Detection of Cancer in Lymph Nodes by Spectral Imaging

通过光谱成像检测淋巴结癌症

• 批准号: 6980561
• 负责人: MAX DIEM
• 金额: $ 10.13万
• 依托单位: HUNTER COLLEGE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-14 至 2005-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6980561
• 关键词: bioimaging /biomedical imaging; biomedical equipment development; breast neoplasms; breast surgery; diagnosis design /evaluation; diagnosis quality /standard; human subject; information systems; infrared spectrometry; lymph nodes; mathematics; metastasis; method development; neoplasm /cancer diagnosis; statistics /biometry; tissue /cell preparation

DESCRIPTION (provided by applicant): This proposal presents data that demonstrate that lymph nodes can be analyzed for the presence of metastatic cancer cells by novel spectroscopic and mathematical methods. These methods use Infrared Spectral Imaging as the primary means for data acquisition, and multivariate statistical algorithms for the analysis of spectral data to produce a diagnosis. Specifically, this proposal will establish the scientific foundation for the detection of breast cancer cells in the axillary lymph nodes, excised during lumpectomies and mastectomies, in order to stage the spread of cancer. The goal of the proposed research is the development of an operating room-based instrument that will produce a diagnosis within 15 minutes after excision of a lymph node. The diagnosis will be presented in the form of a pseudo-color image that highlights the presence of breast cancer cells and/or secondary tumors. Thus, the milestones for this research are a) the development of rapid sample preparation methodology, b) the refinement of the imaging instrumentation, c) the construction of reliable databases and algorithms for the detection of metastatic cancer cells in lymph nodes, and d) the determination of sensitivity and specificity of the optical diagnostic method. The significance of the proposed detection method arises from the fact that many breast cancers are detected only after metastases have occurred. In such cases, the primary tumors have spread into adjacent lymph nodes, which need to be removed to stop the further proliferation of disease. The spread of metastatic cells determines further action, such as chemo- or radiation therapy. Thus, the accuracy and immediate availability of pathological results are of utmost importance. Presently, these results often are not available for hours or even days. The methodology described in this proposal is based on the observation from the PI's and other laboratories that cancerous tissue exhibits subtle infrared spectral differences that permit the distinction of normal and abnormal regions in biopsy tissue. These differences can be amplified by collecting thousands of individual spectra from microscopic regions of the tissue section (spectral imaging), and employing multivariate statistical methods of analysis. In this manner, images are obtained, in the form of pseudo-color maps, in which diseased areas are indicated. The methodology and technology to be developed in this research will readily be transferable to the analysis of lymph nodes affected with cancers other than breast cancer, once databases for other cancers are established. Thus, the proposed research represents a major improvement of present methods via novel optical and algorithmic diagnoses.

描述（由申请人提供）：该提案提供了数据，这些数据表明可以通过新型的光谱和数学方法分析淋巴结的转移性癌细胞。这些方法使用红外光谱成像作为数据获取的主要手段，以及用于分析光谱数据以产生诊断的多元统计算法。 具体而言，该提案将建立科学基础，以检测在乳房切除术和乳腺切除术期间切除的腋窝淋巴结中的乳腺癌细胞，以便进行癌症的扩散。拟议研究的目的是开发手术室仪器，该仪器将在切除淋巴结后15分钟内产生诊断。该诊断将以伪色图像的形式提出，该图像突出显示乳腺癌细胞和/或继发性肿瘤的存在。 因此，这项研究的里程碑是a）a）开发快速样品制备方法，b）成像仪器的改进，c）可靠的数据库和算法的构建，用于检测淋巴结中转移性癌细胞，d）确定光学诊断方法的灵敏度和特异性。 所提出的检测方法的意义来自以下事实：仅在转移发生后才检测到许多乳腺癌。在这种情况下，原发性肿瘤已扩散到相邻的淋巴结中，需要将其去除以阻止疾病的进一步增殖。转移细胞的扩散决定了进一步的作用，例如化学疗法或放射治疗。因此，病理结果的准确性和直接可用性至关重要。目前，这些结果通常在数小时甚至数天都无法使用。 本提案中描述的方法基于PI和其他实验室的观察结果，即癌组织表现出细微的红外光谱差异，允许在活检组织中的正常区域和异常区域区分。这些差异可以通过从组织部分的微观区域（光谱成像）收集数千个单独的光谱，并采用多元分析方法来扩大这些差异。以这种方式，以伪色图的形式获得图像，其中指示患病区域。一旦建立了其他癌症的数据库，本研究中要开发的方法和技术将很容易转移到对受乳腺癌以外的其他癌症影响的淋巴结的分析。因此，拟议的研究代表了通过新型的光学和算法诊断的当前方法的重大改进。