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Philippe Bijlenga, Sandrine Morel, Sven Hirsch, Karl Schaller and Daniel Rüfenacht

The disease resulting in the formation, growth, and rupture of intracranial aneurysms is complex. Research is accumulating evidence that the disease is driven by many different factors, some constant and others variable over time. Combinations of factors may induce specific biophysical reactions at different stages of the disease. A better understanding of the biophysical mechanisms responsible for the disease initiation and progression is essential to predict the natural history of the disease. More accurate predictions are mandatory to adequately balance risks between observation and intervention at the individual level as expected in the age of personalized medicine. Multidisciplinary exploration of the disease also opens an avenue to the discovery of possible preventive actions or medical treatments. Modern information technologies and data processing methods offer tools to address such complex challenges requiring 1) the collection of a high volume of information provided globally, 2) integration and harmonization of the information, and 3) management of data sharing with a broad spectrum of stakeholders.

Over the last decade an infrastructure has been set up and is now made available to the academic community to support and promote exploration of intracranial disease, modeling, and clinical management simulation and monitoring.

The background and purpose of the infrastructure is reviewed. The infrastructure data flow architecture is presented. The basic concepts of disease modeling that oriented the design of the core information model are explained. Disease phases, milestones, cases stratification group in each phase, key relevant factors, and outcomes are defined. Data processing and disease model visualization tools are presented. Most relevant contributions to the literature resulting from the exploitation of the infrastructure are reviewed, and future perspectives are discussed.

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Bawarjan Schatlo, Oliver P. Gautschi, Christoph M. Friedrich, Christian Ebeling, Max Jägersberg, Zsolt Kulscar, Vitor Mendes Pereira, Karl Schaller and Philippe Bijlenga

OBJECTIVE

Although several studies have suggested that the incidence of intracranial aneurysms (IAs) is higher in smokers, the higher prevalence of subarachnoid hemorrhage (SAH) in smokers remains uncertain. It is unclear whether smoking additionally contributes to the formation of multiple aneurysms and the risk of rupture. The aim of this study was to determine whether smoking is associated with IA formation, multiplicity, or rupture.

METHODS

Patients from the prospective multicenter @neurIST database (n = 1410; 985 females [69.9%]) were reviewed for the presence of SAH, multiple aneurysms, and smoking status. The prevalence of smokers in the population of patients diagnosed with at least one IA was compared with that of smokers in the general population.

RESULTS

The proportion of smokers was higher in patients with IAs (56.2%) than in the reference population (51.4%; p < 0.001). A significant association of smoking with the presence of an IA was found throughout group comparisons (p = 0.01). The presence of multiple IAs was also significantly associated with smoking (p = 0.003). A trend was found between duration of smoking and the presence of multiple IAs (p = 0.057). However, the proportion of smokers among patients suffering SAH was similar to that of smokers among patients diagnosed with unruptured IAs (p = 0.48).

CONCLUSIONS

Smoking is strongly associated with IA formation. Once an IA is present, however, smoking does not appear to increase the risk of rupture compared with IAs in the nonsmoking population. The trend toward an association between duration of smoking and the presence of multiple IAs stresses the need for counseling patients with IAs regarding lifestyle modification.

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Pavlina Lenga, Christian Hohaus, Bujung Hong, Adisa Kursumovic, Nicolai Maldaner, Jan-Karl Burkhardt, Philippe Bijlenga, Daniel A. Rüfenacht, Nils O. Schmidt, Peter Vajkoczy and Julius Dengler

OBJECTIVE

Giant posterior circulation aneurysms (GPCirAs) usually cause substantial mass effect on the brainstem, which may lead to neurological deficits. So far, there has been no systematic investigation of factors associated with such deficits in GPCirA. The authors aim to examine the risk factors for cranial nerve deficit (CND), motor deficit, and disability in patients with GPCirA.

METHODS

Using MR images obtained in 30 patients with unruptured GPCirA, the authors examined GPCirA volume, presence of hydrocephalus or partial thrombosis (PT) of the aneurysm, and the degree of brainstem displacement measured by the distance between the McRae line and the tip of the GPCirA (∆MT). They evaluated associations between these factors and neurological deficits.

RESULTS

Thirty GPCirAs in 30 patients were included. The prevalence of CNDs was 50%. Patients with CNDs significantly differed from those without CNDs in terms of age (mean 51.0 years [SD 15.0 years] vs 69.0 years [SD 21.0 years], p = 0.01) and in ∆MT (median 50.7 mm [IQR 39.2–53.9 mm] vs 39.0 mm [IQR 32.3–45.9 mm], p = 0.02). The prevalence of motor deficits was 33.3%. Patients with motor deficits showed a larger ∆MT (median 50.5 mm [IQR 40.8–54.6 mm]) compared with those without (∆MT: median 39.1 mm [IQR 32.8–50.5 mm], p = 0.04). GPCirA volume was larger in patients with poor modified Rankin Scale (mRS) scores (median 14.9 cm3 [IQR 8.6–18.7 cm3]) than in those with mRS scores of 0–2 (median 6.8 cm3 [IQR 4.4–11.7 cm3], p = 0.03). After adjusting for patient age and the occurrence of hydrocephalus or PT, the authors found that higher degrees of disability were significantly associated with aneurysm volume (OR 1.13, 95% CI 1.0–1.3; p = 0.04), but not with ∆MT. The occurrence of CND or motor deficit was not associated with any of the examined variables. There was no correlation between GPCirA volume and ∆MT (rs = 0.01, p = 0.96). The prevalence of neurological deficits did not differ between GPCirA at the basilar apex, the basilar trunk, the vertebrobasilar junction, or the vertebral artery.

CONCLUSIONS

In this study, the neurological condition of the patients was associated only with GPCirA volume and not with the degree of brainstem displacement, the occurrence of PT or hydrocephalus, or the exact location of the GPCirA. These findings highlight the clinical relevance of GPCirA volume and suggest that factors such as brainstem displacement or PT should play less of a role when finding arguments for or against treatment of GPCirA.

Clinical trial registration no.: NCT02066493 (clinicaltrials.gov)

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Julius Dengler, Nicolai Maldaner, Philippe Bijlenga, Jan-Karl Burkhardt, Alexander Graewe, Susanne Guhl, Bujung Hong, Christian Hohaus, Adisa Kursumovic, Dorothee Mielke, Karl-Michael Schebesch, Maria Wostrack, Daniel Rufenacht, Peter Vajkoczy, Nils Ole Schmidt and Giant Intracranial Aneurysm Study Group

OBJECT

The underlying mechanisms causing intracranial perianeurysmal edema (PAE) are still poorly understood. Since PAE is most frequently observed in giant intracranial aneurysms (GIAs), the authors designed a study to examine the occurrence of PAE in relation to the location, size, and partial thrombosis (PT) of GIAs along with the clinical impact of PAE.

METHODS

Magnetic resonance imaging data for patients with a diagnosis of unruptured GIA from the international multicenter Giant Intracranial Aneurysm Registry were retrospectively analyzed with regard to location and size of the GIA, PAE volume, and the presence of PT. The occurrence of PAE was correlated to clinical findings.

RESULTS

Imaging data for 69 GIAs were eligible for inclusion in this study. Perianeurysmal edema was observed in 33.3% of all cases, with the highest frequency in GIAs of the middle cerebral artery (MCA; 68.8%) and the lowest frequency in GIAs of the cavernous internal carotid artery (ICA; 0.0%). Independent predictors of PAE formation were GIA volume (OR 1.13, p = 0.02) and the occurrence of PT (OR 9.84, p = 0.04). Giant intracranial aneurysm location did not predict PAE occurrence. Giant aneurysms with PAE were larger than GIAs without PAE (p < 0.01), and GIA volume correlated with PAE volume (rs = 0.51, p = 0.01). Perianeurysmal edema had no influence on the modified Rankin Scale score (p = 0.30 or the occurrence of aphasia (p = 0.61) or hemiparesis (p = 0.82).

CONCLUSIONS

Perianeurysmal edema was associated with GIA size and the presence of PT. As no PAE was observed in cavernous ICA aneurysms, even though they exerted mass effect on the brain and also displayed PT, the dura mater may serve as a barrier protecting the brain from PAE formation.

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Felicitas J. Detmer, Sara Hadad, Bong Jae Chung, Fernando Mut, Martin Slawski, Norman Juchler, Vartan Kurtcuoglu, Sven Hirsch, Philippe Bijlenga, Yuya Uchiyama, Soichiro Fujimura, Makoto Yamamoto, Yuichi Murayama, Hiroyuki Takao, Timo Koivisto, Juhana Frösen and Juan R. Cebral

OBJECTIVE

Incidental 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.

METHODS

Patient 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.

RESULTS

The 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.

CONCLUSIONS

Developing 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.