A Comprehensive Clinical fMRI Software Solution to Enable Mapping of Critical Functional Networks and Cerebrovascular Reactivity in the Brain

全面的临床 fMRI 软件解决方案，可绘制大脑中的关键功能网络和脑血管反应性

• 批准号: 10365573
• 负责人: CATHERINE L ELSINGER
• 金额: $ 40.24万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-21 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10365573
• 关键词: Area; Blood Vessels; Brain; Brain Neoplasms; Clinical; Clinical Investigator; Clinical Research; Communities; Computer software; Data; Data Set; Disease; Ensure; Environment; Epilepsy; Excision; Failure; Functional Magnetic Resonance Imaging; Hand; Hypercapnia; Image; Impairment; Institution; Language; Lesion; Linear Models; Magnetic Resonance Imaging; Malignant neoplasm of brain; Maps; Measurement; Measures; Methods; Morbidity - disease rate; Motor; Navigation System; Neoplasms; Neurosciences; Neurosciences Research; Operative Surgical Procedures; Pathology; Patients; Procedures; Process; Research; Rest; Seasons; Seeds; Signal Transduction; Software Tools; Surgeon; Technology; Testing; Tissues; Tongue; Work; base; blood oxygen level dependent; brain surgery; brain tumor resection; cerebrovascular; clinical care; compliance behavior; flexibility; foot; graphical user interface; improved; independent component analysis; innovation; malformation; nervous system disorder; neurosurgery; neurovascular; neurovascular coupling; novel; patient population; preservation; prevent; software development; standard of care; tool; visual motor

Project Summary Functional localization of eloquent brain areas for patients undergoing surgery for brain tumors, epilepsy, or other neurological diseases is crucial to prevent post-surgical deficits and reduce morbidity. Task-based (tb) functional MRI (fMRI), which detects blood oxygenation level–dependent (BOLD) signal changes while a patient performs task paradigms, is a standard-of-care clinical procedure for presurgical mapping of eloquent cortices. Two major limitations of clinical tb-fMRI are a patient's inability to perform the task and lesion-induced impairment of neurovascular coupling (which drives the BOLD signal). Resting-state (rs) fMRI, which measures synchronized BOLD signal oscillations during rest, can be used to map brain networks with minimal requirements for patient compliance and has been demonstrated to accurately localize motor and language areas for presurgical planning. Cerebrovascular reactivity (CVR) mapping, accessed by dynamic BOLD imaging during a hypercapnia task such as breath-holding, can be used to identify areas with potential false-negative fMRI results due to neurovascular uncoupling (NVU) and has been suggested as an emerging standard to be used with clinical fMRI. Currently, there are no commercially available FDA-cleared software tools for localizing the resting-state networks (RSNs) or CVR. Clinical investigators have relied on research software packages that are either not clinically integrated or not yet optimized and validated in large patient populations. Thus, a vetted software solution is urgently needed to enable these state-of-the-art fMRI methods to benefit patients beyond the limitations of tb-fMRI. We hypothesize that enhancing, optimizing, and validating our preliminary software and integrating it with an established commercial fMRI platform will create robust solutions for clinical mapping of RSN and CVR. Through three specific aims, the software solutions will be optimized and tested with rs-fMRI and CVR datasets from approximately 350 patients with brain tumors or epilepsy at three institutions. Aim 1 is to create the software for mapping RSNs and determine optimized workflows for localizing eloquent areas including primary visual, motor (hands, tongue, and feet), and language (primary and secondary) areas. Both seed-based correlation and independent component analysis will be incorporated. Aim 2 is to create the software for mapping CVR and determine the optimized workflow for identifying and visualizing brain areas with potential false-negative fMRI results. The software will include a multiple-latency general linear model and a unique graphical user interface to visualize the NVU. Aim 3 is to test and validate the software with presurgical fMRI datasets. The results will be compared against those obtained from (1) processed using widely used research software packages, (2) tb- fMRI, and (3) intraoperative direct cortical stimulation. This research is anticipated to create robust and clinically available software that will greatly increase the patient population who can benefit from presurgical fMRI and will improve confidence in functional localization for surgical planning. This will directly benefit patients by preserving their post-surgical functions while allowing surgeons to safely maximize the resection of brain lesions.

项目摘要 雄辩的大脑区域的功能定位，用于接受手术的脑肿瘤，癫痫或其他 神经系统疾病对于预防手术后缺陷和降低发病率至关重要。基于任务的（TB）功能 MRI（fMRI），检测到血液氧合水平依赖性（粗体）信号发生变化，而患者执行 任务范式是雄辩皮质的预术预绘图的标准临床程序。两个主要 临床TB-FMRI的局限性是患者无法执行任务和病变引起的障碍 神经血管耦合（驱动大胆信号）。静止状态（RS）fMRI，测量同步 休息期间大胆的信号振荡可用于绘制对患者需求最小要求的脑网络 合规性并已被证明可以准确定位运动和语言领域以进行术前计划。 脑血管反应性（CVR）映射，在超碳酸含量任务中通过动态粗体成像访问 作为呼吸的呼吸，可用于识别由于神经血管引起的潜在假阴性fMRI结果的区域 解偶联（NVU）已被认为是与临床fMRI一起使用的新兴标准。现在， 没有商业可用的FDA清理软件工具来本地化静止状态网络（RSN） 或CVR。临床研究人员已经了解了未临床整合的研究软件包 或尚未在大型患者人群中进行优化和验证。那就是急切的软件解决方案 需要使这些最先进的fMRI方法使患者受益于TB-FMI的局限性。我们 假设增强，优化和验证我们的初步软件，并将其集成 已建立的商业FMRI平台将为RSN和CVR的临床映射创建强大的解决方案。通过 三个具体目的，将使用RS-FMRI和CVR数据集对软件解决方案进行优化和测试 在三个机构中，大约有350例脑瘤或癫痫患者。目标1是为 绘制RSN和确定的优化工作流，用于定位雄辩区域，包括主要视觉，电动机 （手，舌和脚）以及语言（主要和次要）区域。基于种子的相关性和 独立的组件分析将合并。 AIM 2是创建用于映射CVR和的软件 确定具有潜在假阴性fMRI的优化工作流程，以识别和可视化大脑区域 结果。该软件将包含多延节通用线性模型和唯一的图形用户界面 可视化NVU。 AIM 3是使用前fMRI数据集测试和验证软件。结果将 比较与使用广泛使用的研究软件包处理的（1）获得的（2）TB- fMRI和（3）术中直接皮质刺激。这项研究预计会在临床上创造强大的 可用的软件将大大增加可以从术前fMRI中受益的患者人群 提高对手术计划功能定位的信心。这将通过保存直接使患者受益 他们的后手术功能，同时允许外科医生安全地最大化脑病变的切除。