Translating The Individualized Functional Connectome To Surgical Planning

 描述(由申请人提供)：脑功能的定位对于减少神经外科手术后的功能缺陷很重要。一个长期的目标是在手术前获得这一信息，以便更好地预测风险并计划手术入路。虽然有许多非侵入性工具可用，但功能磁共振成像在临床上的应用最多。不幸的是，fMRI术前标测在单一受试者水平的信噪比(SNR)和重测可靠性较差，所得到的标测结果与有创电皮质刺激(ECS)的结果并不总是一致，导致许多人质疑其临床应用价值。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局限性。其中许多进展都集中在基于自发活动的连接性成像上，这在一定程度上是由NIH人类连接组项目(HCP)催化的。这些技术创新和理论进步现在已经成熟，可以转化为个别临床患者，但需要优化和验证。该项目的目标是通过开发和验证一套能够提供个人级别精度并指导手术干预的功能标测工具，将基于连接的尖端成像技术转化到临床舞台上。具体地说，我们将开发和验证一种基于连接的分割技术，该技术可以在单个受试者中定位功能网络，包括在大脑解剖结构改变的患者中。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，当患者能够执行任务时，通过灵活地结合自发连接和任务诱发反应获得的信息来提高映射的准确性。这一战略将使我们能够利用20年来使用任务功能磁共振成像进行探索的经验教训，以及最近在连接研究方面取得的革命性进展。该项目的成功完成将极大地提高功能磁共振成像在外科手术计划中的临床价值，以及在广泛的临床应用中。该项目将提供一套全面的、经过广泛测试的功能绘图工具，适用于个别对象的研究，具有比目前更高的敏感性和可靠性。测绘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)为许多神经科和精神科患者设计个性化治疗计划的能力的增强。

 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.