EX VIVO CLINICAL RAMAN SPECTROSCOPY OF BREAST CANCER

乳腺癌离体临床拉曼光谱

• 批准号: 8170390
• 负责人: ZOYA VOLYNSKAYA
• 金额: $ 2.85万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8170390
• 关键词: Algorithms; Benign; Breast Microcalcification; Clinical; Clinical Research; Computer Retrieval of Information on Scientific Projects Database; Data; Data Set; Diagnosis; Diagnostic; Environment; Excision; Freezing; Funding; Goals; Grant; Hour; In Vitro; Institution; Lesion; Malignant - descriptor; Mammary Gland Parenchyma; Mastectomy; Noninfiltrating Intraductal Carcinoma; Pathology; Raman Spectrum Analysis; Research; Research Personnel; Resources; Schedule; Source; Techniques; Testing; Tissues; United States National Institutes of Health; University Hospitals; breast cancer diagnosis; in vivo; malignant breast neoplasm

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We have demonstrated excellent results in diagnosing normal, two types of benign lesions and malignant lesions on freshly excised tissue using Raman spectroscopy. The study thus supported moving the technique to a clinical setting for further testing of its efficacy in breast cancer diagnosis. As a result, we pursued clinical study. We collected data in the University Hospitals of Cleveland pathology suite, typically within half an hour of excision during partial and whole mastectomy. The main goals of this study was to validate our in vitro diagnostic algorithm on a large data set which closely mimics an in vivo environment and to elucidate differences between the Raman spectra of fresh-frozen and fresh breast tissues. Another clinical study is scheduled. The main goal of this study is expanding our diagnostic algorithm to include pathologies not seen previously in our studies, such as ductal carcinoma in situ and microcalcifications.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目和 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 对于中心来说，它不一定是研究者的机构。 我们在使用拉曼光谱诊断新鲜切除的组织上的正常、两种良性病变和恶性病变方面取得了优异的结果。因此，该研究支持将该技术应用于临床，以进一步测试其在乳腺癌诊断中的功效。因此，我们进行了临床研究。我们在克利夫兰大学医院病理室收集数据，通常在部分和整个乳房切除术中切除后半小时内收集。这项研究的主要目标是在密切模拟体内环境的大数据集上验证我们的体外诊断算法，并阐明新鲜冷冻和新鲜乳腺组织的拉曼光谱之间的差异。另一项临床研究已安排。这项研究的主要目标是扩展我们的诊断算法，以包括以前在我们的研究中未见过的病理，例如导管原位癌和微钙化。