FLUORESCENCE DETECTION OF PAPILLARY TUMOR AT CYSTOSCOPY

膀胱镜检查中乳头状肿瘤的荧光检测

• 批准号: 6281787
• 负责人: JOSEPH T ARENDT
• 金额: $ 0.76万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-06-01 至 1999-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6281787
• 关键词: bioengineering /biomedical engineering; biomedical resource; human tissue; statistics /biometry; urinary tract

The goal of the cystoscopy study is to use intrinsic fluorescence without dyes (autofluorescence) spectroscopy to diagnose normal mucosa from papillary tumor during cystoscopy. In the past year we are using using new method for data analysis based on principal component analysis (PCA) followed by least-squares regression (LR). For the ten patients taken with 400 nm excitation, a calibration set and a validation set were randomly formed with five patients each. Analysis with PCA and LR gave 100% sensitivity and 100% specificity for the validation set. The univariate analysis for 400 nm excitation data provided sensitivity and specificity of 100% for the validation set. For eleven patients with 370 nm excitation, a calibration set and a validation set were randomly formed with six and five patients respectively. Analysis with PCA and LR gave 90% sensitivity and 93% specificity for the validation set. With univariate anaylsis resulted in 90% sensitivity and 93% spec ificity for the validation. Normalizing to the patients' normal tissue average improved the results for 370 nm excitation but not significantly for 400 nm excitation. Therefore, papillary tumor can be diagnosed from normal mucosa in a randomly divided set. PCA has the advantage of determining mathematically what the important parts of the spectra are while the univariate method used required user intervention and selecting 460 nm, 600, and 680 nm emissions.

膀胱镜检查研究的目标是利用内在荧光 无染料（自发荧光）光谱诊断正常粘膜 膀胱镜检查期间乳头状肿瘤。 在过去的一年里，我们正在使用 采用基于主成分的数据分析新方法 分析（PCA），然后是最小二乘回归（LR）。 对于十个 使用 400 nm 激发、校准装置和 验证集随机组成，每组有 5 名患者。 分析 PCA 和 LR 给出了 100% 的敏感性和 100% 的特异性 验证集。 400 nm 激发数据的单变量分析 为验证集提供了 100% 的敏感性和特异性。 对于 11 名患者，采用 370 nm 激发、校准装置和 验证集由六名和五名患者随机组成 分别。 PCA 和 LR 分析的灵敏度为 90%，灵敏度为 93% 验证集的特异性。 通过单变量分析得出 验证的灵敏度为 90%，特异性为 93%。 标准化患者的正常组织平均值改善了 370 nm 激发的结果，但 400 nm 激发的结果不显着 励磁。 因此，乳头状瘤可以从正常的检查中诊断出来。 粘膜在随机划分的组中。 PCA的优点是 从数学上确定光谱的重要部分是什么 而使用的单变量方法需要用户干预并且 选择 460 nm、600 和 680 nm 发射。