Hemodynamics derived from computational fluid dynamics based on magnetic resonance angiography is associated with functional outcomes in atherosclerotic middle cerebral artery stenosis

Jiahua Wu, Peng Wang, Leilei Zhou, Danfeng Zhang, Qian Chen, Cunnan Mao, Wen Su, Yingsong Huo, Jin Peng, Xindao Yin, Guozhong Chen, Jiahua Wu, Peng Wang, Leilei Zhou, Danfeng Zhang, Qian Chen, Cunnan Mao, Wen Su, Yingsong Huo, Jin Peng, Xindao Yin, Guozhong Chen

Abstract

Background: To investigate the relationship between fluid-attenuated inversion recovery (FLAIR) vascular hyperintensity (FVH), hemodynamics, and functional outcome in atherosclerotic middle cerebral artery (MCA) stenosis using a computational fluid dynamics (CFD) model based on magnetic resonance angiography (MRA), according to a modified Rankin Scale (mRS) at 3 months.

Methods: A total of 120 patients with 50-99% atherosclerotic MCA stenosis were included. The training and internal validation groups were composed of 99 participants and 21 participants, respectively. Demographic, imaging data, and functional outcome (mRS at 3 months) were collected. Hemodynamic parameters were obtained from the CFD model. The FVH score was based on the number of territories where FVH is positive, according to the spatial distribution in the Alberta Stroke Program Early Computed Tomography Score (ASPECTS). The prediction models were constructed according to clinical and hemodynamic parameters using multivariate logistic analysis. The DeLong test compared areas under the curves (AUCs) of the models.

Results: The multivariable logistic regression analysis showed that the National Institute of Health Stroke Scale (NIHSS) at admission, hypertension, hyperlipidemia, the ratio of wall shear stress before treatment (WSSRbefore), and difference in the ratio of wall shear stress (WSSR) were independently associated with functional outcome (all P<0.05). In the training group before treatment, the AUC of model 1a (only clinical variables) and 2a (clinical variables with addition of WSSRbefore) were 0.750 and 0.802. After treatment, the AUC of model 1b (only clinical variables) and 2b (clinical variables with addition of difference in WSSR) were 0.815 and 0.883, respectively. The AUC of models with hemodynamic parameters was significantly higher than the models based on clinical variables only (all P<0.05, DeLong test). In the internal validation group before treatment, the AUC of the model (clinical variables) was 0.782, and that of the model (clinical variables and WSSRbefore) was 0.800. After treatment, the AUC of the model (clinical variables) was 0.833, and that of the model (clinical variables and difference in WSSR) was 0.861. There were no significant differences between the good and the poor functional outcome group concerning FVHbefore scores before treatment (0.30±0.81 vs. 0.26±0.97; P=0.321) and FVHafter scores after treatment (0.08±0.39 vs. 0.00±0.00; P=0.244).

Conclusions: Hemodynamics was associated with functional outcomes in patients with ischemic stroke attributed to atherosclerotic MCA stenosis, while FVH was not. Hemodynamic parameters were of great importance in the prediction models.

Keywords: Middle cerebral artery (MCA); arterial stenosis; computational fluid dynamics (CFD); magnetic resonance angiography (MRA); stroke.

Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/qims-21-337). The authors have no conflicts of interest to declare.

2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Figures

Figure 1
Figure 1
CFD models and FLAIR images for a case with atherosclerotic right MCA stenosis, who had good functional outcome (mRS at 3 months, 2 score). (A,B) Contours of WSS and pressure before treatment. WSSR of this case before treatment was 6.10 and PR was 0.99. (C,D) FLAIR images before treatment with no FVH (FVH score =0). (E,F) Contours of WSS and pressure after treatment. WSSR of this case after treatment was 1.49 and PR was 1.00. Difference in WSSR =4.61, Difference in PR =0.01. (G,H) FLAIR images after treatment with no FVH (FVH score =0). CFD, computational fluid dynamics; FLAIR, fluid-attenuated inversion recovery; MCA, middle cerebral artery; mRS, modified Rankin Scale; WSS, wall shear stress; WSSR, ratio of wall shear stress; PR, ratio of pressure; FVH, fluid-attenuated inversion recovery vascular hyperintensity.
Figure 2
Figure 2
CFD models and FLAIR images for a case with atherosclerotic right MCA stenosis, who had poor functional outcome (mRS at 3 months, 3 score). (A,B) Contours of WSS and pressure before treatment. WSSR of this case before treatment was 2.78 and PR was 0.98. (C,D) FLAIR images before treatment with no FVH (FVH score =0). (E,F) Contours of WSS and pressure after treatment. WSSR of this case after treatment was 1.27 and PR was 1.00. Difference in WSSR =1.51, Difference in PR =0.02. (G,H) FLAIR images after treatment with no FVH (FVH score =0). CFD, computational fluid dynamics; FLAIR, fluid-attenuated inversion recovery; MCA, middle cerebral artery; mRS, modified Rankin Scale; WSS, wall shear stress; WSSR, ratio of wall shear stress; PR, ratio of pressure; FVH, fluid-attenuated inversion recovery vascular hyperintensity.
Figure 3
Figure 3
ROC curves of the multivariable models before and after treatment. (A) ROC curves of the multivariable models before treatment. Model 1a, only clinical variables; Model 2a, clinical variables with addition of WSSRbefore. The AUC of the model 1a and model 2a were 0.750 and 0.802 respectively. (B) ROC curves of the multivariable models after treatment. Model 1b, only clinical variables; model 2b, clinical variables with addition of difference in WSSR. The AUC of the model 1b and model 2b were 0.815 and 0.883 respectively. ROC, receiver operating characteristic; WSSRbefore, ratio of wall shear stress before treatment; AUC, area under the ROC curve; difference in WSSR, the difference between pre-treatment and post-treatment of WSSR.

Source: PubMed

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