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OBJECTIVEIncidental aneurysms pose a challenge for physicians, who need to weigh the rupture risk against the risks associated with treatment and its complications. A statistical model could potentially support such treatment decisions. A recently developed aneurysm rupture probability model performed well in the US data used for model training and in data from two European cohorts for external validation. Because Japanese and Finnish patients are known to have a higher aneurysm rupture risk, the authors’ goals in the present study were to evaluate this model using data from Japanese and Finnish patients and to compare it with new models trained with Finnish and Japanese data.METHODSPatient and image data on 2129 aneurysms in 1472 patients were used. Of these aneurysm cases, 1631 had been collected mainly from US hospitals, 249 from European (other than Finnish) hospitals, 147 from Japanese hospitals, and 102 from Finnish hospitals. Computational fluid dynamics simulations and shape analyses were conducted to quantitatively characterize each aneurysm’s shape and hemodynamics. Next, the previously developed model’s discrimination was evaluated using the Finnish and Japanese data in terms of the area under the receiver operating characteristic curve (AUC). Models with and without interaction terms between patient population and aneurysm characteristics were trained and evaluated including data from all four cohorts obtained by repeatedly randomly splitting the data into training and test data.RESULTSThe US model’s AUC was reduced to 0.70 and 0.72, respectively, in the Finnish and Japanese data compared to 0.82 and 0.86 in the European and US data. When training the model with Japanese and Finnish data, the average AUC increased only slightly for the Finnish sample (to 0.76 ± 0.16) and Finnish and Japanese cases combined (from 0.74 to 0.75 ± 0.14) and decreased for the Japanese data (to 0.66 ± 0.33). In models including interaction terms, the AUC in the Finnish and Japanese data combined increased significantly to 0.83 ± 0.10.CONCLUSIONSDeveloping an aneurysm rupture prediction model that applies to Japanese and Finnish aneurysms requires including data from these two cohorts for model training, as well as interaction terms between patient population and the other variables in the model. When including this information, the performance of such a model with Japanese and Finnish data is close to its performance with US or European data. These results suggest that population-specific differences determine how hemodynamics and shape associate with rupture risk in intracranial aneurysms.

BACKGROUND AND PURPOSE: Identifying and predicting which aneurysms are likely to quickly occlude and which ones are likely to remain open following treatment with flow-diverting devices is important to develop optimal patient management strategies. The purpose of this study was to evaluate predictions based on computational fluid dynamics models using the elastase rabbit aneurysm model. MATERIALS AND METHODS:A series of 13 aneurysms created in rabbits were treated with flow diverters, and outcomes were angiographically assessed at 8 weeks' follow-up. Computational fluid dynamics models were constructed from pretreatment 3D rotational angiograms and Doppler ultrasound flow velocity measurements. Postimplantation mean aneurysm inflow rate and flow velocity were used to prospectively predict aneurysm occlusion blinded to the actual outcomes. Specifically, if both variables were below their corresponding thresholds, fast occlusion was predicted, while if one of them was above the threshold, slow or incomplete occlusion was predicted.RESULTS: Of the 13 aneurysms included, 8 were incompletely occluded 8 weeks after treatment, and 5 were completely occluded. A total of 10 computational fluid dynamics-based predictions agreed with the angiographic outcome, reaching 77% accuracy, 80% sensitivity, and 75% specificity. Posttreatment mean velocity alone was able to achieve the same predictive power as the combination of inflow rate and velocity. CONCLUSIONS: Subject-specific computational fluid dynamics models of the hemodynamic conditions created immediately after implantation of flow-diverting devices in experimental aneurysms created in rabbits are capable of prospectively predicting, with a reasonable accuracy, which aneurysms will completely occlude and which ones will remain incompletely occluded.

Background and Purpose: Delayed intraparenchymal hemorrhages (DIPHs) are one of the most serious complications of cerebral aneurysm treatment with flow diverters (FD), yet their causes are largely unknown. This study analyzes distal hemodynamic alterations induced by the treatment of intracranial aneurysms with FDs.Methods: A realistic model of the brain arterial network was constructed from MRA images and extended with a constrained constructive optimization technique down to vessel diameters of approximately 50μm. Different variants of the circle of Willis were created by alternatively occluding communicating arteries. Collateral vessels connecting different arterial trees were then added to the model, and a distributed lumped parameter approach was used to model the pulsatile blood flow in the arterial network. The treatment of an ICA aneurysm was modeled by changing the local resistance, flow inertia, and compliance of the aneurysmal segment.Results: The maximum relative change in distal pressure induced by the aneurysm treatment was below 1%. However, for certain combinations of the circle of Willis and distal collateralization, important flow reversals (with a wall shear stress larger than approximately 1.0 dyne/cm2) were observed in collateral vessels, both ipsilaterally and contralaterally to the treated aneurysm.Conclusion: This study suggests the hypothesis that flow diverters treatment of intracranial aneurysms could cause important flow reversal in distal collaterals. Flow reversal has previously been shown to be pro-inflammatory and pro-atherogenic and could therefore have a detrimental effect on these collateral vessels, and thus could be a suitable explanation of DIPHs, while the small distal pressure increase is not.

Introduction: Computational fluid dynamics (CFD) assess biological systems based on specific boundary conditions. We propose modeling more advanced hemodynamic metrics, such as core line length (CL) and critical points which characterize complexity of flow in the context of cerebral vasculature, and specifically cerebral veins during the physiologically evolving early neonatal state of vein of Galen malformations (VOGM). CFD has not been applied to the study of arteriovenous shunting in Vein of Galen Malformations but could help illustrate the pathophysiology of this malformation.Methods: Three neonatal patients with VOGM at Boston Children’s Hospital met inclusion criteria for this study. Structural MRI data was segmented to generate a mesh of the VOGM and venous outflow. Boundary condition flow velocity was derived from PC-MR sequences with arterial and venous dual velocity encoding. The mesh and boundary conditions were applied to model the cerebral venous flow. We computed flow variables including mean wall shear stress (WSSmean), mean OSI, CL, and the mean number of critical points (nCrPointsmean) for each patient specific model. A critical point is defined as the location where the shear stress vector field is zero (stationary point) and can be used to describe complexity of flow.Results: The division of flow into the left and right venous outflow was comparable between PC-MR and CFD modeling. A high complexity recirculating flow pattern observed on PC-MR was also identified on CFD modeling. Regions of similar WSSmean and OSImean (<1.3 fold) in the left and right venous outflow channels of a single patient have several-fold magnitude difference in higher order hemodynamic metrics (> 3.3 fold CL, > 1.7 fold nCrPointsmean). Specifically, the side which developed JBS in each model had greater nCrPointsmean compared to the jugular bulb with no stenosis (VOGM1: 4.49 vs. 2.53, VOGM2: 1.94 vs. 0, VOGM3: 1 vs. 0). Biologically, these regions had subsequently divergent development, with increased complexity of flow associating with venous stenosis. Discussion: Advanced metrics of flow complexity identified in computational models may reflect observed flow phenomena not fully characterized by primary or secondary hemodynamic parameters. These advanced metrics may indicate physiological states that impact development of jugular bulb stenosis in VOGM.