Detecting key stroke risk factor easier and cheaper
Ischemic strokes, a major cause of cardiovascular disease, are on the rise. A leading risk factor in these strokes is plaque formation on the inner wall of arterial vessels, which blocks blood flow. Typically, plaque buildup is detected through imaging techniques that require expensive equipment and professional operators.
To improve detection, researchers are investigating alternatives that could be used outside of clinics. Zhu et al. simulated a vessel system to investigate the potential of a non-invasive, multi-sensor to detect plaque location and length.
“More and more researchers are now working on the development and study of convenient wearable devices to monitor hemodynamic parameters, however, it is difficult to realize the effective monitoring of plaque by only a single signal,” said author Bojing Shi. “Therefore, realizing a multi-sensor co-monitoring of hemodynamic parameters is a very important research topic.”
Using numerical simulation software, the researchers examined the fluid-solid interaction effect between a vessel and the vessel wall. From their results, they were able to determine the location and size of plaque as well, as the responses of artery signals to different plaque sizes. This provides a theoretical basis that can be used to create a non-invasive, multi-sensor plaque detector.
“What excites me most about this research is the ability to determine the location and size of plaque by simultaneously monitoring vessel wall deformation and blood flow velocity,” Shi said. “I certainly hope to apply the results of this research to future studies, and I hope that the results of this study will aid in the development of non-invasive multi-sensors and will provide the necessary theoretical support for clinical use.”
Source: “Biomechanical mechanism of noninvasive plaque detection based on multi-sensor fusion,” by Pengrui Zhu, Yiran Hu, Bojing Shi, and Yubo Fan, Physics of Fluids (2024). The article can be accessed at https://doi.org/10.1063/5.0189604 .