Discrimination of normal, benign, and malignant breast tissues by Raman spectroscopy

化学 阶段(地层学) 乳腺癌 癌症 病理 病态的 核磁共振 医学 内科学 生物 古生物学 物理
作者
M. V. P. Chowdary,K. Kalyan Kumar,Jacob Kurien,Stanley Mathew,C. Murali Krishna
出处
期刊:Biopolymers [Wiley]
卷期号:83 (5): 556-569 被引量:138
标识
DOI:10.1002/bip.20586
摘要

Abstract Breast cancers are the leading cancers among females. Diagnosis by fine needle aspiration cytology (FNAC) is the gold standard. The widely practiced screening method, mammography, suffers from high false positive results and repeated exposure to harmful ionizing radiation. As with all other cancers survival rates are shown to heavily depend on stage of the cancers (Stage 0, 95%; Stage IV, 75%). Hence development of more reliable screening and diagnosis methodology is of considerable interest in breast cancer management. Raman spectra of normal, benign, and malignant breast tissue show significant differences. Spectral differences between normal and diseased breast tissues are more pronounced than between the two pathological conditions, malignant and benign tissues. Based on spectral profiles, the presence of lipids (1078, 1267, 1301, 1440, 1654, 1746 cm −1 ) is indicated in normal tissue and proteins (stronger amide I, red shifted ΔCH 2 , broad and strong amide III, 1002, 1033, 1530, 1556 cm −1 ) are found in benign and malignant tissues. The major differences between benign and malignant tissue spectra are malignant tissues seem to have an excess of lipids (1082, 1301, 1440 cm −1 ) and presence of excess proteins (amide I, amide III, red shifted ΔCH 2 , 1033, 1002 cm −1 ) is indicated in benign spectra. The multivariate statistical tool, principal components analysis (PCA) is employed for developing discrimination methods. A score of factor 1 provided a reasonable classification of all three tissue types. The analysis is further finetuned by employing Mahalanobis distance and spectral residuals as discriminating parameters. This approach is tested both retrospectively and prospectively. The limit test, which provides the most unambiguous discrimination, is also considered and this approach clearly discriminated all three tissue types. These results further support the efficacy of Raman spectroscopic methods in discriminating normal and diseased breast tissues. © 2006 Wiley Periodicals, Inc. Biopolymers 83:556–569, 2006 This article was originally published online as an accepted preprint. The “Published Online” date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com

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