Intra-Operative, Label-Free Detection of Brain Cancer Infiltration with Quantitative Optical Imaging

通过定量光学成像在术中、无标记检测脑癌浸润

• 批准号: 9230360
• 负责人: Xingde Li
• 金额: $ 61.63万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9230360
• 关键词: Address; Adjuvant Therapy; Adult; Algorithms; Area; Biomedical Engineering; Blood; Brain; Brain Neoplasms; Cancer Detection; Cancer Model; Cancer Patient; Cell Line; Cervical; Clinical; Clinical Trials; Code; Color; Coupled; Cues; Data; Detection; Diagnostic; Environment; Evaluation; Excision; Frequencies; Future; Geometry; Glioblastoma; Glioma; Goals; Gold; Histologic; Human; Image; Imagery; Imaging technology; Implant; Infiltration; Label; Lead; Location; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of brain; Maps; Medicine; Methods; Microanatomy; Morphologic artifacts; Motion; Motor; Mus; Neoplasm Metastasis; Neurosurgeon; Normal tissue morphology; Operating Rooms; Operative Surgical Procedures; Optical Coherence Tomography; Optics; Oral; Pathologist; Patients; Pilot Projects; Process; Property; Publishing; Quality of life; Radiation; Raman Spectrum Analysis; Recurrence; Research; Resected; Resistance; Resolution; Retrieval; Sensitivity and Specificity; Source; Specificity; Speech; Speed; Sterility; Surgeon; Surgically-Created Resection Cavity; System; Techniques; Technology; Testing; Time; Tissue imaging; Tissues; Translational Research; Ultrasonography; Validation; Visual; Work; base; blood vessel visualization; brain surgery; brain tissue; cancer surgery; cancer type; chemotherapy; cortex mapping; cost; cost effective; experience; functional status; imaging platform; imaging study; imaging system; improved; in vivo; light intensity; malignant mouth neoplasm; minimal risk; mouse model; multidisciplinary; novel; optical imaging; prevent; programs; public health relevance; reduce symptoms; standard of care; survival outcome; symptomatic improvement; tool; translational medicine

 DESCRIPTION (provided by applicant): Glioma is the most common adult primary brain cancer, with inevitable recurrence and finite survival times. Safe maximal resection for glioma patients remains the standard of care based on best evidence medicine (coupled with adjuvant therapies such as radiation and chemotherapy). Multiple studies have shown clear relief of symptoms, improvement of life quality, survival advantage, and delayed recurrence for patients undergoing safe maximal extent of resection (EOR). This is highly beneficial to high-grade glioma (glioblastoma - GBM) patients, and is even more critical for low-grade glioma patients who enjoy years of improved survival. However, it has been extremely challenging to visually distinguish cancer from non-cancer brain tissue intra- operatively even by very experienced surgeons with the best clinically available technologies. On one hand, remaining cancer quickens recurrence, increases resistance to adjuvant therapies, and worsens survival; on the other hand, resection of normal functional brain (e.g. speech and motor areas) can lead to poor functional status and worse survival outcomes. Currently the lack of effective intra-operative guidance technologies prevents neurosurgeons from achieving maximal safe EOR despite of its clear survival advantage. The objective of this proposal is to develop and evaluate the ability of a high-speed, high-resolution, non- invasive and label-free optical coherence tomography (OCT) imaging technology, along with a novel tissue optical property quantification algorithm, to distinguish cancer from non-cancer in real time with high sensitivity/specificity. Our preliminary data (recently published in Science Translational Medicine) suggests exciting potential of OCT for identifying brain cancer vs. non-cancer. To fully investigate the capability and potential of OCT for label-free, quantitative and real-time assessment of brain cancer in an intra-operative setting, we propose the following aims: In Aim 1, we will develop a high- speed OCT imaging platform to identify human brain cancer infiltration with minimized motion and blood artifacts. We will also develop a novel processing algorithm for rapid and robust optical property retrieval from volumetric OCT imaging data, and a method of constructing a color-coded optical property map to provide a direct visual cue for distinguishing cancer versus non-cancer at high resolution. In Aim 2, we will perform the first systematic evaluation of OCT using ex vivo brain tissues from 30 GBM and 30 low-grade brain cancer patients, and a novel in vivo murine brain cancer model (implanted with patient-derived GBM cell lines). Using histopathological analyses as the gold standard, we will establish the first quantitative OCT diagnostic thresholds and determine the OCT sensitivity/specificity in brain cancer identification. In Aim 3, we will address the feasibiliy of brining real-time intra-operative capabilities of OCT into the operating room (OR) by conducting a pilot in vivo OCT imaging study with an additional 30 GBM and 30 low-grade brain cancer patients. This pilot study should pose minimal risk to the patient as the imaging light intensity is low, all imaging data will be collected in a sterile, non-contact manner, and the pilo study will not influence any clinical decisions nor the extent of resection. In summary, our proposed study will be the first to provide quantitative and real-time brain cancer tissue identification using a color-coded optical property map, the first to provide systematic evaluation of the translational OCT technology (involving 120 patients), and the first to provide non-invasive, label-free, non- contact and real-time differentiation of brain cancer versus non-cancer in the OR. These advances will open doors for future large-scale clinical trials to guide brain surgery and increase extent of resection, not only for glioma but also for patients with other types of cancers (such as cancers metastasized to the brain, oral, cervical and GI cancers), thereby improving patient survival.

 描述（由申请人提供）：胶质瘤是最常见的成人原发性脑癌，具有不可避免的复发和有限的生存时间。神经胶质瘤患者的安全最大切除术仍然是基于最佳证据医学的护理标准（加上辅助治疗，如放疗和化疗）。多项研究表明，接受安全最大范围切除术（EOR）的患者症状明显缓解，生活质量改善，生存优势和延迟复发。这对高级别胶质瘤（胶质母细胞瘤- GBM）患者非常有益，并且对于享有多年改善的存活率的低级别胶质瘤患者甚至更关键。然而，即使是具有最佳临床可用技术的非常有经验的外科医生，在术中视觉上区分癌症与非癌症脑组织也是极具挑战性的。一方面，残留的癌症会加速复发，增加对辅助治疗的抵抗力，并降低生存率;另一方面，切除正常功能的大脑（例如语言和运动区域）可能导致功能状态差和生存结局差。目前，缺乏有效的术中引导技术阻止了神经外科医生实现最大安全的EOR，尽管它具有明显的生存优势。本提案的目的是开发和评估高速、高分辨率、无创和无标记光学相干断层扫描（OCT）成像技术的能力，沿着新的组织光学特性量化算法，以高灵敏度/特异性在真实的时间内区分癌症和非癌症。我们的初步数据（最近发表在《科学转化医学》上）表明，OCT在识别脑癌与非癌症方面具有令人兴奋的潜力。为了充分研究OCT在术中环境中用于脑癌的无标记、定量和实时评估的能力和潜力，我们提出了以下目标：在目标1中，我们将开发高速OCT成像平台，以最小化运动和血液伪影来识别人类脑癌浸润。我们还将开发一种新的处理算法，用于快速和鲁棒的光学特性检索， 体积OCT成像数据，以及构建颜色编码的光学特性图以提供用于以高分辨率区分癌症与非癌症的直接视觉提示的方法。在目标2中，我们将使用30例GBM和30例低级别脑癌患者的离体脑组织以及一种新型体内小鼠脑癌模型（植入患者来源的GBM细胞系）进行OCT的首次系统评价。使用组织病理学分析作为金标准，我们将建立第一个定量OCT诊断阈值，并确定OCT在脑癌识别中的灵敏度/特异性。在目标3中，我们将通过对另外30例GBM和30例低级别脑癌患者进行一项试点体内OCT成像研究，探讨将OCT的实时术中功能引入手术室（OR）的可行性。由于成像光强度较低，因此该初步研究对患者的风险应最小，所有成像数据将以无菌、非接触方式收集，并且初步研究不会影响任何临床决策或切除程度。总之，我们提出的研究将是第一个使用颜色编码的光学特性图提供定量和实时脑癌组织识别的研究，第一个提供系统评估的研究。 这是一项平移式OCT技术（涉及120名患者），也是第一项在手术室中提供非侵入性、无标记、非接触和实时区分脑癌与非癌症的技术。这些进展将为未来的大规模临床试验打开大门，以指导脑外科手术并增加切除范围，不仅适用于胶质瘤，还适用于其他类型的癌症患者（如转移到大脑的癌症，口腔癌，宫颈癌和胃肠道癌），从而提高患者的生存率。