DeepMB: Deep neural network for real-time optoacoustic image reconstruction with adjustable speed of sound

Multispectral optoacoustic tomography (MSOT) is a high-resolution functional imaging modality that can non-invasively access a broad range of pathophysiological phenomena by quantifying the contrast of endogenous chromophores in tissue. Real-time imaging is imperative to translate MSOT into clinical imaging, visualize dynamic pathophysiological changes associated with disease progression, and enable in situ diagnoses. Model-based reconstruction affords state-of-the-art optoacoustic images; however, the image quality provided by model-based reconstruction remains inaccessible during real-time imaging because the algorithm is iterative and computationally demanding. Deep learning affords faster reconstruction, but the lack of ground truth training data can lead to reduced image quality for in vivo data. We introduce a framework, termed DeepMB, that achieves accurate optoacoustic image reconstruction for arbitrary input data in 31 ms per image by expressing model-based reconstruction with a deep neural network. DeepMB facilitates accurate generalization to experimental test data through training on signals synthesized from real-world images and ground truth images generated by model-based reconstruction. The framework affords in-focus images for a broad range of anatomical locations because it supports dynamic adjustment of the reconstruction speed of sound during imaging. Furthermore, DeepMB is compatible with the data rates and image sizes of modern multispectral optoacoustic tomography scanners. We evaluate DeepMB on a diverse dataset of in vivo images and demonstrate that the framework reconstructs images 1000 times faster than the iterative model-based reference method while affording near-identical image qualities. Accurate and real-time image reconstructions with DeepMB can enable full access to the high-resolution and multispectral contrast of handheld optoacoustic tomography

Eigenspectra optoacoustic tomography achieves quantitative blood oxygenation imaging deep in tissues

Light propagating in tissue attains a spectrum that varies with location due to wavelength-dependent fluence attenuation by tissue optical properties, an effect that causes spectral corruption. Predictions of the spectral variations of light fluence in tissue are challenging since the spatial distribution of optical properties in tissue cannot be resolved in high resolution or with high accuracy by current methods. Spectral corruption has fundamentally limited the quantification accuracy of optical and optoacoustic methods and impeded the long sought-after goal of imaging blood oxygen saturation (sO2) deep in tissues; a critical but still unattainable target for the assessment of oxygenation in physiological processes and disease. We discover a new principle underlying light fluence in tissues, which describes the wavelength dependence of light fluence as an affine function of a few reference base spectra, independently of the specific distribution of tissue optical properties. This finding enables the introduction of a previously undocumented concept termed eigenspectra Multispectral Optoacoustic Tomography (eMSOT) that can effectively account for wavelength dependent light attenuation without explicit knowledge of the tissue optical properties. We validate eMSOT in more than 2000 simulations and with phantom and animal measurements. We find that eMSOT can quantitatively image tissue sO2 reaching in many occasions a better than 10-fold improved accuracy over conventional spectral optoacoustic methods. Then, we show that eMSOT can spatially resolve sO2 in muscle and tumor; revealing so far unattainable tissue physiology patterns. Last, we related eMSOT readings to cancer hypoxia and found congruence between eMSOT tumor sO2 images and tissue perfusion and hypoxia maps obtained by correlative histological analysis

Characterization of Brown Adipose Tissue in a Diabetic Mouse Model with Spiral Volumetric Optoacoustic Tomography

PURPOSE Diabetes is associated with a deterioration of the microvasculature in brown adipose tissue (BAT) and with a decrease in its metabolic activity. Multispectral optoacoustic tomography has been recently proposed as a new tool capable of differentiating healthy and diabetic BAT by observing hemoglobin gradients and microvasculature density in cross-sectional (2D) views. We report on the use of spiral volumetric optoacoustic tomography (SVOT) for an improved characterization of BAT. PROCEDURES A streptozotocin-induced diabetes model and control mice were scanned with SVOT. Volumetric oxygen saturation (sO) as well as total blood volume (TBV) in the subcutaneous interscapular BAT (iBAT) was quantified. Segmentation further enabled separating feeding and draining vessels from the BAT anatomical structure. RESULTS Scanning revealed a 46 % decrease in TBV and a 25 % decrease in sO in the diabetic iBAT with respect to the healthy control. CONCLUSIONS These results suggest that SVOT may serve as an effective tool for studying the effects of diabetes on BAT. The volumetric optoacoustic imaging probe used for the SVOT scans can be operated in a handheld mode, thus potentially providing a clinical translation route for BAT-related studies with this imaging technology

High resolution tumor targeting in living mice by means of multispectral optoacoustic tomography

BACKGROUND: Tumor targeting is of high clinical and biological relevance, and major efforts have been made to develop molecular imaging technologies for visualization of the disease markers in tissue. Of particular interest is apoptosis which has a profound role within tumor development and has significant effect on cancer malignancy. METHODS: Herein, we report on targeting of phosphatidylserine-exposing cells within live tumor allograft models using a synthetic near infrared zinc(II)-dipicolylamine probe. Visualization of the probe biodistribution is performed with whole body multispectral optoacoustic tomography (MSOT) system and subsequently compared to results attained by planar and tomographic fluorescence imaging systems. RESULTS: Compared to whole body optical visualization methods, MSOT attains remarkably better imaging capacity by delivering high-resolution scans of both disease morphology and molecular function in real time. Enhanced resolution of MSOT clearly showed that the probe mainly localizes in the vessels surrounding the tumor, suggesting that its tumor selectivity is gained by targeting the phosphatidylserine exposed on the surface of tumor vessels. CONCLUSIONS: The current study demonstrates the high potential of MSOT to broadly impact the fields of tumor diagnostics and preclinical drug development

Steady-state total diffuse reflectance with an exponential decaying source

The increasing preclinical and clinical utilization of digital cameras for photographic measurements of tissue conditions motivates the study of reflectance measurements obtained with planar illumination. We examine herein a formula that models the total diffuse reflectance measured from a semi-infinite medium using an exponentially decaying source, assuming continuous plane wave epi-illumination. The model is validated with experimental reflectance measurements from tissue mimicking phantoms. The need for adjusting the blood absorption spectrum due to pigment packaging is discussed along with the potential applications of the proposed formulation.This research PBGA was supported in part by a Marie Curie Intra European Fellowship within the 7th European Community Framework Program. J. R. acknowledges a Marie Curie CIG grant

Mapping Molecular Agents Distributions in Whole Mice Hearts Using Born-Normalized Optical Projection Tomography

To date there is a lack of tools to map the spatio-temporal dynamics of diverse cells in experimental heart models. Conventional histology is labor intensive with limited coverage, whereas many imaging techniques do not have sufficiently high enough spatial resolution to map cell distributions. We have designed and built a high resolution, dual channel Born-normalized near-infrared fluorescence optical projection tomography system to quantitatively and spatially resolve molecular agents distribution within whole murine heart. We validated the use of the system in a mouse model of monocytes/macrophages recruitment during myocardial infarction. While acquired, data were processed and reconstructed in real time. Tomographic analysis and visualization of the key inflammatory components were obtained via a mathematical formalism based on left ventricular modeling. We observed extensive monocyte recruitment within and around the infarcted areas and discovered that monocytes were also extensively recruited into non-ischemic myocardium, beyond that of injured tissue, such as the septum

Standardization and implementation of fluorescence molecular endoscopy in the clinic

Significance: Near-infrared fluorescence molecular endoscopy (NIR-FME) is an innovative technique allowing for in vivo visualization of molecular processes in hollow organs. Despite its potential for clinical translation, NIR-FME still faces challenges, for example, the lack of consensus in performing quality control and standardization of procedures and systems. This may hamper the clinical approval of the technology by authorities and its acceptance by endoscopists. Until now, several clinical trials using NIR-FME have been performed. However, most of these trials had different study designs, making comparison difficult. Aim: We describe the need for standardization in NIR-FME, provide a pathway for setting up a standardized clinical study, and describe future perspectives for NIR-FME. Body: Standardization is challenging due to many parameters. Invariable parameters refer to the hardware specifications. Variable parameters refer to movement or tissue optical properties. Phantoms can be of aid when defining the influence of these variables or when standardizing a procedure. Conclusion: There is a need for standardization in NIR-FME and hurdles still need to be overcome before a widespread clinical implementation of NIR-FME can be realized. When these hurdles are overcome, clinical outcomes can be compared and systems can be benchmarked, enabling clinical implementation