Clinical Translation of Stimulated Raman Histology

分子分类已经改变了脑肿瘤的诊断和治疗， 靶向治疗的途径。然而，分子分类对于脑肿瘤患者的临床影响 由于周转时间长（数天-数周）以及复杂的基础设施和工作流程， 获取临床标本的遗传和表观遗传数据。 快速（<2分钟）分子诊断筛查系统将重新定义手术和非手术 弥漫性神经胶质瘤的治疗。快速术中分子分类将确定患者， 将受益最大的根治性切除那些与化疗和/或放射敏感的肿瘤，其中更多的 最好的方法是保守手术，更多地依靠辅助治疗。立即 分子分类也将促进靶向治疗的使用，并改变临床治疗的方式。 神经胶质瘤领域的试验设计为能够快速识别潜在的研究对象， 活检期间或活检后不久的分子标准。 通过我们与Invenio Imaging Inc.的学术-工业合作伙伴关系，我们开发，实施和 通过无标记受激拉曼验证了用于快速形态学诊断的精确床边系统 组织学（SRH）成像与基于人工智能的算法配对（Hollon等人，Nature Medicine 2020年）。在这里，我们打算利用和增强我们独特的基于人工智能的术中诊断平台， 预测在活检后几分钟内定义弥漫性胶质瘤的分子改变， 手术室，而不需要病理实验室或专门的分析设施。 这一建议有望产生一个自主的诊断工作流程，为人类脑肿瘤分子 诊断这里提出的工作代表了一个平台方法的发展，通过该平台方法， 通过SRH和人工智能解锁诊断，从而为 人类癌症的分子诊断。

Molecular classification has transformed the diagnosis and treatment of brain tumors and created promising avenues for targeted therapies. However, the clinical impact of molecular classification for brain tumor patients has been blunted by long turnaround times (days-weeks), as well as the complex infrastructure and workflow required to access genetic and epigenetic data from clinical specimens. A system for rapid (<2 minute) molecular diagnostic screening would redefine the surgical and non-surgical treatment of diffuse gliomas. Rapid intraoperative molecular classification would identify the patients who would benefit most from radical resection from those with chemo- and/or radio-sensitive tumors where a more conservative surgical approach, relying more heavily on adjuvant treatment, might be best. Immediate molecular classification would also facilitate the use of targeted therapeutics and transform the way clinical trials in the glioma field are designed by enabling rapid identification of potential study subjects based on molecular criteria during or shortly after biopsy. Through our academic-industrial partnership with Invenio Imaging Inc, we developed, implemented and validated an accurate bedside system for rapid morphologic diagnosis through label-free stimulated Raman histologic (SRH) imaging paired with an artificial intelligence-based algorithm (Hollon et al. Nature Medicine 2020). Here, we intend to leverage and enhance our unique AI-based platform for intraoperative diagnosis to predict the molecular alterations that define diffuse gliomas within minutes of biopsy in the operating room without the need for a pathology lab or specialized analytic facility. This proposal is expected to yield an autonomous diagnostic workflow for human brain tumor molecular diagnostics. The work proposed here represents the development of a platform approach by which molecular diagnosis is unlocked through SRH and artificial intelligence, thus creating a new standard of accessibility for molecular diagnosis in human cancer.