Diagnosis of Cervical Precancers Using Raman Spectroscopy

项目摘要/摘要 宫颈癌是全世界女性中第二常见的恶性肿瘤。据估计， 2007年，仅在美国就有3670人死于这种疾病，11150例新的侵袭性病例 宫颈癌将被诊断出来。尽管宫颈癌前病变的早期发现在 在过去的50年里，降低了与这种疾病相关的死亡率，侵袭前的发病率 宫颈鳞癌。当宫颈癌被及早发现时，它们是高度可治愈的。现有 筛查和检测技术，如巴氏涂片和阴道镜，有几个缺陷，可以防止 对原本可以控制的疾病的有效管理。一种改进的自动诊断方法 敏感度和特异度，可以允许一个“见和治疗”方案将显著提高 疾病的管理。这一提议试图证明拉曼光谱可以 提供宫颈癌前病变的鉴别诊断，包括高级别和低级别与炎症、鳞状细胞癌 宫颈的化生和正常区域。该提案的主要目标是描述和验证 低级别病变可以与高级别病变以及正常宫颈区分开来，这一点 无论患者的绝经状态如何，都可以进行诊断。这将通过以下方式实现 进行了大规模的临床研究，收集了正常宫颈和疾病宫颈的拉曼光谱， 根据组织学分类将它们分开，并通过多类判别算法对它们进行分类。 此外，随着组织光谱特征的独特模型的发展，我们寻求使用该模型 了解疾病的过程，因为它适用于光学光谱学。最后，系统将更新为 尽可能地紧凑，软件开发要容易(一次点击收集和分类 光谱)用于临床使用。拟议工作的结果将通过以下方式对医疗保健产生重大影响 提供了使用单一检测工具进行全面疾病管理的可能性。这将导致 改善病人护理和成本效益。随着这项技术的成功，拉曼光谱可以 适用于其他器官部位，如前列腺和卵巢以及其他疾病，从而影响更广泛的 医学领域。

Project Summary/Abstract Cervical cancer is the second most common malignancy among women worldwide. It is estimated that in 2007, 3,670 deaths will occur in the United States alone from this disease and 11,150 new cases of invasive cervical cancer will be diagnosed. Although early detection of cervical precancer has played a central role in reducing the mortality associated with this disease over the last 50 years, the incidence of pre-invasive squamous carcinoma of the cervix. When cervical cancers are detected early, they are highly curable. Existing screening and detection techniques, the Pap smear and colposcopy, have several deficiencies that prevent efficient management of an otherwise controllable disease. An automated diagnostic method with improved sensitivity and specificity that could allow for a "See and Treat" protocol would significantly improve the management of the disease. This proposal seeks to prove the hypothesis that Raman spectroscopy, can provide differential diagnosis of cervical precancers, both high and low grade from inflammation, squamous metaplasia and normal areas of the cervix. The main objective of this proposal is to characterize and validate that low grade lesions can be differentiate from high grade lesions as well as the normal cervix and that this diagnosis can be performed regardless of the menopausal status of the patient. This will be accomplished by conducting a large clinical investigation, collecting Raman spectra from both normal and diseases cervix, separating them by histological category and classifying them via a multi-class discrimination algorithm. Additionally, with the development of a unique model for tissue spectral signatures, we seek to use this model to understand the disease process as it applies to optical spectroscopy. Finally, the system will be updated to be as compact as possible and the software developed to be "easy" (one click collection and classification of a spectra) for clinical use. The results of the proposed work will have a significant impact on health care by providing the potential for complete disease management with a single detection tool. This would result in improved patient care and cost-effectiveness. With the success of this technique, Raman spectroscopy can be applied to other organ sites such as the prostate and ovary as well as other diseases thus impacting a broader field in medicine.