Investigation of tissue cellularity at the tip of the core biopsy needle with optical coherence tomography.

We report the development and the pre-clinical testing of a new technology based on optical coherence tomography (OCT) for investigating tissue composition at the tip of the core biopsy needle. While ultrasound, computed tomography, and magnetic resonance imaging are routinely used to guide needle placement within a tumor, they still do not provide the resolution needed to investigate tissue cellularity (ratio between viable tumor and benign stroma) at the needle tip prior to taking a biopsy core. High resolution OCT imaging, however, can be used to investigate tissue morphology at the micron scale, and thus to determine if the biopsy core would likely have the expected composition. Therefore, we implemented this capability within a custom-made biopsy gun and evaluated its capability for a correct estimation of tumor tissue cellularity. A pilot study on a rabbit model of soft tissue cancer has shown the capability of this technique to provide correct evaluation of tumor tissue cellularity in over 85% of the cases. These initial results indicate the potential benefit of the OCT-based approach for improving the success of the core biopsy procedures.

Multiwavelength time-resolved near-infrared spectroscopy of the adult head: assessment of intracerebral and extracerebral absorption changes.

An optical technique based on diffuse reflectance measurement combined with indocyanine green (ICG) bolus tracking is extensively tested as a method for the clinical assessment of brain perfusion at the bedside. We report on multiwavelength time-resolved diffuse reflectance spectroscopy measurements carried out on the head of a healthy adult during the intravenous administration of a bolus of ICG. Intracerebral and extracerebral changes in absorption were estimated from an analysis of changes in statistical moments (total number of photons, mean time of flight and variance) of the distributions of times of flight (DTOF) of photons recorded simultaneously at 16 wavelengths from the range of 650-850 nm using sensitivity factors estimated by diffusion approximation based on a layered model of the studied medium. We validated the proposed method in a series of phantom experiments and in-vivo measurements. The results obtained show that changes in the concentration of the ICG can be assessed as a function of time of the experiment and depth in the tissue. Thus, the separation of changes in ICG concentration appearing in intra- and extracerebral tissues can be estimated from optical data acquired at a single source-detector pair of fibers/fiber bundles positioned on the surface of the head.

Label-free light-sheet microfluidic cytometry for the automatic identification of senescent cells.

Label-free microfluidic cytometry is of increasing interest for single cell analysis due to its advantages of high-throughput, miniaturization, as well as noninvasive detection. Here we develop a next generation label-free light-sheet microfluidic cytometer for single cell analysis by two-dimensional (2D) light scattering measurements. Our cytometer integrates light sheet illumination with a disposable hydrodynamic focusing unit, which can achieve 3D hydrodynamic focusing of a sample fluid to a diameter of 19 micrometer without microfabrication. This integration also improves the signal to noise ratio (SNR) for the acquisition of 2D light scattering patterns from label-free cells. Particle sizing with submicron resolution is achieved by our light-sheet flow cytometer, where Euclidean distance-based similarity measures are performed. Label-free, automatic classification of senescent and normal cells is achieved with a high accuracy rate by incorporating our light-sheet flow cytometry with support vector machine (SVM) algorithms. Our light-sheet microfluidic cytometry with a microfabrication-free hydrodynamic focusing unit may find wide applications for automatic and label-free clinical diagnosis.

Investigation of the influence of sampling schemes on quantitative dynamic fluorescence imaging.

Dynamic optical data from a series of sampling intervals can be used for quantitative analysis to obtain meaningful kinetic parameters of probe in vivo. The sampling schemes may affect the quantification results of dynamic fluorescence imaging. Here, we investigate the influence of different sampling schemes on the quantification of binding potential (BP) with theoretically simulated and experimentally measured data. Three groups of sampling schemes are investigated including the sampling starting point, sampling sparsity, and sampling uniformity. In the investigation of the influence of the sampling starting point, we further summarize two cases by considering the missing timing sequence between the probe injection and sampling starting time. Results show that the mean value of BP exhibits an obvious growth trend with an increase in the delay of the sampling starting point, and has a strong correlation with the sampling sparsity. The growth trend is much more obvious if throwing the missing timing sequence. The standard deviation of BP is inversely related to the sampling sparsity, and independent of the sampling uniformity and the delay of sampling starting time. Moreover, the mean value of BP obtained by uniform sampling is significantly higher than that by using the non-uniform sampling. Our results collectively suggest that a suitable sampling scheme can help compartmental modeling of dynamic fluorescence imaging provide more accurate results and simpler operations.

Fast localization method of an anomaly in tissue based on differential optical density.

The position of the source-detector (S-D) relative to an anomaly has an important influence on the detection effect in non-invasive near-infrared spectroscopy-based methods. In this study, a single-source multi-detector structure was designed in order to realize the rapid localization of anomalies within tissue. This method uses finite element analysis of the optical density distribution for different horizontal positions, depths and diameters of anomalies. The difference in optical density between the detectors was then calculated. The simulation results show that the horizontal position of the anomaly in the tissue can be quickly located according to the differential optical density difference curves formed by the multiple detectors. The Gaussian fitting feature of these curves shows strong correlation with the horizontal positions, depths and diameters of the anomaly. Through the differential optical density difference curves, rapid localization within the region of interest can be achieved. This method provides an important reference for sources and detectors location for tumor detection, brain function optical imaging and other fields using near infrared spectroscopy, and improves its detection accuracy.

Intra-class variability in diffuse reflectance spectroscopy: application to porcine adipose tissue.

Optical diffuse reflectance spectroscopy (DRS) has great potential in the study, diagnosis, and discrimination of biological tissues. Discrimination is based on massive measurements that conform training sets. These sets are then used to classify tissues according to the biomedical application. Classification accuracy depends strongly on the training dataset, which typically comes from different samples of the same class, and from different points of the same sample. The variability of these measurements is not usually considered and is assumed to be purely random, although it could greatly influence the results. In this work, spectral variations within and between samples of different animals of ex-vivo porcine adipose tissue are evaluated. Algorithms for normalization, dimensionality reduction by principal component analysis, and variability control are applied. The PC analysis shows the dataset variability, even when a variability removal algorithm is applied. The projected data appear grouped by animal in the PC space. Mahalanobis distance is calculated for every group, and an ANOVA test is performed in order to estimate the variability. The results confirm that the variability is not random and is dependent at least on the anatomical location and the specific animal. The variability magnitude is significant, particularly if the classification accuracy is needed to be high. As a consequence, it should be taken generally into account in classification problems.

Multiscale nonlinear microscopy and widefield white light imaging enables rapid histological imaging of surgical specimen margins.

The ability to histologically assess surgical specimens in real-time is a long-standing challenge in cancer surgery, including applications such as breast conserving therapy (BCT). Up to 40% of women treated with BCT for breast cancer require a repeat surgery due to postoperative histological findings of close or positive surgical margins using conventional formalin fixed paraffin embedded histology. Imaging technologies such as nonlinear microscopy (NLM), combined with exogenous fluorophores can rapidly provide virtual H&E imaging of surgical specimens without requiring microtome sectioning, facilitating intraoperative assessment of margin status. However, the large volume of typical surgical excisions combined with the need for rapid assessment, make comprehensive cellular resolution margin assessment during surgery challenging. To address this limitation, we developed a multiscale, real-time microscope with variable magnification NLM and real-time, co-registered position display using a widefield white light imaging system. Margin assessment can be performed rapidly under operator guidance to image specific regions of interest located using widefield imaging. Using simulated surgical margins dissected from human breast excisions, we demonstrate that multi-centimeter margins can be comprehensively imaged at cellular resolution, enabling intraoperative margin assessment. These methods are consistent with pathology assessment performed using frozen section analysis (FSA), however NLM enables faster and more comprehensive assessment of surgical specimens because imaging can be performed without freezing and cryo-sectioning. Therefore, NLM methods have the potential to be applied to a wide range of intra-operative applications.

Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools.

Type 2 diabetes mellitus (DM2) is one of the most widely prevalent diseases worldwide and is currently screened by invasive techniques based on enzymatic assays that measure plasma glucose concentration in a laboratory setting. A promising plan of action for screening DM2 is to identify molecular signatures in a non-invasive fashion. This work describes the application of portable Raman spectroscopy coupled with several supervised machine-learning techniques, to discern between diabetic patients and healthy controls (Ctrl), with a high degree of accuracy. Using artificial neural networks (ANN), we accurately discriminated between DM2 and Ctrl groups with 88.9-90.9% accuracy, depending on the sampling site. In order to compare the ANN performance to more traditional methods used in spectroscopy, principal component analysis (PCA) was carried out. A subset of features from PCA was used to generate a support vector machine (SVM) model, albeit with decreased accuracy (76.0-82.5%). The 10-fold cross-validation model was performed to validate both classifiers. This technique is relatively low-cost, harmless, simple and comfortable for the patient, yielding rapid diagnosis. Furthermore, the performance of the ANN-based method was better than the typical performance of the invasive measurement of capillary blood glucose. These characteristics make our method a promising screening tool for identifying DM2 in a non-invasive and automated fashion.

Robust layer segmentation of esophageal OCT images based on graph search using edge-enhanced weights.

Automatic segmentation of esophageal layers in OCT images is crucial for studying esophageal diseases and computer-assisted diagnosis. This work aims to improve the current techniques to increase the accuracy and robustness for esophageal OCT image segmentation. A two-step edge-enhanced graph search (EEGS) framework is proposed in this study. Firstly, a preprocessing scheme is applied to suppress speckle noise and remove the disturbance in the esophageal structure. Secondly, the image is formulated into a graph and layer boundaries are located by graph search. In this process, we propose an edge-enhanced weight matrix for the graph by combining the vertical gradients with a Canny edge map. Experiments on esophageal OCT images from guinea pigs demonstrate that the EEGS framework is more robust and more accurate than the current segmentation method. It can be potentially useful for the early detection of esophageal diseases.

Label-free and stable serum analysis based on Ag-NPs/PSi surface-enhanced Raman scattering for noninvasive lung cancer detection.

Surface-enhanced Raman scattering (SERS) has a broad application prospect in the field of tumor detection owing to its ultrahigh detective sensitivity. However, SERS analysis of serum remain a challenge in terms of repeatability and stability due to the maldistribution of the silver nanoparticles (Ag-NPs)-serum. With the aim to make up for this shortcoming, we report a new method for obtaining stable serum Raman signals utilizing the ordered arrays of pyramidal silicon (PSi) and Ag-NPs. We prove the practicability of this method by detecting the samples of serum from 50 lung cancer patients and 50 normal healthy people. Principal component analysis (PCA) of the serum SERS spectra shows that the spectral data of the two sample groups can form obvious and completely separated clusters. The receiver operating characteristic curve provides the sensitivity (100%) and specificity (90%) from the PCA-LDA method. This research indicates that a stable and label-free analysis technique of serum SERS based on Ag-NPs/PSi and PCA-LDA is promising for noninvasive lung cancer diagnoses.

Application of a near-infrared laser tweezers Raman spectroscopy system for label-free analysis and differentiation of diabetic red blood cells.

A home-made near-infrared laser tweezers Raman spectroscopy (LTRS) system was applied to detect hemoglobin variation in red blood cells (RBCs) from diabetes without exogenous labeling. Results showed significant spectral differences existed between the diabetic and normal RBCs, including the peaks dominated by protein components (e.g. 1003 cm-1) and heme groups (e.g. 753 cm-1) in RBCs, and accurate classification results for diabetes detection were obtained by linear discriminant analysis with 100% sensitivity (i.e. no false negatives in the study). This work indicated the great promise of LTRS as a label-free RBC analytical tool for improving the accurate detection of type II diabetes.

Discrimination of lymphoma using laser-induced breakdown spectroscopy conducted on whole blood samples.

Lymphoma is a significant cancer that affects the human lymphatic and hematopoietic systems. In this work, discrimination of lymphoma using laser-induced breakdown spectroscopy (LIBS) conducted on whole blood samples is presented. The whole blood samples collected from lymphoma patients and healthy controls are deposited onto standard quantitative filter papers and ablated with a 1064 nm Q-switched Nd:YAG laser. 16 atomic and ionic emission lines of calcium (Ca), iron (Fe), magnesium (Mg), potassium (K) and sodium (Na) are selected to discriminate the cancer disease. Chemometric methods, including principal component analysis (PCA), linear discriminant analysis (LDA) classification, and k nearest neighbor (kNN) classification are used to build the discrimination models. Both LDA and kNN models have achieved very good discrimination performances for lymphoma, with an accuracy of over 99.7%, a sensitivity of over 0.996, and a specificity of over 0.997. These results demonstrate that the whole-blood-based LIBS technique in combination with chemometric methods can serve as a fast, less invasive, and accurate method for detection and discrimination of human malignancies.

Glycerol dehydration of native and diabetic animal tissues studied by THz-TDS and NMR methods.

The optical clearing method has been widely used for different spectral ranges where it provides tissue transparency. In this work, we observed the enhanced penetration of the terahertz waves inside biological samples (skin, kidney, and cornea) treated with glycerol solutions inducing changes of optical and dielectric properties. It was supported by the observed trend of free-to-bound water ratio measured by the nuclear magnetic resonance (NMR) method. The terahertz clearing efficiency was found to be less for diabetic samples than for normal ones. Results of the numerical simulation proved that pulse deformation is due to bigger penetration depth caused by the reduction of absorption and refraction at optical clearing.

Label-free fluorescence lifetime spectroscopy detects radiation-induced necrotic changes in live brain in real-time.

Current clinical imaging modalities do not reliably identify brain tissue regions with necrosis following radiotherapy. This creates challenges for stereotaxic biopsies and surgical-decision making. Time-resolved fluorescence spectroscopy (TRFS) provides a means to rapidly identify necrotic tissue by its distinct autofluorescence signature resulting from tissue breakdown and altered metabolic profiles in regions with radiation damage. Studies conducted in a live animal model of radiation necrosis demonstrated that necrotic tissue is characterized by respective increases of 27% and 108% in average lifetime and redox ratio, when compared with healthy tissue. Moreover, radiation-damaged tissue not visible by MRI but confirmed by histopathology, was detected by TRFS. Current results demonstrate the ability of TRFS to identify radiation-damaged brain tissue in real-time and indicates its potential to assist with surgical guidance and MRI-guided biopsy procedures.

A spread spectrum approach to time-domain near-infrared diffuse optical imaging using inexpensive optical transceiver modules.

We introduce a compact time-domain system for near-infrared spectroscopy using a spread spectrum technique. The proof-of-concept single channel instrument utilises a low-cost commercially available optical transceiver module as a light source, controlled by a Kintex 7 field programmable gate array (FPGA). The FPGA modulates the optical transceiver with maximum-length sequences at line rates up to 10Gb/s, allowing us to achieve an instrument response function with full width at half maximum under 600ps. The instrument is characterised through a set of detailed phantom measurements as well as proof-of-concept in vivo measurements, demonstrating performance comparable with conventional pulsed time-domain near-infrared spectroscopy systems.

Prediction of the anti-glioma therapeutic effects of temozolomide through in vivo molecular imaging of MMP expression.

Currently, there is no effective way to assess the therapeutic response of temozolomide (TMZ) for the glioma. In this study, the human U87MG-fLuc glioma animal models were set up and the antitumor efficacy of TMZ was evaluated using bioluminescence imaging (BLI) and MRI. Then, bioluminescence tomography (BLT) was reconstructed using an adaptive sparsity matching pursuit (ASMP) algorithm. Second, the expression level of the MMP-750 probe was examined with or without TMZ treatment using FMI. Third, the expression of MMP2 and MMP3 was specifically examined after treatment. The results showed that TMZ effectively inhibited glioma growth. The targeted imaging of MMP-750 was decreased during the treatment of glioma with TMZ. Moreover, the MMP2 and MMP3 expression was found to correlate with the inhibition effect of TMZ. Our study indicated that the therapeutic effects of TMZ can be effectively evaluated at an early stage using molecular imaging, and MMP targeting the fluorescence probe could be utilized for the prediction and assessment of the therapeutic effects of TMZ.

On the dysfunctional hemoglobins and cyanosis connection: practical implications for the clinical detection and differentiation of methemoglobinemia and sulfhemoglobinemia.

Methemoglobinemia and sulfhemoglobinemia are potentially life-threatening blood-related disorders characterized by similar symptoms and markedly distinct treatment procedures. In this paper, we investigate the causal relationship between these conditions and the onset of cyanosis, which is typically associated with a purple or bluish skin coloration. More specifically, we perform controlled experiments to elicit cyanotic appearances resulting from different severity levels of these disorders and varying physiological conditions. We note that such experiments cannot be induced in living subjects without posing risks to their health. Accordingly, we have resorted to an in silico experimental approach supported by biophysical data reported in the literature. Besides bringing new insights about cyanotic chromatic variations elicited by methemoglobinemia and sulfhemoglobinemia, our investigation provides the basis for the proposition of a cost-effective protocol for the noninvasive detection and differentiation of these disorders. Our experimental results indicate that its sensitivity range is wider than what is provided by similar protocols employed in these tasks. Moreover, it has lower operational requirements than laboratory tests ordered to enable the diagnosis of these conditions. We believe that these aspects make the proposed protocol particularly suitable for deployment at the point of care of medical settings with limited access to laboratory resources.

Near-simultaneous quantification of glucose uptake, mitochondrial membrane potential, and vascular parameters in murine flank tumors using quantitative diffuse reflectance and fluorescence spectroscopy.

The shifting metabolic landscape of aggressive tumors, with fluctuating oxygenation conditions and temporal changes in glycolysis and mitochondrial metabolism, is a critical phenomenon to study in order to understand negative treatment outcomes. Recently, we have demonstrated near-simultaneous optical imaging of mitochondrial membrane potential (MMP) and glucose uptake in non-tumor window chambers, using the fluorescent probes tetramethylrhodamine ethyl ester (TMRE) and 2-N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (2-NBDG). Here, we demonstrate a complementary technique to perform near-simultaneous in vivo optical spectroscopy of tissue vascular parameters, glucose uptake, and MMP in a solid tumor model that is most often used for therapeutic studies. Our study demonstrates the potential of optical spectroscopy as an effective tool to quantify the vascular and metabolic characteristics of a tumor, which is an important step towards understanding the mechanisms underlying cancer progression, metastasis, and resistance to therapies.

Assessment of the radiotherapy effect for nasopharyngeal cancer using plasma surface-enhanced Raman spectroscopy technology.

Nasopharyngeal cancer (NPC) is a malignant tumor of the head and neck, which is extremely sensitive to radiotherapy. The aim of this study is to evaluate the feasibility of a label-free nanobiosensor based on plasma surface-enhanced Raman spectroscopy (SERS) to assess the radiotherapy effect in NPC. Here, SERS measurements were performed on plasma samples from 40 pre-treatment and post-treatment NPC as well as 30 healthy volunteers. Results demonstrate that the spectral characteristic of post-treatment samples is obviously different from that of pre-treatment ones, owing to the changes of biomolecules in plasma induced by radiotherapy. Classification sensitivities of 83.3%, 61.8% and 95.1%, and specificities of 91.2%, 67.4% and 93% can be achieved for separating pre- and post-treatment samples, post-treatment and normal samples, and pre-treatment and normal samples, respectively, suggesting the great potential of plasma SERS method as a rapid and convenient tool for radiotherapy assessment and cancer screening in NPC.

Measuring water contents in animal organ tissues using terahertz spectroscopic imaging.

We investigated the water contents in several organ tissues such as the liver, spleen, kidney, and brain tissue of rats using the terahertz spectroscopic imaging technique. The water contents of the tissues were determined by using a simple equation containing the absorption coefficients of fresh and lyophilized tissues and water. We compared the measured water contents with the difference in mass of tissues before and after lyophilization. All results showed a good match except for the kidney, which has several Bowman's capsules.