Fetal hypoxic brain injury is the deprivation of oxygen during labour and is associated with up to 60% mortality. The gold standard of fetal monitoring during labour, the cardio tocograph (CTG) and fetal blood sampling are poor at diagnosing hypoxia continuously and non-invasively. Our research is towards developing a non-invasive, continuous hypoxia assessment system using long wavelength near-infrared spectroscopy through a fiber optic based reflectance. Lactate is a key biomarker for hypoxia determination in babies during birth. For successful implementation of this probe, it is required that it detects lactate in maternal environment and in presence of other spectroscopic interferences. In this paper we look at lactate sensing through a liquid phantom containing spectrally interfering components alongside lactate like glucose, urea, triacetin and albumin. Through these experiments we determine the relevant wavelengths and their combination for effective lactate sensing.
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.
Oral cancer (OC) is one of the most common oral malignancies. Despite significant advances in medical devices, the five-year survival rate of OC remains low. Current technologies based on tissue pathology are insufficient to diagnose OC at early stages. Molecular sensitive technique such as optical spectroscopy, on the other hand, has the potential for early-stage diagnostics and non-invasive tissue interrogation. Raman spectroscopy (RS), for instance, is a powerful vibrational spectroscopy that allows highly sensitive detection of low concentration analytes, as well as molecular fingerprints of bio samples to be studied non-invasively. Additionally, higher spatial resolution, narrow peaks, better sensitivity and minimal sample preparation makes RS a potential tool for analysing oral cancer in a clinical setting. In this study, we will validate the potential of Raman spectroscopy (RS) and surface enhanced Raman spectroscopy (SERS) for oral cancer diagnostics. Patients having biopsy and histopathological examination were involved in this study. Ex vivo measurements were performed on saliva specimen using SERS while in-vivo analysis was performed by RS. Integration of in vivo tissue and ex vivo sample analysis could potentially improve early-stage OC detection, and hence the overall survival rate of OC.
Identifying vulnerable plaques at an early stage is critical to reducing patient mortality associated with cardiovascular diseases. Diffuse reflectance spectroscopy (DRS) can directly measure of absorption and scattering properties of tissue and can detect oxy-haemoglobin inside the plaque associated with intraplaque haemorrhage, which is a feature of vulnerable plaques. This study assesses the potential of using a diffuse reflectance spectroscopy combined with a machine learning algorithm to identify oxygenated haemoglobin in a chick embryo chorioallantoic membrane (CAM) assay model. A total of 88 diffuse reflectance spectra measurements were collected from five 12 to 14-day-old embryos. The first and second derivative of the reflectance spectra were calculated, followed by the use of partial least square-linear discriminant analysis (PLS-LDA) to identify oxygenated haemoglobin in chick embryo vessels. The model achieved a sensitivity and specificity of 96% and 72%, respectively, in differentiating arteries from veins (oxy-haemoglobin) using reflectance data. The sensitivity and specificity were 92% and 88% using the first derivative of reflectance data, and 100% and 92% using the second derivative of reflectance data in the wavelength range of 500-600 nm. Initial results indicate that derivative reflectance combined with multivariate analysis has advantages for detecting tissue oxygenated haemoglobin in CAM assay model. This approach shows promise as a way to identify and study the features of vulnerable plaques.
Oral cancer is one of the most malignant cancers in the world. Early-stage diagnosis of oral cancer is complex process due to the multifocal unspecific development of non-malignant lesions into cancer and impossibility to take biopsy of every lesion. The aim of this study is to develop a screening method for oral cancer diagnosis at early stages using surface enhanced Raman spectroscopy (SERS) and validate the performance of a multimodal system including Raman spectroscopic (RS) and diffuse reflectance spectroscopy (DRS) oral cancer diagnosis and accurate margin detection. The study will involve the identification and integration of spectral biomarkers involved in the carcinogenesis process from different modalities. Each modality SERS, RS and DRS is calibrated and standardized individually. Patients suffering from oral squamous cell carcinoma and other malignant diseases going through biopsy or histopathological examination are enrolled in this study. Ex vivo study involves the SERS analysis of saliva specimen and in vivo analysis will involve measurements on various tissue types, including malignant tissue and healthy contralateral site to evaluate the reproducibility and signal-to-noise ratio using fiber-optic probes for Raman and DRS systems. Feature selection methods and further machine learning tools will be used to discriminate between healthy, benign and cancer lesions based on spectral information and to identify important biomarkers. After data collection, clinician will perform a normal biopsy procedure and histopathological analysis, which will serve as gold standard to determine the sensitivity and specificity of the spectroscopy techniques.
Colorectal cancer (CRC) is the third most common and the second most deadly type of cancer worldwide. Developing new technologies for accurate CRC detection/delineation for resection during microsurgery requires unveiling tissue biochemical and microstructural changes associated with carcinogenesis. These changes can be probed by diffuse reflectance spectroscopy (DRS), which is capable of extracting tissue chromophore concentrations and scattering parameters. Previous CRC studies have been mostly restricted to chromophores in the visible region and analytical light diffusion models. In this study, we extended this wavelength range to 350–1919 nm and used the range between 450–1590 nm to extract tissue biochemical and microstructural parameters. This extraction was performed by using DRS spectral fitting based on a reflectance look-up table built using Monte Carlo simulations of light propagation in tissues. Tissue parameters were used as an input to classification and regression tree algorithm to estimate parameter thresholds leading to best tissue differentiation for CRC detection/delineation. Differentiation between mucosa and tumor tissues was based on 2889 diffuse reflectance spectra from fresh ex vivo tissue samples from 47 subjects. All analyses were performed to investigate data of superficial tissue up to 1.1 mm and deeper tissue layers up to 1.8 mm. The most important parameters for CRC detection were total lipid content, water content, reduced scattering amplitude, Mie scattering power, and microvascular parameters. We not only confirmed the importance of these parameters with metrics in addition to statistical tests and classification models of our previous studies, but also extended the motivation of achieving successful tissue classification with an area under the receiver operating characteristic curve (AUC) higher than 90% with interpretable DRS spectral fitting parameters. Our analysis may have important clinical applications for the rapid diagnosis of colorectal neoplasia.
The Oral Squamous Cell carcinoma (OSCC) is one of the most common and aggressive oral malignancies. Despite all significant advances in medicine, five-year survival rate is still low. This study aims to develop a full scheme for diagnosing oral cancer in early stages by using Raman spectroscopy. Patients undergoing biopsy or histopathological examination will be enrolled in this study. Ex vivo measurement will be carried out using saliva specimens and in vivo analysis will involve measurements taken on healthy and malignant tissue. In the future, this optical diagnostic approach using Raman spectroscopy and SERS can help in improving diagnostic accuracy and the survival rate by affecting the treatment outcome via early stage detection of oral cancer.
Colorectal cancer (CRC) is the second most deadly and third most common type of cancer worldwide. In this study, we assessed the improvement of the diagnostic potential of diffuse reflectance spectroscopy (DRS) for CRC detection upon extending the tissue probed depth (up to 2mm) and wavelength ranges (350-1919 nm) investigated in previous studies. We analyzed almost 3000 DR spectra (7.5 times more than previous studies) collected with 630-µm and 2500-µm source-detector distance probes by using support vector machines with potential to automate tissue classification. We achieved 96.1% sensitivity and 95.7% specificity and 0.987±0.005 AUC on tissue classification.
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.
Even though recent advances in medical devices have significantly improved clinical interventions, more accurate differentiation of biological tissues is still required to improve clinical decision-making. Tissue identification can be performed by using molecular-sensitive techniques such as diffuse reflectance spectroscopy (DRS), which is allows label-free, non-invasive, real-time and in situ interrogation of biological tissues. In this study, we used broadband DRS to extract biomolecule concentrations of gastrointestinal tissues and evaluated its potential for tissue identification and cancer detection. Diffuse reflectance spectra were analysed in an extended wavelength range between 350 nm and 1900 nm. This range covers the third optical window, which may allow better tissue identification for laparoscopy and gastrointestinal robotic surgery. Chromophore concentrations were obtained by using an inverse Monte Carlo Lookup table model to fit the reflectance spectrum.
We present a simple fiber-optics probe system that could be used in any lab for convenient determination of optical properties of liquid phantoms based on diffuse reflectance and transmittance measurements in the visible/near-infrared region. We employed Monte Carlo simulations to determine the optimal system setup and to test the inverse algorithm employed to extract the optical properties from measured reflectance and transmittance. The inverse algorithm involved obtaining the fit merit function for values within the optical property range and determining the minimum. The performance of the method was tested by predictive error and validated using similar matrix of milk–ink phantoms on reflectance and transmittance. In the range of optical properties of phantoms with optical properties of 0 to 0.5 cm − 1 for μa and 20 to 140 cm − 1 for μs, the median prediction error for the test phantoms at 630 nm was 1.51% for μs and 8.82% for μa. The median difference in predicted values versus expected values was 1.15 cm − 1 for μs and 0.01 cm − 1 for μa. In comparison with other techniques, our method was a simple, fast, and convenient way to determine optical properties of liquid phantoms.
Fluorescence spectroscopy has been extensively investigated for disease diagnosis. In this framework, optical tissue phantoms are widely used for validating the biomedical device system in laboratory environment outside clinical procedures. Moreover, it is fundamental to consider that there are several scattering components and chromophores inside biological tissues and the interplay between scattering effects and absorption can result in a distortion of the emitted fluorescence signal. In this work, the photophysical behaviour of a set of liquid tissue like phantoms containing different compositions was analysed: phosphate buffer saline (PBS) was used as background medium, low fat milk as a scatterer, India ink as an absorber and PpIX dissolved in dimethyl formamide (DMF) as fluorophore. We examined the collected data in terms of the impact of surfactant Tween-20 on the background medium, scattering effects and combination of scattering and absorption within a luminescent body on PpIX. The results indicated that the intrinsic emission peaks are red-shifted by the scattering particles or surfactant, whilst the scatterer and absorber can alter the emission intensity substantially. We corroborated that phantoms containing higher surfactant content (< 0.5% Tween 20) are essential to prepare a stable aqueous phantoms.
We present a simple, convenient fibre-optics probe system for the determination optical properties of tissue-like liquid phantoms based on diffuse reflectance and transmittance measurements at the wavelength of visible-near-infrared region. The method combined Monte Carlo simulations, multiple polynomial regression and a Newton-Raphson algorithm for solving nonlinear equation system. In the range of optical properties of phantom with the μa at 0 – 0.5 cm-1 and the μs’ at 3 – 45 cm-1, the mean prediction error at 630 nm was 1.91 % for μs’ and 7.51 % for μa. The performance of the method is further tested by predictive error and validated using similar matrix of milk-ink phantoms on reflectance and transmittance.
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 paper presents a technology of hybrid integration vertical cavity surface emitting lasers (VCSELs) directly on silicon photonics chip. By controlling the reflow of the solder balls used for electrical and mechanical bonding, the VCSELs were bonded at 10 degree to achieve the optimum angle-of-incidence to the planar grating coupler through vision based flip-chip techniques. The 1 dB discrepancy between optical loss values of flip-chip passive assembly and active alignment confirmed that the general purpose of the flip-chip design concept is achieved. This hybrid approach of integrating a miniaturized light source on chip opens the possibly of highly compact sensor system, which enable future portable and wearable diagnostics devices.
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