Rapid Analysis of Intraoperatively Acquired DTI for Identification of Key White M

快速分析术中获得的 DTI 以识别关键白色 M

基本信息

批准号：
8298128
负责人：
ALEXANDRA J GOLBY
金额：
$ 33.33万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-07-06 至 2014-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8298128
关键词：
Address Agreement Anatomy Area Biological Preservation Brain Brain Mapping Brain Neoplasms Clinical Code Computer software Computing Methodologies Corticospinal Tracts Craniotomy Data Data Set Development Diffusion Diffusion Magnetic Resonance Imaging Dissection Documentation Electric Stimulation Equilibrium Excision Eye Surgeon Fiber Functional Magnetic Resonance Imaging Goals Imagery Inferior Injury Language Left Length Lesion Location MRI Scans Magnetic Resonance Imaging Maps Measures Methods Modality Modeling Motor Neurologic Neuronavigation Neurosurgeon Operating Rooms Operative Surgical Procedures Patients Performance Process Published Comment Research Scanning Sensory Slice Software Design Speed Structure Surgeon System Testing Time Translating Update Validation base brain surgery computerized gray matter improved insight interest multithreading neurosurgery novel open source scale up software systems success tumor validation studies virtual white matter

项目摘要

DESCRIPTION (provided by applicant): Surgical removal, or resection, is the most important treatment for brain tumors. When tumors are located near critical brain areas such as motor, sensory, or language functions, the goal of complete resection must be balanced with the goal of preservation of function. Injury to critical white matter connections, or tracts, will leave the patient with serious neurological deficits. However, during surgery, the tracts are not visible to the surgeon's eye, and their consistency may be the same as the tumor. Thus, the surgical treatment of brain tumors can benefit tremendously from more complete, accurate structural-functional brain maps. Diffusion tensor MRI (DTI) is a relatively new MRI modality that is sensitive to the structure of the white matter. This project aims to translate current DTI research into the operating room to address challenges of white matter tract identification during surgery. The long-term objectives of this project are to improve white matter mapping for neurosurgery and to increase our understanding of the effect of neurosurgery on the white matter. The trajectories of the white matter tracts can be mapped using diffusion tensor DTI tractography. But because the tracts of interest must be selected for viewing in a process called virtual dissection that can take 10 minutes per tract, the clinical use of intraoperative DTI tractography has been limited in scope. Most often only one crucial tract has been mapped per patient. We hypothesize that by using the patient's own brain as a reference, i.e. by taking advantage of patient-specific models of crucial tracts contained in their personalized surgical plan, we can quickly and accurately produce an updated brain map when the patient is scanned during surgery. We will develop a software system to produce the white matter brain map on the fly during neurosurgery, and we will perform two validation studies to test our hypothesis. We propose the following objectives that will take advantage of our new state-of-the-art, high field strength intraoperative 3T MRI system and our research neuronavigation software platform, 3D Slicer. (1) Develop and optimize computational methods for rapid identification of crucial fiber tracts in intraoperative DTI. This part of the project will focus on mathematical development of tract similarity measures, and on software design and implementation. (2) Validate speed and accuracy of the system via a multi-rater study and electrical stimulation in the OR. This part of the project will focus on clinical validation of the system by a neurosurgeon and neuroradiologist, and it will allow us to test our original hypothesis that we can quickly create an accurate brain map for the white matter during surgery.

描述（由申请人提供）：手术切除或切除是脑肿瘤最重要的治疗方法。当肿瘤位于运动、感觉或语言功能等关键大脑区域附近时，完全切除的目标必须与保留功能的目标相平衡。关键白质连接或神经束的损伤将使患者出现严重的神经功能缺损。然而，在手术过程中，外科医生的眼睛看不到这些束，它们的稠度可能与肿瘤相同。因此，脑肿瘤的手术治疗可以从更完整、更准确的大脑结构功能图谱中获益匪浅。弥散张量 MRI (DTI) 是一种相对较新的 MRI 模式，对白质结构敏感。该项目旨在将当前的 DTI 研究转化为手术室，以解决手术期间白质束识别的挑战。该项目的长期目标是改进神经外科手术的白质绘图，并增加我们对神经外科手术对白质影响的了解。可以使用扩散张量 DTI 纤维束成像来绘制白质纤维束的轨迹。但由于必须在称为虚拟解剖的过程中选择感兴趣的纤维束进行观察，每个纤维束可能需要 10 分钟，因此术中 DTI 纤维束成像的临床使用范围受到限制。大多数情况下，每位患者只绘制了一个重要的管道。我们假设，通过使用患者自己的大脑作为参考，即通过利用其个性化手术计划中包含的患者特定关键神经束模型，我们可以在手术期间扫描患者时快速准确地生成更新的大脑图。我们将开发一个软件系统，在神经外科手术期间动态生成白质脑图，并且我们将进行两项验证研究来检验我们的假设。我们提出以下目标，这些目标将利用我们最新的最先进的高场强术中 3T MRI 系统和我们的研究神经导航软件平台 3D Slicer。 (1) 开发和优化术中 DTI 中快速识别关键纤维束的计算方法。该项目的这一部分将重点关注区域相似性度量的数学开发以及软件设计和实现。 (2) 通过多评估者研究和手术室中的电刺激来验证系统的速度和准确性。该项目的这一部分将重点关注神经外科医生和神经放射科医生对该系统的临床验证，这将使我们能够测试我们最初的假设，即我们可以在手术过程中快速创建准确的白质脑图。