Integration of 5-ALA Fluorescence Lifetime Imaging with Stereotactic Surgical Navigation for Quantitative Real-Time Spatial Localization of Tumor During Neurosurgical Procedures

项目摘要/摘要 最常见的原发脑癌，胶质母细胞瘤(GBM)的最大手术切除已被证明是 在高度病态的疾病中提高总体存活率。然而，边缘残留肿瘤的勾画 使用传统技术进行外科切除可能具有挑战性，因此使用荧光技术。 引导手术(FGS)已成为肿瘤检测的一种辅助工具。目前，只有一名特工，5- 氨基乙酰丙酸(5-ALA)被批准用于术中检测基底膜。5-丙氨酸代谢为 原卟啉IX(PpIX)通过手术的广域荧光成像进行定性检测 显微镜。这种基于强度的检测是非定量的，对背景光敏感，需要 外科医生在黑暗的领域里工作。我们开发了一种基于光纤的脉冲激励时间分辨方法 荧光寿命成像(FLIM)技术在实时定量检测PPIX荧光中的应用 光照条件。我们在这项研究中的目标是将点扫描胶片技术与 现有的由BrainLab生产的术中立体定向神经导航系统用于空间联合注册电影 外科领域的数据，以获得适用的手术指导。我们的目标是开发新的软件和组织 基于原始患者数据的分类器，并在前瞻性临床研究中应用集成技术 以展示手术导航的好处。 实现开发新的集成技术的总体目标，该技术立即适用于 在脑肿瘤切除中的常规应用，我们将致力于以下目标：目标1)开发新的软件，用于 FLIM设备与BrainLab神经导航系统的集成，用于实时获取空间 定位胶片数据，并在导航空间中显示叠加在患者成像上的数据。目标 2)开发基于PpIX荧光寿命阈值的可手术切除肿瘤分类器 通过一项将胶片数据与组织活检相关联的前瞻性研究确定。目标3)验证 基于FLIM的综合导航在识别残留肿瘤组织方面的准确性，以便于更大程度地 前瞻性临床研究中的切除。

PROJECT SUMMARY/ABSTRACT Maximal surgical resection of the most common primary brain cancer, glioblastoma (GBM), has been shown to improve overall survival in a highly morbid disease. However, delineation of residual tumor at the margins of surgical resections can be challenging using conventional techniques, and therefore the use of fluorescence guided surgery (FGS) has emerged as an adjuvant tool for tumor detection. At present, only one agent, 5- aminoleveulinic acid (5-ALA), is approved for detection of GBM during surgery. Metabolism of 5-ALA into protoporphyrin IX (PpIX) is detected qualitatively by wide-field fluorescence imaging through the surgical microscope. This intensity-based detection is non-quantitative and background light-sensitive, requiring the surgeon to work in a dark field. We have developed a fiber-based pulse-excitation time-resolved method for Fluorescence Lifetime Imaging (FLIm) to detect quantitative PpIX fluorescence in real-time under full illumination conditions. Our goal in this study is to integrate the point-scanning FLIm technology with an existing intraoperative stereotactic neuronavigation system produced by BrainLab to spatially co-register FLIm data across the surgical field for applicable surgical guidance. We aim to develop new software and tissue classifiers based on primary patient data, and to apply the integrated technology in a prospective clinical study to demonstrate the benefits for surgical navigation. To achieve the overall goal of developing a new integrated technology which is immediately applicable for routine use in brain tumor resections, we will undertake the following aims: Aim 1) To develop new software for integration of the FLIm device with the BrainLab neuronavigation system for real-time acquisition of spatial positioning of FLIm data and display of the data overlaid on the patient’s imaging in the navigation space. Aim 2) To develop classifiers for surgically resectable tumor based on PpIX fluorescence lifetime thresholds determined through a prospective study correlating FLIm data to tissue biopsies. Aim 3) To validate the accuracy of integrated FLIm-based navigation in identifying residual tumor tissue to facilitate a greater extent of resection in a prospective clinical study.