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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Dasari, Ramachandra R. Feld, Michael S. Shafer-peltier, Karen E. Fitzmaurice, Maryann Haka, Abigail S. Crowe, Joseph |
| Description | Author Affiliation: Haka AS ( G. R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.); |
| Abstract | We employ Raman spectroscopy to diagnose benign and malignant lesions in human breast tissue based on chemical composition. In this study, 130 Raman spectra are acquired from ex vivo samples of human breast tissue (normal, fibrocystic change, fibroadenoma, and infiltrating carcinoma) from 58 patients. Data are fit by using a linear combination model in which nine basis spectra represent the morphologic and chemical features of breast tissue. The resulting fit coefficients provide insight into the chemical/morphological makeup of the tissue and are used to develop diagnostic algorithms. The fit coefficients for fat and collagen are the key parameters in the resulting diagnostic algorithm, which classifies samples according to their specific pathological diagnoses, attaining 94% sensitivity and 96% specificity for distinguishing cancerous tissues from normal and benign tissues. The excellent results demonstrate that Raman spectroscopy has the potential to be applied in vivo to accurately classify breast lesions, thereby reducing the number of excisional breast biopsies that are performed. |
| ISSN | 00278424 |
| e-ISSN | 10916490 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Issue Number | 35 |
| Volume Number | 102 |
| Language | English |
| Publisher | National Academy of Sciences |
| Publisher Date | 2005-08-01 |
| Publisher Place | United States |
| Access Restriction | Open |
| Subject Keyword | Breast Neoplasms Diagnosis Spectrum Analysis, Raman Adipose Tissue Chemistry Pathology Adolescent Algorithms Biophysical Phenomena Biophysics Biopsy Breast Neoplasms, Male Collagen Menopause Models, Statistical Sensitivity And Specificity Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S. Multidisciplinary |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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