Research Papers

Diagnosing breast cancer using Raman spectroscopy: prospective analysis

[+] Author Affiliations
Abigail S. Haka, Zoya Volynskaya, Joseph A. Gardecki, Jon Nazemi

Massachusetts Institute of Technology, George R. Harrison Spectroscopy Laboratory, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139

Robert Shenk, 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

J. Biomed. Opt. 14(5), 054023 (October 14, 2009). doi:10.1117/1.3247154
History: Received April 15, 2009; Revised July 02, 2009; Accepted August 05, 2009; Published October 14, 2009
Text Size: A A A

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.

Figures in this Article
© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

Abigail S. Haka ; Zoya Volynskaya ; Joseph A. Gardecki ; Jon Nazemi ; Robert Shenk, et al.
"Diagnosing breast cancer using Raman spectroscopy: prospective analysis", J. Biomed. Opt. 14(5), 054023 (October 14, 2009). ; http://dx.doi.org/10.1117/1.3247154


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.