WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, UK.
Analyst. 2018 Dec 3;143(24):6121-6134. doi: 10.1039/c8an01384e.
Pre-processing is an essential step in the analysis of spectral data. Mid-IR spectroscopy of biological samples is often subject to instrumental and sample specific variances which may often conceal valuable biological information. Whilst pre-processing can effectively reduce this unwanted variance, the plethora of possible processing steps has resulted in a lack of consensus in the field, often meaning that analysis outputs are not comparable. As pre-processing is specific to the sample under investigation, here we present a systematic approach for defining the optimum pre-processing protocol for biofluid ATR-FTIR spectroscopy. Using a trial-and-error based approach and a clinically relevant dataset describing control and brain cancer patients, the effects of pre-processing permutations on subsequent classification algorithms were observed, by assessing key diagnostic performance parameters, including sensitivity and specificity. It was found that optimum diagnostic performance correlated with the use of minimal binning and baseline correction, with derivative functions improving diagnostic performance most significantly. If smoothing is required, a Sovitzky-Golay approach was the preferred option in this investigation. Heavy binning appeared to reduce classification most significantly, alongside wavelet noise reduction (filter length ≥6), resulting in the lowest diagnostic performances of all pre-processing permutations tested.
预处理是分析光谱数据的一个重要步骤。生物样本的中红外光谱分析常常受到仪器和样本特定差异的影响，而这些差异可能常常掩盖了有价值的生物学信息。虽然预处理可以有效地减少这种不需要的差异，但大量可能的处理步骤导致该领域缺乏共识，通常意味着分析结果不可比。由于预处理是针对所研究的样本特定的，因此我们在这里提出了一种系统的方法来定义用于生物流体衰减全反射傅里叶变换红外光谱分析的最佳预处理方案。通过使用基于尝试和错误的方法和描述对照和脑癌患者的临床相关数据集，观察预处理排列对后续分类算法的影响，通过评估关键诊断性能参数，包括敏感性和特异性。结果发现，最佳诊断性能与最小分箱和平滑处理的使用相关，而导数函数可显著提高诊断性能。如果需要平滑处理，则在本研究中，Sovitzky-Golay 方法是首选。重分箱处理似乎会显著降低分类效果，同时也会降低小波降噪（滤波器长度≥6）的效果，导致所有测试的预处理排列中诊断性能最低。
