Characterization of metabolic differences between benign and malignant tumors: high-spectral-resolution diffuse optical spectroscopy

Radiology. 2010 Jan;254(1):277-84. doi: 10.1148/radiol.09082134.


Purpose: To develop a near-infrared spectroscopic method to identify breast cancer biomarkers and to retrospectively determine if benign and malignant breast lesions could be distinguished by using this method.

Materials and methods: The study was HIPAA compliant and was approved by the university institutional review board. Written informed consent was obtained. By using self-referencing differential spectroscopy (SRDS) analysis, the existence of specific spectroscopic signatures of breast lesions on images acquired by using diffuse optical spectroscopy imaging in the wavelength range (650-1000 nm) was established. The SRDS method was tested in 60 subjects (mean age, 38 years; age range, 22-74 years). There were 17 patients with benign breast tumors and 22 patients with malignant breast tumors. There were 21 control subjects.

Results: Discrimination analysis helped separate malignant from benign tumors. A total of 40 lesions (22 malignant and 18 benign) were analyzed. Twenty were true-positive lesions, 17 were true-negative lesions, one was a false-positive lesion, and two were false-negative lesions (sensitivity, 91% [20 of 22]; specificity, 94% [17 of 18]; positive predictive value, 95% [20 of 21]; and negative predictive value, 89% [17 of 19]).

Conclusion: The SRDS method revealed localized tumor biomarkers specific to pathologic state.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Biomarkers, Tumor / metabolism*
  • Breast Neoplasms / metabolism*
  • Breast Neoplasms / pathology
  • Case-Control Studies
  • Discriminant Analysis
  • False Positive Reactions
  • Female
  • Humans
  • Middle Aged
  • Predictive Value of Tests
  • Sensitivity and Specificity
  • Spectroscopy, Near-Infrared / instrumentation*
  • Statistics, Nonparametric


  • Biomarkers, Tumor