Revision total hip arthroplasty suffers from low visibility with intra-body navigation hinging primarily on auditory and tactile cues. Consequently, the risk of surgical injury increases. One proposition to increase surgical precision is integrating an algorithm which classifies encountered tissues based on their reflectance spectra into the surgical tools. Previous works have developed machine learning applications for the automatic, binary, classification of tissue based on diffuse reflectance spectroscopy (DRS) signals and exploratory investigations have successfully integrated DRS probes into surgical devices including surgical drills. However, one problem with these studies is a lack of transparency in the algorithms, which is important to increase practitioners’ trust and prevent bias. This study developed four machine learning algorithms which simultaneously classified broadband DRS signals (355 – 1850 nm) of six ovine tissue classes. The algorithms were Linear Discriminant Analysis (LDA), Random Forrest, Convolutional Neural Network (CNN), and a Transformer model. Class-wise wavelength importance was visualized using model-based methods to understand classification mechanisms and increase model-explainability. It is concluded that CNNs hold the potential for successful initial device design and medical integration.
Raman spectroscopy, a non-invasive analytical method, offers insights into molecular structures and interactions in various liquid and solid samples with applications ranging from material science, and chemical analysis to medical diagnostics. Preprocessing of Raman spectra is vital to remove interferences like background signals and calibration errors, ensuring precise data extraction. Artificial intelligence, particularly machine learning (ML), aids in extracting valuable information from complex datasets. However, effective data preprocessing proves to be crucial as it can influence model robustness. This study addresses the integration of preprocessing and ML algorithms, often treated as distinct identities despite their intrinsic interconnection, in Raman spectra of blood samples from patients suffering from ovarian cancer. Optimal preprocessing configuration may not always be evident due to the complexity of spectral data. There are numerous options available for background corrections, normalization, outlier removal, noise filtering, and dimension reduction algorithms for Raman spectra. Moreover, hyperparameter tuning is required to detect the best choices for the preprocessing steps. In this work, we present a pipeline to co-optimize preprocessing techniques and ML classification methods to promote objective selection and minimize processing time. In our approach, preprocessing methods are not chosen arbitrarily but rather systematically evaluated to enhance the robustness of the models. These criteria focus on ensuring that the model performs well not only on the training data but also on unseen data, thus reducing the risk of overfitting and improving the generalization capability of the model. This systematic approach would reduce the time for new studies by detecting the most suitable preprocessing steps and hyperparameters needed and building a robust model for the task.
In this work, we aim to develop a virtual platform to compare the performance of the different manifestations of photon Time of Flight Spectroscopy namely Direct, Indirect and Interferometric photon Time of Flight Spectroscopy (pToFS). Extending the comparison over a range of scenarios, defined by a matrix of optical properties (dubbed here as Virtual Tissue), allows for the definition of different use cases for each of these techniques. The effect of parameters like temporal drift, exposure time and background noise will also be studied.
SignificanceWavelength selection from a large diffuse reflectance spectroscopy (DRS) dataset enables removal of spectral multicollinearity and thus leads to improved understanding of the feature domain. Feature selection (FS) frameworks are essential to discover the optimal wavelengths for tissue differentiation in DRS-based measurements, which can facilitate the development of compact multispectral optical systems with suitable illumination wavelengths for clinical translation.AimThe aim was to develop an FS methodology to determine wavelengths with optimal discriminative power for orthopedic applications, while providing the frameworks for adaptation to other clinical scenarios.ApproachAn ensemble framework for FS was developed, validated, and compared with frameworks incorporating conventional algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), and backward interval partial least squares (biPLS).ResultsVia the one-versus-rest binary classification approach, a feature subset of 10 wavelengths was selected from each framework yielding comparable balanced accuracy scores (PCA: 94.8 ± 3.47 % , LDA: 98.2 ± 2.02 % , biPLS: 95.8 ± 3.04 % , and ensemble: 95.8 ± 3.16 % ) to those of using all features (100%) for cortical bone versus the rest class labels. One hundred percent balanced accuracy scores were generated for bone cement versus the rest. Different feature subsets achieving similar outcomes could be identified due to spectral multicollinearity.ConclusionsWavelength selection frameworks provide a means to explore domain knowledge and discover important contributors to classification in spectroscopy. The ensemble framework generated a model with improved interpretability and preserved physical interpretation, which serves as the basis to determine illumination wavelengths in optical instrumentation design.
We developed a fully-remote biophotonics workshop integrating webinars, computer simulations and at-home experiments to meet the needs of undergraduate students with diverse backgrounds and learning styles. Similar strategies/resources could be used in multidisciplinary programs.
The biophotonics box enables multidisciplinary/interdisciplinary and self-paced learning with at-home experiments using low-resource components. Experiments can increase the interest of students in STEM subjects by emphasizing the real-life applications in biology and medicine.
During the COVID-19 pandemic, social distancing restrictions required courses to be offered fully online, which impacted multidisciplinary courses/events worldwide. The quality of education especially in events relying on in-person activities to convey information quicker than online activities. We have developed a fully-online biophotonics workshop (BW) integrating webinars, at-home experiments, and computer simulations to meet needs of undergraduate students with diverse backgrounds and learning styles. >91.7%, >70%, and >90% of feedback responses were “Very good” and “Good” regarding overall learning, co-ordination and quality of subject matter of BW activities. Other biophotonics/biomedical optics courses may benefit from using similar resources and educational strategies.
Significance: Orthopedic surgery currently comprises over 1.5 million cases annually in the United States alone and is growing rapidly with aging populations. Emerging optical sensing techniques promise fewer side effects with new, more effective approaches aimed at improving patient outcomes following orthopedic surgery.
Aim: The aim of this perspective paper is to outline potential applications where fiberoptic-based approaches can complement ongoing development of minimally invasive surgical procedures for use in orthopedic applications.
Approach: Several procedures involving orthopedic and spinal surgery, along with the clinical challenge associated with each, are considered. The current and potential applications of optical sensing within these procedures are discussed and future opportunities, challenges, and competing technologies are presented for each surgical application.
Results: Strong research efforts involving sensor miniaturization and integration of optics into existing surgical devices, including K-wires and cranial perforators, provided the impetus for this perspective analysis. These advances have made it possible to envision a next-generation set of devices that can be rigorously evaluated in controlled clinical trials to become routine tools for orthopedic surgery.
Conclusions: Integration of optical devices into surgical drills and burrs to discern bone/tissue interfaces could be used to reduce complication rates across a spectrum of orthopedic surgery procedures or to aid less-experienced surgeons in complex techniques, such as laminoplasty or osteotomy. These developments present both opportunities and challenges for the biomedical optics community.
Significance: Despite remarkable advances in the core modalities used in combating cancer, malignant diseases remain the second largest cause of death globally. Interstitial photodynamic therapy (IPDT) has emerged as an alternative approach for the treatment of solid tumors.
Aim: The aim of our study is to outline the advancements in IPDT in recent years and provide our vision for the inclusion of IPDT in standard-of-care (SoC) treatment guidelines of specific malignant diseases.
Approach: First, the SoC treatment for solid tumors is described, and the attractive properties of IPDT are presented. Second, the application of IPDT for selected types of tumors is discussed. Finally, future opportunities are considered.
Results: Strong research efforts in academic, clinical, and industrial settings have led to significant improvements in the current implementation of IPDT, and these studies have demonstrated the unique advantages of this modality for the treatment of solid tumors. It is envisioned that further randomized prospective clinical trials and treatment optimization will enable a wide acceptance of IPDT in the clinical community and inclusion in SoC guidelines for well-defined clinical indications.
Conclusions: The minimally invasive nature of this treatment modality combined with the relatively mild side effects makes IPDT a compelling alternative option for treatment in a number of clinical applications. The adaptability of this technique provides many opportunities to both optimize and personalize the treatment.
Tissue optics education can use several open-source tools available online. Even though these tools can be accessed by a broad student population, education environments, especially during outreach activities, may require more user-friendly and high speed tools that do not require previous programming experience. Then, quick estimators of tissue optical properties based on the tissue chromophore composition and analytical solvers based on diffusion equation can be a more suitable option for short events. In this study, we evaluated students experience during 1.5 hour of computer activities using a tissue-optics computer app. These activities were scheduled during a 7-hour biophotonics workshop given to undergraduate students in 2018 and 2019. Our results suggest the app is user-friendly and suitable for outreach activities. The use of our app may contribute to improve teaching and learning in biomedical optics and biophotonics.
The growth of the global photonics market and technology investment creates a need for skilled professionals with multidisciplinary knowledge. The development of a successful multidisciplinary training for these professionals requires special attention to the implemented educational approaches. Current methods of multidisciplinary teaching and learning include tutoring by a team of experts of different backgrounds and development of projects among multidisciplinary teams of students. In these cases, a detailed feedback is needed from students and teachers in order to improve the course and keep a consistent alignment among the learning outcomes, teaching strategy, and evaluation methods. In this study, we describe the implementation of a method based on continuous improvement of multidisciplinary outreach activities and undergraduate programs. We illustrate the results of this implementation by showing samples of the feedback we received from students and teachers. The overall quality of the teaching and the content of the subject matter was perceived as good by students. Teachers’ evaluation showed students’ knowledge and behavior was satisfactory and the learning outcomes were achieved. Based on this, we believe our educational approach could improve the development and implementation of multidisciplinary activities.
Current methods of teaching tissue optics in biophotonics and biomedical optics courses include creating computer-based learning environments. However, this method assumes students are going to learn or have prior experience on computer programming, which may generate time-consuming activities of several days. Then, the same activities and material of the schools and courses cannot be used in workshops or outreach activities of several hours for generating students interest in biomedical optics. This is partially compensated by websites such as omlc.org, which provide online material about biophotonics fundamentals and time flexibility to access tissue optics tools. On the other hand, students are still required to spend more time to understand tissue optics concepts and those in their first contact with biophotonics may require additional user-friendly tools. With this in mind, user-friendly tools for quick comprehension of tissue optics concepts have potential to accommodate students with diverse backgrounds and improve biomedical optics education. In this study, we designed a tissue-optics computer app that requires no previous programming experience. The app was designed to cover tissue optics topics in short length activities and generate students interest in the biomedical optics field. This computer app was tested in a 1.5 hour session within a 7-hour biophotonics workshop. By the end of the workshop, we collected students feedback about the quality of subject matter and teaching in the computer lab. Our results suggested that our app is user-friendly and is suitable for short activities. We provide a link to access the current version of our app. In the future, the app can be used in outreach activities and workshops for improvement of teaching and learning in tissue optics.
Identifying diseases and evaluating tissue function and viability can be performed by subjective or objective methods. However, subjective techniques may be inaccurate and non-optical objective techniques may be relatively expensive and time-consuming. Then, these techniques may not be suitable for clinical applications that require immediate assessment and intervention. Fluorescence spectroscopy (FS) is one of the optical techniques with great potential for medical diagnostics and surgical guidance. This potential is associated to the possibility of label-free techniques biochemical sensitivity without contrast agents. For clinical applications, fluorescence can be used to assess biomolecular content of respiratory metabolism involving NAD(P)H and FAD. In addition, changes in collagen, elastin, porphyrin, pyridoxine, and tryptophan content can potentially be detected. One way to collect epifluorescence signals from superficial tissue layers is using ultraviolet (UV) excitation. In this study, we used UV excitation FS to investigate the effect of temperature variation (from 0 to 25 degrees Celsius) on tissue autofluorescence. The measurements reproducibility was assessed by variations of the spectral shape accounted by the calculation of the Pearson correlation coefficient for each pair of measurements. Overall, fluorescence measurements were more reproducible at 25°C compared to 0°C. Liver showed lowest fluorescence variability (most homogeneous organ) regarding results from both 300 nm and 340 nm excitations. We report temperature and wavelength-dependent spectral changes due to the tissue thawing by calculating the difference between normalized UVEFS measurements at 0°C and 25°C. Observed differences may be attributed to blood absorption and NADH fluorescence emission. Our results can be used to increase the database of tissue fluorescence spectra using UV excitation for future reference to choose targeted wavelengths in fluorescence instrumentation. Furthermore, our study illustrates expected fluorescence variations during the assessment of organs viability for transplantation, especially due to cold preservation.
The development of photomedical modalities for diagnostics and treatment has created a need for knowledge of the optical properties of the targeted biological tissues. These properties are essential to plan certain procedures, since they determine the light absorption, propagation and penetration in tissues. One way to measure these properties is based on diffuse reflectance spectroscopy (DRS). DRS can provide light absorption and scattering coefficients for each wavelength through a non-invasive, fast and in situ interrogation, and thereby tissue biochemical information. In this study, reflectance measurements of ex vivo mice organs were investigated in a wavelength range between 350 and 1860 nm. To the best of our knowledge, this range is broader than previous studies reported in the literature and is useful to study additional chromophores with absorption in the extended wavelength range. Also, it may provide a more accurate concentration of tissue chromophores when fitting the reflectance spectrum in this extended range. In order to extract these concentrations, optical properties were calculated in a wide spectral range through a fitting routine based on an inverse Monte-Carlo look-up table model. Measurements variability was assessed by calculating the Pearson correlation coefficients between each pair of measured spectra of the same type of organ.
This work presents an investigation of room temperature ultra-fast carrier dynamics in a p-doped dash-in-a-well structure emitting at 1.5 μm using single colour heterodyne pump-probe spectroscopy. This technique enabled simultaneous access to the gain and refractive index dynamics in various operational conditions including both the absorption and gain regime. Comprehensive analysis of the timescales related to carrier relaxation and escape processes in addition to the ’dynamical’ linewidth enhancement factor are presented and compared with results obtained from similar un-doped materials. The direct influence of the p-doping on the carrier dynamics is also discussed.
In this work, the optical properties and emission dynamics of core-shell InGaAs/GaAs nanopillars (NPs) have been in-
vestigated using low-temperature photoluminescence (PL) and time-resolved photoluminescence (TRPL). These novel
structures have recently attracted much interest within the silicon photonics scientific community due to their potential
employment as gain medium for monolithically integrated lasers on silicon substrates. The optimization of the emission
properties of these heterostructures is essential to obtain full compatibility with silicon photonics and requires an accurate
tailoring of the pillar geometry (i.e. size, pitch) and composition. Therefore it is critical to gain deeper insight into the
optical and dynamical properties of different NP designs if optimal device performance is to be achieved. The experimental
characterization, carried out on a number of different NP structures with different geometries and compositions, shows that
the time evolution of the emission peak exhibits a strong excitation-dependent blue-shift which can be attributed to the
band-filling effect. Measured emission decay times were strongly geometry-dependent and varied from nanoseconds to
tens of picoseconds. In addition, a dramatic reduction of the decay time was observed for the highest indium concentration
due to the dominant contribution of the strain-induced non-radiative recombination processes.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.