CAJ | 학술논문

目的探索近红外拉曼光谱技术及化学计量法在口腔鳞状细胞癌诊断中的应用价值.方法收集正常口腔黏膜组织10例、鳞状细胞癌组织20例、白斑30例进行近红外拉曼光谱扫描,分析不同病变类型的特征性光谱,通过化学计量法进行分析建模,并评价其分类诊断效力.结果相对于正常组织,鳞状细胞癌及白斑中DNA、蛋白及脂类合成增强,表现出较明显的增殖活性.在对鳞状细胞癌和正常组织的建模比较中,诊断准确度98.81%;在鳞状细胞癌与白斑建模诊断中,诊断准确度96.30%.结论近红外拉曼光谱检测结合支持向量机分类建模技术,可以检测到口腔正常黏膜、白斑及鳞状细胞癌样本中的生化物质变化,并进行准确分类建模诊断.
목적 탐색근홍외랍만광보기술급화학계량법재구강린상세포암진단중적응용개치.방법 수집정상구강점막조직10례、린상세포암조직20례、백반30례진행근홍외랍만광보소묘,분석불동병변류형적특정성광보,통과화학계량법진행분석건모,병평개기분류진단효력.결과 상대우정상조직,린상세포암급백반중DNA、단백급지류합성증강,표현출교명현적증식활성.재대린상세포암화정상조직적건모비교중,진단준학도98.81%;재린상세포암여백반건모진단중,진단준학도96.30%.결론 근홍외랍만광보검측결합지지향량궤분류건모기술,가이검측도구강정상점막、백반급린상세포암양본중적생화물질변화,병진행준학분류건모진단.
Objective To evaluate the value of the near infrared Raman spectroscope in diagnosing oral squamous cell carcinoma (OSCC). Methods Near infrared Raman spectra of ten normal mucosa, twenty OSCC and thirty oral leukoplakia (OLK) cases were collected in the research. Based on the previous researches, the information of the sub tracted spectra of compared group was gained by the characteristic band in them. A Gaussian radial basis function support vector machine was used to classify spectra and establish the diagnostic models. The efficacy and validity of the algorithm were evaluated. Results By analyzing the subtracted mean spectra, the increasing peak intensity in wavenumber range of 500-2 200 cm~(1) hinted us of the high contents of DNA, protein and lipid in OSCC, which elu cidate the high proliferative activity. The increasing peak intensity in the wavenumber range of 500-2 200 cm~(1) hinted us of the high contents of DNA, protein and lipid in OSCC, which elucidate the high proliferative activity, but the difference between OLK and OSCC was not as much as that between normal and OSCC. The Gaussian radial basis function support vector machine showed powerful ability in grouping and modeling of normal and OSCC, and the specificity, sensitivity and accuracy were 100%, 97.44% and 98.81% correspondingly. The algorithm showed good a bility in grouping and modeling of OLK and OSCC, the specificity, sensitivity and accuracy were 95.00%, 86.36% and 96.30%. Conclusion Combined with support vector machines, near infrared Raman spectroscopy could detect the biochemical variations in oral normal, OLK and OSCC, and establish diagnostic model accurately.