Corneal polarimetry measurement has been the object of several papers. The results of techniques like polarization-sensitive optical coherence tomography (PS-OCT), scanning laser polarimetry, or polarization microscopy are contradictory. Some studies propose a biaxial-like birefringence pattern, while others postulate that birefringence grows at corneal periphery. Several theoretical approaches were proposed for the interpretation of these measurements, but they usually lack accuracy and an adequate consideration of the nonnormal incidence on the tissue. We analyze corneal polarization effects measured by PS-OCT. In vivo and in vitro PS-OCT images of the human cornea are acquired. PS-OCT measurements are apparently not in agreement with the biaxial-like birefringence pattern. We present a polarimetric model of the human cornea based on the extended Jones matrix formalism applied to multilayered systems. We also apply the Poincaré equivalence theorem to extract optic axis orientation and birefringence. The results show that for a fibrils orientation pattern composed by alternating circular and radial fibrils, the birefringence is biaxial-like at the corneal center, and there is an almost circularly symmetric high-birefringence area at corneal periphery. The model could be useful for diagnosis of corneal diseases or corneal compensation in retinal polarimetric imaging.

Biological tissue identification in real clinical scenarios is a relevant and unsolved medical problem, particularly in the operating room. Although it could be thought that healthy tissue identification is an immediate task, in practice there are several clinical situations that greatly impede this process. For instance, it could be challenging in open surgery in complex areas, such as the neck, where different structures are quite close together, with bleeding and other artifacts affecting visual inspection. Solving this issue requires, on one hand, a high contrast noninvasive technique and, on the other hand, powerful classification algorithms. Regarding the technique, optical diffuse reflectance spectroscopy has demonstrated such capabilities in the discrimination of tumoral and healthy biological tissues. The complex signals obtained, in the form of spectra, need to be adequately computed in order to extract relevant information for discrimination. As usual, accurate discrimination relies on massive measurements, some of which serve as training sets for the classification algorithms. In this work, diffuse reflectance spectroscopy is proposed, implemented, and tested as a potential technique for healthy tissue discrimination. A specific setup is built and spectral measurements on several ex vivo porcine tissues are obtained. The massive data obtained are then analyzed for classification purposes. First of all, considerations about normalization, detrending and noise are taken into account. Dimensionality reduction and tendencies extraction are also considered. Featured spectral characteristics, principal component or linear discrimination analysis are applied, as long as classification approaches based on k-nearest neighbors (k-NN), quadratic discrimination analysis (QDA) or Naïve Bayes (NB). Relevant parameters about classification accuracy are obtained and compared, including ANOVA tests. The results show promising values of specificity and sensitivity of the technique for some classification algorithms, even over 95%, which could be relevant for clinical applications in the operating room.

Photodynamic therapy (PDT) dosimetric tools are crucial for treatment planning and noninvasive monitoring by means of fluorescence. Present approaches consider usually a 1D problem, a simple photochemical process, or a spatially homogeneous photosensitizer. In this work, a radially resolved superficial photosensitizer fluorescence and 3D photochemical time-dependent PDT model are presented. The model provides a time-dependent estimation of tissue fluorescence and the photosensitizer and singlet oxygen 3D concentrations. The model is applied to a basal cell carcinoma treated by Metvix topical photosensitizer protocol. The analysis shows the potentiality in treatment planning and monitoring. The fluorescence results are in agreement with previous measurements.

We present a novel depolarization metric for Mueller matrices based on the differential Mueller formalism. The proposed metric relies on the statistical interpretation of the differential Mueller matrix. We show that the differential depolarization index successfully quantifies depolarization even when applied to specific types of Mueller matrices for which some widely used depolarization metrics yield erroneous results. Moreover, the fact that the presented metric is directly linked to the variances and covariances of the elementary anisotropic properties of the sample makes it a valuable tool to quantify depolarization on a physically meaningful basis.