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

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.

Intrinsic near-infrared spectroscopic markers of breast tumors.

We have discovered quantitative optical biomarkers unique to cancer by developing a double-differential spectroscopic analysis method for near-infrared (NIR, 650-1000 nm) spectra acquired non-invasively from breast tumors. These biomarkers are characterized by specific NIR absorption bands. The double-differential method removes patient specific variations in molecular composition which are not related to cancer, and reveals these specific cancer biomarkers. Based on the spectral regions of absorption, we identify these biomarkers with lipids that are present in tumors either in different abundance than in the normal breast or new lipid components that are generated by tumor metabolism. Furthermore, the O-H overtone regions (980-1000 nm) show distinct variations in the tumor as compared to the normal breast. To quantify spectral variation in the absorption bands, we constructed the Specific Tumor Component (STC) index. In a pilot study of 12 cancer patients we found 100% sensitivity and 100% specificity for lesion identification. The STC index, combined with other previously described tissue optical indices, further improves the diagnostic power of NIR for breast cancer detection.

Intrinsic tumor biomarkers revealed by novel double-differential spectroscopic analysis of near-infrared spectra.

We develop a double-differential spectroscopic analysis method for broadband near-infrared (NIR, 650 to 1000 nm) absorption spectra. Application of this method to spectra of tumor-containing breast tissue reveals specific cancer biomarkers. In this method, patient-specific variations in molecular composition are removed by using the normal tissue as an internal control. The effects of concentration differences of the four major tissue absorbers (oxyhemoglobin, deoxyhemoglobin, water, and bulk lipid) between the tumor and normal tissue are accounted for to reveal small spectral components unique to cancer. From a pilot study of 15 cancer patients, we find these spectral components to be characterized by specific NIR absorption bands. Based on the spectral regions of absorption at about 760, 930, and 980 nm, we identify these biomarkers with changes in state or addition of lipid and/or water. To quantify spectral variation in the absorption bands, we construct the specific tumor component (STC) index. The STC index identifies regions of the breast with tumors.

Spectrally resolved neurophotonics: a case report of hemodynamics and vascular components in the mammalian brain.

We developed a spectral technique that is independent of the light transport modality (diffusive or nondiffusive) to separate optical changes in scattering and absorption in the cat's brain due to the hemodynamic signal following visual stimulation. We observe changes in oxyhemoglobin and deoxyhemoglobin concentration signals during visual stimulation reminiscent of the functional magnetic resonance imaging (fMRI) blood oxygenation level dependence (BOLD) effect. Repeated measurements at different locations show that the observed changes are local rather than global. We also determine that there is an apparent large decrease in the water concentration and scattering coefficient during stimulation. We model the apparent change in water concentration on the separation of the optical signal from two tissue compartments. One opaque compartment is featureless (black), due to relatively large blood vessels. The other compartment is the rest of the tissue. When blood flow increases due to stimulation, the opaque compartment increases in volume, resulting in an overall decrease of tissue transmission. This increase in baseline absorption changes the apparent relative proportion of all tissue components. However, due to physiological effects, the deoxyhemoglobin is exchanged with oxyhemoglobin resulting in an overall increase in the oxyhemoglobin signal, which is the only component that shows an apparent increase during stimulation.