Multicompartmental Non-invasive Sensing of Postprandial Lipemia in Humans with Multispectral Optoacoustic Tomography

Disturbed blood lipid profiles after food intake have been associated with increased risk for cardiovascular and metabolic disease. Postprandial lipid profiling (PLP) can be used as a risk factor for cardiovascular disease, insulin resistance and other metabolic diseases but is based today on frequent blood sampling over several hours after a meal, an approach that is invasive and inconvenient for patients. Non-invasive PLP may offer a favorable alternative for disseminated monitoring in humans. In this study, we investigate the use of localized lipid sensing guided by Multispectral Optoacoustic Tomography (MSOT) for non-invasive, label-free assessment of postprandial lipemia in human vasculature and in soft tissues. For penetrating deep in human tissue, we utilize measurements at 930 nm, where lipids exhibit strong light absorption in the near-infrared spectral range (NIR). In a pilot study, we longitudinally measured postprandial lipemia in healthy subjects over 6 hours following consumption of a high-fat meal. Localized measurements were obtained from four anatomical structures: the radial artery, the cephalic vein, the brachioradialis muscle and the subcutaneous fat of the forearm. Analysis of optoacoustic signals demonstrated a 63.4% mean lipid increase in intra-arterial lipids at approximately 4 hours postprandially, a 89.7% mean increase in intra-venous lipids at 3-hours, a 120.8% mean increase in intra-muscular lipids at 3-hours and a 30.5% mean increase in subcutaneous fat lipids at 4-hours. We discuss how portable MSOT offers unprecedented potential to study lipid metabolism that could lead to novel diagnostics and prevention strategies by offering label-free and non-invasive detection of tissue biomarkers implicated in cardiometabolic diseases.Competing Interest StatementV. Ntziachristos has stock/stock options in iThera Medical GmbH. All other authors have no competing interests to declare.View Full Text