Non-invasive measurements of blood glucose levels by time-gating mid-infrared optoacoustic signals.

Non-invasive glucose monitoring (NIGM) represents an attractive alternative to finger pricking for blood glucose assessment and management of diabetes. Nevertheless, current NIGM techniques do not measure glucose concentrations in blood but rely on indirect bulk measurement of glucose in interstitial fluid, where glucose is diluted and glucose dynamics are different from those in the blood, which impairs NIGM accuracy. Here we introduce a new biosensor, termed depth-gated mid-infrared optoacoustic sensor (DIROS), which allows, for the first time, non-invasive glucose detection in blood-rich volumes in the skin. DIROS minimizes interference caused by the stratum corneum and other superficial skin layers by time-gating mid-infrared optoacoustic signals to enable depth-selective localization of glucose readings in skin. In measurements on the ears of (female) mice, DIROS displays improved accuracy over bulk-tissue glucose measurements. Our work demonstrates how signal localization can improve NIGM accuracy and positions DIROS as a holistic approach, with high translational potential, that addresses a key limitation of current NIGM methods.

Spotlight on Nerves: Portable Multispectral Optoacoustic Imaging of Peripheral Nerve Vascularization and Morphology.

Various morphological and functional parameters of peripheral nerves and their vascular supply are indicative of pathological changes due to injury or disease. Based on recent improvements in optoacoustic image quality, the ability of multispectral optoacoustic tomography, to investigate the vascular environment and morphology of peripheral nerves is explored in vivo in a pilot study on healthy volunteers in tandem with ultrasound imaging (OPUS). The unique ability of optoacoustic imaging to visualize the vasa nervorum by observing intraneural vessels in healthy nerves is showcased in vivo for the first time. In addition, it is demonstrated that the label-free spectral optoacoustic contrast of the perfused connective tissue of peripheral nerves can be linked to the endogenous contrast of hemoglobin and collagen. Metrics are introduced to analyze the composition of tissue based on its optoacoustic contrast and show that the high-resolution spectral contrast reveals specific differences between nervous tissue and reference tissue in the nerve's surrounding. How this showcased extraction of peripheral nerve characteristics using multispectral optoacoustic and ultrasound imaging could offer new insights into the pathophysiology of nerve damage and neuropathies, for example, in the context of diabetes is discussed.

Towards in vivo characterization of thyroid nodules suspicious for malignancy using multispectral optoacoustic tomography.

PURPOSE: Patient-tailored management of thyroid nodules requires improved risk of malignancy stratification by accurate preoperative nodule assessment, aiming to personalize decisions concerning diagnostics and treatment. Here, we perform an exploratory pilot study to identify possible patterns on multispectral optoacoustic tomography (MSOT) for thyroid malignancy stratification. For the first time, we directly correlate MSOT images with histopathology data on a detailed level. METHODS: We use recently enhanced data processing and image reconstruction methods for MSOT to provide next-level image quality by means of improved spatial resolution and spectral contrast. We examine optoacoustic features in thyroid nodules associated with vascular patterns and correlate these directly with reference histopathology. RESULTS: Our methods show the ability to resolve blood vessels with diameters of 250 µm at depths of up to 2 cm. The vessel diameters derived on MSOT showed an excellent correlation (R2-score of 0.9426) with the vessel diameters on histopathology. Subsequently, we identify features of malignancy observable in MSOT, such as intranodular microvascularity and extrathyroidal extension verified by histopathology. Despite these promising features in selected patients, we could not determine statistically relevant differences between benign and malignant thyroid nodules based on mean oxygen saturation in thyroid nodules. Thus, we illustrate general imaging artifacts of the whole field of optoacoustic imaging that reduce image fidelity and distort spectral contrast, which impedes quantification of chromophore presence based on mean concentrations. CONCLUSION: We recommend examining optoacoustic features in addition to chromophore quantification to rank malignancy risk. We present optoacoustic images of thyroid nodules with the highest spatial resolution and spectral contrast to date, directly correlated to histopathology, pushing the clinical translation of MSOT.

Fast histological assessment of adipose tissue inflammation by label-free mid-infrared optoacoustic microscopy.

Conventional histology, as well as immunohistochemistry or immunofluorescence, enables the study of morphological and phenotypical changes during tissue inflammation with single-cell accuracy. However, although highly specific, such techniques require multiple time-consuming steps to apply exogenous labels, which might result in morphological deviations from native tissue structures. Unlike these techniques, mid-infrared (mid-IR) microspectroscopy is a label-free optical imaging method that retrieves endogenous biomolecular contrast without altering the native composition of the samples. Nevertheless, due to the strong optical absorption of water in biological tissues, conventional mid-IR microspectroscopy has been limited to dried thin (5-10 µm) tissue preparations and, thus, it also requires time-consuming steps-comparable to conventional imaging techniques. Here, as a step towards label-free analytical histology of unprocessed tissues, we applied mid-IR optoacoustic microscopy (MiROM) to retrieve intrinsic molecular contrast by vibrational excitation and, simultaneously, to overcome water-tissue opacity of conventional mid-IR imaging in thick (mm range) tissues. In this proof-of-concept study, we demonstrated application of MiROM for the fast, label-free, non-destructive assessment of the hallmarks of inflammation in excised white adipose tissue; i.e., formation of crown-like structures and changes in adipocyte morphology.

Deep-Learning-Based Electrical Noise Removal Enables High Spectral Optoacoustic Contrast in Deep Tissue.

Image contrast in multispectral optoacoustic tomography (MSOT) can be severely reduced by electrical noise and interference in the acquired optoacoustic signals. Previously employed signal processing techniques have proven insufficient to remove the effects of electrical noise because they typically rely on simplified models and fail to capture complex characteristics of signal and noise. Moreover, they often involve time-consuming processing steps that are unsuited for real-time imaging applications. In this work, we develop and demonstrate a discriminative deep learning approach to separate electrical noise from optoacoustic signals prior to image reconstruction. The proposed deep learning algorithm is based on two key features. First, it learns spatiotemporal correlations in both noise and signal by using the entire optoacoustic sinogram as input. Second, it employs training on a large dataset of experimentally acquired pure noise and synthetic optoacoustic signals. We validated the ability of the trained model to accurately remove electrical noise on synthetic data and on optoacoustic images of a phantom and the human breast. We demonstrate significant enhancements of morphological and spectral optoacoustic images reaching 19% higher blood vessel contrast and localized spectral contrast at depths of more than 2 cm for images acquired in vivo. We discuss how the proposed denoising framework is applicable to clinical multispectral optoacoustic tomography and suitable for real-time operation.

Disentangling the Frequency Content in Optoacoustics.

Signals acquired by optoacoustic tomography systems have broadband frequency content that encodes information about structures on different physical scales. Concurrent processing and rendering of such broadband signals may result in images with poor contrast and fidelity due to a bias towards low frequency contributions from larger structures. This problem cannot be addressed by filtering different frequency bands and reconstructing them individually, as this procedure leads to artefacts due to its incompatibility with the entangled frequency content of signals generated by structures of different sizes. Here we introduce frequency-band model-based (fbMB) reconstruction to separate frequency-band-specific optoacoustic image components during image formation, thereby enabling structures of all sizes to be rendered with high fidelity. In order to disentangle the overlapping frequency content of image components, fbMB uses soft priors to achieve an optimal trade-off between localization of the components in frequency bands and their structural integrity. We demonstrate that fbMB produces optoacoustic images with improved contrast and fidelity, which reveal anatomical structures in in vivo images of mice in unprecedented detail. These enhancements further improve the accuracy of spectral unmixing in small vasculature. By offering a precise treatment of the frequency components of optoacoustic signals, fbMB improves the quality, accuracy, and quantification of optoacoustic images and provides a method of choice for optoacoustic reconstructions.

Image processing improvements afford second-generation handheld optoacoustic imaging of breast cancer patients.

Background: Since the initial breast transillumination almost a century ago, breast cancer imaging using light has been considered in different implementations aiming to improve diagnostics, minimize the number of available biopsies, or monitor treatment. However, due to strong photon scattering, conventional optical imaging yields low resolution images, challenging quantification and interpretation. Optoacoustic imaging addresses the scattering limitation and yields high-resolution visualization of optical contrast, offering great potential value for breast cancer imaging. Nevertheless, the image quality of experimental systems remains limited due to a number of factors, including signal attenuation with depth and partial view angle and motion effects, particularly in multi-wavelength measurements. Methods: We developed data analytics methods to improve the accuracy of handheld optoacoustic breast cancer imaging, yielding second-generation optoacoustic imaging performance operating in tandem with ultrasonography. Results: We produced the most advanced images yet with handheld optoacoustic examinations of the human breast and breast cancer, in terms of resolution and contrast. Using these advances, we examined optoacoustic markers of malignancy, including vasculature abnormalities, hypoxia, and inflammation, on images obtained from breast cancer patients. Conclusions: We achieved a new level of quality for optoacoustic images from a handheld examination of the human breast, advancing the diagnostic and theranostic potential of the hybrid optoacoustic-ultrasound (OPUS) examination over routine ultrasonography.

Weighted model-based optoacoustic reconstruction for partial-view geometries.

Acoustic heterogeneities in biological samples are known to cause artifacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artifacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this article, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artifacts in reconstructed images without distorting structures or boundaries, compared with both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artifacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation.

Label-free concurrent 5-modal microscopy (Co5M) resolves unknown spatio-temporal processes in wound healing.

The non-invasive investigation of multiple biological processes remains a methodological challenge as it requires capturing different contrast mechanisms, usually not available with any single modality. Intravital microscopy has played a key role in dynamically studying biological morphology and function, but it is generally limited to resolving a small number of contrasts, typically generated by the use of transgenic labels, disturbing the biological system. We introduce concurrent 5-modal microscopy (Co5M), illustrating a new concept for label-free in vivo observations by simultaneously capturing optoacoustic, two-photon excitation fluorescence, second and third harmonic generation, and brightfield contrast. We apply Co5M to non-invasively visualize multiple wound healing biomarkers and quantitatively monitor a number of processes and features, including longitudinal changes in wound shape, microvascular and collagen density, vessel size and fractality, and the plasticity of sebaceous glands. Analysis of these parameters offers unique insights into the interplay of wound closure, vasodilation, angiogenesis, skin contracture, and epithelial reformation in space and time, inaccessible by other methods. Co5M challenges the conventional concept of biological observation by yielding multiple simultaneous parameters of pathophysiological processes in a label-free mode.

Individual transducer impulse response characterization method to improve image quality of array-based handheld optoacoustic tomography.

The physical properties of each transducer element play a vital role in the quality of images generated in optoacoustic (photoacoustic) tomography using transducer arrays. Thorough experimental characterization of such systems is often laborious and impractical. A shortcoming of the existing impulse response correction methods, however, is the assumption that all transducers in the array are identical and therefore share one electrical impulse response (EIR). In practice, the EIRs of the transducer elements in the array vary, and the effect of this element-to-element variability on image quality has not been investigated so far, to the best of our knowledge. We hereby propose a robust EIR derivation for individual transducer elements in an array using sparse measurements of the total impulse response (TIR) and by solving the linear system for temporal convolution. Thereafter, we combine a simulated spatial impulse response with the derived individual EIRs to obtain a full characterization of the TIR, which we call individual synthetic TIR. Correcting for individual transducer responses, we demonstrate significant improvement in isotropic resolution, which further enhances the clinical potential of array-based handheld transducers.

Three-dimensional optoacoustic imaging of nailfold capillaries in systemic sclerosis and its potential for disease differentiation using deep learning.

The autoimmune disease systemic sclerosis (SSc) causes microvascular changes that can be easily observed cutaneously at the finger nailfold. Optoacoustic imaging (OAI), a combination of optical and ultrasound imaging, specifically raster-scanning optoacoustic mesoscopy (RSOM), offers a non-invasive high-resolution 3D visualization of capillaries allowing for a better view of microvascular changes and an extraction of volumetric measures. In this study, nailfold capillaries of patients with SSc and healthy controls are imaged and compared with each other for the first time using OAI. The nailfolds of 23 patients with SSc and 19 controls were imaged using RSOM. The acquired images were qualitatively compared to images from state-of-the-art imaging tools for SSc, dermoscopy and high magnification capillaroscopy. The vascular volume in the nailfold capillaries were computed from the RSOM images. The vascular volumes differ significantly between both cohorts (0.216 ± 0.085 mm3 and 0.337 ± 0.110 mm3; p < 0.0005). In addition, an artificial neural network was trained to automatically differentiate nailfold images from both cohorts to further assess whether OAI is sensitive enough to visualize anatomical differences in the capillaries between the two cohorts. Using transfer learning, the model classifies images with an area under the ROC curve of 0.897, and a sensitivity of 0.783 and specificity of 0.895. In conclusion, this study demonstrates the capabilities of RSOM as an imaging tool for SSc and establishes it as a modality that facilitates more in-depth studies into the disease mechanisms and progression.

Assessment of hessian-based Frangi vesselness filter in optoacoustic imaging.

The Hessian-based Frangi vesselness filter is commonly used to enhance vasculature in optoacoustic (photoacoustic) images, but its accuracy and limitations have never been rigorously assessed. Here we validate the ability of the filter to enhance vessel-like structures in phantoms, and we introduce an experimental approach that uses measurements before and after the administration of gold nanorods (AuNRs) to examine filter performance in vivo. We evaluate the influence of contrast, filter scales, angular tomographic coverage, out-of-plane signals and light fluence on image quality, and gain insight into the performance of the filter. We observe the generation of artifactual structures that can be misinterpreted as vessels and provide recommendations to ensure appropriate use of Frangi and other vesselness filters and avoid misinterpretation of post-processed optoacoustic images.

A Synthetic Total Impulse Response Characterization Method for Correction of Hand-Held Optoacoustic Images.

The impulse response of optoacoustic (photoacoustic) tomographic imaging system depends on several system components, the characteristics of which can influence the quality of reconstructed images. The effect of these system components on reconstruction quality have not been considered in detail so far. Here we combine sparse measurements of the total impulse response (TIR) with a geometric acoustic model to obtain a full characterization of the TIR of a handheld optoacoustic tomography system with concave limited-view acquisition geometry. We then use this synthetic TIR to reconstruct data from phantoms and healthy human volunteers, demonstrating improvements in image resolution and fidelity. The higher accuracy of optoacoustic tomographic reconstruction with TIR correction further improves the diagnostic capability of handheld optoacoustic tomographic systems.

Soft ultrasound priors in optoacoustic reconstruction: Improving clinical vascular imaging.

Using the same ultrasound detector, hybrid optoacoustic-ultrasound (OPUS) imaging provides concurrent scans of tissue slices or volumes and visualizes complementary sound- and light-based contrast at similar resolutions. In addition to the benefit of hybrid contrast, spatial co-registration enables images from one modality to be employed as prior information for improving an aspect of the performance of the other modality. We consider herein a handheld OPUS system and utilize structural information from ultrasound images to guide regional Laplacian regularization-based reconstruction of optoacoustic images. Using phantoms and data from OPUS scans of human radial and carotid arteries, we show that ultrasound-driven optoacoustic inversion reduces limited-view artefacts and improves image contrast. In phantoms, prior-integrated reconstruction leads to a 50 % higher contrast-to-noise ratio (CNR) of the image than standard reconstruction, and a 17 % higher structural similarity (SSIM) index. In clinical data, prior-integrated reconstruction detects deep-seated radial arteries with higher CNR than the standard method at three different depths. In this way, the prior-integrated method offers unique insights into atherosclerotic carotid plaques in humans (with p<0.01 between patients and healthy volunteers), potentially paving the way for new abilities in vascular imaging and more generally in optoacoustic imaging.

Bragg-von Laue diffraction generalized to twisted X-rays.

A pervasive limitation of nearly all practical X-ray methods for the determination of the atomic scale structure of matter is the need to crystallize the molecule, compound or alloy in a sufficiently large (∼ 10 × 10 × 10 µm) periodic array. In this paper an X-ray method applicable to structure determination of some important noncrystalline structures is proposed. It is designed according to a strict mathematical analog of von Laue's method, but replacing the translation group by another symmetry group, and simultaneously replacing plane waves by different exact closed-form solutions of Maxwell's equations. Details are presented for helical structures like carbon nanotubes or filamentous viruses. In computer simulations the accuracy of the determination of structure is shown to be comparable to the periodic case.