Optics Letters

Optoacoustics (OA) is overwhelmingly implemented in the Time Domain (TD) to achieve a high Signal-to-Noise-Ratio (SNR). Implementations in the Frequency Domain (FD) have been proposed, but have not offered competitive advantages over TD methods to reach high dissemination. It is therefore commonly believed that the TD represents the optimal way of performing optoacoustics. Here, we introduce a novel optoacoustic concept based on frequency comb and theoretically demonstrate its superiority to the TD. Then, using recent advances in laser diode illumination, we launch Frequency Comb Optoacoustic Tomography (FCOT), at multiple wavelengths, and experimentally demonstrate its advantages over TD methods in phantoms and in-vivo. We demonstrate that FCOT optimizes the SNR of spectral measurements over TD methods by benefiting from signal acquisition in the TD and processing in the FD, and that it reaches the fastest multi-spectral operation ever demonstrated in optoacoustics while reducing performance compromises present in TD systems.

Full field optical coherence tomography (FF-OCT) enables high-resolution in-depth imaging within turbid media. In this work, we present a simple approach which combines FF-OCT with off-axis interferometry for the reconstruction of the en-face images. With low spatial and temporal coherence illumination, this new method is able to extract an FF-OCT image from only one interference acquisition. This method is described and the proof-of-concept is demonstrated through the observation of scattering samples such as organic and ex-vivo biomedical samples.

Diffuse optical tomography (DOT) is well known to be ill-posed and suffers from a poor resolution. While time domain DOT can bolster the resolution by time-gating to extract weakly scattering photons, it is often confronted by an inferior signal to noise ratio and a low measurement density. This is particularly problematic for non-contact DOT imaging of non-planar objects, which faces an inherent tradeoff between the light collection efficiency and depth of field. We present here ultrafast contour imaging, a method that enables efficient light collection over curved surfaces with a dense spatiotemporal sampling of diffused light, allowing DOT imaging in the objects native geometry with an improved resolution. We demonstrated our approach with both phantom and small animal imaging results. (C)2020 Optical Society of America

According to Rayleighs criterion, two incoherent emitters with a separation below the diffraction limit are not resolvable with a conventional fluorescence microscope. One method of Super-Resolution Microscopy (SRM) circumvents the diffraction-limited resolution by precisely estimating the position of spatiotemporally independent emitters. However, these methods of SRM techniques are not optimal for estimating the separation of two simultaneously excited emitters. Recently, a number of detection methods based on modal imaging have been developed to achieve the quantum Cramer-Rao lower bound (QCRB) to estimate the separations between two nearby emitters. The QCRB determines the minimum achievable precision for all possible detection methods. Current modal imaging techniques assume a scalar field generated from a point source, such as a distant source from an optical fiber or a pinhole. However, for fluorescently labeled samples, point emitters are single fluorophores that are modeled as dipole emitters and, in practice, are often freely rotating. Dipole radiation must be described by vectorial theory, and the assumption of a scalar field no longer holds. Here, we present a method to numerically calculate the QCRB for measuring the separation of two dipole emitters, incorporating the vectorial theory. Furthermore, we propose a near-quantum optimal detection scheme based on one of the modal imaging techniques, super-localization by image inversion interferometry (SLIVER), for estimating the separation of two freely rotating dipoles. In the proposed method, we introduce a vortex wave plate before the SLIVER detection to separate the radial and azimuthal components of the dipole radiation. With numerical simulations, we demonstrated that our method achieves non-divergent precision at any separation between two dipole emitters. We investigated several practical effects relevant to experimental measurements in super-resolution microscopy, including numerical aperture, detection bandwidth, number of estimation parameters, background, and misalignment on separation estimation. Our proposed measurement provides a near quantum-limited detection scheme for measuring the separation of two freely-rotating dipole emitters, such as fluorescently tagged molecules, which are commonly used in super-resolution microscopy.

High-resolution and super-resolution techniques become more frequently used in thick, inhomogeneous samples. In particular for imaging life cells and tissue in which one wishes to observe a biological process at minimal interference and in the natural environment, sample inhomogeneities are unavoidable. Yet sample-inhomogeneities are paralleled by refractive index variations, for example between the cell organelles and the surrounding medium, that will result in the refraction of light, and therefore lead to sample-induced astigmatism. Astigmatism in turn will result in positional inaccuracies of observations that are at the heart of all super-resolution techniques. Here we introduce a simple model and define a figure-of-merit that allows one to quickly assess the importance of astigmatism for a given experimental setting. We found that astigmatism caused by the cells nucleus can easily lead to aberrations up to hundreds of nanometers, well beyond the accuracy of all super-resolution techniques. The astigmatism generated by small objects, like bacteria or vesicles, appear to be small enough to be of any significance in typical super-resolution experimentation.

Accurate and efficient forward models of photon migration in heterogeneous geometries are important for many applications of light in medicine because many biological tissues exhibit a layered structure, with each layer having independent optical properties and thickness. Unfortunately, closed form analytical solutions are not readily available for layered tissue-models, and often are modeled using computationally expensive numerical techniques or theoretical approximations that limit accuracy and real-time analysis. Here, we develop an open-source accurate, efficient, and stable numerical routine to solve the diffusion equation in the steady-state and time-domain for a layered cylinder tissue model with an arbitrary number of layers and specified thickness and optical coefficients. We show that the steady-state (< 0.1 ms) and time-domain (< 0.5 ms) fluence (for an 8-layer medium) can be calculated with absolute numerical errors approaching machine precision. The numerical implementation increased computation speed by 3 to 4 orders of magnitude compared to previously reported theoretical solutions in layered media. We verify our solutions asymptotically to homogeneous tissue geometries using closed form analytical solutions to assess convergence and numerical accuracy. Approximate solutions to compute the reflected intensity are presented which can decrease the computation time by an additional 2-3 orders of magnitude. We also compare our solutions for 2, 3, and 5 layered media to gold-standard Monte Carlo simulations in layered tissue models of high interest in biomedical optics (e.g. skin/fat/muscle and brain). The presented routine could enable more robust real-time data analysis tools in heterogeneous tissues that are important in many clinical applications such as functional brain imaging and diffuse optical spectroscopy.

Visible light optical coherence tomography (VIS-OCT) is an emerging ophthalmic imaging method uniquely featured by ultrahigh depth resolution, retinal microvascular oximetry, and distinct scattering contrast in the visible spectral range. However, the clinical utility of VIS-OCT is impeded by the fundamental trade-off between the imaging depth range and axial resolution, determined by the spectral resolution and bandwidth respectively. While the full potential of VIS-OCT is leveraged by a broad bandwidth, the imaging depth is inversely sacrificed. The effective depth range is further limited by the wavelength-dependent roll-off that the signal-to-noise ratio (SNR) reduces in the deeper imaging range, more so in shorter wavelength. To address this trade-off, we developed a second-generation dual-channel VIS-OCT system including the first linear-in-k VIS-OCT spectrometer, reference pathlength modulation, and per A-line noise cancellation. All combined, we have achieved 7.2dB roll-off over the full 1.74 mm depth range (water) with shot-noise limited performance. The system uniquely enables >60{degrees} wide-field imaging over large retinal curvature at peripheral retina and optic nerve head, as well as high-definition imaging at ultrahigh 1.3 um depth resolution (water). The dual-channel design includes a conventional near infrared (NIR) channel, compatible with Doppler OCT and OCT angiography (OCTA). The comprehensive structure-function measurement by 2nd-Gen VIS-OCT system is a significant advance towards broader adaptation of VIS-OCT in clinical applications.

Optical properties of blood encode oxygen-dependent information. Noninvasive optical detection of these properties is increasingly desirable to extract biomarkers for tissue health. Recently, visible-light optical coherence tomography (vis-OCT) demonstrated retinal oxygen saturation (sO2) measurements using the depth-resolved spectrum of blood. Such measurements rely on differences between the absorption and scattering coefficients of oxygenated and deoxygenated blood. However, there is still broad disagreement, both theoretically and experimentally, on how vis-OCT measures bloods scattering coefficient. Incorrect assumptions of bloods optical properties can add additional uncertainties or biases into vis-OCTs sO2 model. Using Monte Carlo simulation of a retinal vessel, we determined that vis-OCT almost exclusively detects multiple-scattered photons in blood. Meanwhile, photons mostly forward scatter in blood within the visible spectral range, allowing photons to maintain ballistic paths and penetrate deeply, leading to a reduction in the measured scattering coefficient. We defined a scattering scaling factor (SSF) to account for such a reduction and found that SSF varied with measurement conditions, such as numerical aperture, depth resolution, and depth selection. We further experimentally validated SSF in ex vivo blood phantoms pre-set sO2 levels and in the human retina, both of which agreed well with our simulation.

Ultrasound localization microscopy (ULM) is an emerging imaging modality that resolves microvasculature in deep tissues with high spatial resolution. However, existing preclinical ULM applications are largely constrained to anesthetized animals, introducing confounding vascular effects such as vasodilation and altered hemodynamics. As such, ULM quantifications (e.g., vessel diameter, density, and flow velocity) may be confounded by the use of anesthesia, undermining the usefulness of ULM in practice. Here we introduce a method to address this limitation and achieve ULM imaging in awake mouse brain. Pupillary monitoring was used to support the presence of the awake state during ULM imaging. Vasodilation induced by isoflurane was observed by ULM. Upon recovery to the awake state, reductions in vessel density and flow velocity were observed across different brain regions. In the cortex, the effects induced by isoflurane are more pronounced on venous flow than on arterial flow. In addition, serial in vivo imaging of the same animal brain at weekly intervals demonstrated the highly robust longitudinal imaging capability of the proposed technique. The consistency was further verified through quantitative analysis on individual vessels, cortical regions of arteries and veins, and subcortical regions. This study demonstrates longitudinal ULM imaging in the awake mouse brain, which is crucial for many ULM brain applications that require awake and behaving animals.

Functional neuroimaging with ultrafast ultrasound is an emerging neuroimaging tool for studying neural activities in the rodent brain. Existing methods, however, are challenged by the compromise between functional imaging sensitivity (i.e., sensitivity in detecting neural responses) and spatial resolution. For example, functional ultrasound (fUS) uses native red blood cells (RBCs) as imaging targets, which offers high functional imaging sensitivity but limited spatial resolution that is confined by the diffraction limit of ultrasound. On the other hand, functional ultrasound localization microscopy (fULM) employs intravenously injected microbubble (MB) as contrast agent to achieve super-resolved spatial resolution but at the cost of functional imaging sensitivity. This study aims to address this challenge by developing a novel, MB track-based hemodynamic activity estimation method to enhance the functional imaging sensitivity of fULM. Our approach involves conducting functional correlation analysis using the MB signals acquired from the entire MB movement track rather than individual MB centroid locations, which overcomes the signal sparsity issue in fULM. To further boost the functional sensitivity of fULM, we developed a novel approach based on indwelling jugular vein catheters to achieve fULM imaging in awake mice. The in vivo imaging results demonstrate that the proposed techniques successfully enhanced the functional imaging sensitivity of fULM without compromising its high spatial resolution. In the whisker stimulation experiments, the proposed technique enabled detection of significantly activated brain regions within fewer than five stimulation cycles (5 minutes of acquisition), reducing the required time by over 50% compared to conventional fULM.

We present an effective approach to compensate for multiple scattering effects in Quantitative Optical Coherence Tomography (qOCT) imaging, with the goal of accurately extracting tissue attenuation coefficients, which is crucial for precise clinical diagnosis. In clinical practice, especially for intra-operative imaging, an increased working distance is often necessary to avoid interference with surgical instruments and workflow. However, this increased working distance corresponds to an increased beam spot size, leading to more multiply scattered photons in the OCT signal and thereby underestimating the optical attenuation. To address this challenge, we investigated errors in attenuation coefficient quantification under different beam spot sizes. Monte Carlo simulations were employed to generate virtual OCT signals for two distinct beam spot sizes, enabling us to quantify the errors induced by multiple scattering across a range of true optical attenuation coefficients. Based on this analysis, we developed a compensation function to correct these errors. The proposed method was validated through experimental measurements using tissue-mimicking phantoms and demonstrated a significant improvement in the accuracy of attenuation coefficient quantification. Our results underscore the potential of this easy-to-implement technique to enhance the diagnostic reliability of qOCT, facilitating its broader application in clinical settings for accurate tissue characterization.

We present a novel method to improve the imaging efficiency of tiling light sheet microscopy. In the method, scanning non-coaxial beam arrays synchronized with regional virtual confocal slits are used to illuminate imaging plane. There are two advantages. One is the imaging efficiency increases proportional to the number of excitation beams within the non-coaxial beam array. The other is the width of the regional virtual confocal slits could be very wide without admitting off-focus fluorescence generated by the non-coaxial beam array, which makes the method easy to adopt and very robust in practice. We describe the method in detail, characterize the method via numerical simulations. The results suggest that the imaging efficiency and feasibility of the tiling light sheet microscopy could be improved significantly without affecting the 3D imaging ability by using the method. In additions, we propose several configurations to implement the method in practice.

Structured Illumination Microscopy (SIM) provides imaging with spatial super-resolution, as well as optical sectioning capability, without relying on specialized fluorescent dyes. 2D and 3D variants of this method exist, but most bespoke implementations are 2D-SIM, because it is easier to realize and modify than 3D-SIM. 2D-SIM systems, however, often experience reconstruction artifacts, especially when pushing for high lateral spatial resolution in thicker samples. We present enhanced 2D-SIM, an approach to 2D-SIM where both, coarse patterns optimized for removing out-of-focus background, and fine patterns optimized for resolution improvement beyond the diffraction limit are used. In combination, this achieves 2D-SIM reconstructions with high contrast, spatial super-resolution, and significantly reduced reconstruction artifacts. We present the theoretical framework of this technique, and provide enhanced 2D-SIM imaging results of liver sinusoidal endothelial cells stained with fluorophores emitting at visible and near-infrared wavelengths. Quantitative comparisons of power spectral distribution and image resolution are provided.

Fluorescent structures are nowadays commonly used in the field of biological imaging. However the emission of fluorescence is always given within a finite spectrum. When the imaging systems point spread function is measured, this can be described as an incoherent summation of individual single-wavelength PSFs, weighted by the emission spectrum. As the full-width-half-maximum of the PSF scales inversely with the wavelength and most emission spectra exhibit a fluorescence tail at longer wave-lengths, this contributes significantly to lateral broadening. In our work we theoretically quantify this effect by deriving an analytic expression, which has been verified against some numerical simulations (rel. error on average 3 %). We report a FWHM-broadening on the order of 10 nm and additionally propose a way to overcome this broadening by splitting the emission spectrum into multiple wavelength segments. The corresponding image data is recombined in Fourier space by weighted averaging, leading to an improved signal-to-noise ratio at high spatial frequencies and a reduction of the FWHM of up to 8 nm (relative reduction of the broadening by {approx} 70 %). We also introduce a corrected wavelength, which in combination with already existing PSF calculation tools, describes a theoretical PSF which incorporates the aforementioned broadening effect.

Recent studies have proposed improving Laser Speckle Contrast Imaging (LSCI) by using polarimetric filtering to isolate multiply scattered photons from moving red blood cells (RBCs), an approach referred to as Laser Speckle Orthogonal Contrast Imaging (LSOCI). This reliance on multiple scattering enables the development of a calibration method based on a moving reference sample, chosen to generate dynamic circular Gaussian speckle fields that replicate the statistical properties of RBC scattering in both intensity and the distribution of polarization states. Assuming that multiply scattered photons from both RBCs and the reference sample exhibit a homogeneous distribution of polarization states over the Poincare sphere, the proposed calibration links in vivo speckle contrast reduction in a bijective manner to an equivalent speed of the reference sample. We demonstrate that this equivalent-velocity metric yields consistent in vivo measurements across distinct instruments despite the use of different laser spectral widths, thereby providing a standardized and transferable means to quantify microcirculation activity.

Digital holographic microscopy systems in a common-path configuration, compared to systems with a separate reference arm, offer a compact design and resistance to disturbances. They can operate with partially coherent illumination, reducing speckle noise. However, they are limited by the overlapping of the object beam and its laterally shifted replica. As a result, images from different regions of the object overlap on the detector, preventing imaging of dense samples. We present the wavelength-scanning replica-removal method, which solves this problem by enabling the separation of information from both replicas and thereby doubling the effective field of view (FOV). The wavelength-scanning multi-shear replica removal algorithm plays a key role in reconstructing the undisturbed phase from a series of holograms recorded with variable shears. The shear value is controlled by changing the illumination wavelength. This enabled the development of two measurement modes: time-domain wavelength scanning for high-quality imaging, and a single-shot mode with frame division into color channels to improve temporal resolution. The method was validated using resolution tests and biological samples - neurons and dynamic yeast cultures. By combining the advantages of the common-path configuration with dense-structure imaging and dynamic processes, the proposed method constitutes a versatile tool for quantitative phase microscopy.

Beam shaping of ultra-short pulses is essential for medical ultrasound, where single-cycle excitations are required to achieve high axial resolution and improve frame rate. Conventional methods, such as the Gerchberg-Saxton (GS) algorithm or more recent deep learning approaches, are generally effective for continuous-wave excitation but degrade significantly under single-cycle conditions. In diagnostic imaging, high frame rate is critical for applications demanding rapid scanning. In this context, multi-line transmission (MLT) leverages beam shaping to synthesize multiple simultaneous foci, thereby increasing frame rate. In parallel, structured illumination methods for super-resolution and acoustical holography likewise depend on actively shaping single-cycle pulses to produce controlled patterns, highlighting the need for precise short-pulse beam shaping. To address this challenge, we introduce the spatio-temporal adaptive reconstruction (STAR) algorithm, which performs active beam shaping directly in the time domain by integrating the generalized angular spectrum method (GASM) into an iterative optimization scheme. STAR enforces constraints on both the transducer and focal planes, enabling accurate control of single-cycle excitations. Simulations showed that STAR consistently outperformed GS for multi-focus patterns. For example, in a four-foci configuration, STAR achieved a correlation of 0.80 compared to 0.64 for GS, with significantly improved uniformity across focal peaks. Resolution analysis demonstrated that STAR reduced the minimum distinguishable foci spacing from 1.09 mm with GS to 0.87 mm. Experimental hydrophone measurements confirmed these improvements. Across multi-foci patterns, STAR produced more distinct and balanced foci compared to those observed with GS. These results demonstrate that STAR provides robust and efficient active beam shaping of single-cycle pulses, maintaining accuracy across different depths and frequencies for diagnostic applications.

The resolution of 3D Ultrasound Localization Microscopy (ULM) is determined by acquisition parameters such as frequency and transducer geometry but also by microbubble (MB) concentration, which is also linked to the total acquisition time needed to sample the vascular tree at different scales. In this study, we introduce a novel 3D anatomically- and physiologically-realistic ULM simulation framework based on two-photon microscopy (2PM) and in-vivo MB perfusion dynamics. As a proof of concept, using metrics such as MB localization error, MB count and network filling, we could quantify the effect of MB concentration and PSF volume by varying probe transmit frequency (3-15 MHz). We find that while low frequencies can achieve sub-wavelength resolution as predicted by theory, they are also associated with prolonged acquisition times to map smaller vessels, thus limiting effective resolution. A linear relationship was found between maximal MB concentration and inverse point spread function (PSF) volume. Since inverse PSF volume roughly scales cubically with frequency, the reconstruction of the equivalent of 10 minutes at 15 MHz would require hours at 3 MHz. We expect that these findings can be leveraged to achieve effective reconstruction and serve as a guide for choosing optimal MB concentrations in ULM.

Optical coherence tomography (OCT) images are corrupted by multiplicative generalized gamma distributed speckle noise that significantly degrades the contrast to noise ratio (CNR) of microstructural compartments in biological applications. This work proposes a novel algorithm to optimize the negative log likelihood of the spatial distribution of speckle. Specifically, the proposed method formulates a penalized negative log likelihood (P-NLL) cost function and proposes a majorize-minimize-based optimization method that removes speckle from OCT images. The optimization reduces to solving an iterative gradient descent problem. We demonstrate the usefulness of the proposed method by removing speckle in OCT images of uniform phantoms with varying scattering coefficients and human brain tissue.

Holographic Tomography (HT) is an emerging label-free technique for microscopic bioimaging applications, that allows reconstructing the three-dimensional (3D) refractive index (RI) distribution of biological specimens. Recently, an in-flow HT technique has been proposed in which multiple digital holograms are recorded at different viewing angles around the sample while it flows and rotates within a microfluidic channel. However, unlike conventional HT methods, there is no a priori information about cell 3D orientations, that are instead requested to perform any tomographic algorithm. Here we investigate a tracking-based rolling angles recovery method, showing robustness against the samples features. It is based on a phase images similarity metric recently demonstrated, that exploits the local contrast phase measurements to recognize a full cell rotation within the microfluidic channel. Hence, the orientations of the flowing cells are retrieved from their positions, which are in turn computed through the 3D holographic tracking. The performances of the rolling angles recovery method have been assessed both numerically, by simulating a 3D cell phantom, and experimentally, by reconstructing the 3D RI tomograms of two cancer cells. Both the numerical and the experimental analysis have been performed at different spatial resolutions. This rolling angles recovery method, not depending on the cell shapes, the RI contents, and the optical experimental conditions, could pave the way to the study of circulating tumor cells (CTCs) in the challenging tool of liquid biopsy.