International researchers use shear waves to map blood vessel structures

The findings could improve cancer treatment and drug delivery to treat tumors

Researchers at the School of Biomedical Engineering and Imaging Sciences at King’s College London (KCL), together with partners at the University of Michigan, the Institut national de la santé et de la recherche médicale in Paris, Norway and Germany, are using shear waves to image blood vessel structures and thus improve the treatment of tumors and other diseases.

Results published in Scientific advances could improve cancer treatment, potentially optimizing drug delivery while helping researchers better understand tumors.

Experts from Michigan and KCL developed a new theory based on MRI-based elastography imaging to study how shear waves move through tissue. Through their analysis, researchers can measure the architecture of blood vessels non-invasively using readily available clinical imaging devices.

Shear waves store information about the materials they pass through, including tissue stiffness, which can be helpful in diagnosing disease.

This method allows researchers to visualize tiny blood vessels that are normally too small to detect. Their experiments showed that blood vessels leave clear signatures in the wave patterns that can be detected and analyzed.

Ralph Sinkus, Professor of Biomedical Engineering at the School of Biomedical Engineering and Imaging Sciences, KCL, explained the concept of the method: “Imagine trying to kick a football through a forest. If the trees are randomly distributed, the football will bounce around unpredictably. Similarly, waves moving through tissue are influenced by the arrangement of blood vessels.”

The researchers believe their research could have implications for cancer treatment, as tumors often cause abnormal blood vessel growth that is more chaotic than in healthy tissue and could be measured to better understand tumors.

In addition, the research could lead to improvements in drug delivery, as the method could determine whether drugs reach tumor cells or have no effect. This could provide important insights into which drugs are best suited to which tumor types and lead to better treatment outcomes.