Hybrid-array-based optoacoustic and ultrasound (OPUS) imaging of biological tissues.

Hybrid optoacoustic and pulse-echo ultrasound imaging is an attractive multi-modal combination owing to the highly complementary contrast of the two techniques. Efficient hybridization is often hampered by significant dissimilarities between their optimal data acquisition and image formation strategies. Herein, we introduce an approach for combined optoacoustic and ultrasound imaging based on a plano-concave detector array design with a non-uniform pitch distribution. The hybrid design optimized for both modalities allows for maintaining an extended field of view for efficient ultrasound navigation while simultaneously providing broad tomographic coverage for optimal optoacoustic imaging performance. Imaging sessions performed in tissue-mimicking phantoms and healthy volunteers demonstrate that the suggested approach renders an enhanced imaging performance as compared with the previously reported hybrid optoacoustic and ultrasound imaging approaches. Thus, it can greatly facilitate clinical translation of the optoacoustic imaging technology by means of its efficient combination with ultrasonography, a well-established clinical imaging modality

Whole-body live mouse imaging by hybrid reflection-mode ultrasound and optoacoustic tomography.

We present a hybrid preclinical imaging scanner that optimally supports image acquisition in both reflection-mode ultrasonography and optoacoustic (OA) tomography modes. The system comprises a quasi-full-ring tomographic geometry capable of the simultaneous dual-mode imaging through entire cross sections of mice with in-plane spatial resolution in the range of 150 and 350 mu m in the respective OA and ultrasound (US) imaging modes with an imaging speed of up to 10 two-dimensional frames per second. Three-dimensional whole-body data is subsequently rendered by rapid scanning of the imaged plane. The system further incorporates rapid laser wavelength tuning for real-time acquisition of multispectral OA data, which enables studies of longitudinal dynamics as well as fast kinetics and biodistribution of contrast agents. In vivo imaging performance is demonstrated by label-free hybrid anatomical scans through living mice, as well as real-time visualization of optical contrast agent perfusion. By setting new standards for wholebody tomographic imaging performance in both the OA and pulse-echo US modes, the developed hybrid imaging approach is expected to benefit numerous applications where the availability of high-quality structural information provided by the tomographic reflection-mode US can ease interpretation of the functional and molecular imaging results attained by the OA modality

Combined pulse-echo ultrasound and multispectral optoacoustic tomography with a multi-segment detector array.

The high complementarity of ultrasonography and optoacoustic tomography has prompted the development of combined approaches that utilize the same transducer array for detecting both optoacoustic and pulse-echo ultrasound responses from tissues. Yet, due to the fundamentally different physical contrast and image formation mechanisms, the development of detection technology optimally suited for image acquisition in both modalities remains a major challenge. Herein, we introduce a multi-segment detector array approach incorporating array segments of linear and concave geometry to optimally support both ultrasound and optoacoustic image acquisition. The various image rendering strategies are tested and optimized in numerical simulations and calibrated tissue-mimicking phantom experiments. We subsequently demonstrate real-time hybrid optoacoustic ultrasound (OPUS) image acquisition in a healthy volunteer. The new approach enables the acquisition of highquality anatomical data by both modalities complemented by functional information on blood oxygenation status provided by the multispectral optoacoustic tomography

Quantitative image correction using semi- and fully-automatic segmentation of hybrid optoacoustic and ultrasound images.

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 timeconsuming procedure, not efficient procedure, prone to operator errors. Here we evaluate methods for semiand 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

Multi-segment detector array for hybrid reflection-mode ultrasound and optoacoustic tomography.

The complementary contrast features of the optoacoustic (OA) and pulse-echo ultrasound (US) modalities make the combined usage of these imaging technologies highly advantageous. Due to the fundamentally different physical contrast mechanisms development of a detector array optimally suited for both modalities is one of the challenges to efficient implementation of a single OA-US imaging device. We demonstrate imaging performance of the first hybrid detector array whose novel design, incorporating array segments of linear and concave geometry, optimally supports image acquisition in both reflection-mode ultrasonography and optoacoustic tomography modes

Hybrid multispectral optoacoustic and ultrasound tomography for morphological and physiological brain imaging.

Expanding usage of small animal models in biomedical research necessitates development of technologies for structural, functional, or molecular imaging that can be readily integrated in the biological laboratory. Herein, we consider dual multispectral optoacoustic (OA) and ultrasound tomography based on curved ultrasound detector arrays and describe the performance achieved for hybrid morphological and physiological brain imaging of mice in vivo. We showcase coregistered hemodynamic parameters resolved by OA tomography under baseline conditions and during alterations of blood oxygen saturation. As an internal reference, we provide imaging of abdominal organs. We illustrate the performance advantages of hybrid curved detector ultrasound and OA tomography and discuss immediate and long-term implications of our findings in the context of animal and human studies

Hybrid optoacoustic tomography and pulse-echo ultrasonography using concave arrays.

Implementation of hybrid imaging using optoacoustic tomography (OAT) and ultrasound (US) brings together the important advantages and complementary features of both methods. However, the fundamentally different physical contrast mechanisms of the two modalities may impose significant difficulties in the optimal tomographic data acquisition and image formation strategies. We investigate the applicability of the commonly applied imaging geometries for acquisition and reconstruction of hybrid optoacoustic tomography and pulse-echo ultrasound (OPUS) images. Optimization of the ultrasound image formation strategy using concave array geometry was implemented using a synthetic aperture method combined with spatial compounding. Experimental validation was performed using a custom-made multiplexer unit executing switching between the two modalities employing the same transducer array. A variety of array probes with different angular coverages were subsequently tested, including arrays for clinical hand-held imaging as well as stationary arrays for tomographic small animal imaging. The results demonstrate that acquisition of OAT data by mere addition of an illumination source to the common US linear array geometry may result in significant limited-view artifacts and overall loss of image quality. On the other hand, unsatisfactory US image quality is achieved with tomographic arrays solely optimized for OAT image acquisition without considering the optimal transmit-receive beamforming parameters. Optimal selection of the array pitch size, tomographic coverage and spatial compounding parameters has achieved here an accurate hybrid imaging performance, which was experimentally showcased in tissuemimicking phantoms, post-mortem mice, and hand-held imaging of a healthy volunteer. The efficient combination of the two modalities in a single imaging device reveals the true power of functional and molecular imaging capacities of OAT in addition to the morphological and functional imaging capabilities of US

Transmission-reflection optoacoustic ultrasound (TROPUS) imaging of mammary tumors.

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