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

项目总结/摘要 最常见的原发性脑癌胶质母细胞瘤（GBM）的最大手术切除已被证明， 提高高发病率疾病的总生存率。然而，在边缘的残留肿瘤的描绘， 使用常规技术进行手术切除可能具有挑战性，因此使用荧光 引导手术（FGS）已经成为肿瘤检测的辅助工具。目前，只有一个代理商，5- 氨基乙酰丙酸（5-ALA）被批准用于在手术期间检测GBM。5-ALA代谢为 原卟啉IX（PpIX）通过手术显微镜通过宽场荧光成像定性检测。 显微镜这种基于强度的检测是非定量的，并且对背景光敏感，需要 外科医生在黑暗的领域工作。我们开发了一种基于光纤的脉冲激发时间分辨方法， 荧光寿命成像（FLIm），用于在全环境下实时检测定量PpIX荧光 光照条件我们在这项研究中的目标是将点扫描FLIm技术与 BrainLab生产的现有术中立体定向神经导航系统，用于空间配准FLIM 整个手术野的数据，以提供适用的手术指导。我们的目标是开发新的软件和组织 分类器的基础上的主要患者数据，并应用集成技术在前瞻性临床研究 以证明手术导航的益处。 为了实现开发一种新的集成技术的总体目标， 常规使用的脑肿瘤切除术，我们将承担以下目标：目标1）开发新的软件， FLIm设备与BrainLab神经导航系统的集成，用于实时采集空间 定位FLIm数据并显示覆盖在导航空间中患者成像上的数据。目的 2)开发基于PpIX荧光寿命阈值的手术可切除肿瘤分类器 通过将FLIm数据与组织活检相关联的前瞻性研究确定。目的3）验证 基于FLIM的集成导航在识别残留肿瘤组织方面的准确性，以促进更大程度的 在前瞻性临床研究中切除。

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.