IN VIVO CLINICAL RAMAN SPECTROSCOPY OF BREAST CANCER

乳腺癌体内临床拉曼光谱

• 批准号: 8170392
• 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/8170392
• 关键词: Algorithms; Clinic; Clinical; Clinical Research; Computer Retrieval of Information on Scientific Projects Database; Data; Foundations; Freezing; Funding; Goals; Grant; Institution; Investigation; Mastectomy; Operative Surgical Procedures; Patients; Raman Spectrum Analysis; Research; Research Personnel; Resources; Source; Techniques; Tissues; United States National Institutes of Health; breast cancer diagnosis; breast lesion; in vivo; malignant breast neoplasm; time use

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. Previous results from fresh-frozen tissue has demonstrated that Raman spectroscopy accurately classifies breast lesions and supports moving this technique to a clinical setting for further investigation of its efficacy in breast cancer diagnosis. As a result, we pursued clinical study. We collected Raman spectroscopic data in the operative room of the Cleveland Clinic Foundation from 9 patients undergoing partial mastectomy and mastectomy surgery. The main goal of this study is to detect status of margins in real-time using previously developed and prospectively validated chemico-morphological algorithm.

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表示。列出的机构是 对于中心，这不一定是调查员的机构。 新鲜液体组织的先前结果表明，拉曼光谱法准确地对乳房病变进行了分类，并支持将该技术转移到临床环境中，以进一步研究其在乳腺癌诊断中的功效。结果，我们进行了临床研究。我们在克利夫兰诊所基金会的手术室收集了拉曼光谱数据，从9例接受部分乳房切除术和乳房切除术手术的患者。这项研究的主要目的是使用先前开发和前瞻性验证的化学体型算法实时检测边缘的状态。