Acoustic waves are mechanical waves which propagate through a medium via pressure variations. In the biomedical context, Ultrasonography (US) is broadly utilised as it offers images in real time at zero radiation dose and safe use, while being at low cost and high portability. In conventional US imaging, ultrasound waves are sent to a sample, and the intensity of echoes encodes the tissue’s microstructure. This single-parameter tissue characterization restricts the diagnostic value of US to limited scenarios.
We are advancing innovative US-based imaging modes, to combine the availability and flexibility of US with the diagnostic power of multi-modal imaging.
- Beyond echo intensity, the US data encodes the tissue’s speed-of-sound (SoS). Knowledge of the SoS gives information on the tissue composition and thus allows for the diagnosis of diseases affecting the tissue composition such as fatty liver disease, cancer, fat deposits in muscle tissue, among others. We have invented and continue developing Computed Ultrasound-Tomography in Echo-Mode (CUTE), which maps the SoS using conventional US equipment. Together with our collaborators at the Inselspital (Prof. Dr. med. Annalisa Berzigotti), we have already demonstrated the power of CUTE for fatty liver diagnosis.
- In opto- or photo-acoustic imaging (OA), short laser pulses—as opposed to sound—are sent into the tissue where they generate US signals upon optical absorption. While purely optical methods are limited by the strong scattering of optical waves, US waves propagate mostly undisturbed and their detection allows to create high-resolution maps of the tissue’s optical contrast, with promise in, e.g., the diagnosis and monitoring of vascular diseases, arthritis, and cancer. We focus on the combination of OA with classical US-systems, where we are leading in the development of techniques that enable a clinically useful imaging depth.
Ultimately, we aim at developing a single device which will unify the virtues of real-time operability and patient safety with the diagnostic accuracy of multi-modal imaging.
