Development of a Hyper-spectral Spectroscopic Instrument for Non-invasive Diagnos

用于无创诊断的高光谱光谱仪的研制

• 批准号: 8109943
• 负责人: James W Tunnell
• 金额: $ 18.47万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-13 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8109943
• 关键词: Affect; Area; Biochemical; Biological Models; Biopsy; Blood Vessels; Blood Volume; Carcinoma; Carcinoma in Situ; Clinical; Collagen; Dermatologist; Detection; Development; Devices; Diagnosis; Diffuse; Disease; Early identification; Excision; Fiber; Gold; Histology; Histopathology; Image; In Vitro; Light; Location; Malignant Neoplasms; Maps; Measures; Medical; Melanins; Microscopic; Morbidity - disease rate; NADH; Non-Invasive Cancer Detection; Operative Surgical Procedures; Optical Biopsy; Optics; Oxygen; Pathologist; Pathology; Patients; Physiological; Pilot Projects; Process; Property; Sensitivity and Specificity; Skin; Skin Cancer; Spectrum Analysis; Staging; Surface; Surveys; System; Techniques; Technology; Testing; Texas; Tissues; Translating; Universities; Use of New Techniques; austin; base; clinical Diagnosis; design; diagnostic accuracy; instrument; mortality; noninvasive diagnosis; optical fiber; pressure; prototype; public health relevance; sample fixation

DESCRIPTION (provided by applicant): A critical need exists for the non-invasive and early identification of diseases. "Optical biopsy" using spectroscopic instruments offers a means to determine tissue pathology immediately and without the need for surgical biopsy. We propose to develop two spectroscopic systems for noninvasive detection and margin demarcation: 1) a depth sensitive fiber probe (Aim 1) a hyper spectral spectroscopic system (Aim 2). We will develop a depth-sensitive optical fiber probe to measure depth-dependent optical signatures. We will develop a spectroscopic system to translate probe based optical biopsy to a spectral format. These instrument systems can be used in concert to survey wide areas of tissue with the hyper-spectral spectroscopic device and then provide a detailed depth-sensitive analysis with the probe. We will use skin cancer as a model system to test the new spectroscopic instrument. For example, early identification of cancer increases patient survival while non-invasive and rapid identification of cancer will decrease morbidity. Of particular importance is the depth of a malignancy which is often used to stage disease (e.g. carcinoma in situ vs. invasive carcinoma). We will determine the sensitivity and specificity of each device compared to standard histopathology in a clinical pilot study (Aim 3). PUBLIC HEALTH RELEVANCE: There is a critical need for the development of less invasive portable technologies. Over the past decade, optical spectroscopy has been developed to assess tissue pathology and has been shown to provide detailed morphological and biochemical information without tissue removal. This quantitative information can be used to make a final diagnosis (a so called "spectral diagnosis") similar to a pathologist using histology. A spectral diagnosis (SD) is non- invasive, does not require biopsy, fixation, processing or microscopic examination of tissue. The proposed project represents an interdisciplinary effort to develop technologies for the non- invasive detection of skin cancers. Such technologies offer the possibility to reduce morbidity and mortality associated with skin malignancy.

描述(由申请人提供)：迫切需要对疾病进行非侵入性和早期识别。使用光谱仪器的“光学活检”提供了一种立即确定组织病理的方法，而不需要外科活检。我们建议开发两种光谱系统，用于无创检测和边界标定：1)深度敏感光纤探头(AIM 1)，高光谱光谱系统(AIM 2)。我们将开发一种深度敏感的光纤探头来测量随深度变化的光学特征。我们将开发一种光谱系统，将基于探针的光学活检转换为光谱格式。这些仪器系统可以配合使用，通过高光谱光谱设备测量广泛的组织区域，然后使用探头提供详细的深度敏感分析。我们将使用皮肤癌作为模型系统来测试新的光谱仪器。例如，癌症的早期识别可以提高患者的存活率，而非侵入性和快速的癌症识别将降低发病率。特别重要的是恶性肿瘤的深度，这通常用于疾病的分期(例如，原位癌与浸润性癌)。我们将在一项临床先导性研究(目标3)中，与标准组织病理学比较，确定每种设备的敏感性和特异性。 与公共卫生相关：迫切需要开发侵入性更小的便携式技术。在过去的十年里，光学光谱学已被开发用于评估组织病理学，并已被证明在不切除组织的情况下提供详细的形态和生化信息。这种定量信息可以用来做出最终诊断(所谓的“光谱诊断”)，类似于病理学家使用组织学。光谱诊断(SD)是非侵入性的，不需要对组织进行活组织检查、固定、处理或显微镜检查。拟议的项目代表了一项跨学科的努力，以开发皮肤癌的非侵入性检测技术。这些技术提供了降低与皮肤恶性肿瘤相关的发病率和死亡率的可能性。