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| SIMCA法在中红外癌症检测技术中的应用 | |
| 引用本文： | 李庆波,杨丽敏,凌晓锋,王健生,周孝思,石景森,吴瑾光.SIMCA法在中红外癌症检测技术中的应用[J].光谱学与光谱分析,2004,24(4):414-417. |
| 作者姓名： | 李庆波 杨丽敏 凌晓锋 王健生 周孝思 石景森 吴瑾光 |
| 作者单位： | 1. 北京大学化学与分子工程学院,稀土材料化学及应用国家重点实验室,北京,100871 2. 北京大学第三医院,北京,100083 3. 西安交通大学第一医院肝胆外科研究室,陕西,西安,710061 |
| 基金项目： | 国家重点基础研究发展规划 (G1 9980 61 30 7,2 0 0 2CCA0 1 90 0 )，国家自然科学基金(39730 1 60，50 1 0 30 0 1 ,30 371 60 4 )资助项目 |
| 摘 要： | 人体肿瘤的中红外光谱法早期检测是生物医学领域的前沿课题之一。研究了中红外FTIR光谱技术与化学计量方法 (模式识别技术 )相结合对人体恶性肿瘤进行检测的方法 ,并讨论了如何通过采用光谱预处理方法以及波长范围的选择来提高模式识别技术 (SIMCA法 )分类判别效果。研究了 6 3个胃癌病人的癌变组织和癌旁正常组织光谱 ,选择有代表性的 4 0个样品作为训练集 ,剩余的 2 3个样品作为预测集 ,该方法的准确率为 91%。这一研究结果表明傅里叶变换红外光谱法与化学计量学方法相结合可以对良、恶性组织进行鉴别诊断 ,有希望发展成为一种肿瘤快速诊断的新方法。 |
| 关 键 词： | 模式识别技术 癌症 傅里叶变换红外光谱 化学计量学 |
| 文章编号： | 1000-0593(2004)04-0414-04 |
| 修稿时间： | 2003年9月1日 |
Application of the SIMCA Method to Cancer Diagnosis with Fourier-Transform Infrared Spectroscopy |
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| Qing-bo Li,Li-min Yang,Xiao-feng Ling,Jian-sheng Wang,Xiao-si Zhou,Jing-sen Shi,Jin-guang Wu.Application of the SIMCA Method to Cancer Diagnosis with Fourier-Transform Infrared Spectroscopy[J].Spectroscopy and Spectral Analysis,2004,24(4):414-417. | |
| Authors: | Qing-bo Li Li-min Yang Xiao-feng Ling Jian-sheng Wang Xiao-si Zhou Jing-sen Shi Jin-guang Wu |
| Institution: | The State Key Laboratory of Rare Earth Materials and Applications, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China. |
| Abstract: | Early detection of cancer with mid-IR spectroscopy is a focal topic in the biomedical engineering field. A method was investigated for the detection of malignant tissues with Fourier Transform Infrared spectroscopy (FTIR) and chemometrics method of pattern recognition. Spectral pretreatment and wavelength range selection were studied to improve the classification effect of soft independent modeling of class analogy (SIMCA). To distinguish the malignant tissues from normal ones, sixty-three stomach tissue samples were investigated in this paper. Forty samples were chosen randomly as calibration set and the rest twenty-three samples as predicting set. The correctness of classification was 91%, which was satisfactory. This approach was proved to be a reliable and practicable method for cancer diagnosis. Benign and malignant tissues can be identified by the combination of FTIR spectroscopy and chemometrics, which is able to be developed as a rapid diagnosis method of cancer. |
| Keywords: | SIMCA Cancer FTIR Chemometrics |
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