Longitudinal neuropsychological assessment after aneurysmal subarachnoid hemorrhage and its relationship with delayed cerebral ischemia: a prospective Swiss multicenter study.

OBJECTIVE: While prior retrospective studies have suggested that delayed cerebral ischemia (DCI) is a predictor of neuropsychological deficits after aneurysmal subarachnoid hemorrhage (aSAH), all studies to date have shown a high risk of bias. This study was designed to determine the impact of DCI on the longitudinal neuropsychological outcome after aSAH, and importantly, it includes a baseline examination after aSAH but before DCI onset to reduce the risk of bias. METHODS: In a prospective, multicenter study (8 Swiss centers), 112 consecutive alert patients underwent serial neuropsychological assessments (Montreal Cognitive Assessment [MoCA]) before and after the DCI period (first assessment, < 72 hours after aSAH; second, 14 days after aSAH; third, 3 months after aSAH). The authors compared standardized MoCA scores and determined the likelihood for a clinically meaningful decline of ≥ 2 points from baseline in patients with DCI versus those without. RESULTS: The authors screened 519 patients, enrolled 128, and obtained complete data in 112 (87.5%; mean [± SD] age 53.9 ± 13.9 years; 66.1% female; 73% World Federation of Neurosurgical Societies [WFNS] grade I, 17% WFNS grade II, 10% WFNS grades III-V), of whom 30 (26.8%) developed DCI. MoCA z-scores were worse in the DCI group at baseline (-2.6 vs -1.4, p = 0.013) and 14 days (-3.4 vs -0.9, p < 0.001), and 3 months (-0.8 vs 0.0, p = 0.037) after aSAH. Patients with DCI were more likely to experience a decline of ≥ 2 points in MoCA score at 14 days after aSAH (adjusted OR [aOR] 3.02, 95% CI 1.07-8.54; p = 0.037), but the likelihood was similar to that in patients without DCI at 3 months after aSAH (aOR 1.58, 95% CI 0.28-8.89; p = 0.606). CONCLUSIONS: Aneurysmal SAH patients experiencing DCI have worse neuropsychological function before and until 3 months after the DCI period. DCI itself is responsible for a temporary and clinically meaningful decline in neuropsychological function, but its effect on the MoCA score could not be measured at the time of the 3-month follow-up in patients with low-grade aSAH with little or no impairment of consciousness. Whether these findings can be extrapolated to patients with high-grade aSAH remains unclear. Clinical trial registration no.: NCT03032471 (ClinicalTrials.gov).

Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment.

BACKGROUND: Hemodynamic patterns have been associated with cerebral aneurysm instability. For patient-specific computational fluid dynamics (CFD) simulations, the inflow rates of a patient are typically not known. The aim of this study was to analyze the influence of inter- and intra-patient variations of cerebral blood flow on the computed hemodynamics through CFD simulations and to incorporate these variations into statistical models for aneurysm rupture prediction. METHODS: Image data of 1820 aneurysms were used for patient-specific steady CFD simulations with nine different inflow rates per case, capturing inter- and intra-patient flow variations. Based on the computed flow fields, 17 hemodynamic parameters were calculated and compared for the different flow conditions. Next, statistical models for aneurysm rupture were trained in 1571 of the aneurysms including hemodynamic parameters capturing the flow variations either by defining hemodynamic "response variables" (model A) or repeatedly randomly selecting flow conditions by patients (model B) as well as morphological and patient-specific variables. Both models were evaluated in the remaining 249 cases. RESULTS: All hemodynamic parameters were significantly different for the varying flow conditions (p < 0.001). Both the flow-independent "response" model A and the flow-dependent model B performed well with areas under the receiver operating characteristic curve of 0.8182 and 0.8174 ± 0.0045, respectively. CONCLUSIONS: The influence of inter- and intra-patient flow variations on computed hemodynamics can be taken into account in multivariate aneurysm rupture prediction models achieving a good predictive performance. Such models can be applied to CFD data independent of the specific inflow boundary conditions.

Comparison of statistical learning approaches for cerebral aneurysm rupture assessment.

PURPOSE: Incidental aneurysms pose a challenge to physicians who need to decide whether or not to treat them. A statistical model could potentially support such treatment decisions. The aim of this study was to compare a previously developed aneurysm rupture logistic regression probability model (LRM) to other machine learning (ML) classifiers for discrimination of aneurysm rupture status. METHODS: Hemodynamic, morphological, and patient-related information of 1631 cerebral aneurysms characterized by computational fluid dynamics simulations were used to train support vector machines (SVMs) with linear and RBF kernel (RBF-SVM), k-nearest neighbors (kNN), decision tree, random forest, and multilayer perceptron (MLP) neural network classifiers for predicting the aneurysm rupture status. The classifiers' accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were evaluated and compared to the LRM using 249 test cases obtained from two external cohorts. Additionally, important variables were determined based on the random forest and weights of the linear SVM. RESULTS: The AUCs of the MLP, LRM, linear SVM, RBF-SVM, kNN, decision tree, and random forest were 0.83, 0.82, 0.80, 0.81, 0.76, 0.70, and 0.79, respectively. The accuracy ranged between 0.76 (decision tree,) and 0.79 (linear SVM, RBF-SVM, and MLP). Important variables for predicting the aneurysm rupture status included aneurysm location, the mean surface curvature, and maximum flow velocity. CONCLUSION: The performance of the LRM was overall comparable to that of the other ML classifiers, confirming its potential for aneurysm rupture assessment. To further improve the predictions, additional information, e.g., related to the aneurysm wall, might be needed.

Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics.

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.

CO2BOLD assessment of moyamoya syndrome: Validation with single photon emission computed tomography and positron emission tomography imaging.

AIM: To compare the assessment of cerebrovascular reserve (CVR) using CO2BOLD magnetic resonance imaging (MRI) vs positron emission tomography (PET) and single photon emission computed tomography (SPECT) as reference standard. METHODS: Ten consecutive patients (8 women, mean age of 41 ± 26 years) with moyamoya syndrome underwent 14 pre-surgical evaluations for external-internal carotid artery bypass surgery. CVR was assessed using CO2BOLD and PET (4)/SPECT (11) with a maximum interval of 36 d, and evaluated by two experienced neuroradiologists. RESULTS: The inter-rater agreement was 0.81 for SPECT (excellent), 0.43 for PET (fair) and 0.7 for CO2BOLD (good). In 9/14 cases, there was a correspondence between CO2BOLD and PET/SPECT. In 4/14 cases, CVR was over-estimated in CO2BOLD, while in 1/14 case, CVR was underestimated in CO2BOLD. The sensitivity of CO2BOLD was 86% and a specificity of 43%. CONCLUSION: CO2BOLD can be used for pre-surgical assessment of CVR in patients with moyamoya syndrome and combines the advantages of absent irradiation, high availability of MRI and assessment of brain parenchyma, cerebral vessels and surrogate CVR in one stop.

Call for uniform neuropsychological assessment after aneurysmal subarachnoid hemorrhage: Swiss recommendations.

BACKGROUND: In a high proportion of patients with favorable outcome after aneurysmal subarachnoid hemorrhage (aSAH), neuropsychological deficits, depression, anxiety, and fatigue are responsible for the inability to return to their regular premorbid life and pursue their professional careers. These problems often remain unrecognized, as no recommendations concerning a standardized comprehensive assessment have yet found entry into clinical routines. METHODS: To establish a nationwide standard concerning a comprehensive assessment after aSAH, representatives of all neuropsychological and neurosurgical departments of those eight Swiss centers treating acute aSAH have agreed on a common protocol. In addition, a battery of questionnaires and neuropsychological tests was selected, optimally suited to the deficits found most prevalent in aSAH patients that was available in different languages and standardized. RESULTS: We propose a baseline inpatient neuropsychological screening using the Montreal Cognitive Assessment (MoCA) between days 14 and 28 after aSAH. In an outpatient setting at 3 and 12 months after bleeding, we recommend a neuropsychological examination, testing all relevant domains including attention, speed of information processing, executive functions, verbal and visual learning/memory, language, visuo-perceptual abilities, and premorbid intelligence. In addition, a detailed assessment capturing anxiety, depression, fatigue, symptoms of frontal lobe affection, and quality of life should be performed. CONCLUSIONS: This standardized neuropsychological assessment will lead to a more comprehensive assessment of the patient, facilitate the detection and subsequent treatment of previously unrecognized but relevant impairments, and help to determine the incidence, characteristics, modifiable risk factors, and the clinical course of these impairments after aSAH.

Epidemiology, pathophysiology, diagnosis, and management of intracranial artery dissection.

Spontaneous intracranial artery dissection is an uncommon and probably underdiagnosed cause of stroke that is defined by the occurrence of a haematoma in the wall of an intracranial artery. Patients can present with headache, ischaemic stroke, subarachnoid haemorrhage, or symptoms associated with mass effect, mostly on the brainstem. Although intracranial artery dissection is less common than cervical artery dissection in adults of European ethnic origin, intracranial artery dissection is reportedly more common in children and in Asian populations. Risk factors and mechanisms are poorly understood, and diagnosis is challenging because characteristic imaging features can be difficult to detect in view of the small size of intracranial arteries. Therefore, multimodal follow-up imaging is often needed to confirm the diagnosis. Treatment of intracranial artery dissections is empirical in the absence of data from randomised controlled trials. Most patients with subarachnoid haemorrhage undergo surgical or endovascular treatment to prevent rebleeding, whereas patients with intracranial artery dissection and cerebral ischaemia are treated with antithrombotics. Prognosis seems worse in patients with subarachnoid haemorrhage than in those without.

Augmented reality in the surgery of cerebral arteriovenous malformations: technique assessment and considerations.

BACKGROUND: Augmented reality technology has been used for intraoperative image guidance through the overlay of virtual images, from preoperative imaging studies, onto the real-world surgical field. Although setups based on augmented reality have been used for various neurosurgical pathologies, very few cases have been reported for the surgery of arteriovenous malformations (AVM). We present our experience with AVM surgery using a system designed for image injection of virtual images into the operating microscope's eyepiece, and discuss why augmented reality may be less appealing in this form of surgery. METHODS: N = 5 patients underwent AVM resection assisted by augmented reality. Virtual three-dimensional models of patients' heads, skulls, AVM nidi, and feeder and drainage vessels were selectively segmented and injected into the microscope's eyepiece for intraoperative image guidance, and their usefulness was assessed in each case. RESULTS: Although the setup helped in performing tailored craniotomies, in guiding dissection and in localizing drainage veins, it did not provide the surgeon with useful information concerning feeder arteries, due to the complexity of AVM angioarchitecture. CONCLUSION: The difficulty in intraoperatively conveying useful information on feeder vessels may make augmented reality a less engaging tool in this form of surgery, and might explain its underrepresentation in the literature. Integrating an AVM's hemodynamic characteristics into the augmented rendering could make it more suited to AVM surgery.

Augmented reality in the surgery of cerebral aneurysms: a technical report.

BACKGROUND: Augmented reality is the overlay of computer-generated images on real-world structures. It has previously been used for image guidance during surgical procedures, but it has never been used in the surgery of cerebral aneurysms. OBJECTIVE: To report our experience of cerebral aneurysm surgery aided by augmented reality. METHODS: Twenty-eight patients with 39 unruptured aneurysms were operated on in a prospective manner with augmented reality. Preoperative 3-dimensional image data sets (angio-magnetic resonance imaging, angio-computed tomography, and 3-dimensional digital subtraction angiography) were used to create virtual segmentations of patients' vessels, aneurysms, aneurysm necks, skulls, and heads. These images were injected intraoperatively into the eyepiece of the operating microscope. An example case of an unruptured posterior communicating artery aneurysm clipping is illustrated in a video. RESULTS: The described operating procedure allowed continuous monitoring of the accuracy of patient registration with neuronavigation data and assisted in the performance of tailored surgical approaches and optimal clipping with minimized exposition. CONCLUSION: Augmented reality may add to the performance of a minimally invasive approach, although further studies need to be performed to evaluate whether certain groups of aneurysms are more likely to benefit from it. Further technological development is required to improve its user friendliness.