Craniosynostosis is a skull malformation because of premature fusing of one or more cranial sutures. The most common types of craniosynostosis are scaphocephaly (with the sagittal suture fused) and trigonocephaly (with the metopic suture fused). In this paper we describe and discuss how finite element analysis and three-dimensional modeling can be used for preoperative planning of the correction of craniosynostosis and for the postoperative evaluation of the treatment results. We used the engineering software MIMICS MATERIALISE to obtain three-dimensional geometry from computed tomography scans, and applied finite element method for the sake of biomechanical analysis. These simulations help to improve the surgical treatment, making it more accurate, safer, and faster.
this study analyzed morphometric and hemodynamic parameters of aneurysmal and non-aneurysmal middle cerebral artery (McA) bifurcations and their relationship with optimal values derived from the principle of minimum work (PMW). The study included 96 patients with MCA aneurysm and 94 controls. Aneurysm patients presented with significantly higher values of the radius and cross-sectional area of the McA trunk, angle between the post-bifurcation branches (α angle) and volume flow rate (VFR) and had significantly lower values of junction exponent and pulsatility index than the controls. The Φ 1 and Φ 2 angles (angles between the MCA trunk axis and the larger and smaller branch, respectively) and α angle in all groups were significantly larger than the optimal PMW-derived angles. The most important independent predictors of MCA aneurysm were junction exponent (odds ratio, OR = 0.42), α angle (oR = 1.07) and VFR (OR = 2.36). Development of cerebral aneurysms might be an independent effect of abnormalities in hemodynamic and morphometric factors. The risk of aneurysm increased proportionally to the deviation of morphometric parameters of the bifurcation from their optimal pMWderived values. The role of bifurcation angle in aneurysm development needs to be explained in future research as the values of this parameter in both aneurysm patients and non-aneurysmal controls in were scattered considerably around the pMW-derived optimum.
Background
Previously published computational fluid dynamics (CFD) studies regarding intracranial aneurysm (IA) formation present conflicting results. Our study analysed the involvement of the combination of high wall shear stress (WSS) and a positive WSS gradient (WSSG) in IA formation.
Methods
We designed a case-control study with a selection of 38 patients with an unruptured middle cerebral artery (MCA) aneurysm and 39 non-aneurysmal controls to determine the involvement of WSS, oscillatory shear index (OSI), the WSSG and its absolute value (absWSSG) in aneurysm formation based on patient-specific CFD simulations using velocity profiles obtained from transcranial colour-coded sonography.
Results
Among the analysed parameters, only the WSSG had significantly higher values compared to the controls (11.05 vs − 14.76 [Pa/mm], P = 0.020). The WSS, absWSSG and OSI values were not significantly different between the analysed groups. Logistic regression analysis identified WSS and WSSG as significant co-predictors for MCA aneurysm formation, but only the WSSG turned out to be a significant independent prognosticator (OR: 1.009; 95% CI: 1.001–1.017; P = 0.025). Significantly more patients (23/38) in the case group had haemodynamic regions of high WSS combined with a positive WSSG near the bifurcation apex, while in the control group, high WSS was usually accompanied by a negative WSSG (14/39). From the analysis of the ROC curve for WSSG, the area under the curve (AUC) was 0.654, with the optimal cut-off value −0.37 Pa/mm. The largest AUC was recognised for combined WSS and WSSG (AUC = 0.671). Our data confirmed that aneurysms tend to form near the bifurcation apices in regions of high WSS values accompanied by positive WSSG.
Conclusions
The development of IAs is determined by an independent effect of haemodynamic factors. High WSS impacts MCA aneurysm formation, while a positive WSSG mainly promotes this process.
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