Diagnosing breast cancer using Raman spectroscopy: prospective analysis
Abigail S. Haka, Zoya Volynskaya, Joseph A. Gardecki, and Jon Nazemi Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 Robert Shenk and Nancy Wang University Hospitals Case Medical Center and Case Wester...
| Main Authors: | , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Society of Photo-Optical Instrumentation Engineers
2010
|
| Online Access: | http://hdl.handle.net/1721.1/51360 |
| _version_ | 1826200233817669632 |
|---|---|
| author | Haka, Abigail S. Gardecki, Joseph A. Nazemi, Jonathan H. Volynskaya, Zoya I. Shenk, Robert Wang, Nancy Dasari, Ramachandra Rao Fitzmaurice, Maryann Feld, Michael S. |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Haka, Abigail S. Gardecki, Joseph A. Nazemi, Jonathan H. Volynskaya, Zoya I. Shenk, Robert Wang, Nancy Dasari, Ramachandra Rao Fitzmaurice, Maryann Feld, Michael S. |
| author_sort | Haka, Abigail S. |
| collection | MIT |
| description | Abigail S. Haka, Zoya Volynskaya, Joseph A. Gardecki, and Jon Nazemi
Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139
Robert Shenk and Nancy Wang
University Hospitals Case Medical Center and Case Western Reserve, 11100 Euclid Avenue, Cleveland Ohio 44106
Ramachandra R. Dasari
Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139
Maryann Fitzmaurice
University Hospitals Case Medical Center and Case Western Reserve, 11100 Euclid Avenue, Cleveland Ohio 44106
Michael S. Feld
Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139
We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided. |
| first_indexed | 2024-09-23T11:33:39Z |
| format | Article |
| id | mit-1721.1/51360 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:33:39Z |
| publishDate | 2010 |
| publisher | Society of Photo-Optical Instrumentation Engineers |
| record_format | dspace |
| spelling | mit-1721.1/513602022-10-01T04:24:44Z Diagnosing breast cancer using Raman spectroscopy: prospective analysis Haka, Abigail S. Gardecki, Joseph A. Nazemi, Jonathan H. Volynskaya, Zoya I. Shenk, Robert Wang, Nancy Dasari, Ramachandra Rao Fitzmaurice, Maryann Feld, Michael S. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Department of Physics Massachusetts Institute of Technology. Spectroscopy Laboratory Feld, Michael S. Haka, Abigail S. Gardecki, Joseph A. Nazemi, Jonathan H. Volynskaya, Zoya I. Dasari, Ramachandra Rao Feld, Michael S. Abigail S. Haka, Zoya Volynskaya, Joseph A. Gardecki, and Jon Nazemi Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 Robert Shenk and Nancy Wang University Hospitals Case Medical Center and Case Western Reserve, 11100 Euclid Avenue, Cleveland Ohio 44106 Ramachandra R. Dasari Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 Maryann Fitzmaurice University Hospitals Case Medical Center and Case Western Reserve, 11100 Euclid Avenue, Cleveland Ohio 44106 Michael S. Feld Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 We present the first prospective test of Raman spectroscopy in diagnosing normal, benign, and malignant human breast tissues. Prospective testing of spectral diagnostic algorithms allows clinicians to accurately assess the diagnostic information contained in, and any bias of, the spectroscopic measurement. In previous work, we developed an accurate, internally validated algorithm for breast cancer diagnosis based on analysis of Raman spectra acquired from fresh-frozen in vitro tissue samples. We currently evaluate the performance of this algorithm prospectively on a large ex vivo clinical data set that closely mimics the in vivo environment. Spectroscopic data were collected from freshly excised surgical specimens, and 129 tissue sites from 21 patients were examined. Prospective application of the algorithm to the clinical data set resulted in a sensitivity of 83%, a specificity of 93%, a positive predictive value of 36%, and a negative predictive value of 99% for distinguishing cancerous from normal and benign tissues. The performance of the algorithm in different patient populations is discussed. Sources of bias in the in vitro calibration and ex vivo prospective data sets, including disease prevalence and disease spectrum, are examined and analytical methods for comparison provided. Pathology Associates of University Hospitals National Center for Research Resources National Institutes of Health 2010-02-05T13:30:17Z 2010-02-05T13:30:17Z 2009-10 2009-07 Article http://purl.org/eprint/type/JournalArticle 1083-3668 http://hdl.handle.net/1721.1/51360 Haka, Abigail S. et al. “Diagnosing breast cancer using Raman spectroscopy: prospective analysis.” Journal of Biomedical Optics 14.5 (2009): 054023-8. en_US http://dx.doi.org/10.1117/1.3247154 Journal of Biomedical Optics Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Society of Photo-Optical Instrumentation Engineers Michael Feld webpage |
| spellingShingle | Haka, Abigail S. Gardecki, Joseph A. Nazemi, Jonathan H. Volynskaya, Zoya I. Shenk, Robert Wang, Nancy Dasari, Ramachandra Rao Fitzmaurice, Maryann Feld, Michael S. Diagnosing breast cancer using Raman spectroscopy: prospective analysis |
| title | Diagnosing breast cancer using Raman spectroscopy: prospective analysis |
| title_full | Diagnosing breast cancer using Raman spectroscopy: prospective analysis |
| title_fullStr | Diagnosing breast cancer using Raman spectroscopy: prospective analysis |
| title_full_unstemmed | Diagnosing breast cancer using Raman spectroscopy: prospective analysis |
| title_short | Diagnosing breast cancer using Raman spectroscopy: prospective analysis |
| title_sort | diagnosing breast cancer using raman spectroscopy prospective analysis |
| url | http://hdl.handle.net/1721.1/51360 |
| work_keys_str_mv | AT hakaabigails diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT gardeckijosepha diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT nazemijonathanh diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT volynskayazoyai diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT shenkrobert diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT wangnancy diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT dasariramachandrarao diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT fitzmauricemaryann diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis AT feldmichaels diagnosingbreastcancerusingramanspectroscopyprospectiveanalysis |