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Reliable diagnosis of disease using body fluids requires sensitive and accurate detection of disease-specific analytes present in the fluid. In recent years, there has been increasing interest in using surface-enhanced Raman spectroscopy (SERS) for this purpose. The demonstrable signal enhancement and sensitivity of SERS makes it ideally suited for detection of a trace quantity of any analyte. However, lack of reproducibility along with large spatial variability in the measured Raman intensities due to differential (and often random) distribution of surface “hot spots” limits its routine clinical use. We propose here a technique, nanotrap-enhanced Raman spectroscopy (NTERS), for overcoming these long-standing limitations and challenges of SERS. In this technique, hot spots are formed by drying up a microvolume drop of the liquid, containing the mixture of nanoparticles and analytes in the focal volume of the Raman excitation laser, and the Raman signal is detected from these spots containing the analytes localized within the nanoparticle aggregates. The performance of the technique was evaluated in detecting trace quantities of two Raman-active analytes, Rhodamine 6G (R6G) and urea. It was found that R6G and urea could be detected down to a concentration of 50 nM with signal-to-noise ratio (SNR) value of ∼75 and 4 mM with SNR value of ∼500, respectively. A comparison with SERS revealed that NTERS not only had significantly superior (around 2 orders of magnitude) signal enhancement but also had high reproducibility because of its intrinsic ability to form nanoparticle aggregates with high repetitiveness. Another advantage of NTERS is its simplicity and cost effectiveness as it does not require any specialized substrate.

There is a significant current interest in combining multiple modalities in a single optical system for a more complete characterization of tissue for improved diagnosis. We report development of a dual-modal optical system combing the depth-sensitive laser induced fluorescence (LIF) spectroscopy and optical coherence tomography (OCT) for analysis of layered biological tissues. A time-domain, real-time OCT system, assembled in-house, was used as the platform for developing the dual-modal system. It involved appropriate modification of the sample arm of the OCT for making the LIF excitation beam (337 nm) collinear with the OCT illumination beam (1310 nm) and implementation of a confocal fluorescence configuration for rejecting the out-of-focus fluorescence light. The system was first validated using a layered non-biological phantom prepared by placing a thin layer of tissue paper pasted over a green dye card of much larger thickness. A good correlation was observed between the OCT images and the fluorescence signal. The system was also used to record OCT images and fluorescence spectra from a chicken leg tissue covered with a thin layer of epithelial membrane. While OCT images showed the presence of two distinct layers, fluorescence spectra measured from these layers confirmed the biochemical difference between the two. In contrast to the dual-modal LIF-OCT systems reported earlier, the present system can sequentially record fluorescence signal and the OCT image from the same depth of a tissue sample thereby showing its potential for obtaining at once both morphological as well as biochemical information of the tissue layer from that depth.

Optical biopsy has been shown to discriminate between normal and diseased tissue with high sensitivity and specificity. Fiber-optic probe-based spectroscopy systems do not provide the necessary spatial information to guide therapy effectively, ultimately requiring a transition from probe-based spectroscopy to spectral imaging. The effect of such a transition on fluorescence and diffuse reflectance line shape is investigated. Inherent differences in spectral line shape between spectroscopy and imaging are characterized and many of these differences may be attributed to a shift in illumination-collection geometry between the two systems. Sensitivity of the line-shape disparity is characterized with respect to changes in sample absorption and scattering as well as to changes in various parameters of the fiber-optic probe design (e.g., fiber diameter, beam steering). Differences in spectral line shape are described in terms of the relative relationship between the light diffusion within the tissue and the distribution of source-detector separation distances for the probe-based and imaging illumination-collection geometries. Monte Carlo simulation is used to determine fiber configurations that minimize the line-shape disparity between the two systems. In conclusion, we predict that fiber-optic probe designs that mimic a spectral imaging geometry and spectral imaging systems designed to emulate a probe-based geometry will be difficult to implement, pointing toward a posteriori correction for illumination-collection geometry to reconcile imaging and probe-based spectral line shapes or independent evaluation of tissue discrimination accuracy for probe-based and spectral imaging systems.

We report on steady-state measurements on the anisotropy of autofluorescence from malignant and normal breast tissue as a function of tissue thickness. For thin tissue sections the anisotropy from normal tissue was found to be smaller compared with that from malignant tissue. However, the opposite result was obtained for thicker tissues. A phenomenological model was also developed to simulate the dependence of anisotropy on tissue thickness.

Raman spectroscopy has been widely used for cancer diagnosis, but conventional forms provide limited depth information. Spatially offset Raman spectroscopy (SORS) can solve the depth issue, but it has only been used to detect hard tissues such as bone. We explore the feasibility of using SORS to discriminate two layers of soft tissue. Measurements were taken with individual source and detector fibers at a number of spatial offsets from samples consisting of various thicknesses of normal human breast tissues overlying breast tumors. Results show that SORS can detect tumors beneath normal tissue, marking, to the best of our knowledge, the first application of SORS for discriminating two layers of soft tissue.