Artificial Intelligence Based Comprehensive Assessment System of Carotid Plaque Stability
Artificial Intelligence Based Comprehensive Assessment System of Carotid Plaque Stability
Stroke is a common clinical disease with high disability and mortality, which seriously
 threatens human life and health.Carotid atherosclerotic plaque rupture is an important
 pathogenic basis of ischemic stroke, so judging the stability of plaque has important
 clinical significance in preventing ischemic stroke.Ultrasound, as a convenient, rapid,
 noninvasive, radiation-free auxiliary examination technology, is widely used in carotid
 plaque stability examination.At present, there are many methods to judge the stability of
 carotid plaque based on ultrasound, including two-dimensional ultrasound, contrast-enhanced
 ultrasound, ultrasound elastography and so on. However, the results of plaque stability
 judgment by various technologies deviate greatly, which is not conducive to the development
 of standardized diagnosis and treatment strategies by clinicians.Studies have shown that
 because the neovascular epidermal cells in atherosclerotic plaques are imperfect, they are
 easy to rupture after stress, and the ruptured neovasculature will lead to intraplaque
 hemorrhage, thus causing plaque shedding, and eventually obstructing the cerebrovascular
 cause stroke.Contrast-enhanced ultrasound can sensitively detect the distribution and course
 of blood vessels.The plaque's softness and hardness determine its stability, while the
 difference of lipids, fibers and calcium in the plaque determines its softness and
 hardness.Real-time ultrasound elastography can provide tissue mechanical parameters, express
 the soft and hard of tissue with strain value, and provide important reference information
 for judging plaque stability.At present, elastography technology is used to reflect the
 hardness of plaque, so as to further judge its stability.However, the elastography parameters
 are prone to deviations due to the influence of the selected section and the selected region
 of interest.Deep learning is the hottest research method in AI at present. [Deep learning is
 essentially to construct machine learning models with multiple hidden layers, and use
 large-scale data to train to obtain a large number of more representative feature
 information, so as to use these features to classify and predict samples. At present, it is
 widely used in the field of image analysis and plays an important role in medicine.Such as
 pathological image detection, regulatory genomics research, diagnosis of retinopathy and
 quantitative analysis of liver fibrosis, etc.Computational Fluid Dynamics (CFD) is a new
 discipline developed by the combination of numerical calculation and classical fluid
 mechanics theory. It can make it convenient for researchers to build a geometric model of
 cardiovascular system, simulate the real structure of vascular wall and blood, and display
 the results of "numerical experiments" using visualization technology.More intuitive
 Comprehensive response to changes in hemodynamic parameters In recent years, its application
 in cardiovascular hemodynamic research has become increasingly widespread, with a large
 number of relevant literature reports However, no report has been reported on the study of
 carotid plaque stability and fluid dynamics using this technology Based on the above
 reasons,This study attempts to use AI technology to automatically identify and quantitatively
 evaluate the gray scale differences of plaques, elastic image characteristics of plaques,
 microvessel density division of plaque contrast-enhanced ultrasound, and velocity vector
 imaging (VVI) to determine plaque surface stress.To study the effect of hemodynamic
 parameters on carotid plaque using CFD technology, and to establish a systematic
 comprehensive evaluation system for carotid plaque stability, which integrates
 two-dimensional plaque information, texture information, microcirculation perfusion
 information, biomechanical information and blood flow field information, and combines the
 results of clinical follow-up and collagen fiber content of surgical specimens, MMP9/CD34 and
 other examinations.
Inclusion Criteria:

 -  Age < 18 years and < 80 years

 -  At least one imaging examination suggested the presence of carotid plaque

 -  no allergy to contrast-enhanced ultrasound and other contraindications

 -  Voluntary enrollment in this study.

 Exclusion Criteria:

 -  Patients unable to cooperate with posture or hold their breath during ultrasound
 examination

 -  Patients with serious lack of clinical data

 -  drugs for carotid plaque treatment other than lipid-lowering drugs, antiplatelet
 drugs, antioxidants, calcium channel blockers were used during follow-up

 -  patients with loss of Union during follow-up

 -  ischemic stroke caused by non-carotid plaque shedding

 -  atriumPatients with tremor and other serious heart diseases.