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Non-alcoholic fatty liver disease (NAFLD) is an umbrella term referring to a group of conditions associated to fat deposition and damage of liver tissue. Early detection of fat accumulation is essential to avoid progression of NAFLD to serious pathological stages such as liver cirrhosis and hepatocellular carcinoma. We exploited the unique capabilities of transmission-reflection optoacoustic ultrasound (TROPUS), which combines the advantages of optical and acoustic contrasts, for an early-stage multi-parametric assessment of NAFLD in mice. The multispectral optoacoustic imaging allowed for spectroscopic differentiation of lipid content, as well as the bio-distributions of oxygenated and deoxygenated hemoglobin in liver tissues in vivo. The pulse-echo (reflection) ultrasound (US) imaging further provided a valuable anatomical reference whilst transmission US facilitated the mapping of speed of sound changes in lipid-rich regions, which was consistent with the presence of macrovesicular hepatic steatosis in the NAFLD livers examined with ex vivo histological staining. The proposed multimodal approach facilitates quantification of liver abnormalities at early stages using a variety of optical and acoustic contrasts, laying the ground for translating the TROPUS approach toward diagnosis and monitoring NAFLD in patients.

Reflection ultrasound computed tomography (RUCT) attains optimal image quality from objects that can be fully accessed from multiple directions, such as the human breast or small animals. Owing to the full-view tomography approach based on the compounding of images taken from multiple angles, RUCT effectively mitigates several deficiencies afflicting conventional pulse-echo ultrasound (US) systems, such as speckle patterns and interuser variability. On the other hand, the small interelement pitch required to fulfill the spatial sampling criterion in the circular transducer configuration used in RUCT typically implies the use of an excessive number of independent array elements. This increases the system's complexity and costs, and limits the achievable imaging speed. Here, we explore acquisition schemes that enable RUCT imaging with the reduced number of transmit/receive elements. We investigated the influence of the element size in transmission and reception in a ring array geometry. The performance of a sparse acquisition approach based on partial acquisition from a subset of the elements has been further assessed. A larger element size is shown to preserve contrast and resolution at the center of the field of view (FOV), while a reduced number of elements is shown to cause uniform loss of contrast and resolution across the entire FOV. The tradeoffs of achievable FOV, contrast-to-noise ratio, and temporal and spatial resolutions are assessed in phantoms and in vivo mouse experiments. The experimental analysis is expected to aid the development of optimized hardware and image acquisition strategies for RUCT and, thus, result in more affordable imaging systems facilitating wider adoption.

Ultrasound (US) and optoacoustic (OA) imaging provide complementary information for quantitative analysis of the tumor microenvironment. Herein, we demonstrate the unique capabilities of transmission-reflection optoacoustic ultrasound (TROPUS) for characterizing breast cancer in tumor-bearing mice. For this, 4 different mice featuring orthotopic tumor of different sizes were scanned with a full-ring ultrasound transducer array to simultaneously render pulse-echo US images, speed of sound (SoS) maps and OA images. The tumor size, vascular density and its elastic parameters were further quantified in the images. Our results pave the way toward clinical translation of the hybrid TROPUS imaging for tumor detection and characterization.

Intense efforts are underway to develop functional imaging modalities for capturing brain activity at the whole organ scale with high spatial and temporal resolution. Functional optoacoustic (fOA) imaging is emerging as a new tool to monitor multiple hemodynamic parameters across the mouse brain, but its sound validation against other neuroimaging modalities is often lacking. Here we investigate mouse brain responses to peripheral sensory stimulation using both fOA and functional ultrasound (fUS) imaging. The two modalities operate under similar spatio-temporal resolution regime, with a potential to provide synergistic and complementary hemodynamic readouts. Specific contralateral activation was observed with sub-millimeter spatial resolution with both methods. Sensitivity to hemodynamic activity was found to be on comparable levels, with the strongest responses obtained in the oxygenated hemoglobin channel of fOA. While the techniques attained highly correlated hemodynamic responses, the differential fOA readings of oxygenated and deoxygenated haemoglobin provided complementary information to the blood flow contrast of fUS. The multi-modal approach may thus emerge as a powerful tool providing new insights into brain function, complementing our current knowledge generated with well-established neuroimaging methods., NeuroImage, 237, ISSN:1053-8119, ISSN:1095-9572

Multispectral optoacoustic tomography (MSOT) offers the unique capability to map the distribution of spectrally distinctive endogenous and exogenous substances in heterogeneous biological tissues by exciting the sample at various wavelengths and detecting the optoacoustically-induced ultrasound waves. This powerful functional and molecular imaging capability can greatly benefit from hybridization with pulse-echo ultrasound (US), which provides additional information on tissue anatomy and blood flow. However, speed of sound variations and acoustic mismatches in the imaged object generally lead to errors in the coregistration of compounded images and loss of spatial resolution in both imaging modalities. The spatially- and wavelength-dependent light fluence attenuation further limits the quantitative capabilities of MSOT. Proper segmentation of different regions and assignment of corresponding acoustic and optical properties turns then essential for maximizing the performance of hybrid optoacoustic and ultrasound (OPUS) imaging. Particularly, accurate segmentation of the boundary of the sample can significantly improve the images rendered. Herein, we propose an automatic segmentation method based on a convolutional neural network (CNN) for segmenting the mouse boundary in a pre-clinical OPUS system. The experimental performance of the method, as characterized with the Dice coefficient metric between the network output and the ground truth (manually segmented) images, is shown to be superior than that of a state-of-the-art active contour segmentation method in a series of two-dimensional (cross-sectional) OPUS images of the mouse brain, liver and kidney regions.

We present a biosensor based on electromagnetic ring resonator for label-free detection of glucose. The sensing mechanism is based on the principle that the resonant frequencies of such structures depend on the structure geometry and the physical properties of the medium they are in, such as electrical permittivity. The sensor in this paper uses a split-ring resonator fabricated on a flame retardant four substrate via simple printed circuit board fabrication techniques. Glucose oxidase enzyme was incorporated in order to provide biospecificity for glucose. Conductive polymer poly(3,4-ethylenedioxythiophene)poly(styrenesulfonate) , also known as PEDOT:PSS, was used for the immobilization of the enzyme on sensor surface. The redshift of the resonant frequency of the sensor in response to DI water, glucose, and NaCl solutions are shown to be in agreement with simulation results and theoretical expectations. In the presence of the enzyme, the sensor loaded with a glucose solution was observed to experience a resonant frequency shift of 17.5 MHz in 15 min, whereas other reagents such as fructose, sucrose, and NaCl did not respond significantly, confirming the biospecificity. The sensor was measured to have a sensitivity of 0.107 MHz/mgml $^{-1}$ .

Multispectral optoacoustic tomography (MSOT) is a fast-developing imaging modality, combining the high contrast from optical tissue excitation with the high resolution and penetration depth of ultrasound detection. Since light is subject to absorption and scattering when travelling through tissue, adequate knowledge of the spatial fluence distribution is required in order to ensure quantification accuracy of MSOT. In order to reduce the systematic errors in spectral recovery due to fluence and to provide a visually more homogeneous image, correction for fluence is commonly performed on reconstructed images using one of the state-of-the-art methods. These require, as input, information on illumination geometry (a priori known from the system design) as well as spatial reference of an object in a form of either a binary map (assuming uniform optical properties), or a label map, in a more complex scenario of multiple regions with different optical properties. In order to generate such a map, manual segmentation is commonly used by delineating the outer border of the mouse body or major organs present in the slice, which is a time-consuming procedure, not efficient procedure, prone to operator errors. Here we evaluate methods for semi- and fully-automatic segmentation of hybrid optoacoustic and ultrasound images and characterize the performance of the methods using quantitative metrics for evaluating medical image segmentation against the ground truth obtained by manual segmentation.