High-sensitivity photonic crystal sensor for early detection of atherosclerosis

Abstract Early detection of atherosclerosis is crucial to preventing its cardiovascular complications. In this study, a 2D-Photonic Crystal (PhC) sensor model was designed and simulated using the RSoft software to optimize diagnostic sensitivity and accuracy. Five configurations of the sensor were explored to evaluate their performance. Structure A emerged as the most efficient, enabling the reliable identification of atherosclerotic plaques (lipidic, fibrous, and calcified) with a high sensitivity of 756.66 nm RIU −1 , a quality factor of 1753.4, and a figure of merit of 8.33 × 10 5 RIU −1 . The 2D-PhC structure offers distinct advantages over traditional 1D-PhC sensors, including enhanced light interaction and spectral resolution. Compared to 1D-PhCs, the 2D structure provides improved sensitivity and faster detection, which are crucial for distinguishing healthy tissues from pathological ones. Performance analysis demonstrated that the proposed structure outperforms conventional methods such as Doppler ultrasound and angiography in terms of precision and detection speed. These results demonstrate that optimizing 2D photonic crystal microcavities, supported by advanced simulations with RSoft, significantly enhances the detection of cardiovascular diseases. This sensor could be integrated into non-invasive diagnostic devices, contributing to the advancement of current medical technologies.