Slice-based and time-specific hemodynamic measurements discriminate carotid artery vulnerable atherosclerotic plaques

Long-Term Carotid Plaque Progression and the Role of Intraplaque Hemorrhage: A Deep Learning-Based Analysis of Longitudinal Vessel Wall Imaging

Background

Carotid atherosclerosis is a major contributor in the etiology of ischemic stroke. Although intraplaque hemorrhage (IPH) is known to increase stroke risk and plaque burden, its long-term effects on plaque dynamics remain unclear. This study aimed to evaluate the long-term impact of IPH on carotid plaque burden progression using deep learning-based segmentation on multi-contrast magnetic resonance vessel wall imaging (VWI).

Methods

Twenty-eight asymptomatic subjects with carotid atherosclerosis underwent an average of 4.7 ± 0.6 VWI scans over 5.8 ± 1.1 years. Deep learning pipelines were developed and validated to segment the carotid vessel walls and IPH. Bilateral plaque progression was analyzed using generalized estimating equations, and linear mixed-effects models evaluated long-term associations between IPH occurrence, IPH volume, and plaque burden (%WV) progression.

Results

IPH was detected in 23/50 of arteries. Of arteries without IPH at baseline, 11/39 developed new IPH that persisted, while 5/11 arteries with baseline IPH exhibited it throughout the study. Bilateral plaque growth was significantly correlated (r = 0.54, p < 0.001), but this symmetry was weakened with IPH presence. The progression rate for arteries without IPH was -0.001 %/year (p = 0.90). However, IPH presence or development at any point was associated with a 2.3% absolute increase in %WV on average (p < 0.001). The volume of IPH was also positively associated with increased %WV (p = 0.005).

Conclusions

Deep learning-based segmentation pipelines were utilized to identify IPH, quantify IPH volume, and measure their effects on carotid plaque burden during long-term follow-up. Findings demonstrated that IPH may persist for extended periods. While arteries without IPH demonstrated minimal progression under contemporary treatment, presence of IPH and greater IPH volume significantly accelerated long-term plaque growth.

Biomechanical characteristics in the carotid artery: Noninvasive assessment using subharmonic emissions from microbubbles

BACKGROUND

Stroke is closely related to carotid atherosclerotic plaques, which tend to occur in specific parts of the arteries, especially at the bifurcations, and are considered to be caused by biomechanical factors. Quantitative analysis of hemodynamic stress characteristics of the carotid sinus in vivo provides a mechanical basis for the development of atherosclerotic plaque in the carotid sinus. Previous studies found that ultrasound (US) contrast agent microbubbles would vibrate nonlinearly under the excitation of sound pressure, generating subharmonics (transmission fundamental frequency, i.e., f0 and subharmonic frequency at f0 /2), which have the highest sensitivity to pressure changes and exhibit an inverse linear relationship with environmental pressure.

PURPOSE

This study employed subharmonic aided pressure estimation (SHAPE) technology to reflect carotid artery hydrodynamic characteristics in the carotid lumen.

METHODS

From May 2021 to December 2021, this prospective study reviewed a total of 26 normal carotid arteries of 13 participants, all of whom received bilateral carotid artery routine US and SHAPE US examinations. During this study, the lumen of the bilateral distal segment of the common carotid artery (Distal-CCA), carotid artery bifurcation (CAB), and carotid bulb (CB) were scanned section by section from bottom to top in longitudinal and transverse sections. Subsequently, the subharmonic amplitudes in the lumen of normal carotid arteries were collected and analyzed.

RESULTS

This study found that the amplitude of subharmonic amplitude in the carotid was distributed unevenly, with the amplitudes of subharmonic at the CAB being higher. Specifically, the subharmonic gradient of the carotid artery bifurcation apex plane was maximum (9.72 ± 4.31 dB), while the average subharmonic amplitude of the outer lateral layer of the carotid artery was higher (-56.40 ± 6.31 dB) (p < 0.001).

CONCLUSION

The SHAPE technique is capable of indirectly reflecting the pressure changes of vascular system tissues, which may provide a new monitoring method for evaluating mechanical characteristics obviating invasion.

Coronary artery properties in atherosclerosis: A deep learning predictive model

In this work an Artificial Neural Network (ANN) was developed to help in the diagnosis of plaque vulnerability by predicting the Young modulus of the core (E _core ) and the plaque (E _plaque ) of atherosclerotic coronary arteries. A representative in silico database was constructed to train the ANN using Finite Element simulations covering the ranges of mechanical properties present in the bibliography. A statistical analysis to pre-process the data and determine the most influential variables was performed to select the inputs of the ANN. The ANN was based on Multilayer Perceptron architecture and trained using the developed database, resulting in a Mean Squared Error (MSE) in the loss function under 10^-7, enabling accurate predictions on the test dataset for E _core and E _plaque . Finally, the ANN was applied to estimate the mechanical properties of 10,000 realistic plaques, resulting in relative errors lower than 3%.