A systematic evaluation of the impact of contralateral stenosis on ipsilateral internal carotid artery hemodynamics using computational fluid dynamics

Introduction

Assessment and management of internal carotid artery (ICA) stenosis is based on estimation of percentage stenosis via velocity profiles from duplex ultrasound (DUS). In patients with a contralateral ICA stenosis and/or occlusion, ipsilateral DUS-derived velocity profiles may be over-estimated (1-4). These elevations have been shown to be reversible when the contralateral stenosis is treated surgically via carotid endarterectomy (CEA) or carotid artery stenting (CAS) (5). Thus, a contralateral stenosis can lead to overestimation of the ipsilateral percent stenosis (%stenosis) and potentially lead to patients undergoing unnecessary CEA or CAS (3).

Additional hemodynamic indices such as wall shear stress (WSS), pressure gradients (PG), cerebral blood flow (CBF), and extent of collateral circulation are not captured by estimation of %stenosis and have been shown to play important roles in ICA embolism and stroke risk (6-13). It remains unclear how a contralateral ICA stenosis affects the ipsilateral ICA hemodynamics and stroke risk. In this study, we aimed to leverage a patient-specific magnetic resonance imaging (MRI) informed computational fluid dynamics (CFD) model to quantify the impact of contralateral ICA stenosis and/or occlusion on ipsilateral ICA hemodynamics.

Methods

This work started with a previously published MRI-validated CFD model of hemodynamics in the cervical and cerebral arteries in a patient with bilateral asymptomatic ICA stenosis, which defined a ground-truth hemodynamic baseline (14,15). We then systematically altered the level of the contralateral ICA stenosis while keeping the ipsilateral ICA level of stenosis fixed, and compared hemodynamics across all levels of stenosis. To explore the role of external carotid artery (ECA) flow compensation, we used two different sets of boundary conditions: one with fixed ECA outflow waveforms and another with the ECA coupled to a 3-element Windkessel lumped-parameter model. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of the University of Michigan (No. HUM00114275) and informed consent was obtained from the patient.

Ground-truth hemodynamic baseline model

A patient-specific CFD model of cervical and cerebral arteries was built from computed tomography angiogram (CTA) and calibrated using phase-contrast MRI (PC-MRI) flow and arterial spin labeling (ASL) perfusion data to provide a ground-truth hemodynamic baseline for a patient with bilateral asymptomatic ICA stenosis (14,15). In our prior work, two patients with high-grade [defined as >70% extracranial ICA stenosis on DUS or CTA using North American Symptomatic CEA Trial (NASCET) criteria] asymptomatic ICA stenosis were identified from Vascular Surgery clinic at the University of Michigan, consented, and enrolled (14,15). We elected to use one patient for our ground-truth model and chose the patient with the largest amount of patient-specific data (thus providing the highest quality data to define hemodynamics in our ground-truth model). This patient was a 63-year-old male with a history of hypertension, hyperlipidemia, and bilateral asymptomatic ICA stenosis (right ICA 50–69% on DUS and 75% on CTA; left ICA 1–49% on DUS and 25% on CTA; using NASCET criteria). Of note, the patient had a bovine arch [characterized by a common origin of the brachiocephalic trunk and left common carotid artery (CCA)], as well as an incomplete circle of Willis (CoW) with the basilar artery being supplied solely by the left vertebral artery (Vert) and no right posterior communicating artery. On CTA, each stenosis was located at the proximal ICA. The right ICA stenosis was approximately 11.5 mm in length and the left ICA stenosis was approximately 15.2 mm in length. The patient underwent an MRI performed at 3T (MRI750; GE Healthcare, Waukesha, WI), consisting of T1-weighted and 3D-time-of-flight sequences. MRI and CTA were used for anatomical characterization of the thoracic aorta to the CoW. PC-MRI flow rates were obtained at the ascending aorta (AscAo) and main cervical arteries above the carotid bifurcation. Brain tissue perfusion data were collected using ASL.

CFD analysis was performed using the validated open-source computational hemodynamics software CRIMSON (16). An anatomical model of the patient’s large arteries from the aortic arch to the CoW was created from CTA data by segmenting contours along the vessel centerline, followed by lofting to create a 3D anatomical model, which was then discretized into a finite element mesh using linear tetrahedral elements. Lofting refers to a process that combines each vessel’s contours into a 3D solid geometric model. Both global and local mesh refinement strategies were used. Specifically, the global element size was set to an absolute value of 1.5 mm. The element size for all extracranial vessels was set to an absolute value of 0.8 mm. Each intracranial vessel had an element size of 0.3 mm and included a curvature refinement (to add more mesh elements at areas with curvature, such as a stenosis). Vessel walls were assumed rigid with a no-slip boundary condition. PC-MRI volumetric flow waveforms were reconstructed and imposed at the inflow of the AscAo. Each vessel outflow face was coupled to a 3-element Windkessel lumped-parameter model, consisting of a proximal resistance Rp, a distal resistance Rd, and a compliance C, to capture the behavior of the distal vasculature. The Windkessel model parameters were then iteratively calibrated to match the flow (PC-MRI), pressure (cuff), and regional brain perfusion (ASL-MRI) data of the patient. Therefore, this calibrated ground-truth model provides an accurate representation of cervical and cerebral hemodynamics for this patient. Further details of the imaging protocol and patient-specific parameter tuning strategy were previously described (14,15).

Definition of ipsilateral and contralateral ICA stenosis

We defined the ipsilateral ICA stenosis as the ICA with the more severe %stenosis (i.e., the right ICA) and the contralateral ICA stenosis as the ICA with the less severe %stenosis (i.e., the left ICA).

Systematic alteration of contralateral ICA stenosis

We systematically altered the level of the contralateral (left) ICA stenosis while keeping the ipsilateral (right) ICA stenosis fixed (Figure 1). Of note, the length of the contralateral stenosis was kept fixed (at approximately 15.2 mm). We first started with the ground-truth baseline anatomy (i.e., 25% contralateral stenosis and 75% ipsilateral stenosis). Consistent with the NASCET criteria, we then used the area of the distal contralateral ICA as a reference for 0% contralateral stenosis. Finally, the degree of contralateral ICA stenosis from the ground-truth anatomy was altered to the following values: 0%, 50%, 75%, 80%, 85%, 90%, 95% stenosis and 100% (occlusion).

Figure 1 Overview of ground-truth anatomical model and systematic alterations to contralateral ICA stenosis. (A) 3D-reconstructed ground-truth anatomical model. Close-up of right (ipsilateral) carotid bifurcation including the RCCA, RECA, and RICA (green box). RICA has an approximately 75% stenosis (green arrows). Close-up of left (contralateral) carotid bifurcation including the LCCA, LECA, and LICA (red box). LICA has an approximately 25% stenosis (red arrows). Close-up of different models corresponding to increasing levels of contralateral LICA stenosis (B). Progressive LICA stenosis (0%, 50%, 75%, 80%, 85%, 90%, 95%) and LICA occlusion (100% stenosis) depicted (red arrows). 3D, three dimensional; ICA, internal carotid artery; LCCA, left common carotid artery; LECA, left external carotid artery; LICA, left internal carotid artery; RCCA, right common carotid artery; RECA, right external carotid artery; RICA, right internal carotid artery.

Primary boundary conditions for the systematically altered cases

We initially assumed that flow to the extra-cranial arteries [descending aorta (DescAo), ECA, subclavian artery] did not change with different levels of ICA stenosis. Thus, fixed flow waveforms, derived from our ground-truth hemodynamic model (14,15), were imposed at AscAo, DescAo, bilateral subclavian arteries, and ECAs. Conversely, intra-cranial vessels [bilateral anterior cerebral (ACA), middle cerebral (MCA), posterior cerebral (PCA), Vert, and superior cerebellar arteries (SCA)] were coupled to the previously calibrated 3-element Windkessel lumped-parameter models from the baseline ground-truth model. This choice of intracranial outflow boundary conditions therefore, allows for variations in pressure and flow that would naturally occur due to the alterations in the ICA stenoses. Figure 2 shows a representation of inflow, outflow, and the values of the Windkessel boundary conditions.

Figure 2 Representation of primary inflow and outflow boundary conditions. A volumetric flow waveform based on phase-contrast magnetic resonance imaging measurements was prescribed at the inflow at the AscAo. Flow waveforms, derived from our ground-truth and validated computational fluid dynamics model, were prescribed to the outflow of all extra-cranial vessels including the DescAo, R Subclav Art, L Subclav Art, RECA, and LECA. Intra-cranial outflows, which included the Rvert, RSCA, LSCA, RPCA, LPCA, RMCA, LMCA, RACA, and LACA, were coupled to a 3-element Windkessel lumped parameter model consisting of Rp, Rd, and C. Calibrated 3-element Windkessel model parameters can be visualized in the table. AscAo, ascending aorta; C, compliance (10⁹ m³/Pa); DescAo, descending aorta; L Subclav Art, left subclavian artery; LACA, left anterior cerebral artery; LECA, left external carotid artery; LMCA, left middle cerebral artery; LPCA, left posterior cerebral artery; LSCA, left superior cerebellar artery; R Subclav Art, right subclavian artery; RACA, right anterior cerebral artery; RECA, right external carotid artery; RMCA, right middle cerebral artery; RPCA, right posterior cerebral artery; RSCA, right superior cerebellar artery; Rvert, right vertebral artery; Rd, distal resistance (10⁹ Pa·s·m⁻³); Rp, proximal resistance (10⁹ Pa·s·m⁻³); Q3D, 3-Dimensional Flow.

Alternate boundary conditions for the systematically altered cases

To explore the role of ECA flow compensation in the setting of contralateral ICA stenosis and occlusion, we utilized an alternate set of boundary conditions where the bilateral ECA, in addition to all intracranial vessels, were coupled to the previously calibrated 3-element Windkessel lumped-parameter models from the baseline ground-truth model (14,15). This approach, therefore, allows for variations in pressure and flow in those arteries. Flow to all other extra-cranial arteries (DescAo and bilateral subclavian arteries) had fixed flow waveforms, derived from our ground-truth hemodynamic model, imposed at the outlets (Figure 3). These alternate boundary conditions were used for the 90%, 95% stenosis and 100% (occlusion) cases.

Figure 3 Representation of secondary inflow and outflow boundary conditions. A volumetric flow waveform based on phase-contrast magnetic resonance imaging measurements was prescribed at the inflow at the Aao. Flow waveforms, derived from our ground-truth and validated computational fluid dynamics model, were prescribed to the outflo of the DescAo, R Subclav Art, L Subclav Art. The RECA and LECA were coupled to a 3-element Windkessel lumped parameter model consisting of a Rp, Rd, and compliance. Intra-cranial outflow boundary conditions were the same as the primary boundary condition set (Figure 2). I, inflow; O, outflow; W, windkessel. Aao, ascending aorta; DescAo, descending aorta; L Subclav Art, left subclavian artery; LECA, left external carotid artery; R Subclav Art, right subclavian artery; RECA, right external carotid artery; Rd, distal resistance; Rp, proximal resistance.

Flow simulations

For all cases, blood was modeled as an incompressible Newtonian fluid with a dynamic viscosity of 0.004 kg·m⁻¹·s⁻¹ and a density of 1,060 kg·m⁻³. Vessel walls were defined as rigid with a no-slip boundary condition. The CRIMSON Navier-Stokes Flow solver was used to perform computations with 108 cores on a high-performance computing cluster. Simulations were run using a time step size of 0.1 ms for 4 cardiac cycles. The residual required was 1×10⁻⁴. Velocity and pressure fields were extracted for the last cardiac cycle. Each stenosis severity case was run with increased levels of mesh-refinement, specifically to the intracranial vessels, until mesh independence in ICA velocity was achieved.

Quantities of interest and statistical analysis

Velocity waveforms, including peak-systolic velocity (PSV) and end-diastolic velocity (EDV), were collected at the level of maximum stenosis on the ipsilateral ICA for all cases. Pressure waveforms were obtained 1 cm proximal and distal to the ipsilateral ICA stenosis (approximately 2 times the distal ICA diameter) for all cases. Decision for a 1 cm distance was based on our group’s prior experience with CFD and to allow for clinical translation to catheter and duplex-based measurements. These waveforms were used to calculate the PG, defined as the ratio of the average distal and proximal ICA pressures. Time-averaged WSS was collected at the level of the ipsilateral ICA stenosis for all cases. CBF of each brain hemisphere was defined as the total flow of the ACA, MCA, PCA, SCA, and Vert for the contralateral and ipsilateral arteries. Hemodynamic metrics are reported as mean ± standard deviation (SD). Paired Student’s t-test was used to compare differences in ipsilateral ICA hemodynamics for all cases. A P value of <0.05 was considered significant for all statistical tests. Statistical analyses were performed using Stata 17.0 (StataCorp LP, College Station, TX, USA). Paraview (Los Alamos National Laboratory, Santa Fe, NM, USA) was used for visualization of WSS, pressure, and velocity. All analyses were completed by one unblinded author (D.J.B.) with multiple years of experience working with CFD and statistical models and were reviewed with the senior author (C.A.F.), who has extensive experience with CFD modeling.

Results

An overview of the effects of contralateral stenosis on ipsilateral hemodynamics

Table 1 includes a full summary of the changes in both ipsilateral and contralateral hemodynamics (velocity, PG, WSS, and CBF) across varying degrees of contralateral ICA stenosis. Although small increases in ipsilateral velocities were seen ≥75% contralateral stenosis, large changes were not observed until the contralateral stenosis reached ≥90%. Ipsilateral PG, WSS, and CBF were unchanged until the contralateral ICA stenosis reached ≥90% stenosis. Thus, a contralateral stenosis of ≥90% appears to be a critical point at which ipsilateral hemodynamics may be significantly altered.

Effect of contralateral stenosis on ipsilateral velocity

Figure 4 depicts the ipsilateral ICA velocity waveforms with varying degrees of contralateral ICA stenosis. Overall, the ipsilateral velocities were unchanged in the 0–50% contralateral ICA stenosis range. From 75% stenosis onwards, each 5% increase in contralateral stenosis resulted in larger increases in ipsilateral ICA velocities with dramatic increases occurring in the 95% and occlusion cases.

Figure 4 Velocity profiles of ipsilateral ICA with varying degrees of contralateral ICA stenosis. Velocity waveform depicts peak velocity in cm/s over one cardiac cycle, mimicking the typical result of a carotid duplex ultrasound. Common duplex ultrasound thresholds for severe stenosis, PSV of 230 cm/s and EDV of 110 cm/s, are depicted with dotted black lines. Velocity profiles for cases of 0% stenosis, 25%, and 50% stenosis are very similar. To better appreciate differences in the aforementioned cases, an enlarged view of peak systole can be visualized in the top right insert. *, ground-truth calibrated case. Statistical significance cannot be calculated for a single velocity profile because each case only has one value. EDV, end diastolic velocity; ICA, internal carotid artery; PSV, peak systolic velocity.

When the contralateral ICA increased to 75% and 80% stenosis, ipsilateral PSV and EDV slightly increased (PSV: 172.7 and 176.5 cm/s, respectively; EDV: 87.1 and 89.4 cm/s, respectively). When the contralateral ICA increased to 85% and 90% stenosis, ipsilateral PSV and EDV increased further (PSV: 181.9 and 201.0 cm/s, respectively; EDV: 92.3 and 102.0 cm/s, respectively). The most dramatic increases occurred in the 95% stenosis and occlusion cases. When the contralateral ICA increased to 95% stenosis, the ipsilateral PSV and EDV increased to 232.4 and 118.3 cm/s, respectively. Lastly, when the contralateral ICA reached occlusion, the ipsilateral ICA PSV and EDV substantially increased to 312.1 and 151.2 cm/s, respectively.

Effect of contralateral stenosis on ipsilateral pressure

Figure 5 depicts the ipsilateral PG with varying degrees of contralateral ICA stenosis. The ipsilateral PG was unchanged for the 0–75% contralateral stenosis cases. Minimal change from baseline ipsilateral PG was observed for cases with an 80% (PG: 0.994) and 85% (PG: 0.994) contralateral stenosis. When the contralateral ICA stenosis was increased to 90% and 95% the ipsilateral PG decreased to 0.993 and 0.992, respectively. Lastly, when the contralateral ICA reached complete occlusion, the ipsilateral PG decreased further to 0.989 mmHg.

Figure 5 PG of ipsilateral ICA with varying degrees of contralateral ICA stenosis. (A) Pressure (mmHg) at peak systole is mapped to geometric models of the ipsilateral (right) CCA, ECA, and ICA on an anterior view. For adequate visualization of change in pressure across the ipsilateral ICA, pressure range is variable for each case (see scale to the right of each geometric model). (B) Bar-graph depicting PG at the ipsilateral (right) ICA stenosis for varying degrees of contralateral ICA stenosis. PG is defined as the average pressure of the ICA distal to stenosis divided by the average pressure of the ICA proximal to the stenosis. *, ground-truth calibrated case. Statistical significance cannot be calculated for a single PG because each case only has one value. CCA, common carotid artery; ECA, external carotid artery; ICA, internal carotid artery; PG, pressure gradient.

Effect of contralateral stenosis on ipsilateral WSS

Figure 6 depicts the ipsilateral time-averaged WSS with varying degrees of contralateral ICA stenosis. There was no difference in the average ipsilateral WSS between ground-truth (25% contralateral stenosis) and 0%, 50%, 75%, 80%, or 85% contralateral stenosis (P>0.05 for all). When the contralateral ICA reached 90% stenosis, ipsilateral WSS was significantly higher than the ground-truth case (1.67±0.46 vs. 1.43±0.36 Pa, P<0.001). Additionally, with a contralateral ICA of 95% stenosis, ipsilateral WSS was again significantly higher than the ground-truth case (1.96±0.55 vs. 1.43±0.36 Pa, P<0.001). Finally, with a contralateral ICA occlusion, ipsilateral WSS remained significantly higher than the ground-truth case (5.69±1.97 vs. 1.43±0.36 Pa, P<0.001).

Figure 6 WSS of ipsilateral ICA with varying degrees of contralateral ICA stenosis. (A) WSS (Pa), measured as the time-averaged WSS, is depicted at peak systole and mapped to geometric models of the ipsilateral (right) CCA, ECA, and ICA on an anterior view. WSS was measured at the right ICA stenosis (green oval) for each case. (B) Bar-graph depicting values of WSS at the ipsilateral (right) ICA stenosis for varying degrees of contralateral ICA stenosis. *, ground-truth calibrated case. CCA, common carotid artery; ECA, external carotid artery; ICA, internal carotid artery; WSS, wall shear stress.

Effect of contralateral stenosis on CBF

Figure 7A depicts ipsilateral and contralateral CBF with varying degrees of contralateral ICA stenosis. Neither ipsilateral nor contralateral CBF changed significantly until the contralateral ICA stenosis reached ≥90% stenosis. As contralateral stenosis progressed from 90% to occlusion, ipsilateral CBF increased and contralateral CBF decreased.

Figure 7 Cerebral flow with varying degrees of contralateral (left) ICA stenosis. (A) Ipsilateral (right) cerebral blood flow and contralateral (left) cerebral blood flow with varying degrees of contralateral (left) ICA stenosis. Ipsilateral cerebral blood flow defined as the sum of blood flow at the Rvert, RSCA, RPCA, RMCA, and RACA outlets. Contralateral cerebral blood flow defined as the sum of blood flow at the LSCA, LPCA, LMCA, and LACA outlets. *, ground-truth calibrated case. (B) Detailed depiction of vessel-specific cerebral blood flow variations for three cases of contralateral (left) stenosis (90%, 95%, and occlusion). CBF, cerebral blood flow; ICA, internal carotid artery; LACA, left anterior cerebral artery; LMCA, left middle cerebral artery; LPCA, left posterior cerebral artery; LSCA, left superior cerebellar artery; RACA, right anterior cerebral artery; RMCA, right middle cerebral artery; RPCA, right posterior cerebral artery; RSCA, right superior cerebellar artery; Rvert, right vertebral artery.

In the ground-truth case (25% contralateral stenosis), the ipsilateral CBF was 3.99 mL/s and the contralateral CBF was 3.79 mL/s. At both 0% and 50% contralateral ICA stenosis, ipsilateral CBF and contralateral CBF were unchanged relative to the ground-truth. Minimal decreases in contralateral CBF continued as the contralateral ICA stenosis increased from 75% (3.77 mL/s), to 80% (3.76 mL/s), and 85% (3.75 mL/s) while ipsilateral CBF increased to 4.01 mL/s (75%), 4.02 mL/s (80%), and 4.03 mL/s (85%). Larger changes in both ipsilateral and contralateral CBF were observed with contralateral stenoses of 90%, 95%, and occlusion. Ipsilateral CBF increased to 4.08 mL/s and contralateral CBF decreased to 3.71 mL/s with a 90% contralateral stenosis. Additionally, ipsilateral CBF increased to 4.20 mL/s and contralateral CBF decreased to 3.58 mL/s with a 95% contralateral stenosis. Finally, ipsilateral CBF increased to 4.57 mL/s and contralateral CBF decreased to 3.20 mL/s, with a contralateral occlusion.

Figure 7B depicts detailed, vessel-specific distributions of ipsilateral and contralateral CBF for cases with a contralateral stenosis of 90%, 95%, and total occlusion. As the contralateral stenosis increased from 90%, to 95%, to total occlusion, the ipsilateral MCA flow increased from 1.80, to 1.86, to 2.10 mL/s, respectively. Conversely, the contralateral MCA flow decreased from 1.84 mL/s (90% contralateral stenosis) to 1.77 mL/s (95% contralateral stenosis), to 0.41 mL/s (contralateral occlusion). Interestingly, ipsilateral SCA flow decreased (because the RSCA originates from the left Vert due to an anatomic variant). Conversely, with a contralateral occlusion, the contralateral SCA flow increased to 1.56 mL/s from 0.46 mL/s at a 95% stenosis; a finding explained by the contralateral Vert (which supplies the SCA) being the dominant inflow to the contralateral hemisphere. As the contralateral stenosis increased from 90%, to 95%, to occlusion, small increases in ipsilateral PCA, ACA, and Vert flow were observed. Moreover, contralateral PCA and ACA flow remained relatively unchanged across these cases.

Impact of boundary conditions on hemodynamics

Figure 8 depicts changes in CBF and ECA flow between the primary (Figure 8A: ECA flow imposed) and alternate (Figure 8B: ECA coupled to a 3-element Windkessel model) boundary conditions for cases of 90% and 95% contralateral stenosis and contralateral occlusion. When the ECA flow was not imposed (i.e., alternate boundary conditions), bilateral ECA flow increased with increasing contralateral stenosis. Although the amount of CBF was less with the alternate boundary conditions compared to primary boundary conditions, the trends of CBF did not change. Left CBF decreased and right CBF increased with increasing contralateral (left) ICA stenosis.

Figure 8 Comparison of bilateral CBF and ECA flow between primary and alternate boundary conditions. (A) CBF and ECA flow for primary boundary condition for cases of contralateral (left) stenosis (90%, 95%, and occlusion). (B) CBF and ECA flow for alternative boundary condition for cases of contralateral (left) stenosis (90%, 95%, and occlusion). CBF, cerebral blood flow; ECA, external carotid artery; L CBF, left hemispheric cerebral blood flow; LECA, left external carotid artery; R CBF, right hemispheric cerebral blood flow; RECA, right external carotid artery.

Similarly, when assessing the impact of boundary conditions on ipsilateral ICA hemodynamics, the overall values had subtle differences, but the trends were not impacted. As the contralateral stenosis increased from 90%, to 95%, to occlusion, the ipsilateral PSV (190.0, 226.0, 285.7 cm/s) and EDV (101.1, 123.5, 155.4 cm/s) increased. When the contralateral ICA stenosis increased from 90% to 95% and then to occlusion, the ipsilateral PG decreased from 0.994 to 0.992 to 0.989. Lastly, as the contralateral ICA stenosis was increased from 90% to 95% and then to occlusion, the ipsilateral WSS increased from 1.61 to 1.99 Pa and then 5.28 Pa. Table S1 includes a comparison of the changes in ipsilateral hemodynamics between boundary condition sets for the aforementioned cases.

Discussion

In this study, we aimed to assess how a contralateral ICA stenosis affects the hemodynamics of the ipsilateral ICA, thus shedding light on the potential impact on ipsilateral stroke risk. We utilized a validated, patient-specific, MRI-informed CFD model as a ground-truth case and systematically altered levels of contralateral stenosis to quantify the impact of contralateral ICA stenosis on ipsilateral ICA hemodynamics. We found that as contralateral ICA stenosis increased from baseline to occlusion, ipsilateral hemodynamics were affected to varying degrees. Ipsilateral ICA velocities (PSV and EDV) were relatively unchanged until contralateral stenosis was 75% or higher. However, large increases in ipsilateral velocities were observed for cases with a 90% stenosis, 95% stenosis, or occlusion of the contralateral ICA. Additionally, ipsilateral velocities were elevated above common thresholds for consideration of surgical repair (PSV >230 cm/s and EDV >110 cm/s at our institution) in cases with 95% contralateral stenosis or contralateral occlusion. Similar trends were observed for ipsilateral PG and WSS, which remained relatively unchanged until the contralateral stenosis reached 90% or above. Finally, we found minimal changes in ipsilateral and contralateral CBF until the contralateral stenosis reached 90% or above, with substantial redistribution of CBF in the case of a contralateral occlusion. These data demonstrate that contralateral ICA stenosis impacts the ipsilateral ICA hemodynamics and thus may affect ipsilateral stroke risk. Careful consideration of the contralateral %stenosis should be made when considering management of an ipsilateral ICA stenosis.

Several studies have demonstrated that in the presence of a contralateral ICA stenosis or occlusion, the ipsilateral velocities may be increased (1-4). Data from NASCET demonstrated that in patients with severe stenosis, bilaterally, PSV in the unoperated artery was over-estimated by an average of 84 cm/s (1). Additionally, they found elevations in PSV for cases with a contralateral moderate, mild and minimal stenoses (21 cm/s for moderate, 20 cm/s for mild, and 11 cm/s for minimal stenosis) (1). Other authors have suggested that contralateral ICA stenosis ≥50% is a critical threshold for the overestimation of ipsilateral ICA stenosis (2). The over-estimations in ipsilateral ICA velocities have been shown to be reversible with treatment of the contralateral lesion (3-5,17). Ratner et al. found that following CEA/CAS almost 70% of patients had a decrease in their contralateral velocities and over 40% were re-designated into a different %stenosis category (5). Sachar et al. suggested an approximate 25% drop in contralateral velocities after ipsilateral CAS (3). Abou-Zamzam et al. found that CEA resulted in the reclassification of the contralateral carotid stenosis in only 20% of cases (17). Our study supports these findings, as we demonstrate a stepwise increase in ipsilateral velocities with increasing contralateral stenosis. Our data suggests an increase in ipsilateral PSV of up to 147 cm/s and EDV of up to 69 cm/s, depending on the severity of contralateral disease. This is of particular concern when CEA/CAS is considered only on the basis of DUS velocities, which historically has been used as the single diagnostic tool for preoperative planning (18,19). Moreover, our data provides important reference values for the expected increase in ipsilateral velocities based on different contralateral stenosis amounts, which can be used when considering management of patients with bilateral ICA stenoses.

The change in contralateral velocities after ipsilateral intervention is thought to be multifactorial. Many studies have suggested shunting of blood flow to the contralateral artery and the great vessels as the primary mechanism (1,4,5). van Everdingen et al. demonstrated this phenomenon using magnetic resonance angiography to quantify the increase in flow through the contralateral carotid in the presence of high-grade ipsilateral stenosis (20). An additional mechanism to explain this phenomenon relates to vessel compliance. Increased plaque burden in the carotid artery has been associated with decreases in vascular compliance, a finding that has also been demonstrated in the coronary arteries (21-23). Decreases in compliance can result in reduced vascular dilation and thus contribute to larger increases in velocity when there is increased flow. Lastly, cerebral autoregulation plays a critical role in mediating the cerebral flow and thus velocities. Severe bilateral ICA stenosis can contribute to states of decreased flow in the cerebral vasculature and loss of cerebral autoregulation, thus resulting in chronically dilated intracerebral vessels (24,25). Our modeling approach kept the vascular resistances of the intracerebral vessels fixed, and thus did not account for cerebral autoregulation. However, imposing vascular resistances rather than fixed pressure or flow waveforms allows us to capture changes in intracerebral hemodynamics as we increased contralateral ICA stenosis. We observed increases in ipsilateral CBF with increasing degrees of contralateral ICA stenosis (especially in cases of 90% stenosis, 95% stenosis, and occlusion), and thus support shunting of blood flow as a potential mechanism to explain the increased ipsilateral velocities.

Although elevations in velocities and shunting of blood flow have been previously studied, to our knowledge, there have not been any studies assessing alterations in ipsilateral WSS and/or PG with contralateral stenosis, reported in a systematic and controlled manner from a ground-truth model calibrated with rich MRI data. WSS across the carotid bifurcation is variable, with physiological values ranging from 0.4 Pa along the inner curve and carotid bulb (which typically have large amounts of recirculation) to up to 3.0 Pa along the flow divider and >5.0 Pa at the site of stenosis (26). In the absence of stenosis, low WSS (<0.4 Pa) regions are associated with subintimal thickening and are atherosclerosis-prone, with physiological WSS (~1.5 Pa) being athero-protective (27-29). However, in the presence of a stenosis high WSS is associated with vulnerable plaque features and plaque rupture/embolization (10,28,30,31). Trans-lesional PG measurements have been shown to predict response to renal artery stenting and optimize selection for coronary interventions (32-34). Moreover, fractional flow reserve (FFR) has been used to predict hemodynamic significance of coronary artery lesions (33-35). However, traditional measurements of PG are invasive and thus are often not obtained. Moreover, FFR relies on hyperemic conditions and thus is not feasible in the cerebrovascular space. Conversely, CFD-derived trans-lesional PG can be obtained non-invasively and is correlated with ICA stenosis severity and stroke risk (36-38). Nonetheless, well-defined WSS and PG values for different levels of ICA stenosis remain undetermined. Our data demonstrates that both ipsilateral WSS and PG are affected by the level of contralateral stenosis. Specifically, we found that with a contralateral stenosis ≥90% ipsilateral WSS is significantly increased from baseline and PG is decreased from baseline, suggesting that the level of contralateral ICA stenosis (especially ≥90%) impacts the risk of ipsilateral stroke.

Bilateral ICA stenosis has been associated with both increased stroke risk and worse outcomes after revascularization (39-42). A severe ipsilateral ICA stenosis in conjunction with a contralateral ICA stenosis has been suggested as an independent risk factor of transient ischemic attack and/or stroke (42). However, a separate study found that severe contralateral stenosis or occlusion did not increase the risk of ipsilateral stroke, although it was an independent risk factor for myocardial infarction, perioperative stroke, and overall stroke/death (43). When looking at all patients with acute ischemic stroke, both ipsilateral and contralateral ICA stenosis have been associated with worse outcomes after revascularization (39). Moreover, patients with contralateral ICA stenosis greater than 50% have higher mortality after acute ipsilateral ischemic stroke (40,41). Our data sheds light on how changes in hemodynamics may contribute to worse outcomes and increased risk of stroke in patients with bilateral ICA stenosis.

Approximately half of patients will have a compensatory increase in ECA flow in the setting of ICA occlusion (44). Although an average increase in bilateral ECA flow of 200% has been reported, there are variable compensation amounts between ipsilateral and contralateral ECA (44). In this study, we explored scenarios without ECA flow compensation (primary boundary conditions) and with ECA flow compensation (alternate boundary conditions). As expected, we found in cases where ECA flow compensation was allowed that bilateral ECA flow increased with increased contralateral ICA stenosis. Although we found subtle differences in CBF between boundary conditions, trend of CBF changes were similar. Moreover, allowing for ECA flow compensation did not appear to significantly alter ipsilateral ICA hemodynamics. This further supports the generalizability of our findings as they likely apply to patients with and without ECA flow compensation.

This study is limited because it focuses on only one patient, thus limiting the generalizability of our results. Given the analysis is from one patient, we cannot account for the impact of clinical factors associated with carotid artery disease, such as sex, hypertension, smoking status, etc. Additionally, this patient has a bovine arch and an incomplete CoW, which could alter blood flow shunting pathways and thus alter hemodynamics, further limiting the generalizability of our results. Patients with bovine arches have been shown to have higher systolic WSS along the inner curve of the aorta compared to those with conventional aortic arches (45). Additionally, fetuses with bovine arches have lower PSV, shorter acceleration times, and shorter deceleration times in the brachiocephalic, left CCA, and left subclavian arteries on DUS than those with normal arch anatomy (46). Although it is possible that the presence of a bovine arch could impact the results seen in our study, to our knowledge, there are no reports that patients with bovine arches have differences in ICA or intracerebral hemodynamics. Although it is difficult to assess the impact of an incomplete CoW on our results, up to 63–91% of patients have an incomplete CoW (47-49). The exact prevalence of different CoW anatomies is poorly understood (50). The most common CoW abnormality is an absence of one or both posterior communicating arteries (50). However, these studies do not account for occluded or hypoplastic vertebral arteries, which have a prevalence of 6% and 11%, respectively (50-52). Given that this patient had an occluded/hypoplastic right Vert and no right posterior communicating artery, it is reasonable to assume this reflects a common scenario amongst those with incomplete CoW. Nonetheless, we did not assess how different CoW anatomies (including differences in incomplete CoWs) impact ICA and cerebral hemodynamics. Furthermore, in our modeling approach, we did not allow for changes in resistance and compliance and thus do not account for cerebral autoregulation which may affect the distribution of blood flow with varying %stenosis. We modeled the vessel walls as rigid, although, as discussed earlier, carotid disease is associated with increases in stiffness, and therefore, a rigid wall assumption is reasonable. We did not assess or account for plaque composition, which is highly associated with stroke risk (53,54), and thus we may not have captured the full extent of embolic potential. We did not assess how changes in ipsilateral, along with contralateral %stenosis would impact hemodynamics.

Although a growing body of research has implemented hemodynamics as an important risk factor for plaque embolism, thresholds of WSS and PG for different levels of ICA stenosis and high stroke risk have not yet been defined, and thus our results cannot be used to estimate a patients’ stroke risk. Thus, future directions will include analysis of more patients to define hemodynamic phenotypes for different ICA stenosis categories and to determine associations of hemodynamics with clinical outcomes and stroke risk. Although CFD can non-invasively assess patient-specific hemodynamics, as demonstrated in this study, CFD is time-consuming and has complex data inputs and outputs. Thus, it is unlikely that the present CFD workflow would be directly translatable to clinical practice. As such, our group is working to determine the associations between CFD-derived hemodynamics and current clinical imaging (i.e., DUS/CTA).

Conclusions

In this study, using a validated patient-specific CFD model, we found that contralateral ICA stenosis impacts ipsilateral ICA hemodynamics and thus could impact the ipsilateral stroke risk. In the presence of a contralateral stenosis ≥90% ipsilateral velocities, flow, WSS, and PG were significantly altered from baseline. Moreover, in the presence of a contralateral stenosis ≥95% or occlusion, the ipsilateral velocities may be elevated past thresholds for CEA/CAS. Consideration of the contralateral %stenosis should be made when considering management of an ipsilateral ICA stenosis.

Acknowledgments

None.

Footnote

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1093/dss

Funding: This study was supported by the National Institute of Health (No. F32HL168968).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1093/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Institutional Review Board of the University of Michigan (No. HUM00114275) and informed consent was obtained from the patient.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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