Significance: Visible light optical coherence tomography (OCT) is emerging for spectroscopic and ultrahigh resolution imaging, but challenges remain. Depth-dependent dispersion limits retinal image quality and current correction approaches are cumbersome. Inconsistent group refractive indices during image reconstruction also limit reproducibility.

Aim: To introduce and evaluate water wavenumber calibration (WWC), which corrects depth-dependent dispersion and provides an accurate depth axis in water.

Approach: Enabled by a visible light OCT spectrometer configuration with a 3- to 4-dB sensitivity roll-off over 1 mm in air across a 90-nm bandwidth, we determine the spectral phase of a 1-mm water cell, an affine function of water wavenumber. Via WWC, we reconstruct visible light OCT human retinal images with 1.3-μm depth resolution in water.

Results: Images clearly reveal Bruch’s membrane, inner plexiform layer lamination, and a thin nerve fiber layer in the temporal parafovea. WWC halves the processing time, while achieving the same image definition as an assumption-free gold standard approach, suggesting that water wavenumber is a suitable proxy for tissue wavenumber. WWC also provides a depth axis in water without explicitly assuming a group refractive index.

Conclusions: WWC is a simple method that helps to realize the full potential of visible light OCT.

Significance: The retina is critical for vision, and several diseases may alter its biomechanical properties. However, assessing the biomechanical properties of the retina nondestructively is a challenge due to its fragile nature and location within the eye globe. Advancements in Brillouin spectroscopy have provided the means for nondestructive investigations of retina biomechanical properties.

Aim: We assessed the biomechanical properties of mouse retinas using Brillouin microscopy noninvasively and showed the potential of Brillouin microscopy to differentiate the type and layers of retinas based on stiffness.

Approach: We used Brillouin microscopy to quantify stiffness of fresh and paraformaldehyde (PFA)-fixed retinas. As further proof-of-concept, we demonstrated a change in the stiffness of a retina with N-methyl-D-aspartate (NMDA)-induced damage, compared to an undamaged sample.

Results: We found that the retina layers with higher cell body density had higher Brillouin modulus compared to less cell-dense layers. We have also demonstrated that PFA-fixed retina samples were stiffer compared with fresh samples. Further, NMDA-induced neurotoxicity leads to retinal ganglion cell (RGC) death and reactive gliosis, increasing the stiffness of the RGC layer.

Conclusion: Brillouin microscopy can be used to characterize the stiffness distribution of the layers of the retina and can be used to differentiate tissue at different conditions based on biomechanical properties.

Significance: An accurate, automated, and unbiased cell counting procedure is needed for tissue selection for corneal transplantation.

Aim: To improve accuracy and reduce bias in endothelial cell density (ECD) quantification by combining Gabor-domain optical coherence microscopy (GDOCM) for three-dimensional, wide field-of-view (1  mm²) corneal imaging and machine learning for automatic delineation of endothelial cell boundaries.

Approach: Human corneas stored in viewing chambers were imaged over a wide field-of-view with GDOCM without contacting the specimens. Numerical methods were applied to compensate for the natural curvature of the cornea and produce an image of the flattened endothelium. A convolutional neural network (CNN) was trained to automatically delineate the cell boundaries using 180 manually annotated images from six corneas. Ten additional corneas were imaged with GDOCM and compared with specular microscopy (SM) to determine performance of the combined GDOCM and CNN to achieve automated endothelial counts relative to current procedural standards.

Results: Cells could be imaged over a larger area with GDOCM than SM, and more cells could be delineated via automatic cell segmentation than via manual methods. ECD obtained from automatic cell segmentation of GDOCM images yielded a correlation of 0.94 (p  <  0.001) with the manual segmentation on the same images, and correlation of 0.91 (p  <  0.001) with the corresponding manually counted SM results.

Conclusions: Automated endothelial cell counting on GDOCM images with large field of view eliminates selection bias and reduces sampling error, which both affect the gold standard of manual counting on SM images.

Significance: Functional near-infrared spectroscopy (fNIRS) is an emerging brain imaging technique due to its small size, low cost, minimum scanning sonic noise, and portability. Unfortunately, because this technique does not provide neuroanatomical information to accompany the functional data, its data interpretation remains a persistent challenge in fNIRS brain imaging applications. The two most popular approaches for fNIRS anatomical registration are magnetic resonance imaging (MRI) and three-dimensional (3-D) digitization. MRI scanning yields high-precision registration but reduces the cost-effectiveness and accessibility of fNIRS imaging. Alternatively, the low cost and portable 3-D digitizers are affected by magnetic properties of ambient metal objects, including participant clothing, testing equipment, medical implants, and so forth.

Aim: To overcome these obstacles and provide accessible and reliable neuroanatomical registration for fNIRS imaging, we developed and explored a photogrammetry optode registration (POR) method.

Approach: The POR method uses a consumer-grade camera to reconstruct a 3-D image of the fNIRS optode-set, including light emitters and detectors, on a participant’s head. This reconstruction process uses a linear-time incremental structure from motion (LTI-SfM) algorithm, based on 100 to 150 digital photos. The POR method then aligns the reconstructed image with an anatomical template of the brain.

Results: To validate this method, we tested 22 adult and 19 child participants using the POR method and MRI imaging. The results comparisons suggest on average 55% and 46% overlap across all data channel measurements registered by the two methods in adult and children, respectively. Importantly, this overlap reached 65% and 60% in only the frontal channels.

Conclusions: These results suggested that the mismatch in registration was partially due to higher variation in backward optode placement rather than the registration efficacy. Therefore, the photo-based registration method can offer an accessible and reliable approach to neuroanatomical registration of fNIRS as well as other surface-based neuroimaging and neuromodulation methods.

Significance: Photoacoustic imaging (PAI) enables the detection of blood hemoglobin (HB) concentration and oxygenation (sO₂) with high contrast and resolution. Despite the heavy use of photoacoustically determined total hemoglobin (THb) and oxygenation (sO₂) biomarkers in PAI research, their relationship with underlying biochemical blood parameters and the impact of intra- and interspecies genetic variability have yet to be established.

Aim: To explore the relationship between THb and sO₂ photoacoustic biomarkers and the underlying biochemical blood parameters in a species-specific manner.

Approach: Experiments were performed on blood in vitro using tissue-mimicking agar phantoms. Blood was extracted from mouse, rat, human, and naked mole-rat (Heterocephalus glaber), anticoagulated in ethylenediaminetetraacetic acid, and measured within 48 h. THb and sO₂ were measured using a commercial photoacoustic tomography system (InVision 128, iThera Medical GmBH). Biochemical blood parameters such as HB concentration (g/dL), hematocrit (HCT, %), and red blood cell (RBC) count (μL^−  1) were assessed using a hematology analyzer (Mythic 18 Vet, Woodley Equipment).

Results: A significant correlation was observed between THb and biochemical HB, HCT, and RBC in mouse and rat blood. Moreover, PAI accurately recapitulated interspecies variations in HB and HCT between mouse and rat blood and resolved differences in the oxygen dissociation curves measured using sO₂ between human, mouse, and rat. With these validation data in hand, we applied PAI to studies of blood obtained from naked mole-rats and could confirm the high oxygen affinity of this species in comparison to other rodents of similar size.

Conclusions: Our results demonstrate the high sensitivity of photoacoustically determined hemoglobin biomarkers toward species-specific variations in vitro.

Significance: Detection and characterization of coronary atherosclerotic plaques often need reviews of a large number of optical coherence tomography (OCT) imaging slices to make a clinical decision. However, it is a challenge to manually review all the slices and consider the interrelationship between adjacent slices.

Approach: Inspired by the recent success of deep convolutional network on the classification of medical images, we proposed a ResNet-3D network for classification of coronary plaque calcification in OCT pullbacks. The ResNet-3D network was initialized with a trained ResNet-50 network and a three-dimensional convolution filter filled with zeros padding and non-zeros padding with a convolutional filter. To retrain ResNet-50, we used a dataset of ∼4860 OCT images, derived by 18 entire pullbacks from different patients. In addition, we investigated a two-phase training method to address the data imbalance. For an improved performance, we evaluated different input sizes for the ResNet-3D network, such as 3, 5, and 7 OCT slices. Furthermore, we integrated all ResNet-3D results by majority voting.

Results: A comparative analysis proved the effectiveness of the proposed ResNet-3D networks against ResNet-2D network in the OCT dataset. The classification performance (F1-scores  =  94  %   for non-zeros padding and F1-score  =  96  %   for zeros padding) demonstrated the potential of convolutional neural networks (CNNs) in classifying plaque calcification.

Conclusions: This work may provide a foundation for further work in extending the CNN to voxel segmentation, which may lead to a supportive diagnostic tool for assessment of coronary plaque vulnerability.

Significance: Pulsatility is a vital characteristic of the cardiovascular system. Characterization of the pulsatility pattern locally in the peripheral microvasculature is currently not readily available and would provide an additional source of information, which may prove important in understanding the pathophysiology of arterial stiffening, vascular ageing, and their linkage with cardiovascular disease development.

Aim: We aim to confirm the suitability of speckle decorrelation optical coherence tomography angiography (OCTA) under various noncontact/contact scanning protocols for the visualization of pulsatility patterns in vessel-free tissue and in the microvasculature of peripheral human skin.

Results: Results from five healthy subjects show distinct pulsatile patterns both in vessel-free tissue with either noncontact or contact imaging and in individual microvessels with contact imaging. Respectively, these patterns are likely caused by the pulsatile pressure and pulsatile blood flow. The pulse rates show good agreement with those from pulse oximetry, confirming that the pulsatile signatures reflect pulsatile hemodynamics.

Conclusions: This study demonstrates the potential of speckle decorrelation OCTA for measuring localized peripheral cutaneous pulsatility and defines scanning protocols necessary to undertake such measurements. Noncontact imaging should be used for the study of pulsatility in vessel-free tissue and contact imaging with strong mechanical coupling in individual microvessels. Further studies of microcirculation based upon this method and protocols are warranted.

Significance: In breast-preserving tumor surgery, the inspection of the excised tissue boundaries for tumor residue is too slow to provide feedback during the surgery. The discovery of positive margins requires a new surgery which is difficult and associated with low success. If the re-excision could be done immediately this is believed to improve the success rate considerably.

Aim: Our aim is for a fast microscopic analysis that can be done directly on the excised tissue in or near the operating theatre.

Approach: We demonstrate the combination of three nonlinear imaging techniques at selected wavelengths to delineate tumor boundaries. We use hyperspectral coherent anti-Stokes Raman scattering (CARS), second harmonic generation (SHG), and two-photon excited fluorescence (TPF) on excised patient tissue.

Results: We show the discriminatory power of each of the signals and demonstrate a sensitivity of 0.87 and a specificity of 0.95 using four CARS wavelengths in combination with SHG and TPF. We verify that the information is independent of sample treatment.

Conclusions: Nonlinear multispectral imaging can be used to accurately determine tumor boundaries. This demonstration using microscopy in the epi-direction directly on thick tissue slices brings this technology one step closer to clinical implementation.

Significance: Practical implementation of acousto-optic imaging (AOI) encounters difficulties that prevent it from rapid adoption in clinical use. In many practical medical applications, the region of interest may be accessed only from one side, and using a water tank for coupling is not feasible. The solution might be to use reflection-mode imaging with an electronically scanned ultrasound (US) focus. Such an approach, however, entails considerable challenges.

Aim: The possibilities of detecting and localizing light-absorbing inclusions inside turbid media by combining reflection-mode AOI conducted using a one-dimensional US array with electronic scanning of the US focus are investigated experimentally and signal processing algorithms that could be used for this purpose are introduced.

Approach: We determine the speckle contrast decrease due to the acousto-optic effect as a function of the US focal point coordinates. Different signal postprocessing techniques are investigated.

Results: A significant decrease in the determined speckle contrast difference values is observed due to the presence of light-absorbing inclusions. However, local minima occur in the plots only under specific conditions. Subtracting individual distributions and determining symmetry deviations allow for localizing the inclusions.

Conclusions: Detection and localization of optically distinct regions are possible using the introduced approach. Signal postprocessing is required in a general case.

Significance: To advance our understanding of the contrast observed when imaging with polarization-sensitive optical coherence tomography (PS-OCT) and its correlation with oral cancerous pathologies, a detailed comparison with histology provided via ex vivo fixed tissue is required. The effects of tissue fixation, however, on such polarization-based contrast have not yet been investigated.

Aim: A study was performed to assess the impact of tissue fixation on depth-resolved (i.e., local) birefringence measured with PS-OCT.

Approach: A PS-OCT system based on depth-encoded polarization multiplexing and polarization-diverse detection was used to measure the Jones matrix of a sample. A wide variety of ex vivo samples were measured freshly after excision and 24 h after fixation, consistent with standard pathology. Some samples were also measured 48 h after fixation.

Results: The tissue fixation does not diminish the birefringence contrast. Statistically significant changes were observed in 11 out of 12 samples; these changes represented an increase in contrast, overall, by 11% on average.

Conclusions: We conclude that the fixed samples are suitable for studies seeking a deeper understanding of birefringence contrast in oral tissue pathology. The enhancement of contrast removes the need to image immediately postexcision and will facilitate future investigations with PS-OCT and other advanced polarization-sensitive microscopy methods, such as mapping of the local optic axis with PS-OCT and PS-optical coherence microscopy.

Significance: Automatic and accurate classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images is essential for assisting ophthalmologist in the diagnosis and grading of macular diseases. Therefore, more effective OCT volume classification for automatic recognition of macular diseases is needed.

Aim: For OCT volumes in which only OCT volume-level labels are known, OCT volume classifiers based on its global feature and deep learning are designed, validated, and compared with other methods.

Approach: We present a general framework to classify OCT volume for automatic recognizing macular diseases. The architecture of the framework consists of three modules: B-scan feature extractor, two-dimensional (2-D) feature map generation, and volume-level classifier. Our architecture could address OCT volume classification using two 2-D image machine learning classification algorithms. Specifically, a convolutional neural network (CNN) model is trained and used as a B-scan feature extractor to construct a 2-D feature map of an OCT volume and volume-level classifiers such as support vector machine and CNN with/without attention mechanism for 2-D feature maps are described.

Results: Our proposed methods are validated on the publicly available Duke dataset, which consists of 269 intermediate age-related macular degeneration (AMD) volumes and 115 normal volumes. Fivefold cross-validation was done, and average accuracy, sensitivity, and specificity of 98.17%, 99.26%, and 95.65%, respectively, are achieved. The experiments show that our methods outperform the state-of-the-art methods. Our methods are also validated on our private clinical OCT volume dataset, consisting of 448 AMD volumes and 462 diabetic macular edema volumes.

Conclusions: We present a general framework of OCT volume classification based on its 2-D feature map and CNN with attention mechanism and describe its implementation schemes. Our proposed methods could classify OCT volumes automatically and effectively with high accuracy, and they are a potential practical tool for screening of ophthalmic diseases from OCT volume.

Significance: Cerebral blood flow (CBF) regulation at neurovascular coupling (NVC) plays an important role in normal brain functioning to support oxygen delivery to activating neurons. Therefore, studying the mechanisms of CBF adjustment is crucial for the improved understanding of brain activity.

Aim: We investigated the temporal profile of hemodynamic signal change in mouse cortex caused by neural activation and its variation over cortical depth.

Approach: Following the cranial window surgery, intrinsic optical signal imaging (IOSI) was used to spatially locate the activated region in mouse cortex during whisker stimulation. Optical microangiography (OMAG), the functional extension of optical coherence tomography, was applied to image the activated and control regions identified by IOSI. Temporal profiles of hemodynamic response signals obtained by IOSI and OMAG were compared, and OMAG signal was analyzed over cortical layers.

Results: Our results showed that the hemodynamic response to neural activity revealed by blood flow change signal signal through IOSI is slower than that observed by OMAG signal. OMAG also indicated the laminar variation of the response over cortical depth, showing the largest response in cortical layer IV.

Conclusions: Overall, we demonstrated the development and application of dual-modality imaging system composed of IOSI and OMAG, which may have potential to enable the future investigations of depth-resolved CBF and to provide the insights of hemodynamic events associated with the NVC.

Significance: Tumor heterogeneity poses a challenge for the chemotherapeutic treatment of cancer. Tissue dynamics spectroscopy captures dynamic contrast and can capture the response of living tissue to applied therapeutics, but the current analysis averages over the complicated spatial response of living biopsy samples.

Aim: To develop tissue dynamics spectroscopic imaging (TDSI) to map the heterogeneous spatial response of tumor tissue to anticancer drugs.

Approach: TDSI is applied to tumor spheroids grown from cell lines and to ex vivo living esophageal biopsy samples. Doppler fluctuation spectroscopy is performed on a voxel basis to extract spatial maps of biodynamic biomarkers. Functional images and bivariate spatial maps are produced using a bivariate color merge to represent the spatial distribution of pairs of signed drug-response biodynamic biomarkers.

Results: We have mapped the spatial variability of drug responses within biopsies and have tracked sample-to-sample variability. Sample heterogeneity observed in the biodynamic maps is associated with histological heterogeneity observed using inverted selective-plane illumination microscopy.

Conclusion: We have demonstrated the utility of TDSI as a functional imaging method to measure tumor heterogeneity and its potential for use in drug-response profiling.

Significance: Previous studies have been performed to image photosensitizers in certain organs and tumors using fluorescence laminar optical tomography. Currently, no work has yet been published to quantitatively compare the signal compensation of fluorescence laminar optical tomography with two-dimensional (2-D) imaging in tissues.

Aim: The purpose of this study is to quantify the benefit that fluorescence laminar optical tomography holds over 2-D imaging. We compared fluorescence laminar optical tomography with maximum intensity projection imaging to simulate 2-D imaging, as this would be the most similar and stringent comparison.

Approach: A capillary filled with a photosensitizer was placed in a phantom and ex vivo rodent brains, with fluorescence laminar optical tomography and maximum intensity projection images obtained. The signal loss in the Z direction was quantified and compared to see which methodology could compensate better for signal loss caused by tissue attenuation.

Results: The results demonstrated that we can reconstruct a capillary filled with benzoporphyrin derivative photosensitizers faithfully in phantoms and in ex vivo rodent brain tissues using fluorescence laminar optical tomography. We further demonstrated that we can better compensate for signal loss when compared with maximum intensity projection imaging.

Conclusions: Using fluorescence laminar optical tomography (FLOT), one can compensate for signal loss in deeper parts of tissue when imaging in ex vivo rodent brain tissue compared with maximum intensity projection imaging.

Significance: A significant amount of radical related luminescence is observed from the titanium dioxide (TiO₂) plate during irradiation of alpha particles although alpha particles do not emit Cerenkov-light.

Aim: TiO₂ is a promising material for application to photodynamic therapy in combination with positron radionuclides that emit Cerenkov light. However, it is not clear that radicals are produced by the irradiation of alpha particles, since although Cerenkov light is required to produce radicals, alpha particles do not produce Cerenkov light.

Approach: To clarify this point, the author irradiates alpha particles to a TiO₂ plate and measured the produced luminescence of the plate, which indicates the radical production in TiO₂.

Results: A significant amount of luminescence was observed from the TiO₂ plate during irradiation of alpha particles. The spectrum of luminescence from the TiO₂ plate during this irradiation was the same as that emitted by ultraviolet (UV) light irradiated luminescence, which actually showed radical production in a TiO₂ plate. This luminescence was not attributed to the UV light from the air scintillation by alpha particles but to the direct irradiation of alpha particles to the TiO₂ plate.

Conclusions: A significant amount of luminescence from TiO₂ plate was detected during irradiation of alpha particles. The luminescence is thought to be emitted from the radicals produced by the direct alpha particle irradiation to the TiO₂ plate.

Significance: Our study introduces an application of deep learning to virtually generate fluorescence images to reduce the burdens of cost and time from considerable effort in sample preparation related to chemical fixation and staining.

Aim: The objective of our work was to determine how successfully deep learning methods perform on fluorescence prediction that depends on structural and/or a functional relationship between input labels and output labels.

Approach: We present a virtual-fluorescence-staining method based on deep neural networks (VirFluoNet) to transform co-registered images of cells into subcellular compartment-specific molecular fluorescence labels in the same field-of-view. An algorithm based on conditional generative adversarial networks was developed and trained on microscopy datasets from breast-cancer and bone-osteosarcoma cell lines: MDA-MB-231 and U2OS, respectively. Several established performance metrics—the mean absolute error (MAE), peak-signal-to-noise ratio (PSNR), and structural-similarity-index (SSIM)—as well as a novel performance metric, the tolerance level, were measured and compared for the same algorithm and input data.

Results: For the MDA-MB-231 cells, F-actin signal performed the fluorescent antibody staining of vinculin prediction better than phase-contrast as an input. For the U2OS cells, satisfactory metrics of performance were archieved in comparison with ground truth. MAE is <0.005, 0.017, 0.012; PSNR is >40  /  34  /  33  dB; and SSIM is >0.925  /  0.926  /  0.925 for 4′,6-diamidino-2-phenylindole/hoechst, endoplasmic reticulum, and mitochondria prediction, respectively, from channels of nucleoli and cytoplasmic RNA, Golgi plasma membrane, and F-actin.

Conclusions: These findings contribute to the understanding of the utility and limitations of deep learning image-regression to predict fluorescence microscopy datasets of biological cells. We infer that predicted image labels must have either a structural and/or a functional relationship to input labels. Furthermore, the approach introduced here holds promise for modeling the internal spatial relationships between organelles and biomolecules within living cells, leading to detection and quantification of alterations from a standard training dataset.

Significance: Detailed biochemical and morphological imaging of the plaque burdened coronary arteries holds the promise of improved understanding of atherosclerosis plaque development, ultimately leading to better diagnostics and therapies.

Aim: Development of a dual-modality intravascular catheter supporting swept-source optical coherence tomography (OCT) and frequency-domain fluorescence lifetime imaging (FD-FLIM) of endogenous fluorophores with UV excitation.

Approach: We instituted a refined approach to endoscope development that combines simulation in a commercial ray tracing program, fabrication, and a measurement method for optimizing ball-lens performance. With this approach, we designed and developed a dual-modality catheter endoscope based on a double-clad fiber supporting OCT through the core and fluorescence collection through the first cladding. We varied the relative percent of UV excitation launched into the core and first cladding to explore the potential resolution improvement for FD-FLIM. The developed catheter endoscope was optically characterized, including measurement of spatial resolution and fluorescent lifetimes of standard fluorophores. Finally, the system was demonstrated on fresh ex vivo human coronary arteries.

Results: The developed endoscope was shown to have optical performance similar to predictions derived from the simulation approach. The FLIM resolution can be improved by over a factor of 4 by primarily illuminating through the core rather than the first cladding. However, time-dependent solarization losses need to be considered when choosing the relative percentage. We ultimately chose to illuminate with 7% of the power transmitting through the core. The resulting catheter endoscope had 40-μm lateral resolution for OCT and <100  μm lateral resolution for FD-FLIM. Images of ex vivo coronary arteries are consistent with expectations based on histopathology.

Conclusions: The results demonstrate that our approach for endoscope simulation produces reliable predictions of endoscope performance. Simulation results guided our development of a multimodal OCT/FD-FLIM catheter imaging system for investigating atherosclerosis in coronary arteries.

Significance: Cardiac troponin I (cTnI) is a primary biomarker for diagnosis of myocardial infarction (MI). In contrast to central laboratory tests for cTnI, point-of-care (POC) testing has the advantage of providing results when the patient is first encountered, which helps high-risk patients to be treated more rapidly and low-risk patients to be released in a timely fashion. A paper fluidic platform is good for POC testing because the paper is abundant, low cost, and disposable. However, current cTnI assays on paper platforms use antibodies as the recognition element, which has limitations due to the high cost of production and antibody stability issues at the POC.

Aim: To develop an aptamer-based assay on a paper strip using surface-enhanced resonance Raman spectroscopy (SERRS) for detection of cTnI in the clinically relevant range at the POC.

Approach: Gold nanoparticles (AuNPs) were functionalized with a Raman reporter molecule, malachite green isothiocyanate. The functionalized AuNPs were encapsulated in a silica shell and provided a SERRS signal using a handheld Raman system with a 638-nm excitation wavelength. A primary aptamer and a secondary aptamer of cTnI were used in a sandwich assay format to bind the cTnI on a test line of a paper fluidic platform. By measuring the SERRS signal from the test line, the concentration of cTnI was quantitatively determined.

Results: The aptamer-based SERRS assay on a paper strip had a detection range of 0.016 to 0.1  ng  /  ml for cTnI, had good selectivity for cTnI compared to three other markers, had good stability over 10 days, and had good performance in the more complex serum sample matrix.

Conclusions: The aptamer-based SERRS assay on a paper strip has the potential to provide a sensitive, selective, stable, repeatable, and cost-effective platform for the detection of cTnI toward eventual use in diagnosis of MI at the POC.

Significance: Infrared thermographs (IRTs) have been used for fever screening during infectious disease epidemics, including severe acute respiratory syndrome, Ebola virus disease, and coronavirus disease 2019 (COVID-19). Although IRTs have significant potential for human body temperature measurement, the literature indicates inconsistent diagnostic performance, possibly due to wide variations in implemented methodology. A standardized method for IRT fever screening was recently published, but there is a lack of clinical data demonstrating its impact on IRT performance.

Aim: Perform a clinical study to assess the diagnostic effectiveness of standardized IRT-based fever screening and evaluate the effect of facial measurement location.

Approach: We performed a clinical study of 596 subjects. Temperatures from 17 facial locations were extracted from thermal images and compared with oral thermometry. Statistical analyses included calculation of receiver operating characteristic (ROC) curves and area under the curve (AUC) values for detection of febrile subjects.

Results: Pearson correlation coefficients for IRT-based and reference (oral) temperatures were found to vary strongly with measurement location. Approaches based on maximum temperatures in either inner canthi or full-face regions indicated stronger discrimination ability than maximum forehead temperature (AUC values of 0.95 to 0.97 versus 0.86 to 0.87, respectively) and other specific facial locations. These values are markedly better than the vast majority of results found in prior human studies of IRT-based fever screening.

Conclusion: Our findings provide clinical confirmation of the utility of consensus approaches for fever screening, including the use of inner canthi temperatures, while also indicating that full-face maximum temperatures may provide an effective alternate approach.

Significance: Diffuse correlation spectroscopy (DCS) is an established optical modality that enables noninvasive measurements of blood flow in deep tissue by quantifying the temporal light intensity fluctuations generated by dynamic scattering of moving red blood cells. Compared with near-infrared spectroscopy, DCS is hampered by a limited signal-to-noise ratio (SNR) due to the need to use small detection apertures to preserve speckle contrast. However, DCS is a dynamic light scattering technique and does not rely on hemoglobin contrast; thus, there are significant SNR advantages to using longer wavelengths (>1000  nm) for the DCS measurement due to a variety of biophysical and regulatory factors.

Aim: We offer a quantitative assessment of the benefits and challenges of operating DCS at 1064 nm versus the typical 765 to 850 nm wavelength through simulations and experimental demonstrations.

Approach: We evaluate the photon budget, depth sensitivity, and SNR for detecting blood flow changes using numerical simulations. We discuss continuous wave (CW) and time-domain (TD) DCS hardware considerations for 1064 nm operation. We report proof-of-concept measurements in tissue-like phantoms and healthy adult volunteers.

Results: DCS at 1064 nm offers higher intrinsic sensitivity to deep tissue compared with DCS measurements at the typically used wavelength range (765 to 850 nm) due to increased photon counts and a slower autocorrelation decay. These advantages are explored using simulations and are demonstrated using phantom and in vivo measurements. We show the first high-speed (cardiac pulsation-resolved), high-SNR measurements at large source–detector separation (3 cm) for CW-DCS and late temporal gates (1 ns) for TD-DCS.

Conclusions: DCS at 1064 nm offers a leap forward in the ability to monitor deep tissue blood flow and could be especially useful in increasing the reliability of cerebral blood flow monitoring in adults.

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.