Quantifying changes in oxygen saturation of the internal jugular vein in vivo using deep neural networks and subject-specific three-dimensional Monte Carlo models.

Central venous oxygen saturation (ScvO2) is an important parameter for assessing global oxygen usage and guiding clinical interventions. However, measuring ScvO2 requires invasive catheterization. As an alternative, we aim to noninvasively and continuously measure changes in oxygen saturation of the internal jugular vein (SijvO2) by a multi-channel near-infrared spectroscopy system. The relation between the measured reflectance and changes in SijvO2 is modeled by Monte Carlo simulations and used to build a prediction model using deep neural networks (DNNs). The prediction model is tested with simulated data to show robustness to individual variations in tissue optical properties. The proposed technique is promising to provide a noninvasive tool for monitoring the stability of brain oxygenation in broad patient populations.

Specific refraction-index increments of oxygenated hemoglobin from thalassemia-minor patients are not significantly different than those from healthy individuals.

The mass and concentration of hemoglobin per erythrocyte are important hematological parameters. Measuring these parameters from intact erythrocytes requires the value of specific refraction-index increment (RII) of oxygenated hemoglobin, which diverges in the literature. Refractive indices of hemoglobin solutions are measured directly by digital holographic microscopy on a microfluidic channel filled with hemoglobin solutions prepared by hemolysis of fresh human erythrocytes and refractive-index standards sequentially. Hemoglobin extracted from thalassemic patients shows 3-4% higher RII than that from healthy volunteers, but the difference is not significant in comparison to inter-subject variations within each group. The quantified RIIs are applied to quantify mean corpuscular hemoglobin mass of blood from 37 human subjects, and results are in accord with standard clinical test results.

Regulation of lipid droplets in live preadipocytes using optical diffraction tomography and Raman spectroscopy.

Lipid droplets have gained strong interest in recent years to comprehend how they function and coordinate with other parts of the cell. However, it remains challenging to study the regulation of lipid droplets in live preadipocytes using conventional microscopic techniques. In this paper, we study the effects of fatty acid stimulation and cell starvation on lipid droplets using optical diffraction tomography and Raman spectroscopy by measuring size, refractive index, volume, dry mass and degree of unsaturation. The increase of fatty acids causes an increase in the number and dry mass of lipid droplets. During starvation, the number of lipid droplets increases drastically, which are released to mitochondria to release energy. Studying lipid droplets under different chemical stimulations could help us understand the regulation of lipid droplets for metabolic disorders, such as obesity and diabetes.

Hybrid method to estimate two-layered superficial tissue optical properties from simulated data of diffuse reflectance spectroscopy.

An iterative curve fitting method has been applied in both simulation [J. Biomed. Opt.17, 107003 (2012)JBOPFO1083-366810.1117/1.JBO.17.10.107003] and phantom [J. Biomed. Opt.19, 077002 (2014)JBOPFO1083-366810.1117/1.JBO.19.7.077002] studies to accurately extract optical properties and the top layer thickness of a two-layered superficial tissue model from diffuse reflectance spectroscopy (DRS) data. This paper describes a hybrid two-step parameter estimation procedure to address two main issues of the previous method, including (1) high computational intensity and (2) converging to local minima. The parameter estimation procedure contained a novel initial estimation step to obtain an initial guess, which was used by a subsequent iterative fitting step to optimize the parameter estimation. A lookup table was used in both steps to quickly obtain reflectance spectra and reduce computational intensity. On simulated DRS data, the proposed parameter estimation procedure achieved high estimation accuracy and a 95% reduction of computational time compared to previous studies. Furthermore, the proposed initial estimation step led to better convergence of the following fitting step. Strategies used in the proposed procedure could benefit both the modeling and experimental data processing of not only DRS but also related approaches such as near-infrared spectroscopy.

Non-axial-scanning multifocal confocal microscopy with multiplexed volume holographic gratings.

Confocal imaging techniques offer an optical sectioning capability to acquire three-dimensional information from various volumetric samples by discriminating the desired in-focus signals from the out-of-focus background. However, confocal, in general, requires a point-by-point scan in both the lateral and axial directions to reconstruct three-dimensional images. In addition, axial scanning in confocal is slower than scanning in lateral directions. In this Letter, a non-axial-scanning multifocal confocal microscope incorporating multiplexed holographic gratings in illumination and dual detection for depth discrimination is presented. Further, we demonstrate the ability of the proposed confocal microscopy to image ex vivo tissue structures simultaneously at different focal depths without mechanical or electro-optic axial scanning.

Characteristic investigation of scanning surface plasmon microscopy for nucleotide functionalized nanoarray.

A calculation based on surface plasmon coupling condition and Maxwell-Garnett equation was performed for predicting the coupling angle shift and thin film thickness in scanning surface plasmon microscopy (SSPM). The refractive index sensitivity and lateral resolution of an SSPM system was also investigated. The limit of detection of angle shift was 0.01°, the limit of quantification of angle shift was 0.03°, and the sensitivity was around 0.12° shift per nm ZnO film when the film thickness was less than 22.6 nm. Two partially connected Au nano-discs with a center-to-center distance of 1.1 µm could be identified as two peaks. The system was applied to image nanostructure defects and a virus-probe functionalized nanoarray. We expect the potential application in nanobiosensors with further optimization in the future.

Tomographic diffractive microscopy of living cells based on a common-path configuration.

We demonstrate a common-path tomographic diffractive microscopy technique for three-dimensional (3D) refractive-index (RI) imaging of unstained living cells. A diffraction grating is utilized to generate a reference beam that traverses a blank region of the sample in a common-path off-axis interferometry setup. Single-shot phase images captured at multiple illumination angles are used for 3D RI reconstruction based on optical diffraction tomography. The common-path configuration shows lower temporal phase fluctuations and better RI resolution than a Mach-Zehnder configuration. 3D subcellular RI distributions of live HeLa cells are quantified.

Characterization and identification of cell death dynamics by quantitative phase imaging.

SIGNIFICANCE: Investigating cell death dynamics at the single-cell level plays an essential role in biological research. Quantitative phase imaging (QPI), a label-free method without adverse effects of exogenous labels, has been widely used to image many types of cells under various conditions. However, the dynamics of QPI features during cell death have not been thoroughly characterized. AIM: We aim to develop a label-free technique to quantitatively characterize single-cell dynamics of cellular morphology and intracellular mass distribution of cells undergoing apoptosis and necrosis. APPROACH: QPI was used to capture time-lapse phase images of apoptotic, necrotic, and normal cells. The dynamics of morphological and QPI features during cell death were fitted by a sigmoid function to quantify both the extent and rate of changes. RESULTS: The two types of cell death mainly differed from normal cells in the lower phase of the central region and differed from each other in the sharp nuclear boundary shown in apoptotic cells. CONCLUSIONS: The proposed method characterizes the dynamics of cellular morphology and intracellular mass distributions, which could be applied to studying cells undergoing state transition such as drug response.

Quantifying tissue optical properties of human heads in vivo using continuous-wave near-infrared spectroscopy and subject-specific three-dimensional Monte Carlo models.

SIGNIFICANCE: Quantifying subject-specific optical properties (OPs) including absorption and transport scattering coefficients of tissues in the human head could improve the modeling of photon propagation for the analysis of functional near-infrared spectroscopy (fNIRS) data and dosage quantification in therapeutic applications. Current methods employ diffuse approximation, which excludes a low-scattering cerebrospinal fluid compartment and causes errors. AIM: This work aims to quantify OPs of the scalp, skull, and gray matter in vivo based on accurate Monte Carlo (MC) modeling. APPROACH: Iterative curve fitting was applied to quantify tissue OPs from multidistance continuous-wave NIR reflectance spectra. An artificial neural network (ANN) was trained using MC-simulated reflectance values based on subject-specific voxel-based tissue models to replace MC simulations as the forward model in curve fitting. To efficiently generate sufficient data for training the ANN, the efficiency of MC simulations was greatly improved by white MC simulations, increasing the detectors' acceptance angle, and building a lookup table for interpolation. RESULTS: The trained ANN was six orders of magnitude faster than the original MC simulations. OPs of the three tissue compartments were quantified from NIR reflectance spectra measured at the forehead of five healthy subjects and their uncertainties were estimated. CONCLUSIONS: This work demonstrated an MC-based iterative curve fitting method to quantify subject-specific tissue OPs in-vivo, with all OPs except for scattering coefficients of scalp within the ranges reported in the literature, which could aid the modeling of photon propagation in human heads.

Rapid Detection of Virus Nucleic Acid via Isothermal Amplification on Plasmonic Enhanced Digitizing Biosensor.

Rapid detection for infectious diseases is highly demanded in diagnosis and infection prevention. In this work, we introduced a plasmonic enhanced digitizing biosensor for the rapid detection of nucleic acids. The sensor successfully achieved the detection of loop-mediated isothermal amplification for the hepatitis virus in this work. The sensor comprised a nanodisc array and Bst polymerases conjugated on the rough surface of a nanodisc. The rough surface of the nanodisc provided plasmonic hot spots to enhance the fluorescence signal. The virus DNA was detected by conducting a modified loop-mediated isothermal amplification with fluorescence resonance energy transfer reporter conjugated primers on the sensor. The modified isothermal amplification improved the signal contrast and detection time compared to the original assay. By integrating the modified amplification assay and plasmonic enhancement sensor, we achieved rapid detection of the hepatitis virus. Nucleic acid with a concentration of 10-3 to 10-4 mg/mL was detected within a few minutes by our design. Our digitizing plasmonic nanoarray biosensor also showed 20-30 min earlier detection compared to conventional loop-mediated isothermal amplification sensors.

Evaluation of the robustness of cerebral oximetry to variations in skin pigmentation using a tissue-simulating phantom.

Clinical studies have demonstrated that epidermal pigmentation level can affect cerebral oximetry measurements. To evaluate the robustness of these devices, we have developed a phantom-based test method that includes an epidermis-simulating layer with several melanin concentrations and a 3D-printed cerebrovascular module. Measurements were performed with neonatal, pediatric and adult sensors from two commercial oximeters, where neonatal probes had shorter source-detector separation distances. Referenced blood oxygenation levels ranged from 30 to 90%. Cerebral oximeter outputs exhibited a consistent decrease in saturation level with simulated melanin content; this effect was greatest at low saturation levels, producing a change of up to 15%. Dependence on pigmentation was strongest in a neonatal sensor, possibly due to its high reflectivity. Overall, our findings indicate that a modular channel-array phantom approach can provide a practical tool for assessing the impact of skin pigmentation on cerebral oximeter performance and that modifications to algorithms and/or instrumentation may be needed to mitigate pigmentation bias.

High-throughput detection of immobilized plasmonic nanoparticles by a hyperspectral imaging system based on Fourier transform spectrometry.

To facilitate the application of plasmonic nanoparticles (PNPs) in high-throughput detection, we develop a hyperspectral imaging system (HSIS) combining dark-filed microscopy and imaging Fourier transform spectrometry to measure scattering spectra from immobilized PNPs. The current setup has acquisition time of 5 seconds and spectral resolution of 21.4 nm at 532.1 nm. We demonstrate the applicability of the HSIS in conjunction with spectral data analysis to quantify multiple types of PNPs and detect small changes in localized surface plasmon resonance wavelengths of PNPs due to changes in the environmental refractive index.

Automatic detection and characterization of quantitative phase images of thalassemic red blood cells using a mask region-based convolutional neural network.

SIGNIFICANCE: Label-free quantitative phase imaging is a promising technique for the automatic detection of abnormal red blood cells (RBCs) in real time. Although deep-learning techniques can accurately detect abnormal RBCs from quantitative phase images efficiently, their applications in diagnostic testing are limited by the lack of transparency. More interpretable results such as morphological and biochemical characteristics of individual RBCs are highly desirable. AIM: An end-to-end deep-learning model was developed to efficiently discriminate thalassemic RBCs (tRBCs) from healthy RBCs (hRBCs) in quantitative phase images and segment RBCs for single-cell characterization. APPROACH: Two-dimensional quantitative phase images of hRBCs and tRBCs were acquired using digital holographic microscopy. A mask region-based convolutional neural network (Mask R-CNN) model was trained to discriminate tRBCs and segment individual RBCs. Characterization of tRBCs was achieved utilizing SHapley Additive exPlanation analysis and canonical correlation analysis on automatically segmented RBC phase images. RESULTS: The implemented model achieved 97.8% accuracy in detecting tRBCs. Phase-shift statistics showed the highest influence on the correct classification of tRBCs. Associations between the phase-shift features and three-dimensional morphological features were revealed. CONCLUSIONS: The implemented Mask R-CNN model accurately identified tRBCs and segmented RBCs to provide single-RBC characterization, which has the potential to aid clinical decision-making.

Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations.

A robust modelling method was proposed to extract chromophore information in multi-layered skin tissue with spatially-resolved diffuse reflectance spectroscopy. Artificial neural network models trained with a pre-simulated database were first built to map geometric and optical parameters into diffuse reflectance spectra. Nine fitting parameters including chromophore concentrations and oxygen saturation were then determined by solving the inverse problem of fitting spectral measurements from three different parts of the skin. Compared to the Monte Carlo simulation accelerated by a graphics processing unit, the proposed modelling method not only reduced the computation time, but also achieved a better fitting performance.

Morphometric analysis of erythrocytes from patients with thalassemia using tomographic diffractive microscopy.

Complete blood count is the most common test to detect anemia, but it is unable to obtain the abnormal shape of erythrocytes, which highly correlates with the hematologic function. Tomographic diffractive microscopy (TDM) is an emerging technique capable of quantifying three-dimensional (3-D) refractive index (RI) distributions of erythrocytes without labeling. TDM was used to characterize optical and morphological properties of 172 erythrocytes from healthy volunteers and 419 erythrocytes from thalassemic patients. To efficiently extract and analyze the properties of erythrocytes, we developed an adaptive region-growing method for automatically delineating erythrocytes from 3-D RI maps. The thalassemic erythrocytes not only contained lower hemoglobin content but also showed doughnut shape and significantly lower volume, surface area, effective radius, and average thickness. A multi-indices prediction model achieved perfect accuracy of diagnosing thalassemia using four features, including the optical volume, surface-area-to-volume ratio, sphericity index, and surface area. The results demonstrate the ability of TDM to provide quantitative, hematologic measurements and to assess morphological features of erythrocytes to distinguish healthy and thalassemic erythrocytes.

Tip-enhanced fluorescence with radially polarized illumination for monitoring loop-mediated isothermal amplification on hepatitis C virus cDNA.

A tip nanobiosensor for monitoring DNA replication was presented. The effects of excitation power and polarization on tip-enhanced fluorescence (TEF) were assessed with the tip immersed in fluorescein isothiocyanate solution first. The photon count rose on average fivefold with radially polarized illumination at 50 mW. We then used polymerase-functionalized tips for monitoring loop-mediated isothermal amplification on Hepatitis C virus cDNA. The amplicon-SYBR® Green I complex was detected and compared to real-time loop-mediated isothermal amplification. The signals of the reaction using 4 and 0.004 ng∕µl templates were detected 10 and 30 min earlier, respectively. The results showed the potential of TEF in developing a nanobiosensor for real-time DNA amplification.

Precancerous esophageal epithelia are associated with significantly increased scattering coefficients.

The progression of epithelial precancers into cancer is accompanied by changes of tissue and cellular structures in the epithelium. Correlations between the structural changes and scattering coefficients of esophageal epithelia were investigated using quantitative phase images and the scattering-phase theorem. An ex vivo study of 14 patients demonstrated that the average scattering coefficient of precancerous epithelia was 37.8% higher than that of normal epithelia from the same patient. The scattering coefficients were highly correlated with morphological features including the cell density and the nuclear-to-cytoplasmic ratio. A high interpatient variability in scattering coefficients was observed and suggests identifying precancerous lesions based on the relative change in scattering coefficients.

Fiber optic confocal reflectance microscopy: a new real-time technique to view nuclear morphology in cervical squamous epithelium in vivo.

We present a fiber optic confocal reflectance microscope (FCRM) which can be used to image epithelial tissue with sub-cellular resolution in vivo. Confocal images of normal and abnormal appearing cervical tissue were obtained in vivo from eighteen patients undergoing colposcopic examination of the cervix; biopsy specimens were taken from imaged sites. The measured lateral and axial resolutions of the system were 1.6 microm and 3 microm, respectively. Morphologic features, including nuclear size and nuclear-to-cytoplasmic ratio, were extracted from confocal images obtained at various depths beneath the epithelial surface. Image features extracted from confocal images compared well with features extracted from confocal images obtained in vitro and from previous histopathologic studies. This study shows that fiber optic confocal reflectance microscopy can be used to visualize the morphology of cervical epithelium in vivo.

Endoscopic microscopy.

In vivo endoscopic optical microscopy provides a tool to assess tissue architecture and morphology with contrast and resolution similar to that provided by standard histopathology--without need for physical tissue removal. In this article, we focus on optical imaging technologies that have the potential to dramatically improve the detection, prevention, and therapy of epithelial cancers. Epithelial pre-cancers and cancers are associated with a variety of morphologic, architectural, and molecular changes, which currently can be assessed only through invasive, painful biopsy. Optical imaging is ideally suited to detecting cancer-related alterations because it can detect biochemical and morphologic alterations with sub-cellular resolution throughout the entire epithelial thickness. Optical techniques can be implemented non-invasively, in real time, and at low cost to survey the tissue surface at risk. Our manuscript focuses primarily on modalities that currently are the most developed: reflectance confocal microscopy (RCM) and optical coherence tomography (OCT). However, recent advances in fluorescence-based endoscopic microscopy also are reviewed briefly. We discuss the basic principles of these emerging technologies and their current and potential applications in early cancer detection. We also present research activities focused on development of exogenous contrast agents that can enhance the morphological features important for cancer detection and that have the potential to allow vital molecular imaging of cancer-related biomarkers. In conclusion, we discuss future improvements to the technology needed to develop robust clinical devices.

Fiber-optic confocal reflectance microscope with miniature objective for in vivo imaging of human tissues.

We have built a fiber-optic confocal reflectance microscope capable of imaging human tissues in near real time. Miniaturization of the objective lens and the mechanical components for positioning and axially scanning the objective enables the device to be used in inner organs of the human body. The lateral resolution is 2 micrometers and axial resolution is 10 micrometers. Confocal images of fixed tissue biopsies and the human lip in vivo have been obtained at 15 frames/s without any fluorescent stains. Both cell morphology and tissue architecture can be appreciated from images obtained with this microscope.