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.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 我们在诊断正常的两种类型的良性病变和新鲜切除组织的恶性病变方面表现出了很好的结果。因此，该研究支持将技术转移到临床环境中，以进一步测试其在乳腺癌诊断中的功效。结果，我们进行了临床研究。我们在克利夫兰病理学套件的大学医院收集了数据，通常在切除和整个乳房切除术期间切除后半小时内。这项研究的主要目标是在大型数据集上验证我们的体外诊断算法，该数据集密切模仿体内环境，并阐明新鲜冻干和新鲜乳腺组织的拉曼光谱之间的差异。安排了另一项临床研究。这项研究的主要目的是将我们的诊断算法扩展到包括先前在我们的研究中看不见的病理，例如原位导管癌和微钙化。