Implicit Brain MRI Manifolds with Deep Learning. Proc SPIE Int Soc Opt Eng 10574: |
Petersen, Kalen J; Reid, Jacqueline A; Chakravorti, Srijata et al. (2018) Structural and functional connectivity of the nondecussating dentato-rubro-thalamic tract. Neuroimage 176:364-371 |
Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing et al. (2018) Robust Multicontrast MRI Spleen Segmentation for Splenomegaly Using Multi-Atlas Segmentation. IEEE Trans Biomed Eng 65:336-343 |
Huo, Yuankai; Xu, Zhoubing; Bao, Shunxing et al. (2018) Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks. Proc SPIE Int Soc Opt Eng 10574: |
Bobo, Meg F; Bao, Shunxing; Huo, Yuankai et al. (2018) Fully Convolutional Neural Networks Improve Abdominal Organ Segmentation. Proc SPIE Int Soc Opt Eng 10574: |
Jermakowicz, Walter J; Cajigas, Iahn; Dan, Lia et al. (2018) Ablation dynamics during laser interstitial thermal therapy for mesiotemporal epilepsy. PLoS One 13:e0199190 |
Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing et al. (2017) Multi-atlas Segmentation Enables Robust Multi-contrast MRI Spleen Segmentation for Splenomegaly. Proc SPIE Int Soc Opt Eng 10133: |
Showing the most recent 10 out of 31 publications