Computational methods for planning of image-guided surgery methods

图像引导手术方法规划的计算方法

• 批准号: RGPIN-2019-05063
• 负责人: Kunz, Manuela
• 金额: $ 2.04万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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=682173
• 关键词: Computational; methods; planning; image; guided

The proposed research aims to improve surgical interventions using innovative software methods for image-guided surgery. During image-guided interventions, medical images of the affected anatomy are obtained prior to surgery and a 3D virtual model of the anatomy is created by extracting relevant data from these images. This model is then used in specially designed software to support the surgeon in pre-planning the procedure. During this planning, the surgeon makes decisions such as the required size of the incision, which prosthesis components are optimal for the patient, and which instrument positions and trajectories are needed to ensure the best outcome. During surgery, tracking methods are provided in the operating theatre as a navigation aid for the surgeon in following the planned instrument trajectories. ******This research program will focus on novel and advanced methods to improve pre-surgery planning. One theme involves development and testing of computational methods to generate more accurate representations of the affected anatomy in the 3D computer generated model. ******A second theme of this research program will investigate computational methods to create more accurate and clinically relevant planning of prosthesis component size, position, and/or instrument trajectories. This will involve building a mathematical model for the process of surgical decision-making and using this model to design planning systems to support the surgeon more effectively. Artificial intelligence will be employed to identify patterns between planning parameters and clinical outcomes for surgeries for a large population of patients. These patterns can then predict clinical outcomes based on virtual planning of the surgery. By providing a safe and easy-to-use online system, experiences from a wide community of surgeons can be used in developing each new plan.***The proposed program will train graduate and undergraduate students in a highly interdisciplinary environment in software development, medical image modalities, image analysis algorithms, statistical methods, artificial intelligence methods, and graphical user interface design. ******The proposed research has the potential to improve the outcome for surgical interventions, reduce the number of revision or repeat surgeries, make surgical systems more user-friendly, and improve the efficiency in the surgery room. At a time when health care costs are steadily rising and the number of orthopaedic procedures is expected to double in coming years, the proposed research can provide economic solutions for surgical interventions. Just as today we expect that every car be equipped with a navigation device, this research program will be part of a future in which every surgical intervention will be supported by an image-guided navigation device. **

本研究旨在利用影像引导手术的创新软件方法改善手术干预。在图像引导干预期间，在手术前获得受影响解剖结构的医学图像，并通过从这些图像中提取相关数据创建解剖结构的3D虚拟模型。然后，这个模型被用在专门设计的软件中，以支持外科医生预先计划手术。在这个计划过程中，外科医生做出决定，如切口所需的大小，哪些假体组件最适合患者，以及需要哪些器械位置和轨迹来确保最佳结果。在手术过程中，在手术室中提供跟踪方法，作为外科医生跟随计划的器械轨迹的导航辅助。******这个研究项目将专注于新颖和先进的方法来改善术前计划。其中一个主题涉及开发和测试计算方法，以在3D计算机生成的模型中生成更准确的受影响解剖结构表示。******本研究计划的第二个主题将研究计算方法，以创建更准确和临床相关的假体部件尺寸，位置和/或器械轨迹规划。这将包括为手术决策过程建立数学模型，并使用该模型设计计划系统，以更有效地支持外科医生。人工智能将被用于识别大量患者手术的计划参数和临床结果之间的模式。这些模式可以根据手术的虚拟计划预测临床结果。通过提供一个安全且易于使用的在线系统，来自广泛的外科医生社区的经验可以用于制定每个新计划。***该计划将在软件开发、医学图像模式、图像分析算法、统计方法、人工智能方法和图形用户界面设计等高度跨学科的环境中培养研究生和本科生。******提出的研究有可能改善手术干预的结果，减少修改或重复手术的次数，使手术系统更加用户友好，并提高手术室的效率。在医疗保健费用稳步上升和骨科手术数量预计在未来几年翻一番的时候，拟议的研究可以为外科干预提供经济的解决方案。就像今天我们期望每辆汽车都配备导航设备一样，这个研究项目将成为未来每一次手术干预都将由图像引导导航设备支持的一部分。**