We have developed a new theoretical description of the optical coherence tomography (OCT) technique for imaging in highly scattering tissue. The description is based on the extended Huygens–Fresnel principle, valid in both the single- and multiple-scattering regimes. The so-called shower curtain effect, which manifests itself in a standard OCT system, is an inherent property of the present theory. We demonstrate that the shower curtain effect leads to a strong increase in the heterodyne signal in a standard OCT system. This is in contrast to previous OCT models, where the shower curtain effect was not taken into account. The theoretical analysis is verified by measurements on samples consisting of aqueous suspensions of microspheres. Finally, we discuss the use of our new theoretical model for optimization of the OCT system.

We developed a new algorithm that fits optical coherence tomography (OCT) signals as a function of depth to a general theoretical OCT model which takes into account multiple scattering effects. With use of this algorithm, it was possible to extract both the scattering coefficient and anisotropy factor from a particular region of interest in an OCT image. The extraction algorithm was evaluated against measurements from an integrating sphere on a set of tissue phantoms and yielded valid results. Finally, a preliminary ex vivo OCT investigation on human aortic specimen indicated that the algorithm may contribute importantly to differentiation between normal and atherosclerotic arteries. We conclude that this algorithm may facilitate tissue characterization by OCT.

When modeling light interaction with biological tissue, the first step is typically to calculate the distribution of light within the tissue, given the optical properties for a given illumination. This light distribution is described by the solution to the radiative transfer equation (RTE), which is often solved with Monte Carlo (MC) methods,^1,2 in which the light is simulated as photon packets that are gradually absorbed as they travel through the medium and will randomly undergo scattering at a rate dependent on the local optical properties of the medium.

The current gold standard for clinical diagnosis of melanoma is excisional biopsy and histopathologic analysis. Approximately 15–30 benign lesions are biopsied to diagnose each melanoma. In addition, biopsies are invasive and result in pain, anxiety, scarring, and disfigurement of patients, which can add additional burden to the health care system. Among several imaging techniques developed to enhance melanoma diagnosis, optical coherence tomography (OCT), with its high-resolution and intermediate penetration depth, can potentially provide required diagnostic information noninvasively. Here, we present an image analysis algorithm, “optical properties extraction (OPE),” which improves the specificity and sensitivity of OCT by identifying unique optical radiomic signatures pertinent to melanoma detection. We evaluated the performance of the algorithm using several tissue-mimicking phantoms and then tested the OPE algorithm on 69 human subjects. Our data show that benign nevi and melanoma can be differentiated with 97% sensitivity and 98% specificity. These findings suggest that the adoption of OPE algorithm in the clinic can lead to improvements in melanoma diagnosis and patient experience. Significance: This study describes a noninvasive, safe, simple-to-implement, and accurate method for the detection and differentiation of malignant melanoma versus benign nevi.