FLUORESCENCE DETECTION OF PAPILLARY TUMOR AT CYSTOSCOPY

膀胱镜检查研究的目标是使用本征荧光 无染料(自体荧光)光谱诊断正常粘膜 在膀胱镜检查中发现乳头状肿瘤。在过去的一年里，我们正在使用 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)。十个人的 患者接受400 nm激发，校准装置和 验证集随机组成，每组5名患者。分析 与主成分分析和似然比相比，敏感性和特异性分别为100%和100% 验证集。400 nm激发数据的单变量分析 为验证集提供了100%的灵敏度和特异度。 对于11名370 nm激发的患者，一套校准装置和一种 验证集由6名和5名患者随机组成 分别进行了分析。主成分分析和LR分析的敏感度分别为90%和93% 验证集的专用性。通过单因素分析得出 验证灵敏度为90%，特异度为93%。 归一化到患者正常组织的平均值改善了 对370 nm激发的结果不显著，但对400 nm的结果不显著 激动人心。因此，乳头状瘤可以从正常诊断出来。 随机分成一组。主成分分析的优势在于 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和 选择460 nm、600 nm和680 nm发射。

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.