Fluorescence Lifetime Imaging/Spectroscopy System For Robotic Cancer Surgery Guidance

用于机器人癌症手术指导的荧光寿命成像/光谱系统

• 批准号: 10394396
• 负责人: Andrew Charles Birkeland
• 金额: $ 63.85万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-12 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10394396
• 关键词: Accounting; Address; Adopted; Affect; Age; Area; Biochemical; Biological; Cauterize; Characteristics; Classification; Clinical; Clinical Protocols; Clinical Research; Clinical Trials; Colorectal Cancer; Computer software; Coupled; Data; Data Display; Databases; Decision Making; Devices; Diagnostic; Disease; Documentation; Epithelial; Excision; Feedback; Fluorescence; Funding; Goals; Head and Neck Cancer; Hemostatic function; Histopathology; Human; Image; Image-Guided Surgery; Imaging Device; Imaging Techniques; Imaging technology; In Situ; Intuition; Investigation; Knowledge; Label; Legal patent; Location; Malignant Female Reproductive System Neoplasm; Malignant Neoplasms; Malignant neoplasm of thorax; Medical Records; Metabolic; Methods; Morphologic artifacts; Motion; Noise; Normal tissue morphology; Operative Surgical Procedures; Oral; Oral cavity; Oropharyngeal; Patients; Peer Review; Performance; Positron-Emission Tomography; Predictive Value; Procedures; Property; Prospective Studies; Radiology Specialty; Reporting; Risk Management; Robot; Robotics; Scanning; Signal Transduction; Specimen; Speed; Surface; Surgeon; Surgical Oncology; Surgical margins; System; Testing; Time; Tissues; Urologic Cancer; Validation; Visual; Visualization; base; cancer surgery; cohort; data acquisition; data visualization; deep learning; design; diagnostic value; flexibility; fluorescence lifetime imaging; functional outcomes; head and neck cancer patient; human subject; image reconstruction; image registration; improved; information display; innovation; learning progression; malignant mouth neoplasm; malignant oropharynx neoplasm; neoplastic; novel; optical imaging; pragmatic implementation; preservation; prospective; radiomics; robotic system; sex; side effect; solid state; spectroscopic imaging; surgery outcome; symposium; tumor

PROJECT SUMMARY In this competitive renewal for R01 CA187427, we will continue to advance label-free Fluorescence Lifetime Imaging (FLIm) to enhance the functionality of the widely-used da Vinci Surgical platform with an emphasis on Trans-Oral-Robotic-Surgery (TORS). UC Davis has pioneered the intra-operative use of FLIm and our partner, Intuitive Surgical, is the global leader in robotic-assisted surgery. To date, we have demonstrated a) the synergetic integration of a point-scanning FLIm device with the da Vinci Surgical System (first-of-its-kind); b) the potential of this approach to improve surgical decision-making during TORS without modifying conventional clinical protocols; and c) the utility of FLIM-derived parameters detecting biochemical and metabolic characteristics to distinguish oral and oropharyngeal cancer in real-time from surrounding normal tissue in patients in-situ.. We also developed innovative methods for real-time dynamic augmentation of imaging parameters on the surgical field of view. Capitalizing on the major accomplishments and knowledge gained under the current R01, the overarching objective of this renewal application is to 1) demonstrate FLIm’s diagnostic value in prospective studies by accounting for biological/experimental variables identified as critical under the current R01 and leveraging pre-operative imaging and clinical information and 2) enhance the visualization of FLIm-based classifiers on the surgeon console for real-time intraoperative feedback. To accomplish our overall objective, we propose three specific aims: Aim 1. Expand the FLIm database and develop tissue-type classifiers (retrospective analysis) accounting for biological variables (e.g., patient age/sex, tumor origin/location) and experimental situations (e.g., epithelial surface vs deep margins, tumors of an unknown primary) and the pre- operative imaging (CT, PET) features used in surgical planning. Aim 2. Develop, validate and perform regulatory activities for enhanced FLIm data visualization in support of prospective clinical studies. Aim 3. Validate FLIm as a means of real-time intraoperative TORS guidance in a prospective study analysis. In summary, this study will demonstrate the clinical feasibility and utility of FLIm for intraoperative real-time assessment of oral and oropharyngeal cancer surgical margins. The acquired FLIm parameter database will enable subsequent large clinical trials for automated tissue classification and diagnostic prediction. While the focus of this application is on TORS surgeries, the label-free FLIm-based tissue assessment, characterized by simple, fast and flexible data acquisition and display, can be broadly applied to other procedures as the da Vinci Surgical System is used in a wide range of tumor surgeries including urologic, colorectal, gynecologic, and thoracic cancers.

项目摘要 在R 01 CA 187427的竞争性更新中，我们将继续推进无标记荧光寿命 成像（FLIm），以增强广泛使用的da芬奇Surgical平台的功能，重点是 经口腔机器人手术（TORS）。加州大学戴维斯分校率先在术中使用FLIm和我们的合作伙伴， Intuitive Surgical是机器人辅助手术的全球领导者。到目前为止，我们已经证明了a） 点扫描FLIm装置与da芬奇手术系统的协同集成（首创）; B） 这种方法在TORS期间改善手术决策的潜力， c）FLIM衍生参数检测生物化学和代谢的效用 实时区分口腔和口咽癌与周围正常组织的特征 病人在原位..我们还开发了实时动态增强成像的创新方法 手术视野参数。利用根据《行动纲领》取得的主要成就和知识， 目前的R 01，本次更新申请的首要目标是1）证明FLIm的诊断 在前瞻性研究中的价值，通过考虑根据 当前的R 01，利用术前成像和临床信息，以及2）增强 外科医生控制台上基于FLIM的分类器，用于实时术中反馈。为了实现我们的整体 我们提出了三个具体目标：目标1。扩展FLIm数据库并开发组织类型分类器 （回顾性分析）考虑生物变量（例如，患者年龄/性别、肿瘤起源/位置）和 实验情况（例如，上皮表面与深边缘，原发灶不明的肿瘤）和前 手术计划中使用的手术成像（CT、PET）功能。目标2.制定、验证和执行监管 增强FLIm数据可视化的活动，以支持前瞻性临床研究。目标3. FLIM作为 一项前瞻性研究分析中的实时术中TORS引导方法。 总之，本研究将证明FLIm用于术中实时监测的临床可行性和实用性。 口腔和口咽癌手术切缘的评估。获取的FLIm参数数据库将 使后续的大型临床试验能够进行自动组织分类和诊断预测。而 本申请的重点是TORS手术，即基于FLIm的无标记组织评估，其特征在于 简单、快速、灵活的数据采集和显示，可广泛应用于其他如达芬奇芬奇的程序中 手术系统用于广泛的肿瘤手术，包括泌尿外科、结直肠、妇科和 胸部癌症