Considerations of education in the field of biophotonics in engineering: the experience of the subject Fundamentals of Biophotonics

Education in the field of photonics is usually somehow complex due to the fact that most of the programs include just a few subjects on the field, apart from specific Master programs in Photonics. There are also specific doctorate programs dealing with photonics. Apart from the problems shared with photonics in education in general, biophotonics specifically needs an interdisciplinary approach between biomedical and technical or scientific fields. In this work, we present our education experience in teaching the subject Fundamentals of Biophotonics, intended preferentially to engineering Bachelor and Master degrees students, but also to science and medicine students. First it was necessary to join a teaching group coming from the scientific technical and medical fields, working together in the subject. This task was easier as our research group, the Applied Optical Techniques group, had previous contacts and experience in working with medicine professors and medical doctors at hospitals. The orientation of the subject, intended for both technical and medical students, has to be carefully selected. All this information could be employed by other education institutions willing to implement studies on biomedical optics.This work has been partially supported by the project “New active phases in transition metals and rare earth nano-oxides stabilized at high pressure” (MAT2015-69508-P) of the Spanish Ministry of Economy and Competitiveness, cofunded by FEDER funds, and by the San Cándido Foundation

Light scattering influence in cyanobacteria suspensions inside a photobioreactor

The application of biotechnology is increasing in areas such as agriculture, biochemistry or biomedicine. Growing bacteria or algae could be beneficial for supplying fuel, drugs, food or oxygen, among other products. An adequate knowledge of biological processes is becoming essential to estimate and control products production. Cyanobacteria are particularly appropriate for producing oxygen and biomass, by consuming mainly carbon dioxide and light irradiation. These capacities could be employed to provide human subsistence in adverse environments, as basic breathing and food needs would be satisfied. Cyanobacteria growing is carried out in bioreactors. As light irradiation is quite relevant for their behavior, photobioreactors are needed. Photobioreactors are designed to supply and control the amounts of elements they need, in order to maximize growth. The adequate design of photobioreactors greatly influences production throughput. This design includes, on the optical side, optical illumination and optical measurement of cyanobacteria growth. The influence of optical scattering is fundamental for maximizing cyanobacteria growing, as long as for adequately measure this growth. In this work, optical scattering in cyanobacteria suspensions is analyzed. Optical properties of cyanobacteria and its relationship with concentration is taken into account. Several types of cyanobacteria are considered. The influence of different beam spatial profiles and irradiances is studied by a Monte Carlo approach. The results would allow the consideration of the influence of optical scattering in the detected optical signal employed for growth monitoring, as a function of cyanobacteria type and optical beam parameters.This work has been partially supported by the project “New active phases in transition metals and rare earth nano-oxides stabilized at high pressure” (MAT2015-69508-P) of the Spanish Ministry of Economy and Competitiveness, cofunded by FEDER funds, and by the San Cándido Foundation

Diffuse reflectance spectroscopy biomarkers for biological tissues characterization: application to ex-vivo animal tissues

Biological tissues characterization can be approached by non-ionizing optical techniques, in a non-invasive, non-contact way. Optical diagnostic techniques include Optical Coherence Tomography, spectroscopy or fluorescence, among others. Tissue differentiation is difficult to achieve in general with high specificity and sensibility. Spectroscopy is of great interest for this aim, as it provides intrinsic molecular contrast. The different composition and/or structure of biological tissues influence the spectral response. However, the interpretation of spectra is difficult from the raw data, and further data processing is needed. Diffuse Reflectance Spectroscopy (DRS) is particularly well-suited for biomedical applications, as it can work with bulk tissues in reflection, reinforcing the non-invasive character of the technique. DRS has been employed for malignant tissue detection and also for healthy tissue discrimination. These applications require an adequate definition of potential biomarkers for the classification algorithms. The classification process depends strongly on the amount of collected spectra and tissue and specimen variability. In this work several types of ex-vivo porcine tissues are extracted and measured by DRS. Spectral measurements are made on different specimens, and on different points of each sample. Spectra are normalized and several algorithms for dimension and variability reduction are applied, such as Principal Component Analysis or Savitzky-Golay filtering. From these spectra, several biomarkers are proposed for tissue classification, and different classifiers are applied. The results are compared, and the classification efficiency is quantified. The considered approaches could be of particular interest in image-guided surgery or other types of optical biopsy applications.This work has been partially supported by the project "New active phases in transition metals and rare earth nano-oxides stabilized at high pressure" (MAT2015-69508-P) of the Spanish Ministry of Economy and Competitiveness, cofunded by FEDER funds, an by the San Cándido Foundation

Optical propagation analysis in photobioreactor measurements on cyanobacteria

Biotechnology applications are nowadays increasing in many areas, from agriculture to biochemistry, or even biomedicine. Knowledge on biological processes is becoming essential in order to be able to adequately estimate and control the production of these elements. Cyanobacteria present the capability of producing oxygen and biomass, from CO2 and light irradiation. Therefore, they could be fundamental for human subsistence in adverse environments, as basic needs of breathing and food would be guaranteed. Cyanobacteria cultivation, as other microorganisms, is carried out in photo-bioreactors. The adequate design of photobioreactors greatly influences elements production throughput. This design includes optical illumination and optical measurement of cyanobacteria growth. In this work an analysis of optical measurement of cyanobacteria growth in a photobioreactor is made. As cyanobacteria are inhomogeneous elements, the influence of light scattering is significant. Several types of cyanobacteria are considered, as long as several spatial profiles and irradiances of the incident light. Depending on cyanobacteria optical properties, optical distribution of transmitted light can be estimated. These results allow an appropriate consideration, in the optical design, of the relationship between detected light and cyanobacteria growth. As a consequence, the most adequate conditions of elements production from cyanobacteria could be estimated.This work has been partially supported by the project “New active phases in transition metals and rare earth nano-oxides stabilized at high pressure” (MAT2015-69508-P) of the Spanish Ministry of Economy and Competitiveness, cofunded by FEDER funds, and by the San Cándido Foundation

Analysis of polarimetric parameters in strongly oriented biological tissues

The use of polarimetry as a diagnostic tool for biological tissues could show increased contrast in several pathologies. In this work polarimetric parameters are used to analyze structurally oriented biological tissues.This work has been partially supported by the project "New active phases in transition metals and rare earth nano-oxides stabilized at high pressure" (MAT2015-69508-P) of the Spanish Ministry of Economy and Competitiveness, cofunded by FEDER funds, and by the San Cándido Foundation

Nanoparticle-based photodynamic therapy on non-melanoma skin cancer

There are several advantages of Photodynamic Therapy (PDT) for nonmelanoma skin cancer treatment compared to conventional treatment techniques such as surgery, radiotherapy or chemotherapy. Among these advantages its noninvasive nature, the use of non ionizing radiation and its high selectivity can be mentioned. Despite all these advantages, the therapeutic efficiency of the current clinical protocol is not complete in all the patients and depends on the type of pathology. An adequate dosimetry is needed in order to personalize the protocol. There are strategies that try to overcome the current PDT shortcomings, such as the improvement of the photosensitizer accumulation in the target tissue, optical radiation distribution optimization or photochemical reactions maximization. These strategies can be further complemented by the use of nanostructures with conventional PDT. Customized dosimetry for nanoparticle-based PDT requires models in order to adjust parameters of different nature to get an optimal tumor removal. In this work, a predictive model of nanoparticle-based PDT is proposed and analyzed. Dosimetry in nanoparticle-based PDT is going to be influenced by photosensitizer-nanoparticle distribution in the malignant tissue, its influence in the optical radiation distribution and the subsequent photochemical reactions. Nanoparticles are considered as photosensitizer carriers on several types of non-melanoma skin cancer. Shielding effects are taken into account. The results allow to compare the estimated treatment outcome with and without nanoparticles.This work has been partially supported by the project “New active phases in transition metals and rare earth nano-oxides stabilized at high pressure” (MAT2015-69508-P) of the Spanish Ministry of Economy and Competitiveness, cofunded by FEDER funds, and by the San Cándido Foundation

Photoacoustic Tomography predictive model applied to basocellular carcinoma for several sensor geometries

A predictive model for Photoacoustic Tomography images is presented and applied to basocellular carcinoma. It implements optical propagation by a Monte Carlo approach, initial pressure distribution and image reconstruction by the k-space method

Influence of the human skin tumor type in photodynamic therapy analysed by a predictive model

Photodynamic Therapy (PDT) modeling allows the prediction of the treatment results depending on the lesion properties, the photosensitizer distribution, or the optical source characteristics. We employ a predictive PDT model and apply it to different skin tumors. It takes into account optical radiation distribution, a nonhomogeneous topical photosensitizer spatial temporal distribution, and the time-dependent photochemical interaction. The predicted singlet oxygen molecular concentrations with varying optical irradiance are compared and could be directly related with the necrosis area. The results show a strong dependence on the particular lesion. This suggests the need to design optimal PDT treatment protocols adapted to the specific patient and lesion

Analysis of superficial fluorescence patterns in nonmelanoma skin cancer during photodynamic therapy by a dosimetric tool

In this work the superficial fluorescence patterns in different nonmelanoma skin cancers and their photodynamic treatment response are analysed by a fluorescence based dosimetric model. Results show differences of even more than 50% in the fluorescence patterns as photodynamic therapy progresses depending on the malignant tissue type. They demonstrate the great relevance of the biological media as an additional dosimetric factor and contribute to the development of a future customized therapy with the assistance of dosimetric tools to interpret the fluorescence images obtained during the treatment monitoring and the differential photodiagnosis.This work has been partially supported by the project MAT2012-38664-C02-01 of the Spanish Ministery of Economy and Competitiveness and by San Cándido Foundation

Application of classification algorithms to diuse reflectance spectroscopy measurements for ex vivo characterization of biological tissues

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.This research was funded by the Ministry of Science, Innovation and Universities (Spain), grant number PGC2018-101464-B-I00, by the Ministry of Economy and Competitiveness (Spain), grant number RTC-2015-4285-1, and by San Cándido Foundatio