W. Goth, Sacks, M. S., and Tunnell, J. W., “
Interpreting fiber structure from polarization dependent optical anisotropy,”
Proc. SPIE, vol. 10068. pp. 100680P-100680P-8, 2017.
Publisher's VersionAbstractPolarized 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.
H. T. M. Nguyen, Moy, A. J., Zhang, Y., Feng, X., Reichenberg, J. S., Fox, M., and Tunnell, J. W., “
Tumor margin assessment in Mohs surgery using reflectance, fluorescence and Raman spectroscopy,”
Proc. SPIE, vol. 10054. pp. 1005403-1005403-6, 2017.
Publisher's VersionAbstractMohs 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.
A. J. Moy, Feng, X., Nguyen, H. T. M., Zhang, Y., Sebastian, K. R., Reichenberg, J. S., and Tunnell, J. W., “
Spectral biopsy for skin cancer diagnosis: initial clinical results,”
Proc. SPIE, vol. 10037. pp. 1003704-1003704-6, 2017.
Publisher's VersionAbstractSkin 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.
Y. Zhang, Markey, M. K., and Tunnell, J. W., “
Physiological basis for noninvasive skin cancer diagnosis using diffuse reflectance spectroscopy,”
Proc. SPIE, vol. 10037. pp. 1003707-1003707-8, 2017.
Publisher's VersionAbstractDiffuse 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.