In Vivo Validation of Patient-Specific Pressure Gradient Calculations for Iliac Artery Stenosis Severity Assessment.

BACKGROUND

Currently, the decision to treat iliac artery stenoses is mainly based on visual inspection of digital subtraction angiographies. Intra-arterial pressure measurements can provide clinicians with accurate hemodynamic information. However, pressure measurements are rarely performed because of their invasiveness and the time required. Therefore, the aim of the study was to test the feasibility of a computational model that can predict translesional pressure gradients across iliac artery stenoses on the basis of imaging data only.

METHODS AND RESULTS

Patients (N=21) with symptomatic peripheral arterial disease and a peak systolic velocity ratio between 2.5 and 5.0 were included in the study. Patients underwent per-procedural 3-dimensional rotational angiography and hyperemic intra-arterial translesional pressure measurements. Vascular anatomical features were reconstructed from the 3-dimensional rotational angiography data into an axisymmetrical 2-dimensional computational mesh, and flow was estimated on the basis of the stenosis geometry. Computational fluid dynamics were performed to predict the pressure gradient and were compared with the measured pressure gradients. A good agreement by overlapping error bars of the predicted and measured pressure gradients was found in 21 of 25 lesions. Stratification of the stenosis on the basis of the predicted pressure gradient into hemodynamic not significant (<10 mm Hg) and hemodynamic significant (≥10 mm Hg) resulted in sensitivity, specificity, and overall predictive values of 95%, 60%, and 88%, respectively.

CONCLUSIONS

The feasibility of the patient-specific computational model to predict the hyperemic translesional pressure gradient over iliac artery stenosis was successfully tested. Presented results suggest that, with further optimization and corroboration, the model can become a valuable aid to the diagnosis of equivocal iliac artery stenosis.

CLINICAL TRIAL REGISTRATION

URL: http://www.trialregister.nl. Unique identifier: NTR5085.