Rupture Risk Of Cerebral Aneurysms Research Articles

Advancing aneurysm management: the potential of AI and machine learning in enhancing safety and predictive accuracy.

Cerebral aneurysm rupture, the predominant cause of non-traumatic subarachnoid hemorrhage, underscores the need for effective treatment and early detection methods. A study in Neurosurgical Review compared microsurgical clipping to endovascular therapy in 130 patients with middle cerebral artery (MCA) aneurysms, finding significantly fewer serious adverse events (SAEs) and neurological complications in the endovascular group. This suggests endovascular therapy's superiority in safety and reducing complications for MCA aneurysm patients. Furthermore, a systematic review and meta-analysis assessed the diagnostic accuracy of AI algorithms in detecting cerebral aneurysms, revealing a high sensitivity but notable false-positive rates, indicating AI's potential while highlighting the need for further validation. Machine learning algorithms also showed promise in predicting cerebral aneurysm rupture risk, demonstrating reasonable sensitivity and specificity. Additionally, AI-based radiomics models are advancing rapidly, offering enhanced predictive accuracy and personalized treatment planning by analyzing imaging data to identify features indicative of aneurysm conditions. Collectively, these findings emphasize the advantages of endovascular therapy for MCA aneurysms and the emerging role of AI and machine learning in improving early detection and personalized management of cerebral aneurysms.

Hemodynamic study of the ICA aneurysm evolution to attain the cerebral aneurysm rupture risk

The influence of the aneurysm evolution on the hemodynamic characteristic of the blood flow inside the sac region is comprehensively investigated. By using the computational method, the blood flow through the vessel and aneurysm of the sac region is examined to find the role of aneurysm evolution on the wall shear stress, pressure, and risk of aneurysm rupture. Three different models of ICA aneurysms are chosen for the investigation of the aneurysm evolution at risk of rupture. Obtained data shows that the evolution of the aneurysm decreases the wall shear stress and pressure on the sac surface while an oscillatory index of blood increases on the aneurysm wall.

Hemodynamic effects of the blood flow on aneurysm rupture risk: Geometrical aspects

This study provides comprehensive information about the impact of the parent vessel’s shape on the risk of cerebral aneurysm rupture. It focuses on internal carotid artery (ICA) aneurysms with varying parent vessel sizes, analyzing different aspects of blood flow dynamics. By comparing various hemodynamic factors such as wall shear stress (WSS), oscillatory shear index (OSI) and pressure distribution, the researchers aim to establish a meaningful relationship between the parent vessel’s mean diameter and these significant hemodynamic parameters.

Prediction of cerebral aneurysm rupture risk by machine learning algorithms: a systematic review and meta-analysis of 18,670 participants.

It is possible to identify unruptured intracranial aneurysms (UIA) using machine learning (ML) algorithms, which can be a life-saving strategy, especially in high-risk populations. To better understand the importance and effectiveness of ML algorithms in practice, a systematic review and meta-analysis were conducted to predict cerebral aneurysm rupture risk. PubMed, Scopus, Web of Science, and Embase were searched without restrictions until March 20, 2023. Eligibility criteria included studies that used ML approaches in patients with cerebral aneurysms confirmed by DSA, CTA, or MRI. Out of 35 studies included, 33 were cohort, and 11 used digital subtraction angiography (DSA) as their reference imaging modality. Middle cerebral artery (MCA) and anterior cerebral artery (ACA) were the commonest locations of aneurysmal vascular involvement-51% and 40%, respectively. The aneurysm morphology was saccular in 48% of studies. Ten of 37 studies (27%) used deep learning techniques such as CNNs and ANNs. Meta-analysis was performed on 17 studies: sensitivity of 0.83 (95% confidence interval (CI), 0.77-0.88); specificity of 0.83 (95% CI, 0.75-0.88); positive DLR of 4.81 (95% CI, 3.29-7.02) and the negative DLR of 0.20 (95% CI, 0.14-0.29); a diagnostic score of 3.17 (95% CI, 2.55-3.78); odds ratio of 23.69 (95% CI, 12.75-44.01). ML algorithms can effectively predict the risk of rupture in cerebral aneurysms with good levels of accuracy, sensitivity, and specificity. However, further research is needed to enhance their diagnostic performance in predicting the rupture status of IA.

Risk of Cerebral Aneurysm Rupture After Liver Transplantation: Development and Validation of a Hemorrhagic Stroke Scoring Model.

Liver transplantation (LT) patients appear to be more prone to neurological events compared to individuals undergoing other types of solid-organ transplantation. The aims of the present study were to analyze the prevalence of unruptured intracranial aneurysms (UIAs) in patients undergoing liver transplantation (LT) and to examine the perioperative occurrence of subarachnoid hemorrhage (SAH). Also, it intended to systematically identify the risk factors of SAH and hemorrhagic stroke (HS) within a year after LT and to develop a scoring system which involves distinct clinical features of LT patients. Patients who underwent LT from January 2012 to March 2022 were analyzed. All included patients underwent neurovascular imaging within 6 months before LT. We conducted an analysis of prevalence and radiological features of UIA and SAH. The clinical factors that may have an impact on HS within one year of LT were also reviewed. Total of 3,487 patients were enrolled in our study after applying inclusion and exclusion criteria. The prevalence of UIA was 5.4%. The incidence of SAH and HS within one year following LT was 0.5% and 1.6%, respectively. We developed a scoring system based on multivariable analysis to predict the HS within 1-year after LT. The variables were a poor admission mental status, the diagnosis of UIA, serum ammonia levels, and Model for End-stage Liver Disease (MELD) scores. Our model showed good discrimination among the development (C index, 0.727; 95% confidence interval [CI], 0.635-0.820) and validation (C index, 0.719; 95% CI, 0.598-0.801) cohorts. The incidence of UIA and SAH was very low in LT patients. A poor admission mental status, diagnosis of UIA, serum ammonia levels, and MELD scores were significantly associated with the risk of HS within one year after LT. Our scoring system showed a good discrimination to predict the HS in LT patients.

Usage of computational method for hemodynamic analysis of intracranial aneurysm rupture risk in different geometrical aspects

The importance of the parent vessel geometrical feature on the risk of cerebral aneurysm rupture is unavoidable. This study presents inclusive details on the hemodynamics of Internal carotid artery (ICA) aneurysms with different parent vessel mean diameters. Different aspects of blood hemodynamics are compared to find a reasonable connection between parent vessel mean diameter and significant hemodynamic factors of wall shear stress (WSS), oscillatory shear index (OSI), and pressure distribution. To access hemodynamic data, computational fluid dynamics is used to model the blood stream inside the cerebral aneurysms. A hemodynamic comparison of the selected cerebral aneurysm shows that the minimum WSS is reduced by about 71% as the parent vessel’s mean diameter is increased from 3.18 to 4.48 mm.

A novel parameter for the prediction of rupture risk of cerebral aneurysms based on morphology.

Neurosurgeons often encounter dilemmas in the clinical management of cerebral aneurysms owing to an uncertainty of their rupture status and rupture risk. This study evaluates the influence of natural frequency of an aneurysm, as a novel morphological parameter to understand and analyze rupture status and risk prediction. In this work, we employ the natural frequency of 20 idealized and 50 patient specific aneurysms. The natural frequency of patient specific aneurysms is then compared against their rupture status. A strong correlation was observed between various morphological indicators and natural frequency for ideal and patient specific geometries. A statistical analysis with both Mann Whitney U test and T-test for rupture status against natural frequency has given a p-value less than 0.01 indicating a strong correlation between them. The correlation of morphological parameters with natural frequency from Pearson correlation coefficient and T-test suggests a holistic reflection of their effects on the natural frequency of an aneurysm. Thus, natural frequency could be a good indicator to discern the rupture potential of an aneurysm. The correlation between rupture status and natural frequency makes it a novel parameter that can differentiate between ruptured and unruptured patient specific aneurysms.

Several Risk Factors for Aneurysmal Subarachnoid Hemorrhage

We reviewed current literature on the role of seasonal, meteorological, or circadian factors in ruptured cerebral aneurysms. We found that cerebral aneurysm rupture most frequently occurs in winter and spring, and less frequently in summer. The highest number of ruptured cerebral aneurysms happens in the morning, between 8 am and 12 pm. The data regarding meteorological factors' effect on the risk of cerebral aneurysm rupture are conflicting. However, it should be noted that changes in barometric pressure and falling temperature are associated with the risk of aneurysmal subarachnoid hemorrhage.

Numerical simulation of blood flow in Cerebral aneurysms using two-phase model

ABSTRACT: Computational fluid dynamic (CFD) simulation techniques have played an essential role in simulating and understanding the initiation, growth, and rupture of cerebral aneurysms. Hemodynamic parameters are mainly used to examine the rupture risk status of cerebral aneurysms using blood flow CFD simulation. Blood was considered as single-phase flow model with both Newtonian and non-Newtonian to predict the rupture risk analysis. However, to better understand predicting the risk of cerebral aneurysm rupture, blood requires two-phase, such as plasma and red blood cells (RBCs), also known as erythrocytes. In this study, the two-phase blood flow model was solved by the discrete phase model (DPM) with Lagrangian approach, in which blood was modeled two-phase fluid as a continuous phase plasma and particulate phase RBCs. Three patient-specific aneurysm geometries have been selected to determine wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT) with two-phase blood flow simulation. To analyze the velocity distribution inside the aneurysms, velocity streamlines and surface velocities were reported. The pulsatile blood flow simulation was performed for aneurysm geometries, where the mean inlet Reynolds number was calculated between 490 and 1370. The value of WSS, OSI, and RRT was quantified based on the Reynolds number. Reynolds number's minimum value indicates the low WSS, low OSI, and short RRT, and the maximum value of Reynolds number shows the high WSS, high OSI, and long RRT. The high WSS, high OSI, and long RRT, velocity streamlines distribution, surface velocity changes were determined with two-phase blood in aneurysm geometries, aneurysm geometry one and three are the medium and giant size saccular aneurysm may have a higher risk of rupture while aneurysm geometry two is medium size fusiform aneurysm has a lower risk of rupture. The two-phase blood flow model presents reasonable hemodynamic parameters that correlate with aneurysms rupture risk prediction.

Analysis of Morphological-Hemodynamic Risk Factors for Aneurysm Rupture Including a Newly Introduced Total Volume Ratio.

The purpose of this study was to evaluate morphological and hemodynamic factors, including the newly developed total volume ratio (TVR), in evaluating rupture risk of cerebral aneurysms using ≥7 mm sized aneurysms. Twenty-three aneurysms (11 unruptured and 12 ruptured) ≥ 7 mm were analyzed from 3-dimensional rotational cerebral angiography and computational fluid dynamics (CFD). Ten morphological and eleven hemodynamic factors of the aneurysms were qualitatively and quantitatively compared. Correlation analysis between morphological and hemodynamic factors was performed, and the relationship among the hemodynamic factors was analyzed. Morphological factors (ostium diameter, ostium area, aspect ratio, and bottleneck ratio) and hemodynamic factors (TVR, minimal wall shear stress of aneurysms, time-averaged wall shear stress of aneurysms, oscillatory shear index, relative residence time, low wall shear stress area, and ratio of low wall stress area) were statistically different between ruptured and unruptured aneurysms (p < 0.05). By simple regression analysis, the morphological factor aspect ratio and the hemodynamic factor TVR were significantly correlated (r2 = 0.602, p = 0.001). Ruptured aneurysms had complex and unstable flow. In ≥7 mm ruptured aneurysms, high aspect ratio, bottleneck ratio, complex flow, unstable flow, low TVR, wall shear stress at aneurysm, high oscillatory shear index, relative resistance time, low wall shear stress area, and ratio of low wall stress area were significant in determining the risk of aneurysm rupture.

Simulation analysis of aneurysm embolization surgery: Hemorheology of aneurysms with different embolization rates (CTA).

Embolization degree acts as an important factor affecting recurrence of aneurysm. To analyze the role of hemodynamics parameters of different degrees of embolization in the occurrence, development and post-treatment of aneurysms, and to determine the specific factors causing the occurrence and recurrence of aneurysms after hemodynamics treatment. Our study provides a theoretical basis for the prevention and treatment of aneurysms. Computed tomography angiography data of a patient with cerebral aneurysm was used to model 0%, 24%, 52%, 84% and 100% of endovascular embolization, respectively. The time average wall shear stress, time average wall shear stress, oscillatory shear index, hemodynamics formation index and relative retentive time were used to analyze the changes of hemodynamics indexes in different embolic models. With the increase of embolic rate, the values of time average wall shear stress, time average wall shear stress grade and aneurysm index formation gradually increased, and the values of relative retention time gradually decreased. Oscillatory shear index was higher in patients with incomplete embolization and decreased in patients with complete embolization. As the degree of embolization increased, the blood flow tended to stabilize, reducing the risk of cerebral aneurysm rupture, and finding that the wall of the vessel junction was susceptible to injury.

Rupture Risk Assessment for Cerebral Aneurysm Using Interpretable Machine Learning on Multidimensional Data.

Background: Assessment of cerebral aneurysm rupture risk is an important task, but it remains challenging. Recent works applying machine learning to rupture risk evaluation presented positive results. Yet they were based on limited aspects of data, and lack of interpretability may limit their use in clinical setting. We aimed to develop interpretable machine learning models on multidimensional data for aneurysm rupture risk assessment.Methods: Three hundred seventy-four aneurysms were included in the study. Demographic, medical history, lifestyle behaviors, lipid profile, and morphologies were collected for each patient. Prediction models were derived using machine learning methods (support vector machine, artificial neural network, and XGBoost) and conventional logistic regression. The derived models were compared with the PHASES score method. The Shapley Additive Explanations (SHAP) analysis was applied to improve the interpretability of the best machine learning model and reveal the reasoning behind the predictions made by the model.Results: The best machine learning model (XGBoost) achieved an area under the receiver operating characteristic curve of 0.882 [95% confidence interval (CI) = 0.838–0.927], significantly better than the logistic regression model (0.779; 95% CI = 0.729–0.829; P = 0.002) and the PHASES score method (0.758; 95% CI = 0.713–0.800; P = 0.001). Location, size ratio, and triglyceride level were the three most important features in predicting rupture. Two typical cases were analyzed to demonstrate the interpretability of the model.Conclusions: This study demonstrated the potential of using machine learning for aneurysm rupture risk assessment. Machine learning models performed better than conventional statistical model and the PHASES score method. The SHAP analysis can improve the interpretability of machine learning models and facilitate their use in a clinical setting.

A method for giant aneurysm segmentation using Euler’s elastica

Computed Tomography Angiography (CTA) is a medical modality having the advantage to reveal anatomical accuracy essential for delivering a precise diagnosis and an appropriate patient’s management for treating a cerebral aneurysm. Segmentation of aneurysm shapes through CTA medical images is an important step for geometrical quantification and assessment of rupture risk of cerebral aneurysms. Despite intensive researches in image processing applied to image sequences, aneurysm segmentation remains a major challenge that depends on the geometry and positioning of the aneurysm into the brain. In this paper, the segmentation analysis is performed by using GAC and Euler’s elastica models. With Geodesic Active Contour model (GAC) giant aneurysms (Size > 25 mm) are segmented in high-contrast region, while Euler’s elastica model estimates the missing boundaries caused for instance by the low contrast of a thrombus (clot within the cavity during endovascular aneurysm repair) with respect to the neighboring tissues. The experiments indicate that our original model is relevant for segmenting the aneurysm cavity and thrombus both with clear and distinct edges well providing a valuable tool for biological mechanisms understanding such as thrombosis into giant aneurysms, and medical validation.

The Analysis of the Thickness of a Cerebral Aneurysm:Can Predict the Translucent-type of Unruptured Middle Cerebral Artery Aneurysm Preoperatively?

The rupture risk of cerebral aneurysms is determined by various factors. However, it is not clear whether the thickness of the aneurysm wall also influences the rupture risk. In this study, under the assumption that thin-walled aneurysms have a higher rupture risk compared with thick-wall aneurysms, we evaluate the usefulness of computed fluid dynamics(CFD)to identify thin-walled cerebral aneurysms. Fifty-four unruptured middle cerebral aneurysms from 53 patients were analyzed using CFD before the operation. We divided these aneurysms into two groups: translucent-type aneurysms and others. To analyze the difference of these groups, individual elements(age, gender, volume, and aspect ratio)and hemodynamic factors(wall shear stress[WSS], flow coefficient, and flow coefficient per volume)were examined using CFD. Univariate analysis detected significant relationships between the translucent-type aneurysms and gender, aspect ratio, WSS and flow coefficient per volume. Multiple logistics regression also identified a significant relationship with gender and flow coefficient per volume. The receiver operating characteristic curve demonstrated that the flow coefficient per volume could predict translucent-type aneurysms(area under the curve 0.84, cut-off value 1.32, sensitivity 76.2%, and specificity 87.9%). Gender and the flow coefficient per volume could predict translucent-type aneurysms of the middle cerebral artery. CFD analysis might be a useful tool to predict translucent-type aneurysms.

Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): uncertainty quantification of geometric rupture risk parameters

BackgroundGeometric parameters have been proposed for prediction of cerebral aneurysm rupture risk. Predicting the rupture risk for incidentally detected unruptured aneurysms could help clinicians in their treatment decision. However, assessment of geometric parameters depends on several factors, including the spatial resolution of the imaging modality used and the chosen reconstruction procedure. The aim of this study was to investigate the uncertainty of a variety of previously proposed geometric parameters for rupture risk assessment, caused by variability of reconstruction procedures.Materials26 research groups provided segmentations and surface reconstructions of five cerebral aneurysms as part of the Multiple Aneurysms AnaTomy CHallenge (MATCH) 2018. 40 dimensional and non-dimensional geometric parameters, describing aneurysm size, neck size, and irregularity of aneurysm shape, were computed. The medians as well as the absolute and relative uncertainties of the parameters were calculated. Additionally, linear regression analysis was performed on the absolute uncertainties and the median parameter values.ResultsA large variability of relative uncertainties in the range between 3.9 and 179.8% was found. Linear regression analysis indicates that some parameters capture similar geometric aspects. The lowest uncertainties < 6% were found for the non-dimensional parameters isoperimetric ratio, convexity ratio, and ellipticity index. Uncertainty of 2D and 3D size parameters was significantly higher than uncertainty of 1D parameters. The most extreme uncertainties > 80% were found for some curvature parameters.ConclusionsUncertainty analysis is essential on the road to clinical translation and use of rupture risk prediction models. Uncertainty quantification of geometric rupture risk parameters provided by this study may help support development of future rupture risk prediction models.

Hepatitis B virus infected patients show increased risk of cerebral aneurysm rupture: A retrospective analysis

BackgroundThe mechanism responsible for cerebral aneurysm (CA) formation and rupture remains unclear. Some studies showed vascular involvement could be observed in systemic vasculitis caused by Hepatitis B. Therefore, it is necessary to determine the possibility by which hepatitis B virus (HBV) infection might be associated with CA. Methods and ResultsWe retrospectively studied patient details and serological markers of HBV infection among 229 patients presenting with CA on admission to the Neurosurgery Department at Beijing Tiantan Hospital between March 2016 and February 2017. Clinical data, radiologic findings and clinical features of HBV infection were analyzed by SPSS.The results showed a significant association between HBsAg positive (p = 0.014), anti-HBc positive (p = 0.045) and CA rupture. Univariate analysis revealed patients that were HBsAg positive (OR: 4.828; 95% CI: 1.363–17.099; p = 0.015) and anti-HBc positive (OR: 1.804; 95% CI: 1.010–3.223; p = 0.046) were associated with CA rupture. Compared with other confounding risk factors for rupture in the statistical analysis, HBsAg positive status (OR: 4.085; 95% CI: 1.011–16.513; p = 0.048) remained positively associated with CA rupture. ConclusionsObservation showed that HBsAg positivity was associated with CA rupture.

03:18 PM Abstract No. 162 Factors associated with increased risk of cerebral aneurysm rupture: a case-control study comparing un-ruptured and ruptured symptomatic aneurysms with subarachnoid hemorrhage from the HCUP National Inpatient Sample database from 2009 to 2014

03:18 PM Abstract No. 162 Factors associated with increased risk of cerebral aneurysm rupture: a case-control study comparing un-ruptured and ruptured symptomatic aneurysms with subarachnoid hemorrhage from the HCUP National Inpatient Sample database from 2009 to 2014

Analysis of the influence of imaging-related uncertainties on cerebral aneurysm deformation quantification using a no-deformation physical flow phantom

Cardiac-cycle related pulsatile aneurysm motion and deformation is assumed to provide valuable information for assessing cerebral aneurysm rupture risk. Accordingly, numerous studies addressed quantification of cerebral aneurysm wall motion and deformation. Most of them utilized in vivo imaging data, but image-based aneurysm deformation quantification is subject to pronounced uncertainties: unknown ground-truth deformation; image resolution in the order of the expected deformation; direct interplay between contrast agent inflow and image intensity. To analyze the impact of the uncertainties on deformation quantification, a multi-imaging modality ground-truth phantom study is performed. A physical flow phantom was designed that allowed simulating pulsatile flow through a variety of modeled cerebral vascular structures. The phantom was imaged using different modalities [MRI, CT, 3D-RA] and mimicking physiologically realistic flow conditions. Resulting image data was analyzed by an established registration-based approach for automated wall motion quantification. The data reveals severe dependency between contrast media inflow-related image intensity changes and the extent of estimated wall deformation. The study illustrates that imaging-related uncertainties affect the accuracy of cerebral aneurysm deformation quantification, suggesting that in vivo imaging studies have to be accompanied by ground-truth phantom experiments to foster data interpretation and to prove plausibility of the applied image analysis algorithms.

Contrast enhancement of vascular walls of intracranial high flow malformations in black blood MRI indicates high inflammatory activity

BackgroundThere are controversies concerning the natural history of arteriovenous malformations (AVMs) in literature and it is not clear which AVMs should be treated and which should be just observed. Objective criteria beyond growth in serial MRIs or angiographies are needed. The use of black blood MRI is currently under investigation for evaluating the rupture risk of cerebral aneurysms, however its use for assessment of AVMs has yet to be evaluated. We therefore conducted a feasibility study on the application of black blood MRI (bbMRI) in AVMs to assess rupture risk.MethodsRetrospective study of 10 patients with intracranial AVMs and 4 patients with arteriovenous fistulas who received a black blood MRI before treatment.ResultsAVM niduses (9/10) show contrast enhancement irrespective of rupture or size. All arteriovenous fistulas (4 / 4) were contrast enhancing irrespective of rupture.ConclusionHigh flow malformations are in a permanent stage of inflammation which does not seem to allow conclusions on their rupture risk at the current stage. BbMRI is a feasible method of identifying inflammation in AVMs and arteriovenous fistulas. However, future prospective studies are needed to evaluate whether bbMRI contrast enhancement correlates with rupture risk.

Determining Significant Morphological and Hemodynamic Parameters to Assess the Rupture Risk of Cerebral Aneurysms

Hemodynamics and morphology are recognized as major factors in the rupture risk of cerebral aneurysms, and exploration of their relationship is necessary to establish a method that can be employed by clinicians to assess the likelihood of rupture. In this work, morphological analysis and computational fluid dynamics were carried out to examine a database of 58 lateral cerebral aneurysms (26 ruptured and 32 unruptured) distributed among 49 patients. Eight morphological and six hemodynamic parameters were calculated and evaluated for statistical significance. It was observed that size ratio (SR), systolic wall shear stress (SWSS), diastolic wall shear stress (DWSS) and relative residence time (RRT) were statistically significant. The SR, DWSS, SWSS, and RRT were employed in multivariate logistic regression, obtaining a combined morphological–hemodynamic model, a pure morphological model, and a pure hemodynamic model to evaluate the odds ratio for rupture risk. The combined model had the highest efficiency, but no distinctive difference existed in the predictive capacity of the three models.