Robust, high-density lesion mapping in the left atrium with near-infrared spectroscopy

Significance

Radiofrequency ablation (RFA) procedures for atrial fibrillation frequently fail to prevent recurrence, partially due to limitations in assessing extent of ablation. Optical spectroscopy shows promise in assessing RFA lesion formation but has not been validated in conditions resembling those in vivo.

Aim

Catheter-based near-infrared spectroscopy (NIRS) was applied to porcine hearts to demonstrate that spectrally derived optical indices remain accurate in blood and at oblique incidence angles.

Approach

Porcine left atria were ablated and mapped using a custom-fabricated NIRS catheter. Each atrium was mapped first in phosphate-buffered saline (PBS) then in porcine blood.

Results

NIRS measurements showed little angle dependence up to 60 deg. A trained random forest model predicted lesions with a sensitivity of 81.7%, a specificity of 86.1%, and a receiver operating characteristic curve area of 0.921. Predicted lesion maps achieved a mean structural similarity index of 0.749 and a mean normalized inner product of 0.867 when comparing maps obtained in PBS and blood.

Conclusions

Catheter-based NIRS can precisely detect RFA lesions on left atria submerged in blood. Optical parameters are reliable in blood and without perpendicular contact, confirming their ability to provide useful feedback during in vivo RFA procedures.

Validation of the Openwater wearable optical system: cerebral hemodynamic monitoring during a breath-hold maneuver

Significance

Bedside cerebral blood flow (CBF) monitoring has the potential to inform and improve care for acute neurologic diseases, but technical challenges limit the use of existing techniques in clinical practice.

Aim

Here, we validate the Openwater optical system, a novel wearable headset that uses laser speckle contrast to monitor microvascular hemodynamics.

Approach

We monitored 25 healthy adults with the Openwater system and concurrent transcranial Doppler (TCD) while performing a breath-hold maneuver to increase CBF. Relative blood flow (rBF) was derived from changes in speckle contrast, and relative blood volume (rBV) was derived from changes in speckle average intensity.

Results

A strong correlation was observed between beat-to-beat optical rBF and TCD-measured cerebral blood flow velocity (CBFv), R = 0.79 ; the slope of the linear fit indicates good agreement, 0.87 (95% CI: 0.83 - 0.92 ). Beat-to-beat rBV and CBFv were also strongly correlated, R = 0.72 , but as expected the two variables were not proportional; changes in rBV were smaller than CBFv changes, with linear fit slope of 0.18 (95% CI: 0.17 to 0.19). Further, strong agreement was found between rBF and CBFv waveform morphology and related metrics.

Conclusions

This first in vivo validation of the Openwater optical system highlights its potential as a cerebral hemodynamic monitor, but additional validation is needed in disease states.

MamoRef: an optical mammography device using whole-field CW diffuse reflectance. Presentation, validation and preliminary clinical results

Objective.MamoRef is an mammography device that uses near-infrared light, designed to provide clinically relevant information for the screening of diseases of the breast. Using low power continuous wave lasers and a high sensitivity CCD (Charge-coupled device) that captures a diffusely reflected image of the tissue, MamoRef results in a versatile diagnostic tool that aims to fulfill a complementary role in the diagnosis of breast cancer providing information about the relative hemoglobin concentrations as well as oxygen saturation.Approach.We present the design and development of an initial prototype of MamoRef. To ensure its effectiveness, we conducted validation tests on both the theoretical basis of the reconstruction algorithm and the hardware design. Furthermore, we initiated a clinical feasibility study involving patients diagnosed with breast disease, thus evaluating the practical application and potential benefits of MamoRef in a real-world setting.Main results.Our study demonstrates the effectiveness of the reconstruction algorithm in recovering relative concentration differences among various chromophores, as confirmed by Monte Carlo simulations. These simulations show that the recovered data correlates well with the ground truth, with SSIMs of 0.8 or more. Additionally, the phantom experiments validate the hardware implementation. The initial clinical findings exhibit highly promising outcomes regarding MamoRef's ability to differentiate between lesions.Significance.MamoRef aims to be an advancement in the field of breast pathology screening and diagnostics, providing complementary information to standard diagnostic techniques. One of its main advantages is the ability of determining oxy/deoxyhemoglobin concentrations and oxygen saturation; this constitutes valuable complementary information to standard diagnostic techniques. Besides, MamoRef is a portable and relatively inexpensive device, intended to be not only used in specific medical imaging facilities. Finally, its use does not require external compression of the breast. The findings of this study underscore the potential of MamoRef in fulfilling this crucial role.

Machine Learning-Assisted Short-Wave InfraRed (SWIR) Techniques for Biomedical Applications: Towards Personalized Medicine

Personalized medicine transforms healthcare by adapting interventions to individuals' unique genetic, molecular, and clinical profiles. To maximize diagnostic and/or therapeutic efficacy, personalized medicine requires advanced imaging devices and sensors for accurate assessment and monitoring of individual patient conditions or responses to therapeutics. In the field of biomedical optics, short-wave infrared (SWIR) techniques offer an array of capabilities that hold promise to significantly enhance diagnostics, imaging, and therapeutic interventions. SWIR techniques provide in vivo information, which was previously inaccessible, by making use of its capacity to penetrate biological tissues with reduced attenuation and enable researchers and clinicians to delve deeper into anatomical structures, physiological processes, and molecular interactions. Combining SWIR techniques with machine learning (ML), which is a powerful tool for analyzing information, holds the potential to provide unprecedented accuracy for disease detection, precision in treatment guidance, and correlations of complex biological features, opening the way for the data-driven personalized medicine field. Despite numerous biomedical demonstrations that utilize cutting-edge SWIR techniques, the clinical potential of this approach has remained significantly underexplored. This paper demonstrates how the synergy between SWIR imaging and ML is reshaping biomedical research and clinical applications. As the paper showcases the growing significance of SWIR imaging techniques that are empowered by ML, it calls for continued collaboration between researchers, engineers, and clinicians to boost the translation of this technology into clinics, ultimately bridging the gap between cutting-edge technology and its potential for personalized medicine.

Corrigendum: Demographic reporting and phenotypic exclusion in fNIRS

[This corrects the article DOI: 10.3389/fnins.2023.1086208.].

Restoration of metabolic functional metrics from label-free, two-photon human tissue images using multiscale deep-learning-based denoising algorithms

Significance

Label-free, two-photon excited fluorescence (TPEF) imaging captures morphological and functional metabolic tissue changes and enables enhanced understanding of numerous diseases. However, noise and other artifacts present in these images severely complicate the extraction of biologically useful information.

Aim

We aim to employ deep neural architectures in the synthesis of a multiscale denoising algorithm optimized for restoring metrics of metabolic activity from low-signal-to-noise ratio (SNR), TPEF images.

Approach

TPEF images of reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavoproteins (FAD) from freshly excised human cervical tissues are used to assess the impact of various denoising models, preprocessing methods, and data on metrics of image quality and the recovery of six metrics of metabolic function from the images relative to ground truth images.

Results

Optimized recovery of the redox ratio and mitochondrial organization is achieved using a novel algorithm based on deep denoising in the wavelet transform domain. This algorithm also leads to significant improvements in peak-SNR (PSNR) and structural similarity index measure (SSIM) for all images. Interestingly, other models yield even higher PSNR and SSIM improvements, but they are not optimal for recovery of metabolic function metrics.

Conclusions

Denoising algorithms can recover diagnostically useful information from low SNR label-free TPEF images and will be useful for the clinical translation of such imaging.

Spatial analysis of polarimetric images to enhance near-surface sampling sensitivity: feasibility in demineralized teeth and other tissue-like media

Significance

Early tooth demineralization may be detectable through spatial analysis of polarized light images as demonstrated in this study. This may also prove useful in the early detection of epithelial tumors that comprise the majority of the cancer burden worldwide.

Aim

The spatial properties of polarized light images have not been greatly exploited in biomedicine to improve sensitivity to superficial tissue regions; therefore, we investigate the optical sampling depth effects as a function of location in the backscattered polarimetric images.

Approach

Backscattered linear polarization intensity distributions exhibit four-lobed patterns arising through single-scattering, multiple-scattering, and geometrical effects. These photon pathway dynamics are investigated through experimental imaging of microsphere suspensions along with corroborative computational polarization-sensitive Monte Carlo modeling. The studied sampling depth effects of linear and circular polarization images (explored in a previous study) are then evaluated on normal and demineralized human teeth, which are known to differ in their surface and sub-surface structures.

Results

Backscattered linear polarization images exhibit enhanced sensitivity to near-surface properties of media (for example, surface roughness and turbidity) at specific locations within the four-lobed patterns. This yields improved differentiation of two tooth types when spatially selecting image regions in the direction perpendicular to the incident linear polarization vector. Circular polarimetric imaging also yields improved differentiation through spatial selection of regions close to the site of illumination. Improved sensitivity to superficial tissues is achieved through a combination of these linear and circular polarimetric imaging approaches.

Conclusions

Heightened sampling sensitivity to tissue microstructure in the surface/near-surface region of turbid tissue-like media and dental tissue is achieved through a judicious spatial selection of specific regions in the resultant co-linear and cross-circular backscattered polarimetric images.

Deep-learning visualization enhancement method for optical coherence tomography angiography in dermatology

Optical coherence tomography angiography (OCTA) in dermatology usually suffers from low image quality due to the highly scattering property of the skin, the complexity of cutaneous vasculature, and limited acquisition time. Deep-learning methods have achieved great success in many applications. However, the deep learning approach to improve dermatological OCTA images has not been investigated due to the requirement of high-performance OCTA systems and difficulty of obtaining high-quality images as ground truth. This study aims to generate proper datasets and develop a robust deep learning method to enhance the skin OCTA images. A swept-source skin OCTA system was employed to create low-quality and high-quality OCTA images with different scanning protocols. We propose a model named vascular visualization enhancement generative adversarial network and adopt an optimized data augmentation strategy and perceptual content loss function to achieve better image enhancement effect with small amount of training data. We demonstrate the superiority of the proposed method in skin OCTA image enhancement by quantitative and qualitative comparisons.

Three-dimensional angular scattering simulations inform analysis of scattering from single cells

Significance

Organelle sizes, which are indicative of cellular status, have implications for drug development and immunology research. At the single cell level, such information could be used to study the heterogeneity of cell response to drugs or pathogens.

Aim

Angularly resolved elastic light scattering is known to be sensitive to changes in organelle size distribution. We developed a Mie theory-based simulation of angular scattering from single cells to quantify the effects of noise on scattering and size estimates.

Approach

We simulated randomly sampled organelle sizes (drawn from a log normal distribution), interference between different organelles' scattering, and detector noise. We quantified each noise source's effect upon the estimated mean and standard deviation of organelle size distributions.

Results

The results demonstrate that signal-to-noise ratio in the angular scattering increased with the number of scatterers, cell area, and exposure time and decreased with the size distribution width. The error in estimating the mean of the size distributions remained below 5% for nearly all experimental parameters tested, but the widest size distribution tested (standard deviation of 600 nm) reached 20%.

Conclusions

The simulator revealed that sparse sampling of a broad size distribution can dominate the mismatch between actual and predicted size parameters. Alternative estimation strategies could reduce the discrepancy.

Demographic reporting and phenotypic exclusion in fNIRS

Functional near-infrared spectroscopy (fNIRS) promises to be a leading non-invasive neuroimaging method due to its portability and low cost. However, concerns are rising over its inclusivity of all skin tones and hair types (Parker and Ricard, 2022, Webb et al., 2022). Functional NIRS relies on direct contact of light-emitting optodes to the scalp, which can be blocked more by longer, darker, and especially curlier hair. Additionally, NIR light can be attenuated by melanin, which is accounted for in neither fNIRS hardware nor analysis methods. Recent work has shown that overlooking these considerations in other modalities like EEG leads to the disproportionate exclusion of individuals with these phenotypes-especially Black people-in both clinical and research literature (Choy, 2020; Bradford et al., 2022; Louis et al., 2023). In this article, we sought to determine if (Jöbsis, 1977) biomedical optics developers and researchers report fNIRS performance variability between skin tones and hair textures, (2a) fNIRS neuroscience practitioners report phenotypic and demographic details in their articles, and thus, (2b) is a similar pattern of participant exclusion found in EEG also present in the fNIRS literature. We present a literature review of top Biomedical Optics and Human Neuroscience journals, showing that demographic and phenotypic reporting is unpopular in both fNIRS development and neuroscience applications. We conclude with a list of recommendations to the fNIRS community including examples of Black researchers addressing these issues head-on, inclusive best practices for fNIRS researchers, and recommendations to funding and regulatory bodies to achieve an inclusive neuroscience enterprise in fNIRS and beyond.

Design and Validation of a Custom-Made Hyperspectral Microscope Imaging System for Biomedical Applications

Hyperspectral microscope imaging (HMI) is an emerging modality that integrates spatial information collected by standard laboratory microscopy and the spectral-based contrast obtained by hyperspectral imaging and may be instrumental in establishing novel quantitative diagnostic methodologies, particularly in histopathology. Further expansion of HMI capabilities hinges upon the modularity and versatility of systems and their proper standardization. In this report, we describe the design, calibration, characterization, and validation of the custom-made laboratory HMI system based on a Zeiss Axiotron fully motorized microscope and a custom-developed Czerny-Turner-type monochromator. For these important steps, we rely on a previously designed calibration protocol. Validation of the system demonstrates a performance comparable to classic spectrometry laboratory systems. We further demonstrate validation against a laboratory hyperspectral imaging system for macroscopic samples, enabling future comparison of spectral imaging results across length scales. An example of the utility of our custom-made HMI system on a standard hematoxylin and eosin-stained histology slide is also shown.

Dynamic cerebral autoregulation measured by diffuse correlation spectroscopy

Dynamic cerebral autoregulation (dCA) can be derived from spontaneous oscillations in arterial blood pressure (ABP) and cerebral blood flow (CBF). Transcranial Doppler (TCD) measures CBF-velocity and is commonly used to assess dCA. Diffuse correlation spectroscopy (DCS) is a promising optical technique for non-invasive CBF monitoring, so here we aimed to validate DCS as a tool for quantifying dCA. In 33 healthy adults and 17 acute ischemic stroke patients, resting-state hemodynamic were monitored simultaneously with high-speed (20 Hz) DCS and TCD. dCA parameters were calcaulated by a transfer function analysis using a Fourier decomposition of ABP and CBF (or CBF-velocity). Strong correlation was found between DCS and TCD measured gain (magnitude of regulation) in healthy volunteers (r = 0.73, p < 0.001) and stroke patients (r = 0.76, p = 0.003). DCS-gain retained strong test-retest reliability in both groups (ICC 0.87 and 0.82, respectively). DCS and TCD-derived phase (latency of regulation) did not significantly correlate in healthy volunteers (r = 0.12, p = 0.50) but moderately correlated in stroke patients (r = 0.65, p = 0.006). DCS-derived phase was reproducible in both groups (ICC 0.88 and 0.90, respectively). High-frequency DCS is a promising non-invasive bedside technique that can be leveraged to quantify dCA from resting-state data, but the discrepancy between TCD and DCS-derived phase requires further investigation.

Evaluation of the cumulative Cherenkov converted dose on TSET patients with multiple Cherenkov cameras

Cherenkov images can be used for the quality assurance of dose homogeneity in total skin electron therapy (TSET). For the dose mapping purpose, this study reconstructed the patient model from 3D scans using registration algorithms and computer animation techniques. The Cherenkov light emission of the patient's surface was extracted from multi-view Cherenkov images, converted into dose distribution, and projected onto the patient's 3D model, allowing for dose cumulation and evaluation. The projected result from multiple Cherenkov cameras provides additional information about Cherenkov emission on the sides of the patients, which improves the agreement between the Cherenkov converted dose and the OSLD measurements.

Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization

Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO₂), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO₂, lipid and water data were achieved particularly well within the wavelength ranges 350-590 nm and 600-1230 nm for the short-SDD probe, and 380-400 nm, 420-610 nm, and 650-950 nm for the long-SDD probe.

Growth Kinetics Monitoring of Gram-Negative Pathogenic Microbes Using Raman Spectroscopy

Optical density based measurements are routinely performed to monitor the growth of microbes. These measurements solely depend upon the number of cells and do not provide any information about the changes in the biochemical milieu or biological status. An objective information about these parameters is essential for evaluation of novel therapies and for maximizing the metabolite production. In the present study, we have applied Raman spectroscopy to monitor growth kinetics of three different pathogenic Gram-negative microbes Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii. Spectral measurements were performed under 532 nm excitation with 5 seconds of exposure time. Spectral features suggest temporal changes in the "peptide" and "nucleic acid" content of cells under different growth stages. Using principal component analysis (PCA), successful discrimination between growth phases was also achieved. Overall, the findings are supportive of the prospective adoption of Raman based approaches for monitoring microbial growth.

Design and Validation of a Custom-Made Laboratory Hyperspectral Imaging System for Biomedical Applications Using a Broadband LED Light Source

Hyperspectral imaging (HSI) is a promising optical modality that is already being used in numerous applications. Further expansion of the capabilities of HSI depends on the modularity and versatility of the systems, which would, inter alia, incorporate profilometry, fluorescence imaging, and Raman spectroscopy while following a rigorous calibration and verification protocols, thus offering new insights into the studied samples as well as verifiable, quantitative measurement results applicable to the development of quantitative metrics. Considering these objectives, we developed a custom-made laboratory HSI system geared toward biomedical applications. In this report, we describe the design, along with calibration, characterization, and verification protocols needed to establish such systems, with the overall goal of standardization. As an additional novelty, our HSI system uses a custom-built broadband LED-based light source for reflectance imaging, which is particularly important for biomedical applications due to the elimination of sample heating. Three examples illustrating the utility and advantages of the integrated system in biomedical applications are shown. Our attempt presents both the development of a custom-based laboratory HSI system with novel LED light source as well as a framework which may improve technological standards in HSI system design.

Two-step verification method for Monte Carlo codes in biomedical optics applications

SIGNIFICANCE

Code verification is an unavoidable step prior to using a Monte Carlo (MC) code. Indeed, in biomedical optics, a widespread verification procedure for MC codes is still missing. Analytical benchmarks that can be easily used for the verification of different MC routines offer an important resource.

AIM

We aim to provide a two-step verification procedure for MC codes enabling the two main tasks of an MC simulator: (1) the generation of photons' trajectories and (2) the intersections of trajectories with boundaries separating the regions with different optical properties. The proposed method is purely based on elementary analytical benchmarks, therefore, the correctness of an MC code can be assessed with a one-sample t-test.

APPROACH

The two-step verification is based on the following two analytical benchmarks: (1) the exact analytical formulas for the statistical moments of the spatial coordinates where the scattering events occur in an infinite medium and (2) the exact invariant solutions of the radiative transfer equation for radiance, fluence rate, and mean path length in media subjected to a Lambertian illumination.

RESULTS

We carried out a wide set of comparisons between MC results and the two analytical benchmarks for a wide range of optical properties (from non-scattering to highly scattering media, with different types of scattering functions) in an infinite non-absorbing medium (step 1) and in a non-absorbing slab (step 2). The deviations between MC results and exact analytical values are usually within two standard errors (i.e., t-tests not rejected at a 5% level of significance). The comparisons show that the accuracy of the verification increases with the number of simulated trajectories so that, in principle, an arbitrary accuracy can be obtained.

CONCLUSIONS

Given the simplicity of the verification method proposed, we envision that it can be widely used in the field of biomedical optics.

Deep Learning in Biomedical Optics

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Cherenkov imaging for Total Skin Electron Therapy - an evaluation of dose uniformity

Total Skin Electron Therapy (TSET) utilizes high-energy electrons to treat cancers on the entire body surface. The otherwise invisible radiation beam can be observed via the optical Cherenkov photons emitted from interaction between the high-energy electron beam and tissue. Cherenkov emission can be used to evaluate the dose uniformity on the surface of the patient in real-time using a time-gated intensified camera system. Each patient was monitored during TSET by in-vivo detectors (IVD) as well as Scintillators. Patients undergoing TSET in various conditions (whole body and half body) were imaged and analyzed. A rigorous methodology for converting Cherenkov intensity to surface dose as products of correction factors, including camera vignette correction factor, incident radiation correction factor, and tissue optical properties correction factor. A comprehensive study has been carried out by inspecting various positions on the patients such as vertex, chest, perineum, shins, and foot relative to the umbilicus point (the prescription point).

Development of a polarization imaging method to detect paraffin-embedded pathology tissues before applying other techniques

The present article describes the development of a technique, applied to paraffin-embedded tissues, which uses three different wavelengths of monochromatic light (λ1 = 445 nm, λ2 = 540 nm and λ3 = 660 nm) for the measures of the degree of polarization, degree of linear polarization, degree of circular polarization and birefringence, all obtained from measurements of Stokes parameters by using polarized light. The goal of this study was to detect changes in developing embryonic mouse eye when pregnant mice fed diets without folic acid for variable periods compared with a healthy control group. We present a biomedical diagnostic technique based on polarized light detection applied to paraffin-embedded tissues to visualize the structural damage to aid us in the diagnosis before applying other techniques. Through this method, we can visualize and identify which parts of the tissue were altered with respect to the control group.

Visualization of two-dimensional transverse blood flow direction using optical coherence tomography angiography

SIGNIFICANCE

Evaluation of vessel patency and blood flow direction is important in various medical situations, including diagnosis and monitoring of ischemic diseases, and image-guided vascular surgeries. While optical coherence tomography angiography (OCTA) is the most widely used functional extension of optical coherence tomography that visualizes three-dimensional vasculature, inability to provide information of blood flow direction is one of its limitations.

AIM

We demonstrate two-dimensional (2D) transverse blood flow direction imaging in en face OCTA.

APPROACH

A series of triangular beam scans for the fast axis was implemented in the horizontal direction for the first volume scan and in the vertical direction for the following volume scan, and the inter A-line OCTA was performed for the blood flow direction imaging while the stepwise pattern was used for each slow axis scan. The decorrelation differences between the forward and the backward inter A-line OCTA were calculated for the horizontal and the vertical fast axis scans, and the ratio of the horizontal and the vertical decorrelation differences was utilized to show the 2D transverse flow direction information.

RESULTS

OCTA flow direction imaging was verified using flow phantoms with various flow orientations and speeds, and we identified the flow speed range relative to the scan speed for reliable flow direction measurement. We demonstrated the visualization of 2D transverse blood flow orientations in mouse brain vascular networks in vivo.

CONCLUSIONS

The proposed OCTA imaging technique that provides information of 2D transverse flow direction can be utilized in various clinical applications and preclinical studies.

Interferometric diffuse correlation spectroscopy improves measurements at long source-detector separation and low photon count rate

SIGNIFICANCE

The use of diffuse correlation spectroscopy (DCS) has shown efficacy in research studies as a technique capable of noninvasively monitoring blood flow in tissue with applications in neuromonitoring, exercise science, and breast cancer management. The ability of DCS to resolve blood flow in these tissues is related to the optical sensitivity and signal-to-noise ratio (SNR) of the measurements, which in some cases, particularly adult cerebral blood flow measurements, is inadequate in a significant portion of the population. Improvements to DCS sensitivity and SNR could allow for greater clinical translation of this technique.

AIM

Interferometric diffuse correlation spectroscopy (iDCS) was characterized and compared to traditional homodyne DCS to determine possible benefits of utilizing heterodyne detection.

APPROACH

An iDCS system was constructed by modifying a homodyne DCS system with fused fiber couplers to create a Mach-Zehnder interferometer. Comparisons between homodyne and heterodyne detection were performed using an intralipid phantom characterized at two extended source-detector separations (2.4, 3.6 cm), different photon count rates, and a range of reference arm power levels. Characterization of the iDCS signal mixing was compared to theory. Precision of the estimation of the diffusion coefficient and SNR of the autocorrelation curve were compared between different measurement conditions that mimicked what would be seen in vivo.

RESULTS

The mixture of signals present in the heterodyne autocorrelation function was found to agree with the derived theory and resulted in accurate measurement of the diffusion coefficient of the phantom. Improvement of the SNR of the autocorrelation curve up to ∼2  ×   and up to 80% reduction in the variability of the diffusion coefficient fit were observed for all measurement cases as a function of increased reference arm power.

CONCLUSIONS

iDCS has the potential to improve characterization of blood flow in tissue at extended source-detector separations, enhancing depth sensitivity and SNR.

Photoacoustic topography through an ergodic relay for functional imaging and biometric application in vivo

SIGNIFICANCE

Photoacoustic (PA) tomography has demonstrated versatile biomedical applications. However, an array-based PA computed tomography (PACT) system is complex and expensive, whereas a single-element detector-based scanning PA system is too slow to detect some fast biological dynamics in vivo. New PA imaging methods are sought after.

AIM

To overcome these limitations, we developed photoacoustic topography through an ergodic relay (PATER), a novel high-speed imaging system with a single-element detector.

APPROACH

PATER images widefield PA signals encoded by the acoustic ergodic relay with a single-laser shot.

RESULTS

We applied PATER in vivo to monitor changes in oxygen saturation in a mouse brain and also to demonstrate high-speed matching of vascular patterns for biometric authentication.

CONCLUSIONS

PATER has achieved a high-speed temporal resolution over a large field of view. Our results suggest that PATER is a promising and economical alternative to PACT for fast imaging.

Photodynamic therapy dosimetry using multiexcitation multiemission wavelength: toward real-time prediction of treatment outcome

Evaluating the optical properties of biological tissues is needed to achieve accurate dosimetry during photodynamic therapy (PDT). Currently, accurate assessment of the photosensitizer (PS) concentration by fluorescence measurements during PDT is typically hindered by the lack of information about tissue optical properties. In the present work, a hand-held fiber-optic probe instrument monitoring fluorescence and reflectance is used for assessing blood volume, reduced scattering coefficient, and PS concentration facilitating accurate dosimetry for PDT. System validation was carried out on tissue phantoms using nonlinear least squares support machine regression analysis. It showed a high correlation coefficient (>0.99) in the prediction of the PS concentration upon a large variety of phantom optical properties. In vivo measurements were conducted in a PDT chlorine e6 dose escalating trial involving 36 male Swiss mice with Ehrlich solid tumors in which fluences of 5, 15, and 40  J cm  -  2 were delivered at two fluence rates (100 and 40  mW cm  -  2). Remarkably, quantitative measurement of fluorophore concentration was achieved in the in vivo experiment. Diffuse reflectance spectroscopy (DRS) system was also used to independently measure the physiological properties of the target tissues for result comparisons. Then, blood volume and scattering coefficient measured by the fiber-optic probe system were compared with the corresponding result measured by DRS and showed agreement. Additionally, tumor hemoglobin oxygen saturation was measured using the DRS system. Overall, the system is capable of assessing the implicit photodynamic dose to predict the PDT outcome.

Investigation of the quantification of hemoglobin and cytochrome-c-oxidase in the exposed cortex with near-infrared hyperspectral imaging: a simulation study

SIGNIFICANCE

We present a Monte Carlo (MC) computational framework that simulates near-infrared (NIR) hyperspectral imaging (HSI) aimed at assisting quantification of the in vivo hemodynamic and metabolic states of the exposed cerebral cortex in small animal experiments. This can be done by targeting the NIR spectral signatures of oxygenated (HbO2) and deoxygenated (HHb) hemoglobin for hemodynamics as well as the oxidative state of cytochrome-c-oxidase (oxCCO) for measuring tissue metabolism.

AIM

The aim of this work is to investigate the performances of HSI for this specific application as well as to assess key factors for the future design and operation of a benchtop system.

APPROACH

The MC framework, based on Mesh-based Monte Carlo (MMC), reproduces a section of the exposed cortex of a mouse from an in vivo image and replicates hyperspectral illumination and detection at multiple NIR wavelengths (up to 121).

RESULTS

The results demonstrate: (1) the fitness of the MC framework to correctly simulate hyperspectral data acquisition; (2) the capability of HSI to reconstruct spatial changes in the concentrations of HbO2, HHb, and oxCCO during a simulated hypoxic condition; (3) that eight optimally selected wavelengths between 780 and 900 nm provide minimal differences in the accuracy of the hyperspectral results, compared to the "gold standard" of 121 wavelengths; and (4) the possibility to mitigate partial pathlength effects in the reconstructed data and to enhance quantification of the hemodynamic and metabolic responses.

CONCLUSIONS

The MC framework is proved to be a flexible and useful tool for simulating HSI also for different applications and targets.

Selective retina therapy monitoring by speckle variance optical coherence tomography for dosimetry control

SIGNIFICANCE

Selective retina therapy (SRT) selectively targets the retinal pigment epithelium (RPE) and reduces negative side effects by avoiding thermal damages of the adjacent photoreceptors, the neural retina, and the choroid. However, the selection of proper laser energy for the SRT is challenging because of ophthalmoscopically invisible lesions in the RPE and different melanin concentrations among patients or even regions within an eye.

AIM

We propose and demonstrate SRT monitoring based on speckle variance optical coherence tomography (svOCT) for dosimetry control.

APPROACH

M-scans, time-resolved sequence of A-scans, of ex vivo bovine retina irradiated by 1.7-μs duration laser pulses were obtained by a swept-source OCT. SvOCT images were calculated as interframe intensity variance of the sequence. Spatial and temporal temperature distributions in the retina were numerically calculated in a 2-D retinal model using COMSOL Multiphysics. Microscopic images of treated spots were obtained before and after removing the upper neural retinal layer to assess the damage in both RPE and neural layers.

RESULTS

SvOCT images show abrupt speckle variance changes when the retina is irradiated by laser pulses. The svOCT intensities averaged in RPE and photoreceptor layers along the axial direction show sharp peaks corresponding to each laser pulse, and the peak values were proportional to the laser pulse energy. The calculated temperatures in the neural retina layer and RPE were linearly fitted to the svOCT peak values, and the temperature of each lesion was estimated based on the fitting. The estimated temperatures matched well with previously reported results.

CONCLUSION

We found a reliable correlation between the svOCT peak values and the degree of retinal lesion formation, which can be used for selecting proper laser energy during SRT.

Cherenkov imaging for total skin electron therapy (TSET)

BACKGROUND

Total skin electron therapy (TSET) utilizes high-energy electrons to treat malignancies on the entire body surface. The otherwise invisible radiation beam can be observed via the optical Cherenkov photons emitted from interactions between the high-energy electron beam and tissue.

METHODS AND MATERIALS

With a time-gated intensified camera system, the Cherenkov emission can be used to evaluate the dose uniformity on the surface of the patient in real time. Fifteen patients undergoing TSET in various conditions (whole body and half body) were imaged and analyzed. Each patient was monitored during TSET via in vivo detectors (IVD) in nine locations. For accurate Cherenkov imaging, a comparison between IVD and Cherenkov profiles was conducted using a polyvinyl chloride board to establish the perspective corrections.

RESULTS AND DISCUSSION

With proper corrections developed in this study including the perspective and inverse square corrections, the Cherenkov imaging provided two-dimensional maps proportional to dose and projected on patient skin. The results of ratio between chest and umbilicus points were in good agreement with in vivo point dose measurements, with a standard deviation of 2.4% compared to OSLD measurements.

CONCLUSIONS

Cherenkov imaging is a viable tool for validating patient-specific dose distributions during TSET.

In-vivo full-field measurement of microcirculatory blood flow velocity based on intelligent object identification

Microcirculation plays a crucial role in delivering oxygen and nutrients to living tissues and in removing metabolic wastes from the human body. Monitoring the velocity of blood flow in microcirculation is essential for assessing various diseases, such as diabetes, cancer, and critical illnesses. Because of the complex morphological pattern of the capillaries, both In-vivo capillary identification and blood flow velocity measurement by conventional optical capillaroscopy are challenging. Thus, we focused on developing an In-vivo optical microscope for capillary imaging, and we propose an In-vivo full-field flow velocity measurement method based on intelligent object identification. The proposed method realizes full-field blood flow velocity measurements in microcirculation by employing a deep neural network to automatically identify and distinguish capillaries from images. In addition, a spatiotemporal diagram analysis is used for flow velocity calculation. In-vivo experiments were conducted, and the images and videos of capillaries were collected for analysis. We demonstrated that the proposed method is highly accurate in performing full-field blood flow velocity measurements in microcirculation. Further, because this method is simple and inexpensive, it can be effectively employed in clinics.

An Evaluation Framework for Spectral Filter Array Cameras to Optimize Skin Diagnosis

Comparing and selecting an adequate spectral filter array (SFA) camera is application-specific and usually requires extensive prior measurements. An evaluation framework for SFA cameras is proposed and three cameras are tested in the context of skin analysis. The proposed framework does not require application-specific measurements and spectral sensitivities together with the number of bands are the main focus. An optical model of skin is used to generate a specialized training set to improve spectral reconstruction. The quantitative comparison of the cameras is based on reconstruction of measured skin spectra, colorimetric accuracy, and oxygenation level estimation differences. Specific spectral sensitivity shapes influence the results directly and a 9-channel camera performed best regarding the spectral reconstruction metrics. Sensitivities at key wavelengths influence the performance of oxygenation level estimation the strongest. The proposed framework allows to compare spectral filter array cameras and can guide their application-specific development.

Photoacoustic imaging of breast cancer: a mini review of system design and image features

Breast cancer is one of the leading causes for cancer related deaths in women, and early detection is extremely important to improve survival rates. Currently, x-ray mammogram is the only modality for mass screening of asymptomatic women. However, it has decreased sensitivity in radiographically dense breasts, which is also associated with a higher risk for breast cancer. Photoacoustic (PA) imaging is an emerging modality that enables deep tissue imaging of optical contrast at ultrasonically defined spatial resolution, which is much higher than that can be achieved in purely optical imaging modalities. Because of high optical absorption from hemoglobin molecules, PA imaging can map out hemo distribution and dynamics in breast tissue and identify malignant lesions based on tumor associated angiogenesis and hypoxia. We review various PA breast imaging systems proposed over the past few years and summarize the PA features of breast cancer identified in these systems.

Propagating-path uniformly scanned light sheet excitation microscopy for isotropic volumetric imaging of large specimens

We demonstrate a propagating-path uniformly scanned light sheet excitation (PULSE) microscopy based on the oscillation of voice coil motor that can rapidly drive a thin light sheet along its propagation direction. By synchronizing the rolling shutter of a camera with the motion of laser sheet, we can obtain a uniform plane-illuminated image far beyond the confocal range of Gaussian beam. A stable 1.7-μm optical sectioning under a 3.3  mm  ×  3.3  mm wide field of view (FOV) has been achieved for up to 20 Hz volumetric imaging of large biological specimens. PULSE method transforms the extent of plane illumination from one intrinsically limited by the short confocal range (μm scale) to one defined by the motor oscillation range (mm scale). Compared to the conventional Gaussian light sheet imaging, our method greatly mitigates the compromise of axial resolution and successfully extends the FOV over 100 times. We demonstrate the applications of PULSE method by rapidly imaging cleared mouse spinal cord and live zebrafish larva at isotropic subcellular resolution.

Improvements to an optical scintillator imaging-based tissue dosimetry system

Previous work has shown that capturing optical emission from plastic discs attached directly to the skin can be a viable means to accurately measure surface dose during total skin electron therapy. This method can provide accurate dosimetric information rapidly and remotely without the need for postprocessing. The objective of this study was to: (1) improve the robustness and usability of the scintillators and (2) enhance sensitivity of the optical imaging system to improve scintillator emission detection as related to tissue surface dose. Baseline measurements of scintillator optical output were obtained by attaching the plastic discs to a flat tissue phantom and simultaneously irradiating and imaging them. Impact on underlying surface dose was evaluated by placing the discs on-top of the active element of an ionization chamber. A protective coating and adhesive backing were added to allow easier logistical use, and they were also subjected to disinfection procedures, while verifying that these changes did not affect the linearity of response with dose. The camera was modified such that the peak of detector quantum efficiency better overlapped with the emission spectra of the scintillating discs. Patient imaging was carried out and surface dose measurements were captured by the updated camera and compared to those produced by optically stimulated luminescence detectors (OSLD). The updated camera was able to measure surface dose with < 3 %   difference compared to OSLD–Cherenkov emission from the patient was suppressed and scintillation detection was enhanced by 25 × and 7 ×  , respectively. Improved scintillators increase underlying surface dose on average by 5.2  ±  0.1 %   and light output decreased by 2.6  ±  0.3 %  . Disinfection had < 0.02 %   change on scintillator light output. The enhanced sensitivity of the imaging system to scintillator optical emission spectrum can now enable a reduction in physical dimensions of the dosimeters without loss in ability to detect light output.

En-face optical coherence tomography/fluorescence endomicroscopy for minimally invasive imaging using a robotic scanner

We report a compact rigid instrument capable of delivering en-face optical coherence tomography (OCT) images alongside (epi)-fluorescence endomicroscopy (FEM) images by means of a robotic scanning device. Two working imaging channels are included: one for a one-dimensional scanning, forward-viewing OCT probe and another for a fiber bundle used for the FEM system. The robotic scanning system provides the second axis of scanning for the OCT channel while allowing the field of view (FoV) of the FEM channel to be increased by mosaicking. The OCT channel has resolutions of 25  /  60  μm (axial/lateral) and can provide en-face images with an FoV of 1.6  ×  2.7  mm2. The FEM channel has a lateral resolution of better than 8  μm and can generate an FoV of 0.53  ×  3.25  mm2 through mosaicking. The reproducibility of the scanning was determined using phantoms to be better than the lateral resolution of the OCT channel. Combined OCT and FEM imaging were validated with ex-vivo ovine and porcine tissues, with the instrument mounted on an arm to ensure constant contact of the probe with the tissue. The OCT imaging system alone was validated for in-vivo human dermal imaging with the handheld instrument. In both cases, the instrument was capable of resolving fine features such as the sweat glands in human dermal tissue and the alveoli in porcine lung tissue.

Tissue oxygen saturation predicts response to breast cancer neoadjuvant chemotherapy within 10 days of treatment

Ideally, neoadjuvant chemotherapy (NAC) assessment should predict pathologic complete response (pCR), a surrogate clinical endpoint for 5-year survival, as early as possible during typical 3- to 6-month breast cancer treatments. We introduce and demonstrate an approach for predicting pCR within 10 days of initiating NAC. The method uses a bedside diffuse optical spectroscopic imaging (DOSI) technology and logistic regression modeling. Tumor and normal tissue physiological properties were measured longitudinally throughout the course of NAC in 33 patients enrolled in the American College of Radiology Imaging Network multicenter breast cancer DOSI trial (ACRIN-6691). An image analysis scheme, employing z-score normalization to healthy tissue, produced models with robust predictions. Notably, logistic regression based on z-score normalization using only tissue oxygen saturation (StO2) measured within 10 days of the initial therapy dose was found to be a significant predictor of pCR (AUC  =  0.92; 95% CI: 0.82 to 1). This observation suggests that patients who show rapid convergence of tumor tissue StO2 to surrounding tissue StO2 are more likely to achieve pCR. This early predictor of pCR occurs prior to reductions in tumor size and could enable dynamic feedback for optimization of chemotherapy strategies in breast cancer.

High-speed Raman-encoded molecular imaging of freshly excised tissue surfaces with topically applied SERRS nanoparticles

Surface-enhanced Raman scattering (SERS) nanoparticles (NPs) are increasingly being engineered for a variety of disease-detection and treatment applications. For example, we have previously developed a fiber-optic Raman-encoded molecular imaging (REMI) system for spectral imaging of biomarker-targeted SERS NPs topically applied on tissue surfaces to identify residual tumors at surgical margins. Although accurate tumor detection was achieved, the commercial SERS NPs used in our previous studies lacked the signal strength to enable high-speed imaging with high pixel counts (large fields of view and/or high spatial resolution), which limits their use for certain time-constrained clinical applications. As a solution, we explored the use of surface-enhanced resonant Raman scattering (SERRS) NPs to enhance imaging speeds. The SERRS NPs were synthesized de novo, and then conjugated to HER2 antibodies to achieve high binding affinity, as validated by flow cytometry. Under identical tissue-staining and imaging conditions, the targeted SERRS NPs enabled reliable identification of HER2-overexpressed tumor xenografts with 50-fold-enhanced imaging speed compared with our standard targeted SERS NPs. This enables our REMI system to image tissue surfaces at a rate of 150  cm2 per minute at a spatial resolution of 0.5 mm.

Hyperspectral imaging solutions for brain tissue metabolic and hemodynamic monitoring: past, current and future developments

Hyperspectral imaging (HSI) technologies have been used extensively in medical research, targeting various biological phenomena and multiple tissue types. Their high spectral resolution over a wide range of wavelengths enables acquisition of spatial information corresponding to different light-interacting biological compounds. This review focuses on the application of HSI to monitor brain tissue metabolism and hemodynamics in life sciences. Different approaches involving HSI have been investigated to assess and quantify cerebral activity, mainly focusing on: (1) mapping tissue oxygen delivery through measurement of changes in oxygenated (HbO2) and deoxygenated (HHb) hemoglobin; and (2) the assessment of the cerebral metabolic rate of oxygen (CMRO2) to estimate oxygen consumption by brain tissue. Finally, we introduce future perspectives of HSI of brain metabolism, including its potential use for imaging optical signals from molecules directly involved in cellular energy production. HSI solutions can provide remarkable insight in understanding cerebral tissue metabolism and oxygenation, aiding investigation on brain tissue physiological processes.

Simultaneous in vivo confocal reflectance and two-photon retinal ganglion cell imaging based on a hollow core fiber platform

We have developed a compact hollow core fiber (HCF)-based imaging platform capable of simultaneous in vivo confocal reflectance and two-photon imaging through the mouse pupil. We demonstrate the performance of this platform by imaging retinal ganglion cells (RGCs) in which the fluorophores YFP and GCaMP3 are expressed in Thy1-YFP-16 and Thy1-GCaMP3 transgenic mice, respectively. Confocal reflectance images of the mouse retina served as a reference for the simultaneous acquisition of the two-photon signals that clearly showed RGCs with single-cell resolution. The use of an HCF platform makes the system compact with future application in the longitudinal investigation into the structure and function of healthy and diseased RGCs.

Pulsed terahertz imaging of breast cancer in freshly excised murine tumors

This paper investigates terahertz (THz) imaging and classification of freshly excised murine xenograft breast cancer tumors. These tumors are grown via injection of E0771 breast adenocarcinoma cells into the flank of mice maintained on high-fat diet. Within 1 h of excision, the tumor and adjacent tissues are imaged using a pulsed THz system in the reflection mode. The THz images are classified using a statistical Bayesian mixture model with unsupervised and supervised approaches. Correlation with digitized pathology images is conducted using classification images assigned by a modal class decision rule. The corresponding receiver operating characteristic curves are obtained based on the classification results. A total of 13 tumor samples obtained from 9 tumors are investigated. The results show good correlation of THz images with pathology results in all samples of cancer and fat tissues. For tumor samples of cancer, fat, and muscle tissues, THz images show reasonable correlation with pathology where the primary challenge lies in the overlapping dielectric properties of cancer and muscle tissues. The use of a supervised regression approach shows improvement in the classification images although not consistently in all tissue regions. Advancing THz imaging of breast tumors from mice and the development of accurate statistical models will ultimately progress the technique for the assessment of human breast tumor margins.

Wide field of view common-path lateral-shearing digital holographic interference microscope

Quantitative three-dimensional (3-D) imaging of living cells provides important information about the cell morphology and its time variation. Off-axis, digital holographic interference microscopy is an ideal tool for 3-D imaging, parameter extraction, and classification of living cells. Two-beam digital holographic microscopes, which are usually employed, provide high-quality 3-D images of micro-objects, albeit with lower temporal stability. Common-path digital holographic geometries, in which the reference beam is derived from the object beam, provide higher temporal stability along with high-quality 3-D images. Self-referencing geometry is the simplest of the common-path techniques, in which a portion of the object beam itself acts as the reference, leading to compact setups using fewer optical elements. However, it has reduced field of view, and the reference may contain object information. Here, we describe the development of a common-path digital holographic microscope, employing a shearing plate and converting one of the beams into a separate reference by employing a pin-hole. The setup is as compact as self-referencing geometry, while providing field of view as wide as that of a two-beam microscope. The microscope is tested by imaging and quantifying the morphology and dynamics of human erythrocytes.

Adolf Friedrich Fercher: a pioneer of biomedical optics

Adolf Friedrich Fercher, an outstanding pioneer of biomedical optics, passed away earlier this year. He was a brilliant and visionary researcher who pioneered various fields of biomedical optics, such as laser speckle flowgraphy, tissue interferometry, and optical coherence tomography (OCT). On the occasion of the 25th anniversary of OCT, this paper reviews and commemorates Fercher's pioneering work.

Combined high contrast and wide field of view in the scanning laser ophthalmoscope through dual detection of light paths

We demonstrate a multimode detection system in a scanning laser ophthalmoscope (SLO) that enables simultaneous operation in confocal, indirect, and direct modes to permit an agile trade between image contrast and optical sensitivity across the retinal field of view to optimize the overall imaging performance, enabling increased contrast in very wide-field operation. We demonstrate the method on a wide-field SLO employing a hybrid pinhole at its image plane, to yield a twofold increase in vasculature contrast in the central retina compared to its conventional direct mode while retaining high-quality imaging across a wide field of the retina, of up to 200 deg and 20  μm on-axis resolution.

MCMLpar and MCSLinv: A Parallel Version of MCML and an Inverse Monte Carlo Algorithm to Calculate Optical Scattering Parameters

The MCML program for Monte Carlo modeling of light transport in multi-layered tissues has been widely used in the past 20 years or so. Here, we have re-implemented MCML for solving the inverse problem. Our formulation features optimizing the profile log likelihood which takes into account uncertainties due to both experimental and Monte Carlo sampling. We limit the search space for the optimum parameters with relatively few Monte Carlo trials and then iteratively double the number of Monte Carlo trials until the search space stabilizes. At this point, the log likelihood can be fit with a quadratic function to find the optimum. The time-to-solution is only a few minutes in typical cases because we use importance sampling to determine the log likelihood on a grid of parameters at each iteration. Also, our implementation uses OpenMP and SPRNG to generate Monte Carlo trials in parallel.

Vertical-cavity surface-emitting laser sources for gigahertz-bandwidth, multiwavelength frequency-domain photon migration

Frequency-domain photon migration (FDPM) uses modulated laser light to measure the bulk optical properties of turbid media and is increasingly applied for noninvasive functional medical imaging in the near-infrared. Although semiconductor edge-emitting laser diodes have been traditionally used as miniature light sources for this application, we show that vertical-cavity surface-emitting lasers (VCSELs) exhibit output power and modulation performance characteristics suitable for FDPM measurements of tissue optical properties at modulation frequencies exceeding 1 GHz. We also show that an array of multiple VCSEL devices can be coherently modulated at frequencies suitable for FDPM and can improve optical power. In addition, their small size and simple packaging make them an attractive choice as components in wearable sensors and clinical FDPM-based optical spectroscopy systems. We demonstrate the benefits of VCSEL technology by fabricating and testing a unique, compact VCSEL-based optical probe with an integrated avalanche photodiode. We demonstrate sensitivity of the VCSEL-based probe to subcutaneous tissue hemodynamics that was induced during an arterial cuff occlusion of the upper arm in a human subject.

Approximate P3 solution for the semi-infinite medium: steady state and time domain

The steady-state solution of the Green's function obtained by the P3 equation in a semi-infinite medium is presented, the proposed solution is a diffusion-based model. Two time-domain solutions are established: one is the solution under extrapolation boundary condition, which we call the optical parameter method, and the other corresponds to the diffusion equation, which we call the double-diffusion coefficient method. The spatial-resolved reflectance and the time-resolved reflectance are calculated. The Monte Carlo simulation is used to verify the P3 equation. The results show that the P3 steady-state equation and the two time-domain equations are in good agreement with the Monte Carlo simulation. In the steady state, when the distance between the detector and the light source is less than several free paths, the P3 equation is more accurate than the diffusion equation. In other cases, the P3 model and the diffusion model have similar results. However, when the absorption coefficient is large, P3 is more accurate. In the time domain, the optical parameter method is more accurate, and the double-diffusion coefficient method is more consistent with the diffusion equation.

Monte Carlo simulations support non-Cerenkov radioluminescence production in tissue

There is experimental evidence for the production of non-Cerenkov radioluminescence in a variety of materials, including tissue. We constructed a Geant4 Monte Carlo simulation of the radiation from P32 and Tc99m interacting in chicken breast and used experimental imaging data to model a scintillation-like emission. The same radioluminescence spectrum is visible from both isotopes and cannot otherwise be explained through fluorescence or filter miscalibration. We conclude that chicken breast has a near-infrared scintillation-like response with a light yield three orders of magnitude smaller than BGO.

Miniaturized pulsed laser source for time-domain diffuse optics routes to wearable devices

We validate a miniaturized pulsed laser source for use in time-domain (TD) diffuse optics, following rigorous and shared protocols for performance assessment of this class of devices. This compact source (12×6  mm2) has been previously developed for range finding applications and is able to provide short, high energy (∼100  ps, ∼0.5  nJ) optical pulses at up to 1 MHz repetition rate. Here, we start with a basic level laser characterization with an analysis of suitability of this laser for the diffuse optics application. Then, we present a TD optical system using this source and its performances in both recovering optical properties of tissue-mimicking homogeneous phantoms and in detecting localized absorption perturbations. Finally, as a proof of concept of in vivo application, we demonstrate that the system is able to detect hemodynamic changes occurring in the arm of healthy volunteers during a venous occlusion. Squeezing the laser source in a small footprint removes a key technological bottleneck that has hampered so far the realization of a miniaturized TD diffuse optics system, able to compete with already assessed continuous-wave devices in terms of size and cost, but with wider performance potentialities, as demonstrated by research over the last two decades.

Dual-mode endomicroscopy for detection of epithelial dysplasia in the mouth: a descriptive pilot study

Dual-mode endomicroscopy is a diagnostic tool for early cancer detection. It combines the high-resolution nuclear tissue contrast of fluorescence endomicroscopy with quantified depth-dependent epithelial backscattering as obtained by diffuse optical microscopy. In an in vivo pilot imaging study of 27 oral lesions from 21 patients, we demonstrate the complementary diagnostic value of both modalities and show correlations between grade of epithelial dysplasia and relative depth-dependent shifts in light backscattering. When combined, the two modalities provide diagnostic sensitivity to both moderate and severe epithelial dysplasia in vivo.

Simultaneous en-face imaging of multiple layers with multiple reference optical coherence tomography

A technique based on multiple reference optical coherence tomography (MR-OCT) is proposed for simultaneous imaging at multiple depths. The technique has been validated by imaging a reference sample and a fingerprint in-vivo. The principle of scanning multiple selected layers is shown by imaging a partial fingerprint with 200×200×200 voxels of 3×3×0.5  mm size and obtaining an arbitrary amount of layers merely by digital processing. The spacing among the layers can be adjusted arbitrarily, and the SNR roll-off is shown for three different spacings. At a mirror scan frequency of 1 kHz and an A-line rate of 2 kHz, the acquisition time was 20 s for one volume. The results show the feasibility of the application of layer scanning MR-OCT that uses a partial mirror in the reference arm of the Michelson interferometer. The reduced scan range required for layer scanning allows even higher scan rates that are limited only by the voice coil design and the mass-spring system, e.g., mirror mass, spring constant, and damping.

[Non-contacting photoacoustic tomography in biological samples]

In photoacoustic imaging the ultrasonic signals are usually detected by contacting transducers. For some applications, contact with the tissue should be avoided, e.g. in those of brain functional imaging. As alternatives to contacting transducers interferometric techniques can be used to acquire photoacoustic signals remotely. Here, a system for non-contact photoacoustic tomography imaging (NCPAT) has been established. This approach enables NCPAT not to exceed laser exposure safety limits. The stimulated source of NCPAT utilized a laser with center wavelength of 532 nm and output intensity of 17.5 mJ/cm ², and a laser heterodyne interferometry was used to receive the photoacoustic signals. The NCPAT was used to implement on a rotational imaging geometry for photoacoustic tomography with a real-tissue phantom. The photoacoustic imaging was obtained by applying a reconstruction algorithm to the data acquired for NCPAT. Experiments results showed that the NCPAT system with detection 15 dB bandwidth of 2.25 MHz could resolve spherical optical inclusions with dimension of 500 μm and multi-layered structure with optical contrast in strongly scattering medium. The method could expand the scope of photoacoustic and ultrasonic technology to in-vivo biomedical applications where contact is impractical.

Body-monitoring with photonic textiles: a reflective heartbeat sensor based on polymer optical fibres

Knowledge of an individual's skin condition is important for pressure ulcer prevention. Detecting early changes in skin through perfusion, oxygen saturation values, and pressure on tissue and subsequent therapeutic intervention could increase patients' quality of life drastically. However, most existing sensing options create additional risk of ulcer development due to further pressure on and chafing of the skin. Here, as a first component, we present a flexible, photonic textile-based sensor for the continuous monitoring of the heartbeat and blood flow. Polymer optical fibres (POFs) are melt-spun continuously and characterized optically and mechanically before being embroidered. The resulting sensor shows flexibility when embroidered into a moisture-wicking fabric, and withstands disinfection with hospital-type laundry cycles. Additionally, the new sensor textile shows a lower static coefficient of friction (COF) than conventionally used bedsheets in both dry and sweaty conditions versus a skin model. Finally, we demonstrate the functionality of our sensor by measuring the heartbeat at the forehead in reflection mode and comparing it with commercial finger photoplethysmography for several subjects. Our results will allow the development of flexible, individualized, and fully textile-integrated wearable sensors for sensitive skin conditions and general long-term monitoring of patients with risk for pressure ulcer.