Lee Jong Soo, Shuhatovich Olga, Price Roderick, Pikkula Brian, Follen Michele, McKinnon Nick, Macaulay Calum, Knight Bobby, Richards-Kortum Rebecca, Cox Dennis D
Department of Statistics, Rice University, PO Box 1892, Houston, TX 77005, USA.
Gynecol Oncol. 2005 Dec;99(3 Suppl 1):S98-111. doi: 10.1016/j.ygyno.2005.07.052. Epub 2005 Sep 26.
A study was designed to assess variability between different fluorescence spectroscopy devices. Measurements were made with all combinations of three devices, four probes, and three sets of standards trays. Additionally, we made three measurements on the same day over 2 days for the same combination of device, probe, and standards tray to assess reproducibility over a day and across days.
The devices consisted of light sources, fiber-optics, and cameras. We measured thirteen standards and present the data from the frosted cuvette, water, and rhodamine standards. A preliminary analysis was performed with the data that were wavelength calibrated and background subtracted; however, the system has not been corrected for systematic intensity variations caused by the devices. Two analyses were performed on the rhodamine, water, and frosted cuvette standards data. The first one is based on first clustering the measurements and then looking for association between the 5 factors (device, probe, standards tray, day, measurement number) using chi-squared tests on the cross-tabulation of cluster and factor level. This showed that only device and probe were significant. We then did an analysis of variance to assess the percent variance explained by each factor that was significant from the chi-squared analysis.
The data were remarkably similar across the different combinations of factors. The analysis based on the clusters showed that sometimes devices alone, probes alone, but most often combinations of device and probe caused significant differences in measurements. The analysis showed that time of day, location of device, and standards trays do not vary significantly; whereas the devices and probes account for differences in measurement. We expected this type of significance using unprocessed data since the processing corrects for differences in devices. However, this analysis on raw data is useful to explore what combination of device and probe measurements should be targeted for further investigation. This experiment affirms that online quality control is necessary to obtain the best excitation-emission matrices from optical spectroscopy devices.
The fact that the device and probe are the primary sources of variability indicates that proper correction for the transfer function of the individual devices should make the measurements essentially equivalent.
设计了一项研究以评估不同荧光光谱设备之间的变异性。使用三种设备、四种探头和三组标准样品盘的所有组合进行测量。此外,在两天内的同一天,对设备、探头和标准样品盘的相同组合进行了三次测量,以评估一天内和不同天之间的可重复性。
这些设备由光源、光纤和相机组成。我们测量了13种标准品,并展示了来自磨砂比色皿、水和罗丹明标准品的数据。对经过波长校准和背景扣除的数据进行了初步分析;然而,该系统尚未针对设备引起的系统强度变化进行校正。对罗丹明、水和磨砂比色皿标准品的数据进行了两项分析。第一项分析是先对测量值进行聚类,然后使用卡方检验对聚类和因子水平的交叉表来寻找五个因素(设备、探头、标准样品盘、日期、测量次数)之间的关联。结果表明只有设备和探头具有显著性。然后我们进行了方差分析,以评估卡方分析中显著的每个因素所解释的方差百分比。
不同因素组合的数据非常相似。基于聚类的分析表明,有时仅设备、仅探头,但最常见的是设备和探头的组合会导致测量值出现显著差异。分析表明,一天中的时间、设备位置和标准样品盘没有显著变化;而设备和探头导致了测量差异。由于处理过程校正了设备差异,我们使用未处理数据时预期会出现这种显著性。然而,对原始数据的这种分析有助于探索应针对哪些设备和探头测量组合进行进一步研究。该实验证实,在线质量控制对于从光学光谱设备获得最佳激发 - 发射矩阵是必要的。
设备和探头是变异性的主要来源这一事实表明,对各个设备的传递函数进行适当校正应使测量结果基本等效。