Prediction of malignant transformation in oral epithelial dysplasia using infrared absorbance spectra.
Prediction of malignant transformation in oral epithelial dysplasia using infrared absorbance spectra.
复制标题
DOI：
10.1371/journal.pone.0266043
复制
发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
Risk JM
中科院分区：
文献类型：
--
作者：
Ellis BG;Whitley CA;Triantafyllou A;Gunning PJ;Smith CI;Barrett SD;Gardner P;Shaw RJ;Weightman P;Risk JM
口腔上皮发育不良（OED）是一种组织病理学定义的、潜在的口腔癌前病变。转化为原发性癌的比率相对较低（2年内为12%），基于组织病理学分级的预测不可靠，导致治疗过度和治疗不足。替代方法包括红外（IR）光谱学，它能够在包括口腔癌在内的许多癌症中对癌变和非癌变组织进行分类。本研究的目的是探索FTIR（傅里叶变换红外）显微镜和机器学习作为预测OED恶性转化的手段的能力。对17例高风险OED病变患者纵向采集的OED活检样本进行监督、回顾性分析：随访时间超过3年，10例病变转化，7例未转化。FTIR光谱收集自常规的、未染色的组织病理学切片和用于预测恶性转化的机器学习，与OED分类无关。PCA-LDA（主成分分析后线性判别分析）证明，FTIR数据可以预测这17个病变的后续转化状态，灵敏度为79±5%，特异性为76±5%。六个关键波数被确定为这种分类中最重要的。虽然这项初步研究使用了一个小的队列，但严格的纳入标准和基于已知结果的分类，而不是基于OED的分级，使该研究成为口腔癌FTIR领域的一项新研究，并支持该技术在OED监测中的临床潜力。
Oral epithelial dysplasia (OED) is a histopathologically-defined, potentially premalignant condition of the oral cavity. The rate of transformation to frank carcinoma is relatively low (12% within 2 years) and prediction based on histopathological grade is unreliable, leading to both over- and under-treatment. Alternative approaches include infrared (IR) spectroscopy, which is able to classify cancerous and non-cancerous tissue in a number of cancers, including oral. The aim of this study was to explore the capability of FTIR (Fourier-transform IR) microscopy and machine learning as a means of predicting malignant transformation of OED. Supervised, retrospective analysis of longitudinally-collected OED biopsy samples from 17 patients with high risk OED lesions: 10 lesions transformed and 7 did not over a follow-up period of more than 3 years. FTIR spectra were collected from routine, unstained histopathological sections and machine learning used to predict malignant transformation, irrespective of OED classification. PCA-LDA (principal component analysis followed by linear discriminant analysis) provided evidence that the subsequent transforming status of these 17 lesions could be predicted from FTIR data with a sensitivity of 79 ± 5% and a specificity of 76 ± 5%. Six key wavenumbers were identified as most important in this classification. Although this pilot study used a small cohort, the strict inclusion criteria and classification based on known outcome, rather than OED grade, make this a novel study in the field of FTIR in oral cancer and support the clinical potential of this technology in the surveillance of OED.
登录
查看更多内容
影响因子：
6.6
作者：
Donadini, Alessandra;Maffei, Massimo;Giaretti, Walter
通讯作者：
Giaretti, Walter
影响因子：
18.6
作者：
Johnson, Newell W.;Jayasekara, Prasanna;Amarasinghe, A. A. Hemantha K.
通讯作者：
Amarasinghe, A. A. Hemantha K.
影响因子：
2.1
作者：
Mueller, Susan
通讯作者：
Mueller, Susan
DOI：
10.1002/hed.21131
发表时间：
2009-12-01
影响因子：
2.9
作者：
Mehanna, Hisham M.;Rattay, Tim;McConkey, Christopher C.
通讯作者：
McConkey, Christopher C.
影响因子：
4.3
作者：
Banerjee, Satarupa;Pal, Mousumi;Chatterjee, Jyotirmoy
通讯作者：
Chatterjee, Jyotirmoy