Histology verification demonstrates that biospectroscopy analysis of cervical cytology identifies underlying disease more accurately than conventional screening: removing the confounder of discordance.
Histology verification demonstrates that biospectroscopy analysis of cervical cytology identifies underlying disease more accurately than conventional screening: removing the confounder of discordance.
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DOI：
10.1371/journal.pone.0082416
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Martin FL
中科院分区：
文献类型：
--
作者：
Gajjar K;Ahmadzai AA;Valasoulis G;Trevisan J;Founta C;Nasioutziki M;Loufopoulos A;Kyrgiou M;Stasinou SM;Karakitsos P;Paraskevaidis E;Da Gama-Rose B;Martin-Hirsch PL;Martin FL
宫颈细胞学的主观目视评估是有缺陷的，这可以通过观察者间和观察者内的差异来表现，最终导致筛选与代表性组织学中样本分级分类的不一致程度。生物光谱学方法已被建议作为基于传感器的工具，可以提供客观的评估细胞学。然而，迄今为止的研究显然存在缺陷，即当样本先前使用细胞学筛查进行分类时，相应地缺乏诊断效率。这就提出了一个问题，即基于不完善的常规筛查的宫颈细胞学分类是否会降低生物光谱方法的诊断准确性;后者的方法是否更准确并能诊断潜在疾病？本研究的目的是比较使用传统细胞学与基于组织学分类的宫颈细胞学样本的红外（IR）光谱的客观准确性。在典型的临床环境中，在活检前立即收集了总共n=322份液基细胞学样本。 其中，可以获得n = 154的后续组织学检查结果。 细胞学样本进行分类，根据传统的筛选方法，随后询问采用衰减全反射傅里叶变换红外（ATR-FTIR）光谱。红外光谱进行了预处理和分析，使用线性判别分析。应用邓恩检验来识别光谱的差异。在诊断类别中，组织学使我们能够确定常规筛查与生物光谱学的比较效率，以正确识别真正的乳腺癌或潜在疾病。传统的基于细胞学的筛查导致灵敏度和特异性差。红外光谱来源于宫颈细胞学不出现歧视的诊断方式时，类别是基于传统的筛选。红外光谱的分数图显示不同细胞学类别之间的光谱点有明显的交叉。虽然，在不同类别的光谱带之间的显着差异被注意到，交叉样品点的潜在的不良特异性和阻碍生物光谱学的发展作为一种诊断工具。然而，当使用基于组织学的类别进行分析时，红外光谱的分数图显示出明显更好的分离。组织学证明，液基细胞学的ATR-FTIR光谱鉴定了在常规细胞学筛查中遗漏的潜在的神经病变或疾病的存在。这项研究指出，迫切需要一个未来的生物光谱学研究的类别是基于这样的组织学。它将允许验证这种方法作为筛选工具。
Subjective visual assessment of cervical cytology is flawed, and this can manifest itself by inter- and intra-observer variability resulting ultimately in the degree of discordance in the grading categorisation of samples in screening vs. representative histology. Biospectroscopy methods have been suggested as sensor-based tools that can deliver objective assessments of cytology. However, studies to date have been apparently flawed by a corresponding lack of diagnostic efficiency when samples have previously been classed using cytology screening. This raises the question as to whether categorisation of cervical cytology based on imperfect conventional screening reduces the diagnostic accuracy of biospectroscopy approaches; are these latter methods more accurate and diagnose underlying disease? The purpose of this study was to compare the objective accuracy of infrared (IR) spectroscopy of cervical cytology samples using conventional cytology vs. histology-based categorisation. Within a typical clinical setting, a total of n = 322 liquid-based cytology samples were collected immediately before biopsy. Of these, it was possible to acquire subsequent histology for n = 154. Cytology samples were categorised according to conventional screening methods and subsequently interrogated employing attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy. IR spectra were pre-processed and analysed using linear discriminant analysis. Dunn’s test was applied to identify the differences in spectra. Within the diagnostic categories, histology allowed us to determine the comparative efficiency of conventional screening vs. biospectroscopy to correctly identify either true atypia or underlying disease. Conventional cytology-based screening results in poor sensitivity and specificity. IR spectra derived from cervical cytology do not appear to discriminate in a diagnostic fashion when categories were based on conventional screening. Scores plots of IR spectra exhibit marked crossover of spectral points between different cytological categories. Although, significant differences between spectral bands in different categories are noted, crossover samples point to the potential for poor specificity and hampers the development of biospectroscopy as a diagnostic tool. However, when histology-based categories are used to conduct analyses, the scores plot of IR spectra exhibit markedly better segregation. Histology demonstrates that ATR-FTIR spectroscopy of liquid-based cytology identifies the presence of underlying atypia or disease missed in conventional cytology screening. This study points to an urgent need for a future biospectroscopy study where categories are based on such histology. It will allow for the validation of this approach as a screening tool.
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