(PQ7) In Vivo Cellular Optical Imaging of Esophageal Tumors and Microenvironment

(PQ7) 食管肿瘤和微环境的体内细胞光学成像

• 批准号: 9099613
• 负责人: Lev T Perelman
• 金额: $ 53.39万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-16 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9099613
• 关键词: Address; Adopted; Area; Biological; Biometry; Biopsy; Cancer Biology; Cattle; Cells; Clinical; Clinical Data; Clinical Research; Complement; Computer Analysis; Computer software; Connective Tissue; Contrast Media; Detection; Development; Diffuse; Disease Progression; Doctor of Philosophy; Drug Targeting; Dysplasia; Endoscopes; Endoscopy; Epithelial; Esophageal Neoplasms; Esophageal Tissue; Esophagus; FDA approved; Functional Imaging; Gastroenterologist; Gastroenterology; Goals; Heterogeneity; Histopathology; Image; Imaging technology; Institutional Review Boards; Israel; Laboratories; Life; Light; Light-Scattering Spectroscopy; Malignant Neoplasms; Malignant neoplasm of esophagus; Maps; Measurement; Measures; Medical center; Medicine; Microscopy; Monitor; Morphology; Nature; Neoadjuvant Therapy; Nuclear; Operative Surgical Procedures; Optics; Organ; Pathology; Patients; Pharmaceutical Preparations; Principal Investigator; Prior Chemotherapy; Research Personnel; Resected; Resolution; Sampling; Scanning; Site; Spectrum Analysis; Statistical Data Interpretation; Surgical Pathology; Survival Rate; System; Techniques; Technology; Testing; Time; Tissues; absorption; angiogenesis; base; bioimaging; cancer cell; cancer survival; cancer therapy; cell type; chemotherapy; combinatorial; density; experience; high risk; imaging modality; imaging system; improved; in vivo; in vivo imaging; instrumentation; microscopic imaging; multidisciplinary; neoplastic cell; novel; novel diagnostics; oncology; optical imaging; outcome forecast; personalized medicine; photonics; programs; public health relevance; research study; spectrograph; spectroscopic imaging; standard of care; targeted treatment; tissue phantom; treatment response; tumor; tumor microenvironment

 DESCRIPTION (provided by applicant): In this application we propose to develop the in vivo native contrast endoscopic imaging system that can identify cellular composition of the esophageal cancer tumors and their microenvironment in order to determine the optimal course of cancer therapy. Esophageal cancer is one of the deadliest forms of cancers with an overall 14% five-year survival rate. The survival rate among operable cancers is 22%, which increases to 37% with the use of chemotherapy prior to surgery as a neoadjuvant therapy. Currently, there are several FDA-approved chemotherapy drugs, which can be used in various combinations. Each of these drugs targets particular cancer cell types. Because tumors are almost always composed of several cancer cell types, combinatorial therapies are most effective. The only existing way of determining the cell type of the cancer is histopathology, which samples a small proportion of the tumor and, given the large heterogeneity between different tumor areas, is prone to biopsy errors. Additionally, there is no good way of determining the cancer responsiveness to the chemotherapy, which is closely related to the types of cells composing the tumor and the tumor microenvironment. Thus, the largest impediment for determining optimal targeted therapies for esophageal cancer treatment is the absence of the in vivo imaging method that can identify cancer cell types, tumor microenvironment, and are able to closely monitor treatment progress. Due to its ability to sense cellular organization of tumors and identify cell types, while providing gross anatomical imaging, light scattering spectroscopy (LSS) based imaging would be uniquely equipped to address the problem of identifying the cytotypes and cytotype distributions of cancer tumors. We propose to complement LSS information with diffuse reflectance spectroscopy (DRS) information which is sensitive to the microenvironment of the tumor, such as degree of angiogenesis and connective tissue density. Therefore, the purpose of this program is to extend the LSS and DRS technologies and develop native contrast real time dual mode endoscopic spectral imaging system (DMESIS) and test it in clinical experiments in patients with suspected esophageal cancer by comparing to histopathology results from tumor biopsies.

 描述（由申请人提供）：在本申请中，我们提出开发体内天然对比内窥镜成像系统，其可以识别食管癌肿瘤的细胞组成及其微环境，以确定癌症治疗的最佳过程。 食管癌是最致命的癌症之一，总体五年生存率为14%。可手术癌症的存活率为22%，在手术前使用化疗作为新辅助治疗后，存活率增加到37%。目前，有几种FDA批准的化疗药物，可以以各种组合使用。这些药物中的每一种都针对特定的癌细胞类型。由于肿瘤几乎总是由几种癌细胞类型组成，因此组合疗法是最有效的。确定癌症细胞类型的唯一现有方法是组织病理学，其对肿瘤的一小部分进行采样，并且鉴于不同肿瘤区域之间的巨大异质性，易于发生活检错误。此外，还没有很好的方法来确定癌症对化疗的反应性，这与组成肿瘤的细胞类型和肿瘤微环境密切相关。因此，确定食管癌治疗的最佳靶向疗法的最大障碍是缺乏可以识别癌细胞类型、肿瘤微环境并能够密切监测治疗进展的体内成像方法。 由于其能够感测肿瘤的细胞组织并识别细胞类型，同时提供大体解剖成像，基于光散射光谱（LSS）的成像将被独特地装备以解决识别癌症肿瘤的细胞型和细胞型分布的问题。我们建议补充LSS信息与漫反射光谱（DRS）的信息，这是敏感的肿瘤的微环境，如血管生成和结缔组织密度的程度。因此，本项目的目的是扩展LSS和DRS技术，开发天然对比真实的时间双模内窥镜光谱成像系统（DMESIS），并通过与肿瘤活检的组织病理学结果进行比较，在疑似食管癌患者的临床实验中对其进行测试。