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Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and "digital drying".
Journal of Biophotonics ( IF 2.0 ) Pub Date : 2020-06-23 , DOI: 10.1002/jbio.202000118 Alexandra Sala 1 , Katie E Spalding 1 , Katherine M Ashton 2 , Ruth Board 3 , Holly J Butler 1 , Timothy P Dawson 2 , Dean A Harris 4 , Caryn S Hughes 1 , Cerys A Jenkins 5 , Michael D Jenkinson 6 , David S Palmer 7 , Benjamin R Smith 1, 7 , Catherine A Thornton 8 , Matthew J Baker 1
Journal of Biophotonics ( IF 2.0 ) Pub Date : 2020-06-23 , DOI: 10.1002/jbio.202000118 Alexandra Sala 1 , Katie E Spalding 1 , Katherine M Ashton 2 , Ruth Board 3 , Holly J Butler 1 , Timothy P Dawson 2 , Dean A Harris 4 , Caryn S Hughes 1 , Cerys A Jenkins 5 , Michael D Jenkinson 6 , David S Palmer 7 , Benjamin R Smith 1, 7 , Catherine A Thornton 8 , Matthew J Baker 1
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In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection‐Fourier transform infrared (ATR‐FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR‐FTIR on both liquid and air‐dried samples to investigate “digital drying” as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least‐squares method, have demonstrated a greater random forest (RF) classification performance than the air‐dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.0% and specificity values higher than 83.0%. Moreover, quantum cascade laser infrared (QCL‐IR) based spectroscopic imaging is utilized on liquid samples to assess the implications of a deep‐penetration light source on disease classification. The RF classification of QCL‐IR data has provided sensitivity and specificity amounting to 85.1% and 75.3% respectively.
中文翻译：
结合红外光谱和“数字干燥”技术，快速分析液态人类血清中的疾病状态。
近年来，已对干燥的人血清样品进行衰减全反射傅里叶变换红外光谱（ATR-FTIR）光谱研究，以消除水成分的光谱干扰，从而对脑肿瘤的诊断进行了研究，并取得了可喜的结果。这项研究评估了液体和风干样品上的ATR-FTIR，以研究“数字干燥”作为分析从液体样品中获得的光谱的另一种方法。在区分癌症样品和对照样品时，由水减法和最小二乘法组成的数字干燥方法已证明比风干光谱方法具有更好的随机森林（RF）分类性能，灵敏度值高于93.0％，特异性值更高比83.0％。此外，基于量子级联激光红外（QCL-IR）的光谱成像用于液体样品，以评估深穿透光源对疾病分类的影响。QCL-IR数据的RF分类提供的灵敏度和特异性分别为85.1％和75.3％。
更新日期：2020-06-23
中文翻译：
结合红外光谱和“数字干燥”技术，快速分析液态人类血清中的疾病状态。
近年来，已对干燥的人血清样品进行衰减全反射傅里叶变换红外光谱（ATR-FTIR）光谱研究，以消除水成分的光谱干扰，从而对脑肿瘤的诊断进行了研究，并取得了可喜的结果。这项研究评估了液体和风干样品上的ATR-FTIR，以研究“数字干燥”作为分析从液体样品中获得的光谱的另一种方法。在区分癌症样品和对照样品时，由水减法和最小二乘法组成的数字干燥方法已证明比风干光谱方法具有更好的随机森林（RF）分类性能，灵敏度值高于93.0％，特异性值更高比83.0％。此外，基于量子级联激光红外（QCL-IR）的光谱成像用于液体样品，以评估深穿透光源对疾病分类的影响。QCL-IR数据的RF分类提供的灵敏度和特异性分别为85.1％和75.3％。
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