Achieving precision in Image-guided Neurosurgery via an open source collaborative software environment

通过开源协作软件环境实现图像引导神经外科手术的精确度

• 批准号: 523447-2018
• 负责人: Collins, DLouis
• 金额: $ 31.39万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Health Research Projects
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=694925
• 关键词: Achieving; precision; Image; guided; Neurosurgery

Each year, thousands of Canadians undergo neurosurgery for resection of brain lesions suchas tumours, epileptic foci and vascular malformations that are in close proximity to areas ofthe brain that are critical to movement, vision, sensation, or language. Accurate guidanceinformation is required to balance two constraints: achieving maximal resection ofpathological tissue while minimizing potential neurological deficits. Image-guidedneurosurgery systems (i.e., a GPS for surgery) provide tools to visualize and interpret patientspecificvolumes of anatomical, vascular and functional data to enable precise surgicalinterventions. Unfortunately, brain tissue can deform up to 30mm or more during surgery(known as brain shift). Over the past 15 years, Collins' NeuroImaging and SurgicalTechnologies (NIST) lab at the MNI has developed an open-source research image-guidedsurgery platform known as IBIS. Our novel contribution uses ultrasound, acquired intraoperatively,to achieve accurate patient-image registration, even in the presence of brain shift.However, our methods can sometimes be limitated in terms of accuracy, robustness, andanatomical coverage.We propose to integrate data from multiple sensors and multiple algorithms to accurately androbustly account for brain shift and allow for accurate guidance throughout surgery. To dothis we will apply Kalman filters in a multi-channel registration framework. To reducedevelopment costs and facilitate inter-lab collaborations, we will integrate our IBIS softwareinto 3DSlicer to take advantage of a huge user base (280,000 downloads, 250+/week). Ourindustrial partner Synaptive Medical, a dynamic Toronto-based startup, will provide input,ensure commercial relevance and help trainees learn about development andcommercialization of medical devices. Synaptive's help will facilitate translation of our imageguidedtechnology to the operating room so that all patients can benefit from these tools.

每年，数以千计的加拿大人接受神经外科手术切除脑病变，如肿瘤，癫痫灶和血管畸形，这些病变靠近对运动，视觉，感觉或语言至关重要的大脑区域。需要精确的指导信息来平衡两个约束：实现病理组织的最大切除，同时最大限度地减少潜在的神经功能缺损。图像引导神经外科系统（即，用于外科手术的GPS）提供了可视化和解释患者特定体积的解剖、血管和功能数据的工具，以实现精确的外科干预。不幸的是，在手术过程中，脑组织可能会变形30毫米或更多（称为脑移位）。在过去的15年里，柯林斯在MNI的神经影像和外科技术（NIST）实验室开发了一个开源的研究图像引导手术平台，称为IBIS。我们的新贡献是使用术中获得的超声波来实现精确的患者图像配准，即使在存在脑移位的情况下。然而，我们的方法有时会在准确性，鲁棒性和解剖覆盖范围方面受到限制。我们建议整合来自多个传感器和多种算法的数据，以准确地解释脑移位，并在整个手术过程中提供准确的指导。为此，我们将在多通道配准框架中应用卡尔曼滤波器。为了降低开发成本并促进实验室间的协作，我们将把我们的IBIS软件集成到3DSlicer中，以利用庞大的用户群（280，000次下载，每周250次以上）。我们的工业合作伙伴Synaptive Medical是一家充满活力的多伦多初创公司，将提供投入，确保商业相关性，并帮助学员了解医疗设备的开发和商业化。Synaptive的帮助将促进我们的图像引导技术在手术室的应用，使所有患者都能从这些工具中受益。