Translating The Individualized Functional Connectome To Surgical Planning

将个性化功能连接组转化为手术计划

• 批准号: 9252600
• 负责人: Hesheng Liu
• 金额: $ 44.05万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9252600
• 关键词: Address; Algorithms; Anatomy; Area; Atlases; Brain; Characteristics; Clinical; Development; Functional Magnetic Resonance Imaging; Goals; Handedness; Human; Image; Imaging technology; Individual; Laboratories; Language; Language Disorders; Maps; Methods; Neurologic; Neurosurgical Procedures; Noise; Operative Surgical Procedures; Patients; Population; Postoperative Period; Reproducibility; Research; Rest; Risk; Series; Signal Transduction; Technology; Testing; Translating; United States National Institutes of Health; Validation; base; clinical application; cognitive function; cohort; connectome; design; flexibility; improved; individualized medicine; innovation; novel strategies; public health relevance; response; tool; treatment planning

 DESCRIPTION (provided by applicant): Localization of brain function is important to minimize functional deficits after neurosurgical procedures. A long-standing goal has been to obtain this information pre-operatively to better predict risk and plan the surgical approach. Although many non-invasive tools are available, fMRI has seen the greatest clinical use. Unfortunately, pre-operative mapping with fMRI suffers from poor signal to noise ratio (SNR) and test-retest reliability at the single-subject level, and the resulting maps are not always consistent with the findings of invasive electrical cortical stimulation (ECS), causing many to question its clinical utility. Recently, our laboratory and others have made major advances that may help address these limitations. Many of these advances have focused on connectivity imaging based on spontaneous activity, catalyzed in part by the NIH Human Connectome Project (HCP). These technical innovations and theoretical advancements are now ripe for being translated to individual clinical patients, but require optimization and validation. The goal of this project is o translate cutting-edge connectivity-based imaging technology to the clinical arena by developing and validating a set of functional mapping tools that can provide individual-level precision and guide surgical intervention. Specifically, we will develop and validate a connectivity-based parcellation technology that can localize functional networks in individual subjects, including in patients with altered brain anatomy. Second, we will develop and validate a connectivity-based method to quantify the lateralization of important cognitive functions and overcome the influence of anatomical asymmetry. Finally, we propose a strategy to improve mapping accuracy when patients are able to perform tasks by flexibly combining the information obtained from spontaneous connectivity and task-evoked responses. This strategy will allow us to leverage the lessons learned from 20 years of exploration using task fMRI and recent revolutionary advancements in connectivity research. The successful completion of this project will greatly improve the clinical value of fMRI in surgical planning, as well as in a wide range of clinical applications. The project will offer a set of comprehensive and extensively tested functional mapping tools suitable for the study of individual subjects with greater sensitivity and reliabilit than are currently available. This increase in mapping precision will directly translate into an enhanced ability to a) predict and reduce postoperative functional deficits, as well as to b) design individualized treatment plans for many neurological and psychiatric patients.

 描述（由申请人提供）：脑功能定位对于尽量减少神经外科手术后的功能缺陷非常重要。一个长期的目标是在术前获得这些信息，以更好地预测风险并计划手术方法。虽然有许多非侵入性的工具，但fMRI已经看到了最大的临床用途。不幸的是，术前映射与功能磁共振成像患有不良的信噪比（SNR）和重测信度在单一的主题水平，并得到的地图并不总是与侵入性电皮层刺激（ECS）的结果一致，导致许多人质疑其临床效用。最近，我们的实验室和其他实验室取得了重大进展，可能有助于解决这些限制。这些进展中的许多都集中在基于自发活动的连接成像上，部分由NIH人类连接组计划（HCP）催化。这些技术创新和理论进步现在已经成熟，可以转化为个体临床患者，但需要优化和验证。该项目的目标是通过开发和验证一套功能映射工具，将尖端的基于连接的成像技术转化为临床竞技场，这些工具可以提供个人水平的精度并指导手术干预。具体来说，我们将开发和验证一种基于连通性的包裹技术，该技术可以定位个体受试者的功能网络，包括大脑解剖结构改变的患者。其次，我们将开发和验证一种基于连接性的方法来量化重要认知功能的偏侧化，并克服解剖不对称的影响。最后，我们提出了一种策略，以提高映射的准确性时，患者能够执行任务，灵活地结合从自发连接和任务诱发的反应所获得的信息。这一策略将使我们能够利用20年来使用任务功能磁共振成像和最近在连接研究方面的革命性进展进行探索的经验教训。本项目的成功完成将极大地提高功能磁共振成像在手术规划中的临床价值，以及在广泛的临床应用中的价值。该项目将提供一套全面和广泛测试的功能映射工具，适用于研究个体受试者，具有比目前更高的灵敏度和可靠性。这种标测精度的提高将直接转化为a）预测和减少术后功能缺陷以及B）为许多神经和精神病患者设计个性化治疗计划的增强能力。