A novel molecular communication inspired detection method for the evolution of atherosclerosis

Atherosclerosis is a leading cause of potentially serious cardiovascular diseases such as heart attack, stroke, and peripheral artery disease. Due to the prolonged and non-reversible process of thickening arteries walls, atherosclerosis plaques in the blood vessels are formed that restrict the blood flow. Early detection plays a vital role in minimizing the risk as there is no reliable method to detect the early stage of the disease. This paper proposes a novel atherosclerosis detection method based on the emerging paradigm of molecular communications. The work could pave the way to implement a low-cost and straightforward early detection method of atherosclerosis in the future.

We used COMSOL to model the physical field, coupled the fluid module and the fluid particle tracking module, and mapped the contrast agent into nanoparticles (NPs). The NPs are released at the entrance of the blood vessel and received at the exit of the blood vessel, while NPs are propagating through different arterial stenosis. The arrival probability of NPs is defined as the ratio of the number of NPs that reach the outlet to the total number of released NPs. As a result of atherosclerosis, the arrival probability of Nps is affected by the dynamic flow nature changes, thereby reflecting the arterial stenosis degree. Furthermore, we introduce the multi-release method in this study, which has a similar concept of Inter-symbol interference in traditional communication. This multi-release method leads the overlapping concentrations of NPs remaining in the vessels and enhances the differences of arrival probability in different degrees of stenosis, which increases the chance of more observable results.

The assessment of arterial stenosis degree can be from the early stage to the late stage of the disease. To evaluate the arterial stenosis degree, we analyzed the Poincaré maps, representing the arrival probability of NPs at different arterial stenosis. Moreover, we could directly use data to quantify the pathological process at various stages. The difference between the data results obtained through multiple release methods is more prominent than a single-released method.

This research proposes a new atherosclerosis detection method based on molecular communication, that is, to evaluate the arterial stenosis degree by modelling and using statistical data of NPs emission and reception in blood vessels. This method can not only use a simple method to detect the early stage of the disease. In addition, we can directly use data to quantify the pathological process of each stage, which is straightforward to assist doctors and may reduce the labour cost of traditional detection.