This PDF file contains the front matter associated with SPIE Proceedings Volume 11247, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

Blood pressure is a primary candidate to be remotely characterized by continuous monitoring devices, as high blood pressure is frequently a symptom of chronic conditions such as diabetes, obesity, and cardiovascular disease while also leading to morbidity itself. Much work has been done to characterize an electrocardiogram (EKG)-photoplethysmogram (PPG) continuous monitor, however a dual PPG continuous monitor may yield more accurate results due to the lack of the inherent pre-ejection period. To predict the anticipated signal of a remote dual-photoplethysmogram (PPG) blood pressure monitor, we utilized parallelized multi-layer Monte Carlo modelling to estimate light transport through the index finger at the proximal phalange. Monte Carlo models of the digital artery and surrounding tissue were created that represent various skin tones as well as the presence of arterioles. Additionally, the signal contribution by arteriole and artery was also determined. By varying incident wavelength, source-detector separation, skin tone, and arterial diameter as a function of pulse propagation; the feasibility of a proximal phalange PPG can be estimated and further optimized to aid development of a dual-PPG blood pressure monitor. The modelling results indicate that at a separation of 3.0mm, 700nm wavelength provides signal resolution that is indicative of contribution from the artery and not the arterioles, which could be beneficial for estimating pulse transit time toward calculating blood pressure. Further work should be completed to optimize sourcedetector separation for arterial contribution to signal and explore various locations on the body, as much optical property variation exists within literature.

For noninvasive glucose sensing, we investigate the relationship between Raman spectrometer specification, especially collection efficiency, and glucose prediction performance in computer simulation. The computer simulation for synthetic Raman spectrum generation was designed to include glucose Raman signals at specific glucose concentrations, and Monte-Carlo simulation was used to simulate spectrum generation in a multi-layer model of skin tissue. We quantified the tendency between the decrease in collection efficiency and the deterioration of glucose prediction performance. This study can be important in the analysis of spectrometer specification for required performance for noninvasive glucose sensing, especially in a miniaturized portable or wearable device.

150 million people worldwide suffer one or more urinary tract infections (UTIs) annually. UTIs are a significant health burden: societal costs of UTI exceed $3.5 billion in the U.S. alone; 5% of sepsis cases arise from a urinary source; and UTIs are a prominent contributor toward antimicrobial resistance (AMR). Current diagnostic frameworks exacerbate this burden by providing inaccurate and delayed diagnosis. Rapid point-of-care bacterial identification will allow for early precision treatment, fundamentally altering the UTI paradigm. Raman spectroscopy has a proven ability to provide rapid bacterial identification but is limited by weak bacterial signal and a susceptibility to background fluorescence. These limitations may be overcome using surface enhanced Raman spectroscopy (SERS), provided close and consistent application of bacteria to the SERS-active surface can be achieved. Physical filtration provides a means of capturing uropathogens, separating them from the background solution and acting as SERS-active surface. This work demonstrates that filters can provide a means of aggregating bacteria, thereby allowing subsequent enhancement of the acquired Raman signal using metallic nanoparticles. 60 bacterial suspensions of common uropathogens were vacuum filtered onto commercial polyvinylidene fluoride membrane filters and Raman signals were enhanced by the addition of silver nanoparticles directly onto the filter surface. SERS spectra were acquired using a commercial Raman spectrometer (Ocean Optics, Inc.). Principal Component – Linear Discriminant Analysis provided discrimination of infected from control samples (accuracy: 88.75%, 95% CI: 79.22-94.59%, p-value <0.05). Amongst infected samples uropathogens were classified with 80% accuracy. This study has demonstrated that combining Raman spectroscopy with membrane filtration and SERS can provide identification of infected samples and rapid bacterial classification.

The accurate and rapid diagnosis of myocardial infarction (MI) is essential to implement timely and definitive treatment to the patient. Cardiac Troponin I (cTnI) has been widely used as a biomarker for early diagnosis of MI. Point-of-care (POC) testing is favored because it can provide timely results when the patient is first encountered (e.g. ambulance, clinic, or emergency department). However, the clinical cut-off of cTnI for diagnosis of MI is in the pico- to femtomolar range (i.e. 0.01-0.1 ng/ml). Thus, a sensitive sensing system is needed to quantitively measure cTnI at the POC. Surface-enhanced Raman spectroscopy (SERS) is a sensitive optical technique that can be used to measure trace analytes in a sample. Moreover, paper-based sensing systems have demonstrated potential as a platform to implement assays, especially at the POC. This research describes the development of a paper-based SERS assay for detection of cTnI in the physiological relevant range. Aptamer is used in the assay for recognizing the cTnI in a sample. SERS is used to sensitively transduce the sensing signal from the assay. A handheld Raman spectrometer is used to measure the SERS signal. By measuring the change in the SERS signal, the concentration of target molecule is quantitatively determined. Moreover, spectral processing techniques are used to evaluate their effect on signal-to-noise ratio as well as sensitivity of the assay. Results showed the designed sensing system can be used to measure cTnI (0-0.5 ng/mL) in standard buffer solutions.

Oral cancers, are one of the major cancers among South Asian populations, particularly men. The low 5-year disease-free survival rate of this is attributed to late detection. Several Raman spectroscopy (RS) studies both non-invasive (in vivo) and less invasive (exfoliated cells, serum) have successfully stratified healthy, precancer, cancer, cancer-field-effects, potential recurrences. In view of attributes of serum, viz., transportability for centralized analysis, better patient compliances, in the present study, we have further examined efficacy of serum RS in delineating oral premalignant disorders (OPMD) - often known precede frank tumors- such as oral submucous fibrosis (OSMF-3), leukoplakia (LP-3), lichen planus (L-4) and habitues without lesions (HWL-10), along with healthy (C-8) ,cancer (Ca-10) subjects and Unknown (T- 8).Raman spectra acquired using Witech Raman spectrometer were analysed by principal component analysis (PCA) and PCA-based linear discriminant analysis. Data analysed in two approaches i.e .individual OPMD groups along with control and tumors; pooled OPMD subjects, controls and tumor subjects. Raman spectral features suggest variation among groups in amino acids, lipids, beta-carotene, and DNA content, Multivariate analysis, in both approaches, revealed clear classification of control and tumor groups but OPMD spectra misclassified with cancers/HWLs. Consequent examination of medical records show few of OPMD subjects carried tumors as well. Though, study shows clinical utility of serum RS as a minimally invasive, rapid and objective approach to obtain a reliable screening/diagnostic modality for oral cancers, in view of high misclassifications among OPMD spectra, further studies with a higher sample size is warranted.

The nervous system in the gastrointestinal wall is an autonomic nervous system that is essential for intestinal peristalsis, mucous secretion, and blood flow regulation. The degeneration or deficiency may cause passage disorder or functional obstruction. Pathological diagnosis accompanied by invasive tissue collection is essential for diagnosing the presence of this nervous system in the gastrointestinal wall. Therefore, we focused on Raman spectroscopy as a non-invasive diagnostic method. The purpose of this study is to develop new diagnostic methods based on optical techniques for non-invasive detection of the nervous system in the gastrointestinal wall using Raman spectroscopy.

Introduction: Current clinical guidelines recommend augmenting the mean arterial pressure (MAP) in acute spinal cord injury (SCI) patients to increase perfusion and oxygen delivery to the spinal cord, and potentially improve neurologic function. However, it is difficult for clinicians to hemodynamically manage acute SCI patients without real-time physiologic information about the effect of MAP augmentation within the injured cord. In this study, we investigated the utilization of a customized optical sensor, based on near-infrared spectroscopy (NIRS), to non-invasively monitor spinal cord oxygenation during the first week post-injury in a porcine model. Methods: Six Yucatan mini-pigs received a weight-drop T10 contusion-compression injury. A multi-wavelength NIRS system with a custom-made miniaturized sensor was placed directly onto the dura. The spinal cord tissue oxygenation index (TOI) and concentrations of oxygenated, deoxygenated, and total hemoglobin were monitored before and after SCI. To validate the NIRS measures, invasive intraparenchymal (IP) combined PO2/blood flow sensors were inserted into the spinal cord adjacent to the NIRS sensor. Episodes of MAP alteration and hypoxia were performed acutely after injury, 2 days post-injury, and 7 days post-injury to simulate the types of hemodynamic changes SCI patients experience post-injury. Results: Non-invasive NIRS monitoring identified changes in spinal cord oxygenation levels during the MAP alterations. Changes of TOI followed similar patterns of IP-derived oxygenation changes. Conclusion: Our novel NIRS sensor is feasible as a non-invasive technique to monitor real-time changes in spinal cord oxygenation 7 days post-injury in a porcine model of SCI.

Dysfunctional hemoglobin derivatives, such as carboxyhemoglobin and methemoglobin, do not participate in vital oxygen transport and are therefore of great importance in clinical diagnostics. The optical determination of their concentrations in whole blood is difficult due to the strong light scattering processes, which depend on numerous parameters unknown at the time of measurement. For this reason, the erythrocytes are usually destroyed prior analysis. This can be an exclusion criterion for subsequent analyses. We present a new method for the determination of hemoglobin derivatives in unaltered whole blood using Support Vector regression (SVR) in the spectral range from 450 to 700 nm. Diffuse reflection as well as diffuse, unscattered and total transmission of 358 blood samples were measured using a double integrating sphere setup and used to train SVR models that predict hemoglobin derivative concentrations in unknown samples. The proportions of the hemoglobin derivatives as well as the hematocrit and osmotic concentration of the samples were adjusted using a tonometer and buffer solutions. 34 separate whole blood samples were used as test set. Overall R2 greater than 0.97 and mean absolute errors smaller than 2.03 % solely on total transmission spectra indicate that SVR is an appropriate method.

Clinical hematological practice often relies on analysis of the peripheral blood based on microscopic evaluation of blood smears and complete blood count (CBC). Accurate examination of blood cell abnormalities using such methods necessitates complex, time-consuming, and expensive sample preparation as well as instruments which require a many reagents and intensive maintenance. Further, hematology analysis is performed at healthcare centers by trained personnel which significantly limits monitoring frequency for patients with severe conditions and can compromise the treatment outcome. Therefore, a portable, easy-to-use, and inexpensive hematology analysis device can potentially improve quality of life for patients with blood diseases and allow point-of-care monitoring and diagnosis. In this work, we demonstrate label-free blood cell assessment based on deep-ultraviolet (UV) microscopy. Our approach provides quantitative endogenous molecular information from live cells and enables assessment and differentiation of blood cell types based on their molecular and structural signatures. We show the ability of our method by performing classification of polymorphonuclear leukocyte (PMNL) subtypes based on features extracted from deep-UV images. In addition, we demonstrate a pseudo-colorization scheme which accurately mimics the colors produced by standard Giemsa staining and enable visual examination of blood smears. The results of our work paves the way for development of a low-cost and easy-to-use hematological analysis device that can be used for point-of-care applications.

Standard coagulation testing is limited to measuring clotting time and lacks information on global hemostasis and coagulation status of patients undergoing complex cardiac surgical procedures. Here, we assessed the accuracy of our novel bedside optical sensor, iCoagLab, to measure global coagulation status from temporal speckle intensity fluctuations in 25µL of blood obtained from patients during cardiac surgery. Our results showed a dose-dependent prolongation and significant modulation of iCoagLab-ACT, angle and MA metrics throughout surgery which closely mirrored standard-reference Hepcon-ACT measurements. In conclusion, iCoagLab accurately assessed global hemostasis using a drop of blood, likely opening the opportunity for multifunctional, bedside coagulation monitoring in patients undergoing cardiac surgical procedures.

We present a simple method for the diagnosis of urinary schistosomiasis using an in-line lensless holographic microscope combined with flow cytometry technique. Using simple image processing algorithms and binary image classifier, our system provides automated detection of Schistosoma haematobium eggs in infected urine samples. Registered hologram is reconstructed by applying backpropagation from sensor to sample plane and reconstructed image is automatically analysed for the presence of S. haematobium eggs. Designed for use in a resource-poor laboratory setting, our proposed method has been implemented using a Raspberry Pi computer. From pre-clinical test performed with human urine samples spiked with S. haematobium eggs (approximately 200 eggs per 12 ml of urine), we achieved a sensitivity and specificity of 50.6% and 98.6% respectively. Our proposed method requires no complex sample preparation methods making the system simple to operate and useable in point-of-care diagnosis of urinary schistosomiasis.This method can be optimized to complement existing diagnostic procedures for the detection of S. haematobium eggs and can be deployed to inaccessible remote areas.

Complete Blood Count (CBC) is a routine blood test program that is often prescribed by physicians. It analyzes the values of various blood cells and can be used for detection of related diseases and infections. Flow cytometry has been one of the widely used technique to count, characterize and classify blood cells in the previous studies. However, the technique suffers from time-consuming procedure for analyzing the target cell and the bulky design of the detection platform. Hence, we propose a high-throughput lensless holographic microscopy for rapid blood analysis and imaging in large field-of-view (FOV) of 30 mm2. The holographic technique can simultaneously record the amplitude and phase of the diffraction pattern, which are different due to cell sizes and materials for further cell counting. Then the original cell images are digitally reconstructed by scalar diffraction theory and inverse Fourier transform to identify red blood cells, white blood cells and platelets. The lens-free holographic platform has compact size that makes it easy-to-handle. The lens-free design is able to analyze the blood samples on a chip by using the spatial coherence light (LED) emanating from a pinhole, and imaging on the CMOS sensor with a spatial resolution of 1.67 μm. The application of a CBC can diagnose anemia, infections, and other disorders. We believe that the lensless on-chip holographic platform will be a cost-effective tool for point-of-care cytometry.

In this study, we applied photoplethysmography (PPG) as an alternative, convenient, and affordable method for bovine heat detection. Heat detection is an essential part of effective herd reproduction management. Currently, there are many different heat detection techniques, but they can be ineffective or impractical to use. Since heat affects local vulvar blood circulation (resulting in swelling and erythema), photoplethysmography could represent an affordable alternative to detect this bovine phenomenon. In this study, we enrolled 20 animals in heat and other stages of the bovine reproduction cycle. We analyzed the PPG signal in terms of baseline (DC component), power, kurtosis, and erythema index. One vaginal measurement site, approximately 8 cm from the vulva, exhibited significant differences in mucous color (PPG green and red baseline, both erythema indices). What is more, cows in heat displayed higher PPG signal power and kurtosis, but differences were not significant. Photoplethysmography exhibited the potential to detect bovine heat.