The optical attenuation coefficient (AC), an important tissue parameter that measures how quickly incident light is attenuated when passing through a medium, has been shown to enable quantitative analysis of tissue properties from optical coherence tomography (OCT) signals. Successful extraction of this parameter would facilitate tissue differentiation and enhance the diagnostic value of OCT. In this review, we discuss the physical and mathematical basis of AC extraction from OCT data, including current approaches used in modeling light scattering in tissue and in AC estimation. We also report on demonstrated clinical applications of the AC, such as for atherosclerotic tissue characterization, malignant lesion detection, and brain injury visualization. With current studies showing AC analysis as a promising technique, further efforts in the development of methods to accurately extract the AC and to explore its potential use for more extensive clinical applications are desired.

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins.

The PeriFlux 6000 EPOS system combines diffuse reflectance spectroscopy (DRS) and laser Doppler flowmetry (LDF) for the assessment of oxygen saturation (expressed in percentage), red blood cell (RBC) tissue fraction (expressed as volume fraction, %RBC), and perfusion (%RBC  ×  mm  /  s) in the microcirculation. It also allows the possibility of separating the perfusion into three speed regions (0 to 1, 1 to 10, and >10  mm  /  s). We evaluate the speed-resolved perfusion components, i.e., the relative amount of perfusion within each speed region, using a blood-flow phantom. Human blood was pumped through microtubes with an inner diameter of 0.15 mm. Measured DRS and LDF spectra were compared to Monte Carlo-simulated spectra in an optimization routine, giving the best-fit parameters describing the measured spectra. The root-mean-square error for each of the three speed components (0 to 1, 1 to 10, and >10  mm  /  s, respectively) when describing the blood-flow speed in the microtubes was 2.9%, 8.1%, and 7.7%. The presented results show that the system can accurately discriminate blood perfusion originating from different blood-flow speeds, which may enable improved measurement of healthy and dysfunctional microcirculatory flow.

There is an increasing use of near-infrared lasers in biomedical applications operating in the spectrum between 1300 and 1400 nm. To corroborate and expand the existing safety data for skin exposure to lasers in this wavelength region, the in-vivo ED₅₀ damage thresholds were determined in Guizhou miniature pigs for 1319-nm laser radiation. Exposure durations of 0.4, 1.0, and 3.0 s and 1  /  e² beam diameters of 0.98 and 1.96 cm were employed. Damage lesion determinations were performed at 1- and 24 h post exposure. The Bliss probit analysis was employed to establish the ED₅₀ damage thresholds. Histopathological studies of skin damage were performed at 48 h after irradiation to reveal the damage characteristics. The skin damage thresholds at 1 h post exposure, given in peak radiant exposure, were 35.5, 36.1, and 37.1  J  /  cm² at exposure durations of 0.4, 1.0, and 3.0 s with the spot diameter of 0.98 cm, and 28.6  J  /  cm² at exposure duration of 3.0 s with the spot diameter of 1.96 cm. At 24 h post exposure, the ED₅₀s increased slightly. Histologically, the thermal damage characteristics at the near-threshold level included gathering of the nuclear chromatin and cell vacuolation in the epidermis and deposition of blood cells in the capillary vessels. However, at the apparently above-threshold level, the damage characteristics included obvious stretching of the nuclear chromatin in the epidermis, closing of the capillary lumen, structural change of collagen fibers, and coagulative necrosis of the hair follicle cells. The damage induced by this laser could go deep into the fatty tissue. The obtained results may contribute to the knowledge base for the damage mechanisms and expand the database for the refinement of laser safety standards in the wavelength range of 1300 to 1400 nm.

Subglottic stenosis (SGS) is a challenging disease to diagnose in neonates. Long-range optical coherence tomography (OCT) is an optical imaging modality that has been described to image the subglottis in intubated neonates. A major challenge associated with OCT imaging is the lack of an automated method for image analysis and micrometry of large volumes of data that are acquired with each airway scan (1 to 2 Gb). We developed a tissue segmentation algorithm that identifies, measures, and conducts image analysis on tissue layers within the mucosa and submucosa and compared these automated tissue measurements with manual tracings. We noted small but statistically significant differences in thickness measurements of the mucosa and submucosa layers in the larynx (p  <  0.001), subglottis (p  =  0.015), and trachea (p  =  0.012). The automated algorithm was also shown to be over 8 times faster than the manual approach. Moderate Pearson correlations were found between different tissue texture parameters and the patient’s gestational age at birth, age in days, duration of intubation, and differences with age (mean age 17 days). Automated OCT data analysis is necessary in the diagnosis and monitoring of SGS, as it can provide vital information about the airway in real time and aid clinicians in making management decisions for intubated neonates.

Structured light imaging (SLI) with high spatial frequency (HSF) illumination provides a method to amplify native tissue scatter contrast and better differentiate superficial tissues. This was investigated for margin analysis in breast-conserving surgery (BCS) and imaging gross clinical tissues from 70 BCS patients, and the SLI distinguishability was examined for six malignancy subtypes relative to three benign/normal breast tissue subtypes. Optical scattering images recovered were analyzed with five different color space representations of multispectral demodulated reflectance. Excluding rare combinations of invasive lobular carcinoma and fibrocystic disease, SLI was able to classify all subtypes of breast malignancy from surrounding benign tissues (p-value  <  0.05) based on scatter and color parameters. For color analysis, HSF illumination of the sample generated more statistically significant discrimination than regular uniform illumination. Pathological information about lesion subtype from a presurgical biopsy can inform the search for malignancy on the surfaces of specimens during BCS, motivating the focus on pairwise classification analysis. This SLI modality is of particular interest for its potential to differentiate tissue classes across a wide field-of-view (∼100  cm²) and for its ability to acquire images of macroscopic tissues rapidly but with microscopic-level sensitivity to structural and morphological tissue constituents.

Subdiffuse spatial frequency domain imaging (sd-SFDI) data of 42 freshly excised, bread-loafed tumor resections from breast-conserving surgery (BCS) were evaluated using texture analysis and a machine learning framework for tissue classification. Resections contained 56 regions of interest (RoIs) determined by expert histopathological analysis. RoIs were coregistered with sd-SFDI data and sampled into ∼4  ×  4  mm² subimage samples of confirmed and homogeneous histological categories. Sd-SFDI reflectance textures were analyzed using gray-level co-occurrence matrix pixel statistics, image primitives, and power spectral density curve parameters. Texture metrics exhibited statistical significance (p-value  <  0.05) between three benign and three malignant tissue subtypes. Pairs of benign and malignant subtypes underwent texture-based, binary classification with correlation-based feature selection. Classification performance was evaluated using fivefold cross-validation and feature grid searching. Classification using subdiffuse, monochromatic reflectance (illumination spatial frequency of f_x  =  1.37  mm^−  1, optical wavelength of λ  =  490  nm) achieved accuracies ranging from 0.55 (95% CI: 0.41 to 0.69) to 0.95 (95% CI: 0.90 to 1.00) depending on the benign–malignant diagnosis pair. Texture analysis of sd-SFDI data maintains the spatial context within images, is free of light transport model assumptions, and may provide an alternative, computationally efficient approach for wide field-of-view (cm²) BCS tumor margin assessment relative to pixel-based optical scatter or color properties alone.

Single-shot, two-frame, π-shifted spatially multiplexed interference microscopy (π-SMIM) is presented as an improvement to previous SMIM implementations, introducing a versatile, robust, fast, and accurate method for cumbersome, noisy, and low-contrast phase object analysis. The proposed π-SMIM equips a commercially available nonholographic microscope with a high-speed (video frame rate) enhanced quantitative phase imaging (QPI) capability by properly placing a beam-splitter in the microscope embodiment to simultaneously (in a single shot) record two holograms mutually phase shifted by π radians at the expense of reducing the field of view. Upon subsequent subtractive superimposition of holograms, a π-hologram is generated with reduced background and improved modulation of interference fringes. These features determine superior phase retrieval quality, obtained by employing the Hilbert spiral transform on the π-hologram, as compared with a single low-quality (low signal-to-noise ratio) hologram analysis. In addition, π-SMIM enables accurate in-vivo analysis of high dynamic range phase objects, otherwise measurable only in static regime using time-consuming phase-shifting. The technique has been validated utilizing a 20  ×    /  0.46 NA objective in a regular Olympus BX-60 upright microscope for QPI of different lines of prostate cancer cells and flowing microbeads.

For early diagnosis of rheumatoid arthritis (RA), it is important to visualize its potential marker, vascularization in the synovial membrane of the finger joints. Photoacoustic (PA) imaging, which can image blood vessels at high contrast and resolution, is expected to be a potential modality for earlier diagnosis of RA. In previous studies of PA finger imaging, different acoustic schemes, such as linear-shaped arrays, have been utilized, but these have limited detection views, rendering inaccurate reconstruction, and most of them require rotational detection. We are developing a PA system for finger vascular imaging using a ring-shaped array ultrasound (US) transducer. By designing the ring-array sensor based on simulations, using phantom experiments, it was demonstrated that we have created a system that can image small objects around 0.1 to 0.5 mm in diameter. The full width at half maximum of the slice direction of the system was within 2 mm and corresponded to that of the simulation. Moreover, we could clearly visualize healthy index finger vasculature and the location of the distal interphalangeal and proximal interphalangeal joints by PA and US echo images. In the future, this system could be used as a method for visualizing the three-dimensional vascularization of RA patients’ fingers.

Dynamic optical coherence elastography (OCE) tracks elastic wave propagation speed within tissue, enabling quantitative three-dimensional imaging of the elastic modulus. We show that propagating mechanical waves are mode converted at interfaces, creating a finite region on the order of an acoustic wavelength where there is not a simple one-to-one correspondence between wave speed and elastic modulus. Depending on the details of a boundary’s geometry and elasticity contrast, highly complex propagating fields produced near the boundary can substantially affect both the spatial resolution and contrast of the elasticity image. We demonstrate boundary effects on Rayleigh waves incident on a vertical boundary between media of different shear moduli. Lateral resolution is defined by the width of the transition zone between two media and is the limit at which a physical inclusion can be detected with full contrast. We experimentally demonstrate results using a spectral-domain OCT system on tissue-mimicking phantoms, which are replicated using numerical simulations. It is shown that the spatial resolution in dynamic OCE is determined by the temporal and spatial characteristics (i.e., bandwidth and spatial pulse width) of the propagating mechanical wave. Thus, mechanical resolution in dynamic OCE inherently differs from the optical resolution of the OCT imaging system.

We present a multispectral fundus camera that performs fast imaging of the ocular posterior pole in the visible and near-infrared (400 to 1300 nm) wavelengths through 15 spectral bands, using a flashlight source made of light-emitting diodes, and CMOS and InGaAs cameras. We investigate the potential of this system for visualizing occult and overlapping structures of the retina in the unexplored wavelength range beyond 900 nm, in which radiation can penetrate deeper into the tissue. Reflectance values at each pixel are also retrieved from the acquired images in the analyzed spectral range. The available spectroscopic information and the visualization of retinal structures, specifically the choroidal vasculature and drusen-induced retinal pigment epithelium degeneration, which are hardly visible in conventional color fundus images, underline the clinical potential of this system as a new tool for ophthalmic diagnosis.

Minimally invasive robotic surgery using fluorescence-guided images with a video laparoscope has been widely used because of its advantages of small incision, fast recovery time, and efficiency. However, the penetration depth limitation of fluorescence is a disadvantage caused by the absorption and scattering in tissues and blood cells. If this limitation can be overcome by additional imaging modalities, the surgical procedure can be quite efficient and precise. High-energy annihilation-gamma photons have a stronger penetration capability than visible and fluorescence photons. To characterize and validate a multimodal annihilation-gamma/near-infrared (NIR)/visible laparoscopic imaging system, an internal detector composed of an annihilation-gamma detector and an optical system was assembled inside a surgical stainless pipe with an outer diameter of 15.8 mm and an external detector with a dimension of 100  ×  100  mm² placed at the opposite side of the internal detector. Integrated images of 511-keV gamma rays, NIR fluorescence, and visible light were obtained simultaneously. The 511-keV gamma image could be clearly seen with the acquisition of 5 s, while NIR and visible images could be presented in real time. This multimodal system has the potential for improving the surgery time and the quality of patient care.

Scanning laser ophthalmoscopes (SLOs) have the potential to perform high speed, high contrast, functional imaging of the human retina for diagnosis and follow-up of retinal diseases. Commercial SLOs typically use a monochromatic laser source or a superluminescent diode for imaging. Multispectral SLOs using an array of laser sources for spectral imaging have been demonstrated in research settings, with applications mainly aiming at retinal oxygenation measurements. Previous SLO-based oximetry techniques are predominantly based on wavelengths that depend on laser source availability. We describe an SLO system based on a supercontinuum (SC) source and a double-clad fiber using the single-mode core for illumination and the larger inner cladding for quasi-confocal detection to increase throughput and signal-to-noise ratio. A balanced detection scheme was implemented to suppress the relative intensity noise of the SC source. The SLO produced dual wavelength, high-quality images at 10  frames  /  s with a maximum 20 deg imaging field-of-view with any desired combination of wavelengths in the visible spectrum. We demonstrate SLO-based dual-wavelength oximetry in vessels down to 50  μm in diameter. Reproducibility was demonstrated by performing three different imaging sessions of the same volunteer, 8 min apart. Finally, by performing a wavelength sweep between 485 and 608 nm, we determined, for our SLO geometry, an approximately linear relationship between the effective path length of photons through the blood vessels and the vessel diameter.

Ovarian cancer is the deadliest gynecologic cancer due predominantly to late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Multiphoton microscopy (MPM) is a relatively new imaging technique sensitive to endogenous fluorophores, which has tremendous potential for clinical diagnosis, though it is limited in its application to the ovaries. Wide-field fluorescence imaging (WFI) has been proposed as a complementary technique to MPM, as it offers high-resolution imagery of the entire organ and can be tailored to target specific biomarkers that are not captured by MPM imaging. We applied texture analysis to MPM images of a mouse model of ovarian cancer. We also conducted WFI targeting the folate receptor and matrix metalloproteinases. We find that texture analysis of MPM images of the ovary can differentiate between genotypes, which is a proxy for disease, with high statistical significance (p  <  0.001). The wide-field fluorescence signal also changes significantly between genotypes (p  <  0.01). We use the features to classify multiple tissue groups to over 80% accuracy. These results suggest that MPM and WFI are promising techniques for the early detection of ovarian cancer.

Inexpensive near-infrared microscopy (NIRM) was developed as a convenient technique to detect the medulla loss of scalp hair while reducing analytical time with easy sample preparation, leading to a field screening tool for breast cancer. NIRM has been evaluated as an alternative to synchrotron-based nanoscopy and to the relatively expensive method of conventional infrared microscopy to determine the degree and pattern of medulla loss of scalp hairs of patients with breast cancer and benign diseases, as well as normal healthy individuals. NIR imaging showed a strong, scattering-based hyperintense contrast of the medulla compared to the fully attenuated cortex in medullated healthy hair. Complete medulla loss (CML) per hair strand was more extensively (60.9  ±  10.2  %  ) (p  <  0.001) detected in the hair of all cancer patients than in the hair of either healthy individuals (less than 3.7  ±  7.5  %  ) or those with benign disease (30.6  ±  5.9  %  ), suggesting a potential biomarker for breast cancer diagnosis. The medulla structure was retained mostly in the hair of age-matched healthy individuals, but discontinuous medulla loss was observed concomitantly with less CML in fibroadenoma patients. Potentially, compact NIRM modules can be integrated into a mobile platform as point-of-care technology for breast cancer screening.

Emerging technologies are enabling the feasibility of new types of point-of-care diagnostic devices. A portable, multimodal microscopy platform intended for use in remote diagnostic applications is presented. Use of such a system could bring high-quality microscopy to field use for diseases such as malaria, allowing better diagnostic and surveillance information to be gathered. The microscope was designed using off-the-shelf components and a manual filter selection to generate bright-field, fluorescent, and cross-polarized images of samples mounted to microscopy slides. Design parameters for the system are discussed, and characterization is performed using standardized imaging targets, multimodal phantoms, and blood smears simulating those used in malaria diagnosis. The microscope is shown to be able to image below element 9-3 of a 1951 U.S. Air Force target, indicating that the system is capable of resolving features <775  nm. Morphological indicators of Plasmodium falciparum can be visualized in images from each modality and combined into high-contrast composite images. To optimize parasitic feature contrast across all three imaging modes, several different staining techniques were compared, with results indicating that use of a single nucleic acid binding fluorophore is preferable.

A closed-form expression is obtained for the temporal correlation function of the scattered radiation detected in optical coherence tomography (OCT), taking into account the flow velocity gradient across the OCT detection volume in the suspension of flowing Brownian particles. The analytical approach we use includes both the laser beam and wavefront curvature radii changing over the depth. Also, we compare our results with a previously obtained theoretical model, partially an empirical approach. Our findings suggest the importance of the flow velocity gradient for accurate measurements of flow velocity vector, particle diffusivity, shear-induced diffusion, and potentially other OCT applications.

The erratum corrects an error in the article, “Nanoscale photoacoustic tomography for label-free super-resolution imaging: simulation study,” by P. Samant et al.