Label-free fluorescence lifetime imaging for intraoperative real-time guidance of neurological procedures

无标记荧光寿命成像，用于神经系统手术的术中实时指导

• 批准号: 10312134
• 负责人: Orin Bloch
• 金额: $ 62.04万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-15 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10312134
• 关键词: Affect; Area; Biochemical; Biometry; Biopsy; Brain; Brain Neoplasms; Cauterize; Characteristics; Classification; Clinical; Clinical Research; Clinical Trials; Complement; Complex; Comprehensive Cancer Center; Craniotomy; Data; Data Display; Databases; Diagnostic; Diagnostic Imaging; Diagnostic Procedure; Discrimination; Engineering; Environment; Epilepsy; Equipment; Excision; Fluorescence; Glioma; Goals; Harvest; Hemostatic function; Histopathology; Human; Image; Image-Guided Surgery; Imaging Device; Imaging Techniques; Imaging technology; Intervention; Label; Letters; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of brain; Manufacturer Name; Measurement; Metabolic; Microscope; Necrosis; Neoplasm Metastasis; Neurodegenerative Disorders; Neurologic; Neuronavigation; Neurosurgeon; Neurosurgical Procedures; Normal tissue morphology; Operative Surgical Procedures; Optics; Outcome; Pathologic; Pathology; Patient-Focused Outcomes; Patients; Predictive Value; Procedures; Property; Protocols documentation; Qi; Radiation necrosis; Resources; Scanning; Signal Transduction; Specimen; Surgeon; Surgical Oncology; Surgically-Created Resection Cavity; System; Techniques; Technology; Testing; Time; Tissue Sample; Tissues; Tumor Tissue; Validation; Visual; Visualization; brain abnormalities; brain tissue; brain tumor resection; cohort; data acquisition; diagnostic value; flexibility; fluorescence lifetime imaging; image processing; imaging system; improved; instrumentation; learning progression; multidisciplinary; nervous system disorder; neuro-oncology; neuropathology; novel; optical imaging; pragmatic implementation; prospective; real-time images; standard of care; success; temporal measurement; tool; tumor

PROJECT SUMMARY/ABSTRACT The outcome of brain tumor surgery is critically dependent on the neurosurgeon's ability to distinguish between abnormal and normal tissue in real-time. Our goal is to enhance this discrimination by using label-free Fluorescence Lifetime Imaging (FLIm) to detect tissue biochemical and metabolic characteristics that distinguish among different tissue types and, by integrating FLIm into the neurosurgical workflow, to provide this information in a real-time, visual format useful for guiding tumor biopsy and resection. FLIm-derived tissue fluorescence feature information will be co-registered with the preoperative-MRI (pMRI) and projected onto the conventional surgical microscope field-of-view (FOV). This should improve delineation of tumor margins and thus increase both the diagnostic yield of brain biopsy and the extent of tumor resection. The proposed FLIm technique will incorporate the following features: (1) Safe, rapid, and simultaneous measurement of time-resolved fluorescence decays in multiple spectral emission bands that will acquire extensive information in one scanning measurement of a large area of tissue selected by the surgeon; and (2) Fast analysis, display, and augmentation of fluorescence parameters that enable real-time visualization of optical data encoding diagnostic information onto the surgical FOV. The proposed clinical studies using FLIm as a stand- alone tool will establish classifiers to correlate FLIm parameters with specific tissue pathologies, an important step in demonstrating FLIm's diagnostic value. The proposed integration of FLIm as an adjunct to the neuronavigation system and surgical microscope will provide data for combined analysis to validate the benefit of FLIm diagnostics in neurosurgical procedures. Three aims are proposed: Aim 1) Construct and integrate a FLIm device as a diagnostic adjunct with conventional neurosurgical tools. Aim 2) Clinically evaluate the relationship between FLIm parameters and distinct tissue pathologies and develop classifiers for different tissue types. Aim 3) Validate FLIm for real-time intraoperative guidance through a prospective analysis. In summary, this study will demonstrate the clinical feasibility and utility of FLIm for intraoperative real-time assessment of neurosurgical margins and the resulting improvement in neuropathologic diagnostic yield. The acquired FLIm parameter database will enable subsequent clinical trials for automated tissue classification and diagnostic prediction. The new FLIm instrumentation, characterized by simple, fast and flexible data acquisition and display, and its seamless integration with existing neurosurgical imaging, will provide a less expensive alternative to intraoperative MRI and a valuable complement to current standard-of-care diagnostic procedures. Success in this area will warrant a more generalized use of FLIm in surgical oncology (other cancers) as well as guided interventions for treatment of functional neurologic diseases (e.g. epilepsy, neurodegenerative diseases).

项目摘要/摘要 脑肿瘤手术的结果至关重要取决于神经外科医生的区分能力 异常和正常组织实时。我们的目标是通过不使用标签来增强这种歧视 荧光寿命成像（FLIM），以检测区分区分的组织生化和代谢特征 在不同的组织类型中，以及通过将FLIM整合到神经外科工作流程中，以提供此信息 实时的视觉格式可用于指导肿瘤活检和切除。 Flim衍生的组织荧光 功能信息将与术前MRI（PMRI）共同注册，并投影到常规 手术显微镜视野（FOV）。这应该改善肿瘤边缘的描述，从而增加 脑活检的诊断产量和肿瘤切除程度。 提出的FLIM技术将包含以下功能：（1）安全，快速和同时 在多个光谱发射带中的时间分辨荧光衰减的测量 对外科医生选择的大片组织进行一次扫描测量中的广泛信息； （2） 快速分析，显示和增强荧光参数，可实时可视化光学 将诊断信息编码到手术FOV上的数据。提出的使用FLIM作为独立的临床研究 单独的工具将建立分类器将FLIM参数与特定的组织病理相关联，这是一个重要的 一步，展示FLIM的诊断价值。提议的FLIM作为辅助 神经训练系统和手术显微镜将提供合并分析的数据以验证收益 神经外科手术中的FLIM诊断。提出了三个目标：目标1）构建和整合 FLIM设备作为常规神经外科工具的诊断辅助手段。目标2）临床评估 FLIM参数与不同组织病理学之间的关系，并为不同组织开发分类器 类型。目标3）通过前瞻性分析验证FLIM进行实时术中指导。 总之，这项研究将证明FLIM对术中实时的临床可行性和效用 神经外科边缘的评估以及神经病理诊断产量的改善。这 获得的FLIM参数数据库将实现随后的临床试验，以进行自动组织分类和 诊断预测。新的Flim仪器以简单，快速和灵活的数据获取为特征 并显示及其与现有神经外科成像的无缝集成，将提供更便宜的 替代术中MRI以及对当前护理标准诊断程序的有价值的补充。 在这一领域的成功将保证在手术肿瘤学（其他癌症）中更广泛地使用FLIM以及 用于治疗功能性神经系统疾病的指导干预措施（例如癫痫，神经退行性疾病）。