Abstract Body: Introduction: Internal carotid artery (ICA) stenosis is classified as percentage stenosis (%Stenosis) using duplex ultrasound (DUS) velocities or computed tomography angiography (CTA) anatomy. However, variability exists between velocity and anatomic-based %Stenosis classifications and neither classification method accounts for hemodynamics such as flow, pressure gradient (PG), and wall shear stress (WSS), which impact stroke risk.

Hypothesis: We hypothesize that PG and WSS derived from computational fluid dynamics simulations (CFD) will assist in ICA %Stenosis classification.

Aims: Evaluate differences in ICA hemodynamics among %Stenosis groups and define PG/WSS hemodynamic ranges for ICA stenosis.

Methods: Patients with asymptomatic >70% ICA stenosis on DUS were prospectively enrolled for phase-contrast (PC) magnetic resonance imaging (MRI). Geometric models of the bilateral common carotid artery (CCA), ICA, and external carotid artery (ECA) were created from CTA. PC MRI-derived flow waveforms were prescribed to the CCA and ECA and the ICA outlet was coupled to a 3-element Windkessel model. Navier-Stokes equations were used to solve for velocity and pressures. ICA flow, PG=P_distal/P_proximal, and WSS were estimated using CFD. DUS and CTA were used to assess %Stenosis of the bilateral ICA. Cases with agreement in %Stenosis on DUS and CTA were used to define average hemodynamics for %Stenosis groups. Average hemodynamics were then used to clarify %Stenosis classification in the cases without agreement on DUS and CTA. Figure 1 depicts the model inputs, outputs, and application.

Results: Thirty arteries were included (average age 71.3 years, 53.3% male). DUS and CTA %Stenosis agreed in 24/30 (80%) cases (6 mild, 3 moderate, 15 severe). Table 1 depicts standard diagnostics and hemodynamics for cases with %Stenosis agreement. As %Stenosis increased, WSS increased and PG decreased. No significant differences in ICA flow were observed. Figure 2 depicts the 6 cases which had disagreement in %Stenosis classifications. Velocity tended to over-estimate %Stenosis compared to anatomy. Addition of PG and WSS assisted in clarifying the %Stenosis classification in cases with disagreement.

Conclusions: While velocity and anatomic %Stenosis agree in most cases, 20% show discrepancies. Using hemodynamic parameters (WSS/PG), in addition to velocity and anatomical %Stenosis, provides a comprehensive assessment of stenosis severity and can discriminate %Stenosis in discordant cases.