The model combining variables from various domains was able to discriminate between ruptured and unruptured aneurysms with an AUC of 86%. Internal validation indicated potential for the application of this model in clinical practice after evaluation with longitudinal data.

Purpose-The mechanisms of cerebral aneurysm rupture are not fully understood. We analyzed the associations of hemodynamics, morphology, patient age and gender with aneurysm rupture stratifying by location.Methods-Using image-based models, 20 hemodynamic and 17 morphological parameters were compared in 1931 ruptured and unruptured aneurysms with univariate logistic regression. Rupture rates were compared between males and females as well as younger and older patients and bifurcation versus sidewall aneurysms for different aneurysm locations. Subsequently, associations between hemodynamics and morphology and patient as well as aneurysm characteristics were analyzed for aneurysms at five locations.Results-Compared to unruptured aneurysms, ruptured aneurysms were characterized by a more irregular shape and were exposed to a more adverse hemodynamic environment described by faster flow, higher wall shear stress, more oscillatory shear, and more unstable and complex flows. These associations with rupture status were consistent for different aneurysm locations. Rupture rates were significantly higher in males at the internal carotid artery (ICA) bifurcation, ophthalmic ICA and the middle cerebral artery (MCA) bifurcation. At the anterior communicating artery (ACOM) and MCA bifurcation, they were significantly higher for younger patients. Bifurcation aneurysms had significantly larger rupture rates at the MCA and posterior communicating artery *

No abstract

Augmented and virtual reality systems have the potential to improve safety and outcomes of renal interventions. In the last ten years, many technical advances have led to more sophisticated systems, which are already applied in clinical practice. Further research is required to cope with current limitations of virtual and augmented reality assistance in clinical environments.

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.

No abstract

Background: For a treatment decision of unruptured cerebral aneurysms, physicians and patients need to weigh the risk of treatment against the risk of hemorrhagic stroke caused by aneurysm rupture. The aim of this study was to externally evaluate a recently developed statistical aneurysm rupture probability model, which could potentially support such treatment decisions. Methods: Segmented image data and patient information obtained from two patient cohorts including 203 patients with 249 aneurysms were used for patient-specific computational fluid dynamics simulations and subsequent evaluation of the statistical model in terms of accuracy, discrimination, and goodness of fit. The model’s performance was further compared to a similaritybased approach for rupture assessment by identifying aneurysms in the training cohort that were similar in terms of hemodynamics and shape compared to a given aneurysm from the external cohorts. Results: When applied to the external data, the model achieved a good discrimination and goodness of fit (area under the receiver operating characteristic curve AUC=0.82), which was only slightly reduced compared to the optimism-corrected AUC in the training population (AUC=0.84). The accuracy metrics indicated a small decrease in accuracy compared to the training data (misclassification error of 0.24 vs. 0.21). The model’s prediction accuracy was improved when combined with the similarity approach (misclassification error of 0.14). Conclusions: The model’s performance measures indicated a good generalizability for data acquired at different clinical institutions. Combining the model-based and similarity-based approach could further improve the assessment and interpretation of new cases, demonstrating its potential use for clinical risk assessment.

Background and Purpose Intracranial aneurysms at the posterior communicating artery (PCOM) origin are known to have high rupture risk compared to other locations. We tested the hypothesis that different angio-architectures (i.e. branch point configuration) of PCOM aneurysms associated with aneurysm hemodynamics which in turn predisposes aneurysms to rupture. Materials and Methods A total of 313 PCOM aneurysms (145 ruptured, 168 unruptured) were studied with image-based computational fluid dynamics (CFD). Aneurysms were classified into different angio-architecture types depending on the location of the aneurysm with respect to parent artery bifurcation. Hemodynamic characteristics were compared between ruptured and unruptured aneurysms, as well as among aneurysms with different angio-architectures. Results Angio-architecture was associated with rupture (p=0.0033). Ruptured aneurysms had higher, more concentrated and more oscillatory wall shear stress distributions (WSSmax, p<0.0001; SCI, p=0.0001; OSImean, p<0.0001), stronger and more concentrated inflow jets (Q, p=0.01; ICI, p=0.0002), and more complex and unstable flow patterns (CORELEN, p<0.0001; PODENT, p=0.0008) as compared to unruptured aneurysms. These adverse conditions were more common in aneurysms with bifurcation-type angio-architectures, compared to those with lateral or sidewall angio-architectures. Interestingly, ruptured aneurysms also had lower normalized mean WSS (WSSnorm, p=0.0182) and minimum WSS (WSSmin, p=0.0017) than unruptured aneurysms. Conclusions High-flow intra-saccular hemodynamic characteristics, commonly found in bifurcation-type angio-architectures, are associated with PCOM aneurysm rupture status. These characteristics include strong and concentrated inflow jets, concentrated regions of elevated WSS, oscillatory WSS, lower normalized WSS, and complex unstable flow patterns.