Clinical diagnostic devices provide new sources of information that give insight about the state of health which can then be used to manage patient care. These tools can be as simple as an otoscope to better visualize the ear canal or as complex as a wireless capsule endoscope to monitor the gastrointestinal tract. It is with tools such as these that medical practitioners can determine when a patient is healthy and to make an appropriate diagnosis when he/she is not. The goal of diagnostic medicine then is to efficiently determine the presence and cause of disease in order to provide the most appropriate intervention. The earliest form of medical diagnostics relied on the eye – direct visual observation of the interaction of light with the sample. This technique was espoused by Hippocrates in his 5th century BCE work Epidemics, in which the pallor of a patient's skin and the coloring of the bodily fluids could be indicative of health. In the last hundred years, medical diagnosis has moved from relying on visual inspection to relying on numerous technological tools that are based on various types of interaction of the sample with different types of energy – light, ultrasound, radio waves, X-rays etc. Modern advances in science and technology have depended on enhancing technologies for the detection of these interactions for improved visualization of human health. Optical methods have been focused on providing this information in the micron to millimeter scale while ultrasound, X-ray, and radio waves have been key in aiding in the millimeter to centimeter scale. While a few optical technologies have achieved the status of medical instruments, many remain in the research and development phase despite persistent efforts by many researchers in the translation of these methods for clinical care. Of these, Raman spectroscopy has been described as a sensitive method that can provide biochemical information about tissue state while maintaining the capability of delivering this information in real-time, non-invasively, and in an automated manner. This review presents the various instrumentation considerations relevant to the clinical implementation of Raman spectroscopy and reviews a subset of interesting applications that have successfully demonstrated the efficacy of this technique for clinical diagnostics and monitoring in large (n ≥ 50) in vivo human studies.

A major challenge in endocrine surgery is the intraoperative detection of parathyroid glands during both thyroidectomies and parathyroidectomies. Current localization techniques such as ultrasound and sestamibi scan are mostly preoperative and rely on an abnormal parathyroid for its detection. In this paper, we present near-infrared (NIR) autofluorescence as a nonintrusive, real-time, automated in vivo method for the detection of the parathyroid gland. A pilot in vivo study was conducted to assess the ability of NIR fluorescence to identify parathyroid glands during thyroid and parathyroidectomies. Fluorescence measurements at 785 nm excitation were obtained intra-operatively from the different tissues exposed in the neck region in 21 patients undergoing endocrine surgery. The fluorescence intensity of the parathyroid gland was found to be consistently greater than that of the thyroid and all other tissues in the neck of all patients. In particular, parathyroid fluorescence was two to eleven times higher than that of the thyroid tissues with peak fluorescence occurring at 820 to 830 nm. These results indicate that NIR fluorescence has the potential to be an excellent optical tool to locate parathyroid tissue during surgery.

The risk of local recurrence for breast cancers is strongly correlated with the presence of a tumor within 1 to 2 mm of the surgical margin on the excised specimen. Previous experimental and theoretical results suggest that spatially offset Raman spectroscopy (SORS) holds much promise for intraoperative margin analysis. Based on simulation predictions for signal-to-noise ratio differences among varying spatial offsets, a SORS probe with multiple source-detector offsets was designed and tested. It was then employed to acquire spectra from 35 frozen–thawed breast tissue samples in vitro. Spectra from each detector ring were averaged to create a composite spectrum with biochemical information covering the entire range from the tissue surface to ∼2 mm below the surface, and a probabilistic classification scheme was used to classify these composite spectra as “negative” or “positive” margins. This discrimination was performed with 95% sensitivity and 100% specificity, or with 100% positive predictive value and 94% negative predictive value.

Raman spectroscopy (RS) is used to analyze the physiochemical properties of bone because it is non-destructive and requires minimal sample preparation. With over two decades of research involving measurements of mineral-to-matrix ratio, type-B carbonate substitution, crystallinity, and other compositional characteristics of the bone matrix by RS, there are multiple methods to acquire Raman signals from bone, to process those signals, and to determine peak ratios including sub-peak ratios as well as the full-width at half maximum of the most prominent Raman peak, which is nu1 phosphate (ν₁PO₄). Selecting which methods to use is not always clear. Herein, we describe the components of RS instruments and how they influence the quality of Raman spectra acquired from bone because signal-to-noise of the acquisition and the accompanying background fluorescence dictate the pre-processing of the Raman spectra. We also describe common methods and challenges in preparing acquired spectra for the determination of matrix properties of bone. This article also serves to provide guidance for the analysis of bone by RS with examples of how methods for pre-processing the Raman signals and for determining properties of bone composition affect RS sensitivity to potential differences between experimental groups. Attention is also given to deconvolution methods that are used to ascertain sub-peak ratios of the amide I band as a way to assess characteristics of collagen type I. We provide suggestions and recommendations on the application of RS to bone with the goal of improving reproducibility across studies and solidify RS as a valuable technique in the field of bone research.

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.