Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.
Polarized light is commonly used to detect optical anisotropies, such as birefringence, in tissues. This optical anisotropy is often attributed to underlying structural anisotropy in tissue, which may originate from regularly aligned collagen fibers. In these cases, the optical anisotropy, such as birefringence, is interpreted as a relative measure of the structural anisotropy of the collagen fibers. However, the relative amplitude of optical anisotropy depends on factors other than fiber orientation, and few models allow quantitative interpretation of absolute measures of true fiber orientation distribution from the optical signal. Our model uses the Mie solution to scattering of linearly polarized light from infinite cylindrical scatterers. The model is expanded to include populations of scatterers with physiologically relevant size and orientation distributions. We investigated the influences of fiber diameter, orientation distribution, and wavelength on the back-scattering signal with our computational model, and used these results to extract structural information from experimental fiber phantoms and bovine tendon. Our results demonstrated that by fitting our model to the experimental data using limited assumptions, we could extract fiber orientation distributions and diameters that were comparable to those found in scanning electron microscope images of the same fiber sample. We found a higher alignment of fibers in the bovine tendon sample, and the extracted fiber diameter was within the expected physiological range. Our model showed that the amplitude of optical anisotropy can vary widely due to factors other than the orientation distribution of fiber structures, including index of refraction, and therefore should not be taken as a sole indicator of structural anisotropy. This work highlights that the accuracy of model assumptions plays a crucial role in extracting quantitative structural information from optical anisotropy.
Mohs surgery is the current gold standard to treat large, aggressive or high-risk non-melanoma skin cancer (NMSC) cases. While Mohs surgery is an effective treatment, the procedure is time-consuming and expensive for physicians as well as burdensome for patients as they wait for frozen section histology. Our group has recently demonstrated high diagnostic accuracy using a noninvasive “spectral biopsy” (combination of diffuse reflectance (DRS), fluorescence (FS) and Raman spectroscopy (RS)) to classify NMSC vs. normal lesion in a screening setting of intact tissue. Here, we examine the sensitivity of spectral biopsy to pathology in excised Mohs sections. The system is designed with three modalities integrated into one fiber probe, which is utilized to measure DRS, FS, and RS of freshly excised skin from patients with various NMSC pathologies including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), where each measurement location is correlated to histopathology. The spectral biopsy provides complimentary physiological information including the reduced scattering coefficient, hemoglobin content and oxygen saturation from DRS, NADH and collagen contribution from FS and information regarding multiple proteins and lipids from RS. We then apply logistic regression model to the extracted physiological parameters to classify NMSC vs. normal tissue. The results on the excised tissue are generally consistent with in vivo measurements showing decreased scattering within the tumor and reduced fluorescence. Due to the high sensitivity of RS to lipids, subcutaneous fat often dominates the RS signal. This pilot study demonstrates the potential for a spectral biopsy to classify NMSC vs. normal tissue, indicating the opportunity to guide Mohs excisions.
Skin cancer is the most common form of cancer in the United States and is a recognized public health issue. Diagnosis of skin cancer involves biopsy of the suspicious lesion followed by histopathology. Biopsies, which involve excision of the lesion, are invasive, at times unnecessary, and are costly procedures ( $2.8B/year in the US). An unmet critical need exists to develop a non-invasive and inexpensive screening method that can eliminate the need for unnecessary biopsies. To address this need, our group has reported on the continued development of a noninvasive method that utilizes multimodal spectroscopy towards the goal of a “spectral biopsy” of skin. Our approach combines Raman spectroscopy, fluorescence spectroscopy, and diffuse reflectance spectroscopy to collect comprehensive optical property information from suspicious skin lesions. We previously described an updated spectral biopsy system that allows acquisition of all three forms of spectroscopy through a single fiber optic probe and is composed of off-the-shelf OEM components that are smaller, cheaper, and enable a more clinic-friendly system. We present initial patient data acquired with the spectral biopsy system, the first from an extensive clinical study (n = 250) to characterize its performance in identifying skin cancers (basal cell carcinoma, squamous cell carcinoma, and melanoma). We also present our first attempts at analyzing this initial set of clinical data using statistical-based models, and with models currently being developed to extract biophysical information from the collected spectra, all towards the goal of noninvasive skin cancer diagnosis.
Diffuse reflectance spectroscopy offers a noninvasive, fast, and low-cost alternative to visual screening and biopsy for skin cancer diagnosis. We have previously acquired reflectance spectra from 137 lesions in 76 patients and determined the capability of spectral diagnosis using principal component analysis (PCA). However, it is not well elucidated why spectral analysis enables tissue classification. To provide the physiological basis, we used the Monte Carlo look-up table (MCLUT) model to extract physiological parameters from those clinical data. The MCLUT model results in the following physiological parameters: oxygen saturation, hemoglobin concentration, melanin concentration, vessel radius, and scattering parameters. Physiological parameters show that cancerous skin tissue has lower scattering and larger vessel radii, compared to normal tissue. These results demonstrate the potential of diffuse reflectance spectroscopy for detection of early precancerous changes in tissue. In the future, a diagnostic algorithm that combines these physiological parameters could be enable non-invasive diagnosis of skin cancer.
Laser-mediated photothermal ablation of cancer cells aided by photothermal agents is a promising strategy for localized, externally controlled cancer treatment. We report the synthesis, characterization, and in vitro evaluation of conductive polymeric nanoparticles (CPNPs) of poly(diethyl-4,4'-[2,5-bis(2,3-dihydrothieno[3,4-b][1,4]dioxin-5-yl)-1,4-phenyle ne] bis(oxy)dibutanoate) (P1) and poly(3,4-ethylenedioxythiophene) (PEDOT) stabilized with 4-dodecylbenzenesulfonic acid and poly(4-styrenesulfonic acid-co-maleic acid) as photothermal ablation agents. The nanoparticles were prepared by oxidative-emulsion polymerization, yielding stable aqueous suspensions of spherical particles of <100 nm diameter as determined by dynamic light scattering and electron microscopy. Both types of nanoparticles show strong absorption of light in the near infrared region, with absorption peaks at 780 nm for P1 and 750 nm for PEDOT, as well as high photothermal conversion efficiencies ( 50%), that is higher than commercially available gold-based photothermal ablation agents. The nanoparticles show significant photostability as determined by their ability to achieve consistent temperatures and to maintain their morphology upon repeated cycles of laser irradiation. In vitro studies in MDA-MB-231 breast cancer cells demonstrate the cytocompatibility of the CPNPs and their ability to mediate complete cancer cell ablation upon irradiation with an 808-nm laser, thereby establishing the potential of these systems as agents for laser-induced photothermal therapy.
A method for the synthesis of electroactive polymers is demonstrated, starting with the synthesis of extended conjugation monomers using a three-step process that finishes with Negishi coupling. Negishi coupling is a cross-coupling process in which a chemical precursor is first lithiated, followed by transmetallation with ZnCl2. The resultant organozinc compound can be coupled to a dibrominated aromatic precursor to give the conjugated monomer. Polymer films can be prepared via electropolymerization of the monomer and characterized using cyclic voltammetry and ultraviolet-visible-near infrared (UV-Vis-NIR) spectroscopy. Nanoparticles (NPs) are prepared via emulsion polymerization of the monomer using a two-surfactant system to yield an aqueous dispersion of the polymer NPs. The NPs are characterized using dynamic light scattering, electron microscopy, and UV-Vis-NIR-spectroscopy. Cytocompatibility of NPs is investigated using the cell viability assay. Finally, the NP suspensions are irradiated with a NIR laser to determine their effectiveness as potential materials for photothermal therapy (PTT).
Skin cancer is the most common form of cancer in the United States and is a recognized public health issue. Diagnosis of skin cancer involves biopsy of the suspicious lesion followed by histopathology. Biopsies, which involve excision of the lesion, are invasive, at times unnecessary, and are costly procedures ( $2.8B/year in the US). An unmet critical need exists to develop a non-invasive and inexpensive screening method that can eliminate the need for unnecessary biopsies. To address this need, our group has reported on the continued development of a multimodal spectroscopy (MMS) system towards the goal of a spectral biopsy of skin. Our approach combines Raman spectroscopy, fluorescence spectroscopy, and diffuse reflectance spectroscopy to collect comprehensive optical property information from suspicious skin lesions. We describe our present efforts to develop an updated MMS system composed of OEM components that will be smaller, less expensive, and more clinic-friendly than the previous system. Key system design choices include the selection of miniature spectrometers, a fiber-coupled broadband light source, a fiber coupled diode laser, and a revised optical probe. Selection of these components results in a 50% reduction in system footprint, resulting in a more clinic-friendly system. We also present preliminary characterization data from the updated MMS system, showing similar performance with our revised optical probe design. Finally, we present in vivo skin measurements taken with the updated MMS system. Future work includes the initiation of a clinical study (n = 250) of the MMS system to characterize its performance in identifying skin cancers.
Raman spectroscopy (RS) is proving to be a valuable tool for real time noninvasive skin cancer detection via optical fiber probe. However, current methods utilizing RS for skin cancer diagnosis rely on statistically based algorithms to provide tissue classification and do not elucidate the underlying biophysical changes of skin tissue. Therefore, we aim to use RS to explore skin biochemical and structural characteristics and then correlate the Raman spectrum of skin tissue with its disease state. We have built a custom confocal micro-Raman spectrometer system with an 830nm laser light. The high resolution capability of the system allows us to measure spectroscopic features from individual tissue components in situ. Raman images were collected from human skin samples from Mohs surgical biopsy, which were then compared with confocal laser scanning, two-photon fluorescence and hematoxylin and eosin-stained images to develop a linear model of skin tissue Raman spectra. In this model, macroscopic tissue spectra obtained from RS fiber probe were fit into a linear combination of individual basis spectra of primary skin constituents. The fit coefficient of the model explains the biophysical changes spanning a range of normal and various disease states. The model allows for determining parameters similar to that a pathologist is familiar reading and will be a significant guidance in developing RS diagnostic decision schemes.
Our group previously introduced Polarized Spatial Frequency Domain Imaging (PSFDI), a wide-field, reflectance imaging technique which we used to empirically map fiber direction in porcine pulmonary heart valve leaflets (PHVL) without optical clearing or physical sectioning of the sample. Presented is an extended analysis of our PSFDI results using an inverse Mueller matrix model of polarized light scattering that allows additional maps of fiber orientation distribution, along with instrumentation permitting increased imaging speed for dynamic PHVL fiber measurements. We imaged electrospun fiber phantoms with PSFDI, and then compared these measurements to SEM data collected for the same phantoms. PHVL was then imaged and compared to results of the same leaflets optically cleared and imaged with small angle light scattering (SALS). The static PHVL images showed distinct regional variance of fiber orientation distribution, matching our SALS results. We used our improved imaging speed to observe bovine tendon subjected to dynamic loading using a biaxial stretching device. Our dynamic imaging experiment showed trackable changes in the fiber microstructure of biological tissue under loading. Our new PSFDI analysis model and instrumentation allows characterization of fiber structure within heart valve tissues (as validated with SALS measurements), along with imaging of dynamic fiber remodeling. The experimental data will be used as inputs to our constitutive models of PHVL tissue to fully characterize these tissues' elastic behavior, and has immediate application in determining the mechanisms of structural and functional failure in PHVLs used as bio-prosthetic implants.
Abstract. We illustrate wide-field imaging of skin using a structured light (SL) approach that highlights the contrast from superficial tissue scattering. Setting the spatial frequency of the SL in a regime that limits the penetration depth effectively gates the image for photons that originate from the skin surface. Further, rendering the SL images in a color format provides an intuitive format for viewing skin pathologies. We demonstrate this approach in skin pathologies using a custom-built handheld SL imaging system.
The measurement of soft tissue fiber orientation is fundamental to pathophysiology and biomechanical function in a multitude of biomedical applications. However, many existing techniques for quantifying fiber structure rely on transmitted light, limiting general applicability and often requiring tissue processing. Herein, we present a novel wide-field reflectance-based imaging modality, which combines polarized light imaging (PLI) and spatial frequency domain imaging (SFDI) to rapidly quantify preferred fiber orientation on soft collagenous tissues. PLI utilizes the polarization dependent scattering property of fibers to determine preferred fiber orientation; SFDI imaging at high spatial frequency is introduced to reject the highly diffuse photons and to control imaging depth. As a result, photons scattered from the superficial layer of a multi-layered sample are highlighted. Thus, fiber orientation quantification can be achieved for the superficial layer with optical sectioning. We demonstrated on aortic heart valve leaflet that, at spatial frequency of f $=$ 1mm&\#x2212;1, the diffuse background can be effectively rejected and the imaging depth can be limited, thus improving quantification accuracy.
Abstract. Diffuse reflectance spectroscopy (DRS) can be used to noninvasively measure skin properties. To extract skin properties from DRS spectra, you need a model that relates the reflectance to the tissue properties. Most models are based on the assumption that skin is homogenous. In reality, skin is composed of multiple layers, and the homogeneity assumption can lead to errors. In this study, we analyze the errors caused by the homogeneity assumption. This is accomplished by creating realistic skin spectra using a computational model, then extracting properties from those spectra using a one-layer model. The extracted parameters are then compared to the parameters used to create the modeled spectra. We used a wavelength range of 400 to 750 nm and a source detector separation of 250 μm. Our results show that use of a one-layer skin model causes underestimation of hemoglobin concentration [Hb] and melanin concentration [mel]. Additionally, the magnitude of the error is dependent on epidermal thickness. The one-layer assumption also causes [Hb] and [mel] to be correlated. Oxygen saturation is overestimated when it is below 50% and underestimated when it is above 50%. We also found that the vessel radius factor used to account for pigment packaging is correlated with epidermal thickness.
V. P. Pattani, Shah, J., Atalis, A., Sharma, A., and Tunnell, J. W., “
Current cancer therapies can cause significant collateral damage due to a lack of specificity and sensitivity. Therefore, we explored the cell death pathway response to gold nanorod (GNR)-mediated photothermal therapy as a highly specific cancer therapeutic to understand the role of apoptosis and necrosis during intense localized heating. By developing this, we can optimize photothermal therapy to induce a maximum of ‘clean’ cell death pathways, namely apoptosis, thereby reducing external damage. GNRs were targeted to several subcellular localizations within colorectal tumor cells in vitro, and the cell death pathways were quantitatively analyzed after photothermal therapy using flow cytometry. In this study, we found that the cell death response to photothermal therapy was dependent on the GNR localization. Furthermore, we demonstrated that nanorods targeted to the perinuclear region irradiated at 37.5 W/cm2 laser fluence rate led to maximum cell destruction with the ‘cleaner’ method of apoptosis, at similar percentages as other anti-cancer targeted therapies. We believe that this indicates the therapeutic potential for GNR-mediated photothermal therapy to treat cancer effectively without causing damage to surrounding tissue.
The guest editors introduce a Biomedical Optics Express feature issue that includes contributions from participants at the 2013 conference on Advances in Optics for Biotechnology, Medicine and Surgery XIII.
Diffuse reflectance spectroscopy provides a noninvasive means to measure optical and physiological properties of tissues. To expand on these measurements, we have developed a handheld diffuse reflectance spectral imaging (DRSi) system capable of acquiring wide field hyperspectral images of tissue. The image acquisition time was approximately 50 seconds for a 50x50 pixel image. A transport model was used to fit each spectra for reduced scattering coefficient, hemoglobin concentration and melanin concentration resulting in optical property maps. The system was validated across biologically relevant levels of reduced scattering (5.14% error) and absorption (8.34% error) using tissue simulating phantoms. DRSi optical property maps of a pigmented skin lesion were acquired in vivo. These trends in optical properties were consistent with previous observations using point probe devices.
Abstract. The goal of this study was to determine the diagnostic capability of a multimodal spectral diagnosis (SD) for in vivo noninvasive disease diagnosis of melanoma and nonmelanoma skin cancers. We acquired reflectance, fluorescence, and Raman spectra from 137 lesions in 76 patients using custom-built optical fiber-based clinical systems. Biopsies of lesions were classified using standard histopathology as malignant melanoma (MM), nonmelanoma pigmented lesion (PL), basal cell carcinoma (BCC), actinic keratosis (AK), and squamous cell carcinoma (SCC). Spectral data were analyzed using principal component analysis. Using multiple diagnostically relevant principal components, we built leave-one-out logistic regression classifiers. Classification results were compared with histopathology of the lesion. Sensitivity/specificity for classifying MM versus PL (12 versus 17 lesions) was 100%/100%, for SCC and BCC versus AK (57 versus 14 lesions) was 95%/71%, and for AK and SCC and BCC versus normal skin (71 versus 71 lesions) was 90%/85%. The best classification for nonmelanoma skin cancers required multiple modalities; however, the best melanoma classification occurred with Raman spectroscopy alone. The high diagnostic accuracy for classifying both melanoma and nonmelanoma skin cancer lesions demonstrates the potential for SD as a clinical diagnostic device.
Abstract. The sampling depth of light for diffuse reflectance spectroscopy is analyzed both experimentally and computationally. A Monte Carlo (MC) model was used to investigate the effect of optical properties and probe geometry on sampling depth. MC model estimates of sampling depth show an excellent agreement with experimental measurements over a wide range of optical properties and probe geometries. The MC data are used to define a mathematical expression for sampling depth that is expressed in terms of optical properties and probe geometry parameters.