Hemodynamics and Autonomic and Cognitive Performance After Carotid Revascularization Procedures
Condition: Carotid Artery Diseases
MeSH terms: Carotid Artery Diseases
Study type: Interventional

Summary: 
      Carotid revascularization procedures are performed for more than 87% of cases in patients
      with asymptomatic internal carotid stenosis (ICS), who are assumed to have a life expectancy
      of at least 5 years. Hence, the investigators aim to compare carotid artery stenting (CAS)
      with carotid endarterectomy (CEA) in terms of long-term prognostic endpoints in patients with
      uneventful perioperative course. CEA and CAS, as a consequence of either surgical trauma or
      mechanical stimuli related to the compliance mismatch between the stented segment and the
      native artery, may perturb carotid baroreceptors function causing an impairment of
      cardiovascular autonomic control. Also, CEA and CAS result in different postoperative
      geometric features of carotid arteries that entail relevant modifications of rheological
      parameters, that may be associated with the risk of local complications. Finally, long-term
      and sustained cognitive benefits after CAS as compared to CEA are yet to be demonstrated.
    

Detailed description: 
      Hypothesis and Significance: Late clinical outcome and prognosis after CAS may be inferior to
      that after CEA in terms of autonomic modulation, hemodynamic remodeling, and cognitive
      function.

      Specific Aim: 1) To compare the impact of CEA and CAS on long-term post-operative
      baroreceptor function and on cognitive brain function, and analyze their influence on
      clinical outcome. The specific goal is to assess the potential correlation between
      post-operative autonomic and cognitive function. 2) To assess the solicitation on the carotid
      wall due to CAS as compared to CEA through structural analysis and mechanical modeling. The
      specific goal is to assess the potential correlation between stenting, wall damage,
      baroceptor impairment, and late neurological sequelae. 3) To assess the post-operative
      carotid hemodynamics combining medical image analysis, clinical data, and computer
      simulations. The specific goal aims at correlating both local (e.g., wall stress stress) and
      global phenomena (controlateral flow, arterial stiffening) with baroreflex function and
      post-operative neurological outcomes.

      Experimental Design Aim 1: A computerized method requiring small operator interaction will be
      used to assess indices of autonomic sympathovagal balance directed to the sinoatrial node,
      sympathetic vasomotor modulation, and baroreflex gain, all from spontaneous beat-by-beat
      variations of the R-R interval and systolic arterial pressure (SAP) variability, considering
      only sinus rhythm conditions. After electrode and sensor positioning, patients will be
      maintained for 10 minute in resting supine position, necessary for stabilization,
      subsequently blood pressure waveforms, electrocardiogram and respiratory activity will be
      continuously recorded during a nominal 5-minute baseline and then for subsequent 5-minute
      period of active standing.

      Cardiovascular signals will be acquired by a 4 channel digital polygraph. The
      electrocardiogram will be recorded with two electrodes placed on the patient's chest,
      breathing pattern will be recorded by a piezoelectric belt and finger arterial blood pressure
      will be continuously monitored by a CNAP 500 HD continuous noninvasive hemodynamics monitor
      (CNSystems Medizintechnik AG, Austria). As described previously, (8) a series of indexes
      indirectly reflecting autonomic cardiovascular modulation will be derived from the spectral
      analysis of R-R interval and SAP variability. Postoperative cardiovascular autonomic control
      will be correlated to clinical outcome and measures of cognitive performance. Enrolled
      patients will be submitted to Mini-Mental State Examination for general cognitive impairment
      screening. Cognitive P300 evoked potentials will be then recorded, before and after
      treatment, with Ag/AgCl electrodes with a Brain Vision Recorder (Brain Products GmbH,
      Gilching, Germany). P300 evoked potentials will be generated after a binaurally presented
      tone discrimination paradigm (odd-ball paradigm) with frequent (80%) tones of 1000 Hz and
      rare (20%) target tones of 2000 Hz at 75 dB HL. Filter bandpass will be 0.01 to 30 Hz. Active
      electrodes will be placed at Cz (vertex) and Fz (frontal), respectively, and referenced to
      linked earlobe A1/2 electrodes (10/20 international system). During the paradigm, the
      patients will be instructed to keep a running mental count of the rare 2000-Hz target tones.
      To verify attention, P300 recordings with a discrepancy of>10% between the actual number of
      stimuli and the number counted by the patients will be rejected and repeated. P300 evoked
      potential recording will result in a stable sequence of positive and negative peaks.
      Latencies in milliseconds (ms) of the cognitive P300 peak will be assessed. To confirm
      reproducibility, two sets of P300 measurements will be recorded for all patients.

      Experimental Design Aim 2: The computer-based simulation of CAS is performed exploiting a
      computational framework, which can be used to analyze both stent apposition and vessel wall
      stress in a virtual manner. The framework accounts for two main parts: the vessel model and
      stent model. Preoperative and postoperative medical images (including high resolution
      Contrast Enhanced (CE)-MRI and Computed Tomography Angiography (CTA)) will represent the
      input to build a patient specific carotid model. The 3D lumen profile of the vessel is
      reconstructed through the segmentation of DICOM image stack using tools like ITK-SNAP
      (www.itksnap.org) or VMTK (www.vmtk.org). The computational domain (the so-called mesh), used
      to solve the equilibrium equations governing the structural stent-vessel interaction, is
      created by an in-house developed procedure, coded in Matlab (The Mathworks Inc., Natick,MA,
      USA). The non-linear mechanical response of the arterial tissue is reproduced adopting an
      anisotropic hyperelastic strain-energy function, accounting for two families of fibers,
      oriented along a preferred direction with a certain degree of dispersion. The model
      parameters will be calibrated with respect to experimental tensile tests of the carotid
      tissue. The arterial model is then assembled in the simulation environment with a given stent
      model, picked from a predefined library of stent designs (the stent mesh generation is based
      on geometrical measurements performed on high-resolution micro-CT of stent samples). The CAS
      simulation is performed through structural finite element analysis (FEA); the commercial FEA
      solver Abaqus (Simulia, Dassault Systemes, FR), is adopted to run the simulations. The
      engineering outcomes of the simulations, (i.e. the nodal displacement field, stress tensor
      and strain at each integration points of the mesh), are elaborated to assess clinically
      relevant parameters of stenting performance (e.g. lumen gain, vessel straightening, stent
      cell size). The output will be used as an input of the Computational Fluid Dynamics analysis
      to evaluate the impact of the implanted design on the local haemodynamics (e.g., wall shear
      stress, oscillatory shear index, etc). Similarly, the structural analysis of CEA will be
      performed through the virtual pressurization of the post-operative arterial geometry.

      Experimental design 3: Moving from Computational Fluid Dynamics and Fluid-Structure
      Interaction analysis, the investigators plan to introduce a specific model to describe the
      baroreflex function and this may be affected by the two different types of treatment (CEA and
      CAS). This requires the set up of a so-called "geometrical multiscale" model. With this, the
      investigators mean a numerical model coupling a local description of the hemodynamics (the
      one developed in Aim 2) with a more systemic representation. The latter consists of two
      components:

      a) a 1D network mathematically described by a system of partial differential equations
      representing the propagation of the pressure wave along the arterial tree; each segment of
      the network is given by a hyperbolic system called "Euler equations" b) a compartment model
      for representing the peripheral microcirculation and for including the feedback mechanisms
      induced by the baroreflex function. Following, this will be represented by a system of
      ordinary differential equations where resistances properly depend on the baroreflex function.

      In this aim the investigators plan two sub-aims:

        1. Set up of a computational multiscale model within the framework of the LifeV solver, a
           finite element general purpose C++ Object Oriented library, developed by A. Veneziani
           and his collaborators (in Milan Politecnico and Lausanne EPFL) www.lifev.org and openly
           downloadable. At this stage, the investigators will reproduce the general model of
           Blanco et al. In particular, the identification of the parameters for the two different
           levels of models (1D and Lumped Parameters) will be carried out following the procedure
           suggested. Validation of the solver will also take advantage of the benchmarks presented
           in this paper.

        2. Adoption of the solver previously developed for the test cases considered in Aim 2. This
           means that the 3D model developed in Aim 2 will be adopted for the 3D part of the
           geometrical multiscale model. This will allow to provide a quantitative analysis of the
           different impact of the two treatments and ultimately to assess in a virtual scenario
           how the changes of carotid compliance may impair the baroreflex function. All the CAS
           and CEA cases considered in Aim 2 will be equipped of this multiscale framework. The
           expected deliverables of this aim are therefore: a) a validated open source geometrical
           multiscale solver including the baroreflex function to be used systematically in
           patient-specific settings. b) extensive comparison of the performances of the different
           options.
    

Intervention name(s): Carotid revascularization performed using CAS; Carotid revascularization performed using CEA
Intervention type(s): Procedure; Procedure
Intervention description(s): Carotid artery stenting (CAS) is an endovascular stent procedure used to treat narrowing of the carotid artery and decrease the risk of stroke; Carotid endarterectomy (CEA) is a surgical procedure used to correct stenosis in the common carotid artery or internal carotid artery and reduce the risk of stroke
Allocation: Randomized
Intervention model: Parallel Assignment
Masking: None (Open Label)
Primary purpose: Treatment
Keywords: carotid endarterectomy; carotid stenting; autonomic function; computational fluid dynamic; cognitive function