This research field focuses on advancing ultrasound-based methods to assess the mechanical competence of bone. By integrating physics, biomechanics, computational modeling, signal processing, 3D CAD modeling, and robotics, the aim is to develop safer, radiation-free approaches for evaluating bone quality and structure in clinical settings. Briefly, the work involves the development of computational models (COMSOL, k-Wave) to explore novel ultrasound techniques for assessing cortical bone properties. These models are then translated into experimental testing using a custom-built water tank system that incorporates a robotic arm for precise and reproducible scanning of bone specimens. This platform enables the characterization of cortical bone structural and mechanical properties through a combination of advanced ultrasound approaches. Through this multidisciplinary framework, the research aims to establish ultrasound as a powerful, non-invasive tool for comprehensive bone diagnostics.

This area of research aims to build on the cardiovascular story that the Cardoso Lab has been working on since its inception. Namely, how calcifications of different sizes affect atherosclerotic plaque progression and vulnerability. This work comprises of a series of computational models and experiments, which go together hand in hand.  Fluid structure interaction studies are being conducted on idealized and human-derived (microCT based) coronary models, aiming to expand the understanding of atherosclerotic plaques of different phenotypes. Previously, the lab has published studies focusing on the rupture phenotype while currently the lab is applying new and old techniques to investigating the erosion phenotype.  On the experimental side, one group is using a murine model of atherosclerosis to assess plaque mechanics in the aorta, and another is developing a tunable model for mineralizing porcine coronaries with aims to perform mechanical testing and eventually additional computational studies.

Atherosclerotic plaque rupture leads to acute cardiovascular events, including myocardial infarction and stroke, in more than half a million Americans every year. Unlike stable plaques, which are easily identified through conventional imaging, vulnerable plaques are asymptomatic and often remain undetected. Yet, they possess characteristic microstructural and biomechanical signatures that predispose them to rupture, highlighting the urgent need for early, non-invasive detection. A key mechanical trigger of plaque rupture is the presence of microcalcifications within the fibrous cap. Despite their clinical significance, these tiny calcium deposits (5–100 μm) remain beyond the resolution limits of current clinical imaging. Therefore, the purpose of this line of research is to develop a screening tool for the diagnosis of vulnerable plaques, with the ultimate goal of preventing acute cardiovascular events. Ongoing studies will lead to the development of advanced ultrasound techniques to assess microcalcifications in vivo, and a machine learning model to predict plaque instability, and ultimately provide a more accurate and personalized cardiovascular risk stratification.