Multispectral, non-contact diffuse optical tomography of healthy human finger joints.

Rheumatoid arthritis (RA) is an inflammatory joint disease often affecting the hands, which if untreated causes disability. Diffuse optical tomography (DOT) provides information about the underlying functional properties of biological tissue. To detect pathophysiological changes in inflamed RA joints, a good understanding of the baseline values for healthy subjects is first required. Finger joints from healthy subjects were imaged using a non-contact, multispectral, continuous wave DOT system, recovering physiological parameters of oxygen saturation, total haemoglobin, water concentration and scatter amplitude. Reconstructed values across the cohort demonstrated good consistency between finger joints from the same participant, with greater variation seen between subjects.

Raman spectroscopy of bone composition during healing of subcritical calvarial defects.

Subcritical calvarial defects heal spontaneously and optical methods can study the healing without mechanically perturbing the bone. In this study, 1mm defects were created on the skulls (in vivo) of Sprague-Dawley rats (n = 14). After 7 (n = 7) and 14 days (n = 7) of healing, the subjects were sacrificed and additional defects were similarly created (control). Raman spectroscopy (785nm) was performed at the two time points and defect types. Spectra were quantified by the mineral/matrix ratio, carbonate/phosphate ratio and crystallinity. Mineral/matrix of in vivo defects is lower than that of controls by ~34% after 7 days and ~21% after 14 days. Carbonate/phosphate is 8% and 5% higher while crystallinity is 7% and 3% lower, respectively. Optical profiling shows that the surface roughness increases 1.2% from controls to in vivo after 7 days, then decreases 13% after 14 days. Overall, the results show maturation of mineral crystals during healing and agree with microscopic assessment.

Comparison of tissue oximeters on a liquid phantom with adjustable optical properties: an extension.

Cerebral near-infrared spectroscopy (NIRS) oximetry may help clinicians to improve patient treatment. However, the application of NIRS oximeters is increasingly causing confusion to the users due to the inconsistency of tissue oxygen haemoglobin saturation (StO2) readings provided by different oximeters. To establish a comparability of oximeters, in our study we performed simultaneous measurements on the liquid phantom mimicking properties of neonatal heads and compared the tested device to a reference NIRS oximeter (OxiplexTS). We evaluated the NIRS oximeters FORE-SIGHT, NIRO and SenSmart, and reproduced previous results with the INVOS and OxyPrem v1.3 oximeters. In general, linear relationships of the StO2 values with respect to the reference were obtained. Device specific hypoxic and hyperoxic thresholds (as used in the SafeBoosC study, www.safeboosc.eu) and a table allowing for conversion of StO2 values are provided.

Spatially resolved diffuse reflectance spectroscopy endoscopic sensing with custom Si photodetectors.

Early detection and surveillance of disease progression in epithelial tissue is key to improving long term patient outcomes for colon and esophageal cancers, which account for nearly a quarter of cancer related mortalities worldwide. Spatially resolved diffuse reflectance spectroscopy (SRDRS) is a non-invasive optical technique to sense biological changes at the cellular and sub-cellular level that occur when normal tissue becomes diseased, and has the potential to significantly improve the current standard of care for endoscopic gastrointestinal (GI) screening. Herein the design, fabrication, and characterization of the first custom SRDRS device to enable endoscopic SRDRS GI tissue characterization using a custom silicon (Si) thin film multi-pixel endoscopic optical sensor (MEOS) is described.

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.

Identifying intestinal fibrosis and inflammation by spectroscopic photoacoustic imaging: an animal study in vivo.

Crohn's disease (CD) is a chronic autoimmune disease characterized by obstructing intestinal strictures. Conventional imaging modalities can identify the strictures but cannot characterize whether a stricture is predominantly inflammatory or fibrotic. The purpose of this study is to examine the capability of photoacoustic (PA) imaging to characterize intestinal fibrosis and inflammation in vivo. Intestinal strictures in a rat model of CD were imaged with a PA-ultrasound parallel imaging system. Internal and external illuminations were attempted, both with transcutaneous PA signal reception. The PA signal magnitudes acquired at wavelengths targeting individual molecular components and the derived functional information showed significant differences between the inflammatory and fibrotic strictures, consistent with histological inflammation and fibrosis.

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.

Quantitative characterization of turbidity by radiative transfer based reflectance imaging.

A new and noncontact approach of multispectral reflectance imaging has been developed to inversely determine the absorption coefficient of µ a , the scattering coefficient of µs and the anisotropy factor g of a turbid target from one measured reflectance image. The incident beam was profiled with a diffuse reflectance standard for deriving both measured and calculated reflectance images. A GPU implemented Monte Carlo code was developed to determine the parameters with a conjugate gradient descent algorithm and the existence of unique solutions was shown. We noninvasively determined embedded region thickness in heterogeneous targets and estimated in vivo optical parameters of nevi from 4 patients between 500 and 950nm for melanoma diagnosis to demonstrate the potentials of quantitative reflectance imaging.

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.

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.

Fiber-based visible and near infrared optical coherence tomography (vnOCT) enables quantitative elastic light scattering spectroscopy in human retina.

Elastic light scattering spectroscopy (ELSS) has been proven a powerful method in measuring tissue structures with exquisite nanoscale sensitivity. However, ELSS contrast in the living human retina has been relatively underexplored, primarily due to the lack of imaging tools with a large spectral bandwidth. Here, we report a simple all fiber-based setup to implement dual-channel visible and near infrared (NIR) optical coherence tomography (vnOCT) for human retinal imaging, bridging over a 300nm spectral gap. Remarkably, the fiber components in our vnOCT system support single-mode propagation for both visible and NIR light, both of which maintain excellent interference efficiencies with fringe visibility of 97% and 90%, respectively. The longitudinal chromatic aberration from the eye is corrected by a custom-designed achromatizing lens. The elegant fiber-based design enables simultaneous imaging for both channels and allows comprehensive ELSS analysis on several important anatomical layers, including nerve fiber layer, outer segment of the photoreceptors and retinal pigment epithelium. This vnOCT platform and method of ELSS analysis open new opportunities in understanding structure-function relationship in the human retina and in exploring new biomarkers for retinal diseases.

Transcranial diffuse optical assessment of the microvascular reperfusion after thrombolysis for acute ischemic stroke.

In this pilot study, we have evaluated bedside diffuse optical monitoring combining diffuse correlation spectroscopy and near-infrared diffuse optical spectroscopy to assess the effect of thrombolysis with an intravenous recombinant tissue plasminogen activator (rtPA) on cerebral hemodynamics in an acute ischemic stroke. Frontal lobes of five patients with an acute middle cerebral artery occlusion were measured bilaterally during rtPA treatment. Both ipsilesional and contralesional hemispheres showed significant increases in cerebral blood flow, total hemoglobin concentration and oxy-hemoglobin concentration during the first 2.5 hours after rtPA bolus. The increases were faster and higher in the ipsilesional hemisphere. The results show that bedside optical monitoring can detect the effect of reperfusion therapy for ischemic stroke in real-time.

Spectroscopic photoacoustic imaging of radiofrequency ablation in the left atrium.

Catheter-based radiofrequency ablation for atrial fibrillation has long-term success in 60-70% of cases. A better assessment of lesion quality, depth, and continuity could improve the procedure's outcome. We investigate here photoacoustic contrast between ablated and healthy atrial-wall tissue in vitro in wavelengths spanning from 410 nm to 1000 nm. We studied single- and multi-wavelength imaging of ablation lesions and we demonstrate that a two-wavelength technique yields precise detection of lesions, achieving a diagnostic accuracy of 97%. We compare this with a best single-wavelength (640 nm) analysis that correctly identifies 82% of lesions. We discuss the origin of relevant spectroscopic features and perspectives for translation to clinical imaging.

Ex vivo classification of spinal cord tumors using autofluorescence spectroscopy and immunohistochemical indexes.

Spinal cord tumors are complicated and infrequent, which poses a major challenge to surgeons during neurosurgery. Currently, the intraoperative identification of the tissues' pathological properties is usually difficult for surgeons. This issue influences the decision-making in treatment planning. Traditional pathological diagnoses can facilitate judging the tissues' properties, but the diagnosis process is complex and time-consuming. In this study, we evaluated the potential of autofluorescence spectroscopy for the fast pathological diagnosis of specific spinal cord tumors. The spectral properties of six types of spinal cord tumors were acquired ex vivo. Several peak intensity ratios were calculated for classification and then associated with the pathological immunohistochemical indexes. Our results revealed the spectral properties of three types of intramedullary tumors different from those of the other three types of extramedullary tumors. Furthermore, some peak intensity ratios revealed a high correlation with the immunohistochemical index of glial fibrillary acidic protein (GFAP). Thus, we believe that autofluorescence spectroscopy has the potential to provide real-time pathological information of spinal cord tumors and help surgeons validate tumor types and perform precise tumor resection.

Diffuse optical monitoring of peripheral tissues during uncontrolled internal hemorrhage in a porcine model.

Reliable, continuous and noninvasive blood flow and hemoglobin monitoring in trauma patients remains a critical, but generally unachieved goal. Two optical sensing methods - diffuse correlation spectroscopy (DCS) and diffuse reflectance spectroscopy (DRS) - are used to monitor and detect internal hemorrhage. Specifically, we investigate if cutaneous perfusion measurements acquired using DCS and DRS in peripheral (thighs and ear-lobe) tissues could detect severe hemorrhagic shock in a porcine model. Four animals underwent high-grade hepato-portal injury in a closed abdomen, to induce uncontrolled hemorrhage and were subsequently allowed to bleed for 10 minutes before fluid resuscitation. DRS and DCS measurements of cutaneous blood flow were acquired using fiber optical probes placed on the thigh and earlobe of the animals and were obtained repeatedly starting from 1 to 5 minutes pre-injury, up to several minutes post shock. Clear changes were observed in measured optical spectra across all animals at both sites. DCS-derived cutaneous blood flow decreased sharply during hemorrhage, while DRS-derived vascular saturation and hemoglobin paralleled cardiac output. All derived optical parameters had the steepest changes during the rapid initial hemorrhage unambiguously. This suggests that a combined DCS and DRS based device might provide an easy-to-use, non-invasive, internal-hemorrhage detection system that can be used across a wide array of clinical settings.

Erratum: Time-resolved fluorescence spectroscopy for clinical diagnosis of actinic cheilitis: erratum.

[This corrects the article on p. 4210 in vol. 7, PMID: 27867726.].

Optical property uncertainty estimates for spatial frequency domain imaging.

Spatial frequency domain imaging (SFDI) is a wide-field diffuse optical imaging modality that has attracted considerable interest in recent years. Typically, diffuse reflectance measurements of spatially modulated light are used to quantify the optical absorption and reduced scattering coefficients of tissue, and with these, chromophore concentrations are extracted. However, uncertainties in estimated absorption and reduced scattering coefficients are rarely reported, and we know of no method capable of providing these when look-up table (LUT) algorithms are used to recover the optical properties. We present a method to generate optical property uncertainty estimates from knowledge of diffuse reflectance measurement errors. By employing the Cramér-Rao bound, we can quickly and efficiently explore theoretical SFDI performance as a function of spatial frequencies and sample optical properties, allowing us to optimize spatial frequency selection for a given application. In practice, we can also obtain useful uncertainty estimates for optical properties recovered with a two-frequency LUT algorithm, as we demonstrate with tissue-simulating phantom and in vivo experiments. Finally, we illustrate how absorption coefficient uncertainties can be propagated forward to yield uncertainties for chromophore concentrations, which could significantly impact the interpretation of experimental results.

High throughput detection chain for time domain optical mammography.

A novel detection chain, based on 8 Silicon Photomultipliers (forming a wide-area custom-made detection probe) and on a time-to-digital converter, was developed to improve the signal level in multi-wavelength (635-1060 nm) time domain optical mammography. The performances of individual components and of the overall chain were assessed using established protocols (BIP and MEDPHOT). The photon detection efficiency was improved by up to 3 orders of magnitude, and the maximum count rate level was increased by a factor of 10 when compared to the previous system, based on photomultiplier tubes and conventional time-correlated single-photon counting boards. In the estimate of optical parameters, the novel detection chain provides performances comparable to the previous system, widely validated in clinics, but with higher signal level, higher robustness, and at a lower price per channel, thus targeting important requirements for clinical applications.

Detecting brain tumor in pathological slides using hyperspectral imaging.

Hyperspectral imaging (HSI) is an emerging technology for medical diagnosis. This research work presents a proof-of-concept on the use of HSI data to automatically detect human brain tumor tissue in pathological slides. The samples, consisting of hyperspectral cubes collected from 400 nm to 1000 nm, were acquired from ten different patients diagnosed with high-grade glioma. Based on the diagnosis provided by pathologists, a spectral library of normal and tumor tissues was created and processed using three different supervised classification algorithms. Results prove that HSI is a suitable technique to automatically detect high-grade tumors from pathological slides.

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.