Background Specifying generic flow boundary conditions in aneurysm hemodynamic simulations yields a great degree of uncertainty for the evaluation of aneurysm rupture risk. Herein, we proposed the use of flowrate-independent parameters in discriminating unstable aneurysms and compared their prognostic performance against that of conventional absolute parameters.
Methods This retrospective study included 186 aneurysms collected from three international centers, with the stable aneurysms having a minimum follow-up period of 24 months. The flowrate-independent aneurysmal wall shear stress (WSS) and energy loss (EL) were defined as the coefficients of the second-order polynomials characterizing the relationships between the respective parameters and the parent-artery flows. Performance of the flowrate-independent parameters in discriminating unstable aneurysms with the logistic regression, Adaboost, and support-vector machine (SVM) methods was quantified and compared against that of the conventional parameters, in terms of sensitivity, specificity, and area under the curve (AUC).
Results In discriminating unstable aneurysms, the proposed flowrate-independent EL achieved the highest sensitivity (0.833, 95% CI 0.586 to 0.964) and specificity (0.833, 95% CI 0.672 to 0.936) on the SVM, with the AUC outperforming the conventional EL by 0.133 (95% CI 0.039 to 0.226, p=0.006). Likewise, the flowrate-independent WSS outperformed the conventional WSS in terms of the AUC (difference: 0.137, 95% CI 0.033 to 0.241, p=0.010).
Conclusion The flowrate-independent hemodynamic parameters surpassed their conventional counterparts in predicting the stability of aneurysms, which may serve as a promising set of hemodynamic metrics to be used for the prediction of aneurysm rupture risk when physiologically real vascular boundary conditions are unavailable.
- Blood Flow
Data availability statement
Data are available upon reasonable request.
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MZ and XH contributed equally.
Contributors (1) Guarantor of integrity of the entire study and responsible for the overall content, CO and CD; (2) study concepts/study design, CO, CD, YQ, and MZ; (3) patient data acquisition, YQ, WC, XZ, and CO; (4) numerical simulation, XH, MZ, and CO; (5) data analysis, all authors; (6) manuscript drafting, CO and MZ; (7) manuscript revision for important intellectual content, all authors; (8) approval of final version of submitted manuscript, all authors; (9) agrees to ensure any questions related to the work are appropriately resolved, all authors; and (10) manuscript editing, all authors.
Funding This study is supported by the National Natural Science Foundation (Grants No.: 81974177 and 81974178).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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