Molecular sensors detect artery plaque using particle timing patterns
Molecular Communication for Plaque Sensing in a Vascular Bifurcation with Receiver Constraints
Emerging Technologies
Summary
This work studies how tiny particles can be used to sense blockages caused by plaque in blood vessels, especially at points where vessels split. The researchers used computer simulations of blood flow to see how plaque changes how particles travel and arrive at sensors. They found ways to estimate the amount of blockage based on when and how many particles a sensor detects, even with limited data and timing accuracy. This approach could help build tiny communication networks inside the body that also monitor health conditions.
What this means in practice
- •For biomedical device engineers: Develop implantable sensors that detect vascular plaque by monitoring molecular signal timing in arterial bifurcations.$Commercial implications: Enables design of medical devices that monitor cardiovascular health through molecular communication-based sensing within arteries.
- •For healthcare monitoring teams: Use molecular signal analysis as a minimally invasive method to track plaque progression from inside blood vessels.
Authors
Alexander Wietfeld, Luiz C. P. Wille, Pit Hofmann, Jonas Fuchtmann, Randy Gelfert, Frank H. P. Fitzek, Wolfgang Kellerer, Jens Kirchner
Abstract
Future molecular communication (MC) networks are envisioned to use the human cardiovascular system as a channel. Disease-related changes affect particle transport, allowing an MC receiver to also act as a sensor. In this work, we investigate plaque formation in a carotid bifurcation through a systematic fluid-dynamics simulation study with non-Newtonian blood rheology. We analyze how plaque geometry changes branch-specific particle reception and timing, and use these observations to estimate plaque-induced channel obstruction. At an illustrative reference of only 128 emitted particles, a 250 ms observation window and 50 ms temporal resolution, a Ridge detector estimates maximum local channel-width reduction with a mean absolute error of 8.30 percentage points. We evaluate robustness across system constraints like particle budgets, observation windows, branch access, detection efficiency, count resolution, and synchronization. Coarse counting has little effect when timing features remain available, whereas limited temporal resolution and clock uncertainty substantially affect short-window estimates. Extending the observation window to 1 s reduces these timing-related penalties. The results establish a baseline for plaque sensing from constrained MC observations and identify receiver capabilities relevant to the Internet of Bio-Nano Things.