Hemodynamics and Autonomic and Cognitive Performance After Carotid Revascularization Procedures

Carotid Artery Diseases Clinical Trial

— BAROX  

Official title:

Impact of Carotid Endarterectomy and Stenting on Hemodynamics, Fluid-structure Interaction, Autonomic Modulation, and Cognitive Brain Function

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03493971
• Other study ID #: 62/int/2017
• Secondary ID: PE-2013-02355484
• Status: Completed
• Phase: N/A
• Start date: March 21, 2018
• Est. completion date: November 29, 2023

Study information

• Verified date: November 2023
• Source: Ospedale San Donato
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 70
• Est. completion date: November 29, 2023
• Est. primary completion date: April 20, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 75 Years

Eligibility

Inclusion Criteria:

• Informed consent signed

• Patients with >=70% symptomatic or >=80% asymptomatic internal carotid stenosis

Exclusion Criteria:

• Incapability to give informed consent

• Previous disabling stroke

• Contralateral carotid occlusion or >70% stenosis

• Systemic disease judged non compatible with the procedures or randomization

• Suspected or manifested pregnancy

• General contraindications to MRI or CT studies

Related Conditions & MeSH terms

• Carotid Artery Diseases

Intervention

Procedure:
• Carotid revascularization performed using CAS
Carotid artery stenting (CAS) is an endovascular stent procedure used to treat narrowing of the carotid artery and decrease the risk of stroke
• Carotid revascularization performed using CEA
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

Locations

Country	Name	City	State
Italy	IRCCS Policlinico San Donato	San Donato Milanese	Milan

Sponsors (3)

Lead Sponsor	Collaborator
Ospedale San Donato	Emory University, University of Pavia

Country where clinical trial is conducted

Italy, 

References & Publications (17)

Auricchio F, Conti M, De Beule M, De Santis G, Verhegghe B. Carotid artery stenting simulation: from patient-specific images to finite element analysis. Med Eng Phys. 2011 Apr;33(3):281-9. doi: 10.1016/j.medengphy.2010.10.011. Epub 2010 Nov 9. — View Citation

Auricchio F, Conti M, Ferrara A, Morganti S, Reali A. Patient-specific finite element analysis of carotid artery stenting: a focus on vessel modeling. Int J Numer Method Biomed Eng. 2013 Jun;29(6):645-64. doi: 10.1002/cnm.2511. Epub 2012 Sep 29. — View Citation

Auricchio F, Conti M, Ferraro M, Reali A. Evaluation of carotid stent scaffolding through patient-specific finite element analysis. Int J Numer Method Biomed Eng. 2012 Oct;28(10):1043-55. doi: 10.1002/cnm.2509. Epub 2012 Aug 25. — View Citation

Blanco PJ, Trenhago PR, Fernandes LG, Feijoo RA. On the integration of the baroreflex control mechanism in a heterogeneous model of the cardiovascular system. Int J Numer Method Biomed Eng. 2012 Apr;28(4):412-33. doi: 10.1002/cnm.1474. Epub 2011 Nov 2. — View Citation

Bohm M, Cotton D, Foster L, Custodis F, Laufs U, Sacco R, Bath PM, Yusuf S, Diener HC. Impact of resting heart rate on mortality, disability and cognitive decline in patients after ischaemic stroke. Eur Heart J. 2012 Nov;33(22):2804-12. doi: 10.1093/eurheartj/ehs250. Epub 2012 Aug 26. — View Citation

Bunch CT, Kresowik TF. Can randomized trial outcomes for carotid endarterectomy be achieved in community-wide practice? Semin Vasc Surg. 2004 Sep;17(3):209-13. doi: 10.1016/s0895-7967(04)00043-2. — View Citation

Conti M, Van Loo D, Auricchio F, De Beule M, De Santis G, Verhegghe B, Pirrelli S, Odero A. Impact of carotid stent cell design on vessel scaffolding: a case study comparing experimental investigation and numerical simulations. J Endovasc Ther. 2011 Jun;18(3):397-406. doi: 10.1583/10-3338.1. — View Citation

Cutlip DE, Pinto DS. Extracranial carotid disease revascularization. Circulation. 2012 Nov 27;126(22):2636-44. doi: 10.1161/CIRCULATIONAHA.112.110411. No abstract available. — View Citation

Davies PF. Overview: temporal and spatial relationships in shear stress-mediated endothelial signalling. J Vasc Res. 1997 May-Jun;34(3):208-11. doi: 10.1159/000159224. No abstract available. — View Citation

De Santis G, Conti M, Trachet B, De Schryver T, De Beule M, Degroote J, Vierendeels J, Auricchio F, Segers P, Verdonck P, Verhegghe B. Haemodynamic impact of stent-vessel (mal)apposition following carotid artery stenting: mind the gaps! Comput Methods Biomech Biomed Engin. 2013;16(6):648-59. doi: 10.1080/10255842.2011.629997. Epub 2011 Dec 8. — View Citation

De Santis G, Trachet B, Conti M, De Beule M, Morbiducci U, Mortier P, Segers P, Verdonck P, Verhegghe B. A computational study of the hemodynamic impact of open- versus closed-cell stent design in carotid artery stenting. Artif Organs. 2013 Jul;37(7):E96-106. doi: 10.1111/aor.12046. Epub 2013 Apr 12. — View Citation

Hathcock JJ. Flow effects on coagulation and thrombosis. Arterioscler Thromb Vasc Biol. 2006 Aug;26(8):1729-37. doi: 10.1161/01.ATV.0000229658.76797.30. Epub 2006 Jun 1. — View Citation

Hayase H, Tokunaga K, Nakayama T, Sugiu K, Nishida A, Arimitsu S, Hishikawa T, Ono S, Ohta M, Date I. Computational fluid dynamics of carotid arteries after carotid endarterectomy or carotid artery stenting based on postoperative patient-specific computed tomography angiography and ultrasound flow data. Neurosurgery. 2011 Apr;68(4):1096-101; discussion 1101. doi: 10.1227/NEU.0b013e318208f1a0. — View Citation

Irvine CD, Gardner FV, Davies AH, Lamont PM. Cognitive testing in patients undergoing carotid endarterectomy. Eur J Vasc Endovasc Surg. 1998 Mar;15(3):195-204. doi: 10.1016/s1078-5884(98)80176-7. — View Citation

Marrocco-Trischitta MM, Cremona G, Lucini D, Natali-Sora MG, Cursi M, Cianflone D, Pagani M, Chiesa R. Peripheral baroreflex and chemoreflex function after eversion carotid endarterectomy. J Vasc Surg. 2013 Jul;58(1):136-44.e1. doi: 10.1016/j.jvs.2012.11.130. Epub 2013 Apr 28. — View Citation

Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P, Sandrone G, Malfatto G, Dell'Orto S, Piccaluga E, et al. Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ Res. 1986 Aug;59(2):178-93. doi: 10.1161/01.res.59.2.178. — View Citation

Towfighi A, Saver JL. Stroke declines from third to fourth leading cause of death in the United States: historical perspective and challenges ahead. Stroke. 2011 Aug;42(8):2351-5. doi: 10.1161/STROKEAHA.111.621904. Epub 2011 Jul 21. — View Citation

* Note: There are 17 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	R-R interval (sec) and Systolic Arterial Pressure (SAP) (mmHg) in rest and tilt position for baroreceptor function	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Cognitive P300 latency (ms)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Mean and maximum flow velocity magnitude (cm/sec) in common carotid artery (CCA) and internal carotid artery (ICA) along the cardiac cycle	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Systolic wall shear stress (dyn/cm2)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Time-averaged wall shear stress (TAWSS) (dyn/cm2)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Oscillatory index (OSI) (%)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Flow helicity (-)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	CCA/ICA Flow split (%)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Common carotid artery (CCA) - internal carotid artery (ICA) mean and maximum pressure drop (mmHg)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Carotid wall von Mises stress (dyn/cm2) at the systolic peak	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Carotid wall maximum principal stress (dyn/cm2) at the systolic peak and corresponding directions (-) Maximum, mean, and min principal strain (-) and corresponding directions (-)	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Carotid augmentation index (%) of pressure wave	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months
Secondary	Effective reflecting distance (mm) of pressure wave	Comparison pre- and post-CAS, Comparison pre- and post-CEA	20 months