Jonathan C Lau1, Keith W MacDougall2, Miguel F Arango3, Terry M Peters4, Andrew G Parrent2, Ali R Khan4. 1. Imaging Research Laboratories, Robarts Research Institute, Western University, London, Ontario, Canada; Biomedical Engineering Graduate Program, Western University, London, Ontario, Canada; Division of Neurosurgery, Department of Clinical Neurological Sciences, London Health Sciences Centre, University Hospital, Western University, London, Ontario, Canada. Electronic address: jonathan.c.lau@gmail.com. 2. Division of Neurosurgery, Department of Clinical Neurological Sciences, London Health Sciences Centre, University Hospital, Western University, London, Ontario, Canada. 3. Department of Anesthesia and Perioperative Medicine, London Health Sciences Centre, University Hospital, Western University, London, Ontario, Canada. 4. Imaging Research Laboratories, Robarts Research Institute, Western University, London, Ontario, Canada; Biomedical Engineering Graduate Program, Western University, London, Ontario, Canada; Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Abstract
BACKGROUND: Template and atlas guidance are fundamental aspects of stereotactic neurosurgery. The recent availability of ultra-high field (7 Tesla) magnetic resonance imaging has enabled in vivo visualization at the submillimeter scale. In this Doing More with Less article, we describe our experiences with integrating ultra-high field template data into the clinical workflow to assist with target selection in deep brain stimulation (DBS) surgical planning. METHODS: The creation of a high-resolution 7T template is described, generated from group data acquired at our center. A computational workflow was developed for spatially aligning the 7T template with standard clinical data and furthermore, integrating the derived imaging volumes into the surgical planning workstation. RESULTS: We demonstrate that our methodology can be effective for assisting with target selection in 2 cases: unilateral internal pallidum DBS for painful dystonia and bilateral subthalamic nucleus DBS for Parkinson's disease. CONCLUSIONS: In this article, we have described a workflow for the integration of high-resolution in vivo ultra-high field templates into the surgical navigation system as a means to assist with DBS planning. The method does not require any additional cost or time to the patient. Future work will include prospectively evaluating different templates and their impact on target selection. Crown
BACKGROUND: Template and atlas guidance are fundamental aspects of stereotactic neurosurgery. The recent availability of ultra-high field (7 Tesla) magnetic resonance imaging has enabled in vivo visualization at the submillimeter scale. In this Doing More with Less article, we describe our experiences with integrating ultra-high field template data into the clinical workflow to assist with target selection in deep brain stimulation (DBS) surgical planning. METHODS: The creation of a high-resolution 7T template is described, generated from group data acquired at our center. A computational workflow was developed for spatially aligning the 7T template with standard clinical data and furthermore, integrating the derived imaging volumes into the surgical planning workstation. RESULTS: We demonstrate that our methodology can be effective for assisting with target selection in 2 cases: unilateral internal pallidum DBS for painful dystonia and bilateral subthalamic nucleus DBS for Parkinson's disease. CONCLUSIONS: In this article, we have described a workflow for the integration of high-resolution in vivo ultra-high field templates into the surgical navigation system as a means to assist with DBS planning. The method does not require any additional cost or time to the patient. Future work will include prospectively evaluating different templates and their impact on target selection. Crown
Authors: Jonathan C Lau; Andrew G Parrent; John Demarco; Geetika Gupta; Jason Kai; Olivia W Stanley; Tristan Kuehn; Patrick J Park; Kayla Ferko; Ali R Khan; Terry M Peters Journal: Hum Brain Mapp Date: 2019-06-07 Impact factor: 5.038
Authors: Mohamad Abbass; Greydon Gilmore; Alaa Taha; Ryan Chevalier; Magdalena Jach; Terry M Peters; Ali R Khan; Jonathan C Lau Journal: Brain Struct Funct Date: 2021-10-23 Impact factor: 3.270