Dermal features derived from optoacoustic tomograms via machine learning correlate microangiopathy phenotypes with diabetes stage.

Skin microangiopathy has been associated with diabetes. Here we show that skin-microangiopathy phenotypes in humans can be correlated with diabetes stage via morphophysiological cutaneous features extracted from raster-scan optoacoustic mesoscopy (RSOM) images of skin on the leg. We obtained 199 RSOM images from 115 participants (40 healthy and 75 with diabetes), and used machine learning to segment skin layers and microvasculature to identify clinically explainable features pertaining to different depths and scales of detail that provided the highest predictive power. Features in the dermal layer at the scale of detail of 0.1-1 mm (such as the number of junction-to-junction branches) were highly sensitive to diabetes stage. A 'microangiopathy score' compiling the 32 most-relevant features predicted the presence of diabetes with an area under the receiver operating characteristic curve of 0.84. The analysis of morphophysiological cutaneous features via RSOM may allow for the discovery of diabetes biomarkers in the skin and for the monitoring of diabetes status.

Optoacoustic biomarkers of lipids, hemorrhage and inflammation in carotid atherosclerosis.

Imaging plays a critical role in exploring the pathophysiology and enabling the diagnostics and therapy assessment in carotid artery disease. Ultrasonography, computed tomography, magnetic resonance imaging and nuclear medicine techniques have been used to extract of known characteristics of plaque vulnerability, such as inflammation, intraplaque hemorrhage and high lipid content. Despite the plethora of available techniques, there is still a need for new modalities to better characterize the plaque and provide novel biomarkers that might help to detect the vulnerable plaque early enough and before a stroke occurs. Optoacoustics, by providing a multiscale characterization of the morphology and pathophysiology of the plaque could offer such an option. By visualizing endogenous (e.g., hemoglobin, lipids) and exogenous (e.g., injected dyes) chromophores, optoacoustic technologies have shown great capability in imaging lipids, hemoglobin and inflammation in different applications and settings. Herein, we provide an overview of the main optoacoustic systems and scales of detail that enable imaging of carotid plaques in vitro, in small animals and humans. Finally, we discuss the limitations of this novel set of techniques while investigating their potential to enable a deeper understanding of carotid plaque pathophysiology and possibly improve the diagnostics in future patients with carotid artery disease.

Clinical and Translational Imaging and Sensing of Diabetic Microangiopathy: A Narrative Review.

Microvascular changes in diabetes affect the function of several critical organs, such as the kidneys, heart, brain, eye, and skin, among others. The possibility of detecting such changes early enough in order to take appropriate actions renders the development of appropriate tools and techniques an imperative need. To this end, several sensing and imaging techniques have been developed or employed in the assessment of microangiopathy in patients with diabetes. Herein, we present such techniques; we provide insights into their principles of operation while discussing the characteristics that make them appropriate for such use. Finally, apart from already established techniques, we present novel ones with great translational potential, such as optoacoustic technologies, which are expected to enter clinical practice in the foreseeable future.

Opening a window to skin biomarkers for diabetes stage with optoacoustic mesoscopy.

Being the largest and most accessible organ of the human body, the skin could offer a window to diabetes-related complications on the microvasculature. However, skin microvasculature is typically assessed by histological analysis, which is not suited for applications to large populations or longitudinal studies. We introduce ultra-wideband raster-scan optoacoustic mesoscopy (RSOM) for precise, non-invasive assessment of diabetes-related changes in the dermal microvasculature and skin micro-anatomy, resolved with unprecedented sensitivity and detail without the need for contrast agents. Providing unique imaging contrast, we explored a possible role for RSOM as an investigational tool in diabetes healthcare and offer the first comprehensive study investigating the relationship between different diabetes complications and microvascular features in vivo. We applied RSOM to scan the pretibial area of 95 participants with diabetes mellitus and 48 age-matched volunteers without diabetes, grouped according to disease complications, and extracted six label-free optoacoustic biomarkers of human skin, including dermal microvasculature density and epidermal parameters, based on a novel image-processing pipeline. We then correlated these biomarkers to disease severity and found statistically significant effects on microvasculature parameters as a function of diabetes complications. We discuss how label-free RSOM biomarkers can lead to a quantitative assessment of the systemic effects of diabetes and its complications, complementing the qualitative assessment allowed by current clinical metrics, possibly leading to a precise scoring system that captures the gradual evolution of the disease.

Skeletal muscle optoacoustics reveals patterns of circulatory function and oxygen metabolism during exercise.

Imaging skeletal muscle function and metabolism, as reported by local hemodynamics and oxygen kinetics, can elucidate muscle performance, severity of an underlying disease or outcome of a treatment. Herein, we used multispectral optoacoustic tomography (MSOT) to image hemodynamics and oxygen kinetics within muscle during exercise. Four healthy volunteers underwent three different hand-grip exercise challenges (60s isometric, 120s intermittent isometric and 60s isotonic). During isometric contraction, MSOT showed a decrease of HbO2, Hb and total blood volume (TBV), followed by a prominent increase after the end of contraction. Corresponding hemodynamic behaviors were recorded during the intermittent isometric and isotonic exercises. A more detailed analysis of MSOT readouts revealed insights into arteriovenous oxygen differences and muscle oxygen consumption during all exercise schemes. These results demonstrate an excellent capability of visualizing both circulatory function and oxygen metabolism within skeletal muscle under exercise, with great potential implications for muscle research, including relevant disease diagnostics.

Non-invasive multispectral optoacoustic tomography resolves intrahepatic lipids in patients with hepatic steatosis.

Hepatic steatosis is characterized by intrahepatic lipid accumulation and may lead to irreversible liver damage if untreated. Here, we investigate whether multispectral optoacoustic tomography (MSOT) can offer label-free detection of liver lipid content to enable non-invasive characterization of hepatic steatosis by analyzing the spectral region around 930 nm, where lipids characteristically absorb. In a pilot study, we apply MSOT to measure liver and surrounding tissues in five patients with liver steatosis and five healthy volunteers, revealing significantly higher absorptions at 930 nm in the patients, while no significant difference was observed in the subcutaneous adipose tissue of the two groups. We further corroborated the human observations with corresponding MSOT measurements in high fat diet (HFD) - and regular chow diet (CD)-fed mice. This study introduces MSOT as a potential non-invasive and portable technique for detecting/monitoring hepatic steatosis in clinical settings, providing justification for larger studies.

Artificial intelligence in atherosclerotic disease: Applications and trends.

Atherosclerotic cardiovascular disease (ASCVD) is the most common cause of death globally. Increasing amounts of highly diverse ASCVD data are becoming available and artificial intelligence (AI) techniques now bear the promise of utilizing them to improve diagnosis, advance understanding of disease pathogenesis, enable outcome prediction, assist with clinical decision making and promote precision medicine approaches. Machine learning (ML) algorithms in particular, are already employed in cardiovascular imaging applications to facilitate automated disease detection and experts believe that ML will transform the field in the coming years. Current review first describes the key concepts of AI applications from a clinical standpoint. We then provide a focused overview of current AI applications in four main ASCVD domains: coronary artery disease (CAD), peripheral arterial disease (PAD), abdominal aortic aneurysm (AAA), and carotid artery disease. For each domain, applications are presented with refer to the primary imaging modality used [e.g., computed tomography (CT) or invasive angiography] and the key aim of the applied AI approaches, which include disease detection, phenotyping, outcome prediction, and assistance with clinical decision making. We conclude with the strengths and limitations of AI applications and provide future perspectives.

Multispectral optoacoustic tomography of lipid and hemoglobin contrast in human carotid atherosclerosis.

Several imaging techniques aim at identifying features of carotid plaque instability but come with limitations, such as the use of contrast agents, long examination times and poor portability. Multispectral optoacoustic tomography (MSOT) employs light and sound to resolve lipid and hemoglobin content, both features associated with plaque instability, in a label-free, fast and highly portable way. Herein, 5 patients with carotid atherosclerosis, 5 healthy volunteers and 2 excised plaques, were scanned with handheld MSOT. Spectral unmixing allowed visualization of lipid and hemoglobin content within three ROIs: whole arterial cross-section, plaque and arterial lumen. Calculation of the fat-blood-ratio (FBR) value within the ROIs enabled the differentiation between patients and healthy volunteers (P = 0.001) and between plaque and lumen in patients (P = 0.04). Our results introduce MSOT as a tool for molecular imaging of human carotid atherosclerosis and open new possibilities for research and clinical assessment of carotid plaques.

Multispectral optoacoustic tomography of peripheral arterial disease based on muscle hemoglobin gradients-a pilot clinical study.

BACKGROUND: Current imaging assessment of peripheral artery disease (PAD) relies on anatomical cross-sectional visualizations of the affected arteries. Multispectral optoacoustic tomography (MSOT) is a novel molecular imaging technique that provides direct and label-free visualizations of soft tissue perfusion and oxygenation. METHODS: MSOT was prospectively assessed in a pilot trial in healthy volunteers (group n1=4, mean age 31, 50% male and group n3=4, mean age 37.3, 75% male) and patients with intermittent claudication (group n2=4, mean age 72, 75% male, PAD stage IIb). We conducted cuff-induced ischemia (group n1) and resting state measurements (groups n2 and n3) over the calf region. Spatially resolved mapping of oxygenated (HbO2), deoxygenated (Hb) and total (THb) hemoglobin, as well as oxygen saturation (SO2), were measured via hand-held hybrid MSOT-Ultrasound based purely on hemoglobin contrast. RESULTS: Calf measurements in healthy volunteers revealed distinct dynamics for HbO2, Hb, THb and SO2 under cuff-induced ischemia. HbO2, THb and SO2 levels were significantly impaired in PAD patients compared to healthy volunteers (P<0.05 for all parameters). Revascularization led to significant improvements in HbO2 of the affected limb. CONCLUSIONS: Clinical MSOT allows for non-invasive, label-free and real-time imaging of muscle oxygenation in health and disease with implications for diagnostics and therapy assessment in PAD.

Multicompartmental non-invasive sensing of postprandial lipemia in humans with multispectral optoacoustic tomography.

OBJECTIVE: Postprandial lipid profiling (PLP), a risk indicator of cardiometabolic disease, is based on frequent blood sampling over several hours after a meal, an approach that is invasive and inconvenient. Non-invasive PLP may offer an alternative for disseminated human monitoring. Herein, we investigate the use of clinical multispectral optoacoustic tomography (MSOT) for non-invasive, label-free PLP via direct lipid-sensing in human vasculature and soft tissues. METHODS: Four (n = 4) subjects (3 females and 1 male, age: 28 ± 7 years) were enrolled in the current pilot study. We longitudinally measured the lipid signals in arteries, veins, skeletal muscles, and adipose tissues of all participants at 30-min intervals for 6 h after the oral consumption of a high-fat meal. RESULTS: Optoacoustic lipid-signal analysis showed on average a 63.4% intra-arterial increase at ~ 4 h postprandially, an 83.9% intra-venous increase at ~ 3 h, a 120.8% intra-muscular increase at ~ 3 h, and a 32.8% subcutaneous fat increase at ~ 4 h. CONCLUSION: MSOT provides the potential to study lipid metabolism that could lead to novel diagnostics and prevention strategies by label-free, non-invasive detection of tissue biomarkers implicated in cardiometabolic diseases.

A sparse deep learning approach for automatic segmentation of human vasculature in multispectral optoacoustic tomography.

Multispectral Optoacoustic Tomography (MSOT) resolves oxy- (HbO2) and deoxy-hemoglobin (Hb) to perform vascular imaging. MSOT suffers from gradual signal attenuation with depth due to light-tissue interactions: an effect that hinders the precise manual segmentation of vessels. Furthermore, vascular assessment requires functional tests, which last several minutes and result in recording thousands of images. Here, we introduce a deep learning approach with a sparse-UNET (S-UNET) for automatic vascular segmentation in MSOT images to avoid the rigorous and time-consuming manual segmentation. We evaluated the S-UNET on a test-set of 33 images, achieving a median DICE score of 0.88. Apart from high segmentation performance, our method based its decision on two wavelengths with physical meaning for the task-at-hand: 850 nm (peak absorption of oxy-hemoglobin) and 810 nm (isosbestic point of oxy-and deoxy-hemoglobin). Thus, our approach achieves precise data-driven vascular segmentation for automated vascular assessment and may boost MSOT further towards its clinical translation.

Multispectral optoacoustic tomography of muscle perfusion and oxygenation under arterial and venous occlusion: A human pilot study.

Perfusion and oxygenation are critical parameters of muscle metabolism in health and disease. They have been both the target of many studies, in particular using near-infrared spectroscopy (NIRS). However, difficulties with quantifying NIRS signals have limited a wide dissemination of the method to the clinics. Our aim was to investigate whether clinical multispectral optoacoustic tomography (MSOT) could enable the label-free imaging of muscle perfusion and oxygenation under clinically relevant challenges: the arterial and venous occlusion. We employed a hybrid clinical MSOT/ultrasound system equipped with a hand-held scanning probe to visualize hemodynamic and oxygenation changes in skeletal muscle under arterial and venous occlusions. Four (N = 4) healthy volunteers were scanned over the forearm for both 3-minute occlusion challenges. MSOT-recorded pathophysiologically expected results during tests of disturbed blood flow with high resolution and without the need for contrast agents. During arterial occlusion, MSOT-extracted Hb-values showed an increase, while HbO2 - and total blood volume (TBV)-values remained roughly steady, followed by a discrete increase during the hyperemic period after cuff deflation. During venous occlusion, results showed a clear increase in intramuscular HbO2 , Hb and TBV within the segmented muscle area. MSOT was found to be capable of label-free non-invasive imaging of muscle hemodynamics and oxygenation under arterial and venous occlusion. We introduce herein MSOT as a novel modality for the assessment of vascular disorders characterized by disturbed blood flow, such as acute limb ischemia and venous thrombosis.

Cardiovascular optoacoustics: From mice to men - A review.

Imaging has become an indispensable tool in the research and clinical management of cardiovascular disease (CVD). An array of imaging technologies is considered for CVD diagnostics and therapeutic assessment, ranging from ultrasonography, X-ray computed tomography and magnetic resonance imaging to nuclear and optical imaging methods. Each method has different operational characteristics and assesses different aspects of CVD pathophysiology; nevertheless, more information is desirable for achieving a comprehensive view of the disease. Optoacoustic (photoacoustic) imaging is an emerging modality promising to offer novel information on CVD parameters by allowing high-resolution imaging of optical contrast several centimeters deep inside tissue. Implemented with illumination at several wavelengths, multi-spectral optoacoustic tomography (MSOT) in particular, is sensitive to oxygenated and deoxygenated hemoglobin, water and lipids allowing imaging of the vasculature, tissue oxygen saturation and metabolic or inflammatory parameters. Progress with fast-tuning lasers, parallel detection and advanced image reconstruction and data-processing algorithms have recently transformed optoacoustics from a laboratory tool to a promising modality for small animal and clinical imaging. We review progress with optoacoustic CVD imaging, highlight the research and diagnostic potential and current applications and discuss the advantages, limitations and possibilities for integration into clinical routine.