This PDF file contains the front matter associated with SPIE Proceedings Volume 12856, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Current pulse oximetry has been facing inevitable challenges of skin tones, low perfusion, and motion artefacts due to the limitations of Lambert-Beer’s law based photoplethysmography (PPG). This becomes a hurdle to achieve clinical standard practice when using a wearable device. Opto-physiological monitoring (OPM) is the exploration outcome of utilizing Radiative Transfer Theorem (RTT) to generate high-definition models to interact light with various types of tissues. A multi-wavelength opto-electronic patch sensor (mOEPS) based on these OPM models, has been developed to overcome those limitations of PPG devices. The mOEPS has multi-spectral illuminations associated with a specific sensing configuration and bespoke electronics with real-time embedded AI signal processing platform. to work out heart rate (HR), blood oxygen saturation (SpO₂%), perfusion index (PI), and respiration rate (RR). One physical intensity protocol with five subjects aligned with Monk Skin Tone (MST) scale has been carried out in a controlled chamber to validate the mOEPS functionalities where the sensor was attached on the back of wrist and chest of the subjects. The unprocessed signals captured by OPM sensor clearly reveal multi-spectral pulsatile waveforms for subjects with all skin types. The comparison of HR, RR, SpO₂ gathering with the references from the comparators is executed to show the performance differences between mOEPS and these patient monitor and wearable devices. The outcomes demonstrate that the mOEPS enables physiological monitoring for all types of skin tones in real-time and at any time either in clinical sets or personal/home care at routine physical states compared to present PPG technology.

Bile duct cancer, or cholangiocarcinoma, is a prevalent liver cancer often diagnosed at advanced stages, leading to poor survival rates. Therefore, the development of a reliable early detection technique is urgently needed. Current imaging techniques lack the necessary accuracy to distinguish between dysplastic and benign biliary ducts. Endoscopic techniques, while capable of directly assessing the bile duct lining, often suffer from insufficient sampling. In this paper we discuss a novel endoscopic optical light scattering technique designed to evaluate the malignant potential of the bile duct. The technique employs an ultraminiature spatial gating fiber optic probe compatible with cholangioscopes and endoscopic retrograde cholangiopancreatography (ERCP) catheters. The miniature optical probe enables the detailed investigation of the internal cellular composition of the bile duct epithelium using light scattering spectroscopy (LSS) and also allows for the assessment of the phenotypic properties of the underlying connective tissue with diffuse reflectance spectroscopy (DRS). In a pilot in vivo double-blind prospective study involving 29 patients undergoing routine ERCP procedures, the technique detected malignant transformation with 97% accuracy. Our pilot study suggests that biliary duct pre-cancer can be identified non-invasively in vivo, offering a promising new avenue for early detection and intervention in bile duct cancer.

Multi-Exposure Speckle Imaging (MESI) utilizes laser speckle for visualizing flow and quantifying flow changes. Using a coherent laser source to illuminate the sample, the reflected speckle pattern is captured at various exposure times, enabling the estimation of flow dynamics. Free space MESI setups have a fixed imaging geometry limiting the flexibility in certain applications such as handheld, bandage integrated, or endoscopic systems. This study explores the use of an optical imaging fiber bundle to capture the reflected speckle pattern. A bundle containing 18,000 individual 7.6μm fibers was incorporated into a MESI optical setup with two paths: a conventional free space configuration and a fiber bundle configuration. MESI images were acquired of tissue simulating phantoms (microfluidic channel of 300μm; flow rates of 1-100 μL/min), in-vivo mouse cortical flow, and stroke response (ROI selection from capillaries and vessels). The inverse correlation time (ICT) of the speckle autocorrelation function is determined by fitting a physics-based speckle model to the contrast of the captured images. For both microfluidic and in-vivo experiments, ICT measurements from the fiber path were linearly related to ICT measurements from the free space path with Pearson correlation coefficient of 0.993-1.00 and 0.952-0.988 for the microfluidic and in-vivo data, respectively. There is a strong positive correlation in both experiments showing the feasibility of detecting differences in flow speeds using MESI through a fiber bundle. Integrating an optical fiber bundle into the MESI system increases the flexibility of the technique for use in other applications.

Nanobubbles (NBs) have demonstrable potential for ultrasound imaging and therapeutic applications. Recent studies have even shown their capacity for cellular internalization, which has important implications for their in-vivo stability and bioaccumulation. Traditional methods for observing NBs often involve fluorescence labelling, which can influence NB behaviour. Moreover, these methods are unsuitable for detecting intact (acoustically active) NBs within a cellular environment. This study introduces a label-free approach employing optical coherence tomography (OCT) to investigate the temporal variations in speckle intensity of the OCT backscatter signal of cells interacting with NBs. The temporal variations in the signal intensity of cell aggregates result from the motion of subcellular scatterers within the cellular environment. In this work, we investigate whether internalized NBs modify the temporal variations in the signal intensity. For our experimental imaging set-up, we used a Thorlabs MEMS-VCSEL Swept Source OCT system with a central wavelength of 1300 nm to acquire M-Mode and B-Mode acquisitions. PC3 prostate cancer cells and in-house lipid-shelled NBs were used. The sensitivity of the speckle decorrelation technique was tested on our system using an intensity autocorrelation function on polystyrene microspheres and diluted NBs. Our study demonstrates that speckle decorrelation OCT can effectively detect NBs within a compact cell pellet under specific conditions and was verified using contrast-enhanced ultrasound. This approach provides an additional optical method for NB detection within cellular environments and holds the potential for broader applications in detecting NBs in in-vivo applications.

Structurally anisotropic materials are ubiquitous in several application fields, yet their accurate optical characterization remains challenging due our incomplete understanding of how anisotropic light transport properties arise from the microscopic scattering coefficients. In fact, even when the dynamics of light transport is directly measured, coarse simplifications are often introduced due to a lack of established theoretical models or numerical methods. Here, we apply a general Monte Carlo implementation capable of handling direction-dependent scattering to the analysis of light transport in a sample of polytetrafluoroethylene (PTFE) tape. Using only a set of transient transmittance intensity profiles, the analysis retrieves the tensor components of the diffusive rates and the scattering coefficients along all three directions, in excellent agreement with Monte Carlo simulations.

Laser speckle contrast imaging(LSCI) has been developed to measure blood perfusion non-invasively for a long time. However, there are some limitations to analyzing the random speckle phenomenon and relying on the statistical description in bio-application. This study aimed to verify the three-dimensional convolution neural network(3D-CNN) model for analyzing laser speckle images and predicting the perfusion velocity. The dataset for training deep learning was processed in the form of 3D-image and the image was from a real-time LSCI system. The model can potentially measure static and dynamic speckle information and predict perfusion velocity under the static tissue.

Three major one layer tissue models (Modified Beer-Lambert,¹ Jacques 1999,² Pilon 2009³) are compared to Monte Carlo simulated diffuse reflectance spectra and measured tissue phantom spectra with known ground truth. These ground truth values were obtained using inverse adding doubling and absorbance measurements and validated using a phantom with known ground truth (BioPixs). Finally, a two layer model (Pilon 2009) was evaluated against Monte Carlo simulations and used to analyse skin reflectance data (NIST⁴). These models were compared on goodness of fit and parameter extraction accuracy. It was found that the Pilon 2009 one layer model performed best against Monte Carlo simulations and phantom measurements, however the Pilon 2009 two layer model had significant regions of inaccuracy. These inaccurate regions correspond to circumstances where the epidermal layer has significant thickness and melanin content, while the dermal layer has low fraction of blood meaning that the haemoglobin impact is “masked”. The extraction of parameters from the NIST skin dataset using this model returns values that do not correspond well to literature values suggesting that many of these spectra lie within an inaccurate region or indicates oversimplification of the tissue modelling. This suggests both Pilon 2009 and Jacques 1999 are suitable for modelling tissue that can be approximated as a single, homogeneous, semi-infinite slab, however the Pilon 2009 two layer model is not yet effective when encountering empirical data.

Tumors arise from the uncontrolled growth of cells and can be benign or cancerous. The size of the tumor is one of the key factors in assessing its malignancy potential. Generally, larger tumor polyp tends to have higher risk of developing into a cancer. Smaller polyps often start benign but some of it evolve over time to adenomatous or cancerous and extend to other parts of the body. To mitigate this risk, even smaller polyps are usually removed if found during screening. However, the detection of small polyps, especially flat or sessile types, remains a challenge. Advanced techniques are being developed to identify early-stage tumors by studying biomechanical, biochemical, and morphological changes. Tumor progression alters the viscoelasticity, local refractive index, and surface roughness, increasing tissue disorder both structurally and optically. This disorder can localize light through multiple scattering and can be utilized to provide cavity feedback for lasing emission called ‘random lasing’. In this work, we simulate a tumor polyp growth in a phantom tissue impregnated with a gain medium and investigate the resulting random lasing emission. We find that the emission properties such as the intensity, lasing threshold, emission wavelength, and linewidth are all influenced by the presence of the polyp and this technique could precisely identify even polyps of size ~ millimeters. Overall, this research showcases the potential of random lasing to investigate disorder-induced changes for early and sensitive detection of tumor and identification of tissue abnormalities.