Risk Factors for Intracranial Aneurysm Rupture: A Systematic Review

Effect of the aspect ratio and wall heterogeneities on the mechanical behaviour of the aneurysm wall: Experimental investigation on phantom arteries

The management of unruptured intracranial aneurysms (UIA) involves assessing the risk of rupture, which requires a thorough understanding of risk factors such as the geometric characteristics of the neck (neck size) or local structural heterogeneities. This study explores the impact of neck size on the rupture risk of the aneurysmal sac and examines how local heterogeneities, such as calcifications or variations in tissue composition, influence the mechanical response of the wall of a saccular aneurysm during the insertion of an innovative arterial wall deformation device (DDP). The results reveal that high aspect ratios (AR) are associated with increased hemodynamic stress, thereby raising the risk of rupture. Additionally, this study provides valuable insights into the complex relationship between tissue heterogeneity, especially calcifications, and the mechanical response of aneurysm walls to mechanical stimuli. It appears that local heterogeneities weaken the integrity of the arterial wall, thus increasing the potential for rupture. Finally, although the DDP is not intended to treat intracranial aneurysms (IA), it could prove to be a relevant tool for deepening the understanding of their rupture mechanisms.

Age-specific gender differences in morphological parameters of intracranial aneurysms

Background

Gender differences are shown to exist in the incidence and outcome of subarachnoid hemorrhage as well as in the formation and progression of intracranial aneurysms. However, few studies investigated the gender difference in the morphology of intracranial aneurysms.

Methods

A total of 308 consecutive patients with 346 intracranial aneurysms from 2014 to 2020 were retrospectively analyzed. Differences in 10 morphological parameters of intracranial aneurysms between males and females were compared. Continuous variables were expressed as the median [interquartile range (IQR)] and the differences were analyzed using the Mann-Whitney test. Categorical variables were expressed as numbers (frequencies) and the differences were analyzed using χ2 test. Moreover, subgroup analyses were performed according to age stratifications: ≥60 years, 50-59 years, and <50 years.

Results

The median aspect ratio maximum [1.38, IQR (1.17-1.83) vs. 1.27, IQR (1.00-1.57)], median aspect ratio [1.29, IQR (1.00-1.76) vs. 1.18, IQR (0.93-1.54)], median bottleneck factor [1.17, IQR (1.00-1.47) vs. 1.03, IQR (0.86-1.27)], and median volume-to-ostium area ratio [5.67, IQR (2.85-9.03) vs. 3.86, IQR (1.94-7.48)] in males were significantly higher than those in females (all P < 0.01). Particularly, the differences in the above morphological parameters between genders were most prominent in patients aged ≥ 60 years, whereas no differences were found in patients aged < 50 years. There were no significant differences in other morphological parameters between males and females, including neck width, transverse, height, maximum, aneurysm volume, and height-width ratio.

Conclusions

Gender difference existed in the morphology of intracranial aneurysms and was affected by age. The difference was prominent in patients aged ≥ 60 years, whereas no difference was found in patients aged < 50 years.

Comprehensive analysis of risk factors for intracranial aneurysm rupture: a retrospective cohort study

Background

Intracranial aneurysms (IAs) can lead to subarachnoid hemorrhage, a life-threatening event associated with high morbidity and mortality. Identifying individuals at elevated risk is crucial for guiding timely interventions and improving patient outcomes.

Methods

In this retrospective cohort study, 850 patients who received interventional or surgical treatment for IAs between January 2018 and January 2024 were included. Demographic data (e.g., age, sex), lifestyle factors, and comorbidities were recorded. Hematologic, biochemical, and coagulation parameters were measured to evaluate their potential association with IA rupture. A univariate logistic regression was first conducted, followed by a multivariate logistic regression with a backward stepwise approach to derive the final predictive model. The model's performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis.

Results

Younger age, female sex, higher neutrophil count, lower hematocrit, and elevated markers of inflammation and coagulation (including fibrinogen and D-dimer) emerged as key risk factors. Electrolyte imbalances, such as low potassium, and elevated lactate dehydrogenase were also significantly associated with rupture. The optimized model achieved an AUC of 0.815, with good calibration and clinical utility indicated by decision curve analysis.

Conclusion

These findings highlight the interplay of demographic, inflammatory, metabolic, and coagulation parameters in determining rupture risk in patients with IAs. Incorporating these risk factors into clinical practice may enhance early detection, guide targeted prevention strategies, and ultimately improve outcomes for high-risk individuals.

Multicenter study of association between socioeconomic status and treatment of ruptured cerebral aneurysms compared to unruptured cerebral aneurysms: insights from 4,517 patients using the area deprivation index

BACKGROUND

Socioeconomic status influences health outcomes, including cerebrovascular diseases. Patients from socioeconomically deprived areas may present with more severe conditions due to delayed access to care. This study evaluates the association between neighborhood-level deprivation, measured by the Area Deprivation Index (ADI), and the treatment of ruptured intracranial aneurysms (RIAs) compared with unruptured intracranial aneurysms (UIAs) across multiple centers.

METHODS

This retrospective cohort study analyzed data from 4517 patients treated for cerebral aneurysms at 10 US comprehensive stroke centers between 2018 and 2024. Patients were stratified by national ADI decile based on their residential addresses. Multivariable logistic regression was used to examine the relationship between ADI and aneurysm rupture (reference being unruptured aneurysms) and controlled for age, sex, smoking history, family history, and race.

RESULTS

Of 4517 total patients, 1260 (27.9%) underwent treatment of RIAs. Multivariable analysis confirmed ADI as an independent predictor of presentation for treatment of RIA (odds ratio (OR)=1.100, 95% confidence interval (CI)=1.068-1.133, P<0.0001) after adjusting for age, sex, smoking history, and race. This corresponds to a 10% increase in likelihood of presenting for treatment of a ruptured vs unruptured intracranial aneurysm with each ADI decile.

CONCLUSION

Socioeconomic deprivation independently predicts treatment of RIAs compared with the treatment of UIAs. These findings highlight disparities in aneurysm detection and management, emphasizing the need for targeted preventive care and accessible screening programs to mitigate the impact of socioeconomic disadvantage on cerebral aneurysm outcomes.

Systematic Review of Radiomics and Artificial Intelligence in Intracranial Aneurysm Management

Intracranial aneurysms, with an annual incidence of 2%-3%, reflect a rare disease associated with significant mortality and morbidity risks when ruptured. Early detection, risk stratification of high-risk subgroups, and prediction of patient outcomes are important to treatment. Radiomics is an emerging field using the quantification of medical imaging to identify parameters beyond traditional radiology interpretation that may offer diagnostic or prognostic significance. The general radiomic workflow involves image normalization and segmentation, feature extraction, feature selection or dimensional reduction, training of a predictive model, and validation of the said model. Artificial intelligence (AI) techniques have shown increasing interest in applications toward vascular pathologies, with some commercially successful software including AiDoc, RapidAI, and Viz.AI, as well as the more recent Viz Aneurysm. We performed a systematic review of 684 articles and identified 84 articles exploring the applications of radiomics and AI in aneurysm treatment. Most studies were published between 2018 and 2024, with over half of articles in 2022 and 2023. Studies included categories such as aneurysm diagnosis (25.0%), rupture risk prediction (50.0%), growth rate prediction (4.8%), hemodynamic assessment (2.4%), clinical outcome prediction (11.9%), and occlusion or stenosis assessment (6.0%). Studies utilized molecular data (2.4%), radiologic data alone (51.2%), clinical data alone (28.6%), and combined radiologic and clinical data (17.9%). These results demonstrate the current status of this emerging and exciting field. An increased pace of innovation in this space is likely with the expansion of clinical applications of radiomics and AI in multiple vascular pathologies.

Current Management of Aneurysmal Subarachnoid Hemorrhage

The diagnosis of aneurysmal subarachnoid hemorrhage (aSAH) is most difficult in patients who are in good clinical condition with a small hemorrhage, especially when a ruptured aneurysm might not be considered, or if a computed tomographic (CT) scan is not obtained, or if when a CT is obtained, the findings are subtle and missed by an inexperienced reviewer. All acute onset (thunderclap) headaches should be considered ruptured aneurysms until proven otherwise. Treatment begins with immediate control of pain and blood pressure, placement of an external ventricular drain (EVD) in poor-grade patients and those with acute hydrocephalus on CT scanning, administration of antifibrinolytic tranexamic acid, and then repair of the aneurysm with either surgical clipping or endovascular techniques as soon as the appropriate treatment team can be assembled. After securing the aneurysm, aSAH patient treatment is focused on maintaining euvolemia and a favorable systemic metabolic state for brain repair. A significant and aneurysm-specific threat after aSAH is delayed arterial vasospasm and resulting cerebral ischemia, which is detected by vigilant bedside examinations for new-onset focal deficits or neurological decline, assisted with daily transcranial Doppler examinations and the judicious use of vascular imaging and cerebral perfusion studies with CT. The management of diagnosed symptomatic vasospasm is the prompt induction of hypertension with vasopressors, but if this fails to reverse deficits quickly after reaching a target systolic blood pressure of 200 mmHg, endovascular angioplasty is indicated, providing CT scanning rules out an established cerebral infarction. Balloon angioplasty should be considered early for all patients found to have severe angiographic vasospasm, with or without detectable signs of ischemic neurological deterioration due to either sedation or a pre-existing deficit.

Radiomic profiling of high-risk aneurysms with blebs: an exploratory study

BACKGROUND

Blebs significantly increase rupture risk of intracranial aneurysms. Radiomic analysis offers a robust characterization of the aneurysm wall. However, the unique radiomic profile of various compartments, including blebs, remains unexplored. Likewise, the correlation between these imaging markers and fluid/mechanical metrics is yet to be investigated. To address this, we analyzed the radiomic features (RFs) of bleb-containing aneurysms and their relationship with wall tension and shear stress metrics, aiming to enhance risk assessment.

METHODS

Aneurysms were imaged using high-resolution magnetic resonance imaging (MRI). A T1 and a T1 after contrast (T1+Gd) sequences were acquired. 3D models of aneurysm bodies and blebs were generated, and RFs were extracted. Aneurysms with and without blebs were matched based on location and size for analysis. Univariate regression models and Spearman's correlations were used to establish associations between bleb-dependent RFs and mechanical/fluid dynamics metrics.

RESULTS

Eighteen aneurysms with blebs were identified. Fifty-five RFs were significantly different between blebs and body within the same aneurysms. Of these RFs, 9% (5/55) were first-order, and 91% (50/55) were second-order features. After aneurysms with and without blebs were matched for location and size, five RFs 5% (5/93) were significantly different. Forty-one out of the 55 RFs different between bleb and body sac of the primary aneurysm were moderately and strongly correlated with mechanical and fluid dynamics metrics.

CONCLUSION

Aneurysm blebs exhibit distinct radiomic profiles compared with the main body of the aneurysm sac. The variability in bleb wall characteristics may arise from differing mechanical stresses and localized hemodynamics. Leveraging radiomic profiling could help identify regions with a heightened risk of rupture.

Computational fluid dynamics and shape analysis enhance aneurysm rupture risk stratification

PURPOSE

Accurately quantifying the rupture risk of unruptured intracranial aneurysms (UIAs) is crucial for guiding treatment decisions and remains an unmet clinical challenge. Computational Flow Dynamics and morphological measurements have been shown to differ between ruptured and unruptured aneurysms. It is not clear if these provide any additional information above routinely available clinical observations or not. Therefore, this study investigates whether incorporating image-derived features into the established PHASES score can improve the classification of aneurysm rupture status.

METHODS

A cross-sectional dataset of 170 patients (78 with ruptured aneurysm) was used. Computational fluid dynamics (CFD) and shape analysis were performed on patients' images to extract additional features. These derived features were combined with PHASES variables to develop five ridge constrained logistic regression models for classifying the aneurysm rupture status. Correlation analysis and principal component analysis were employed for image-derived feature reduction. The dataset was split into training and validation subsets, and a ten-fold cross validation strategy with grid search optimisation and bootstrap resampling was adopted for determining the models' coefficients. Models' performances were evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

The logistic regression model based solely on PHASES achieved AUC of 0.63. All models incorporating derived features from CFD and shape analysis demonstrated improved performance, reaching an AUC of 0.71. Non-sphericity index (shape variable) and maximum oscillatory shear index (CFD variable) were the strongest predictors of a ruptured status.

CONCLUSION

This study demonstrates the benefits of integrating image-based fluid dynamics and shape analysis with clinical data for improving the classification accuracy of aneurysm rupture status. Further evaluation using longitudinal data is needed to assess the potential for clinical integration.

Evaluation of an endovascular aneurysm model in pigs for chronic experiments

BACKGROUND AND AIMS

Cerebral aneurysms are a potentially life-threatening condition for humans. Due to the anatomical variability of different aneurysm types in human patients, animal models are indispensable for endovascular research. The aim of our study was to evaluate an endovascular aneurysm model in chronical experiments using 12 female Aachen minipigs.

MATERIALS AND METHODS

For aneurysm creation in external carotid and subclavian arteries, Amplatzer vascular plugs were used as occlusion devices, leaving simple stumps that serve as surrogate aneurysms. If necessary and anatomically possible, additional embolic materials, such as coils and liquid embolic agents were used.

RESULTS

We created 42 aneurysms. Aneurysm creation was possible without complications in all cases. There was no spontaneous thrombosis of fabricated aneurysms. Complete perfusion arrest behind the fabricated aneurysm was challenging but achieved in 45% of cases. We were not able to identify significant factors that have an impact on the persisting perfusion of fabricated aneurysms on final imaging, particularly not the presence of side branches in the aneurysm lumen (P = 0.734) or volumes of the fabricated aneurysms (P = 0.620). Albeit not significant, the use of additional occlusive measures (coils, liquid embolic agents) and antithrombotic drugs (ASA, heparin and tirofiban) may be factors for persisting perfusion: Perfusion arrest behind the fabricated aneurysm was twice as high in animals treated with ASA and heparin compared to animals treated with ASA, heparin, and tirofiban (48% vs. 22%; P = 0.149).

CONCLUSION

Despite its limitations, including persistent perfusion and impaired predictability for long-term experiments, the endovascular aneurysm model shows potential to replace certain surgical models and offers broad applications in biomedical research and aneurysm therapy.

Sex disparities in the risk of intracranial aneurysm rupture: a case-control study

Background

There are sex disparities in the risk of ruptured intracranial aneurysm (IA), but which sex-specific factors are related to ruptured IA remains inconclusive.

Methods

Data from electronic medical records from two tertiary hospitals, collected between January 2012 and December 2019, were analyzed for this study. All IAs were confirmed by computed tomographic angiography or digital subtraction angiography. Sex-specific factors associated with ruptured IA were analyzed using multivariable logistic models with a case-control study design. Age, aneurysm size, and aneurysm location subgroup analyses were conducted according to sex.

Results

In total, 1883 patients [1,117 (59.32%) female, 766 (40.68%) male] with 2,423 IAs were included; 734 (38.98%) of patients had ruptured IAs. Compared with males, females had a higher risk of ruptured IA [odds ratio, 1.72 (95% confidence interval, 1.38-2.14)]. Age, aneurysm location, aneurysm size, multiple aneurysms, hypertension, history of intracerebral hemorrhage, and ischemic stroke were associated with risk of IA rupture in both sexes. In the subgroups based on the covariates used in this study, we only identified statistically significant interaction between sex and age. Although ruptured IAs were most common in males and females aged 50-59 and 60-69 years, respectively, risk of IA rupture peaked at ages 30 and 30-50 years in females and males, respectively, and decreased with age in both sexes.

Conclusion

Females have an overall greater IA incidence and higher risk of IA rupture than males. Young age is one sex-specific risk factor associated with ruptured IA which could related to potential influence of hypertension, which might suggest more attention of IA rupture prevention in younger female.

O304 alleviates abdominal aortic aneurysm formation via AMPK/mTOR/MMP pathway activation

Background

Abdominal aortic aneurysm (AAA) rupture is a significant cause of mortality in the elderly population. Despite experimental models identifying promising pharmacological therapies, there is still a lack of pharmacological interventions for AAA prior to surgery. This study aims to evaluate the regulatory role of the novel adenosine monophosphate-activated protein kinase (AMPK) agonist O304 in AAA formation and explore its underlying molecular mechanisms.

Methods

We evaluated the expression of AMPK signaling pathway components and contractile vascular smooth muscle cell (VSMC)-related genes in AAA samples from mice using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). We evaluate the TGF-β expression by western blotting and RT-qPCR and TGF-β concentration in blood by ELISA. We developed an in vitro model of transforming growth factor-β (TGF-β)-induced VSMC phenotypic switching. After treatment with O304, we analyzed the expression of contractile genes and proteins in VSMCs by immunofluorescence and Western blotting. We also evaluated the expression of AMPK signaling pathway components and matrix metalloproteinases by western blotting and immunofluorescence analysis. We established a mouse model of AAA to evaluate the impact of O304 on aneurysm diameter and blood pressure, analyzed VSMC phenotypic switching through immunofluorescence analysis, and assessed the regulatory effects of O304 on AMPK signaling in the mouse model of AAA by Western blotting.

Results

AMPK signaling pathway components and contractile genes in VSMCs were downregulated in mouse AAA samples, underscoring the crucial role of AMPK signaling in VSMC phenotypic switching. In the TGF-β-induced model of VSMC phenotypic switching, O304 activated AMPK signaling and prevented VSMC phenotypic switching from the contractile to the synthetic phenotype. Moreover, O304 significantly activated AMPK signaling, increased the proportion of contractile VSMCs, and reduced AAA formation and blood pressure in the mouse model of AAA.

Conclusion

During AAA development, VSMCs transitioned from the contractile to the proliferative phenotype, a process that has previously been associated with AMPK pathway inhibition. O304, an AMPK agonist, activated the AMPK pathway, preventing VSMC phenotypic switching and inhibiting AAA formation. These findings highlight the therapeutic potential of targeting the AMPK pathway in AAA.

Intra-Aneurysmal High-Resolution 4D MR Flow Imaging for Hemodynamic Imaging Markers in Intracranial Aneurysm Instability

BACKGROUND AND PURPOSE

Prediction of aneurysm instability is crucial to guide treatment decisions and to select appropriate patients with unruptured intracranial aneurysms (IAs) for preventive treatment. High-resolution 4D MR flow imaging and 3D quantification of aneurysm morphology could offer insights and new imaging markers for aneurysm instability. In this cross-sectional study, we aim to identify 4D MR flow imaging markers for aneurysm instability by relating hemodynamics in the aneurysm sac to 3D morphologic proxy parameters for aneurysm instability.

MATERIALS AND METHODS

In 35 patients with 37 unruptured IAs, a 3T MRA and a 7T 4D MRI flow scan were performed. Five hemodynamic parameters-peak-systolic wall shear stress (WSSMAX) and time-averaged wall shear stress (WSSMEAN), oscillatory shear index (OSI), mean velocity, and velocity pulsatility index-were correlated to 6 3D morphology proxy parameters of aneurysm instability-major axis length, volume, surface area (all 3 size parameters), flatness, shape index, and curvedness-by Pearson correlation with 95% CI. Scatterplots of hemodynamic parameters that correlated with IA size (major axis length) were created.

RESULTS

WSSMAX and WSSMEAN correlated negatively with all 3 size parameters (strongest for WSSMEAN with volume (r = -0.70, 95% CI -0.83 to -0.49) and OSI positively (strongest with major axis length [r = 0.87, 95% CI 0.76-0.93]). WSSMAX and WSSMEAN correlated positively with shape index (r = 0.61, 95% CI 0.36-0.78 and r = 0.49, 95% CI 0.20-0.70, respectively) and OSI negatively (r = -0.82, 95% CI -0.9 to -0.68). WSSMEAN and mean velocity correlated negatively with flatness (r = -0.35, 95% CI -0.61 to -0.029 and r = -0.33, 95% CI -0.59 to 0.007, respectively) and OSI positively (r = 0.54, 95% CI 0.26-0.74). Velocity pulsatility index did not show any statistically relevant correlation.

CONCLUSIONS

Out of the 5 included hemodynamic parameters, WSSMAX, WSSMEAN, and OSI showed the strongest correlation with morphologic 3D proxy parameters of aneurysm instability. Future studies should assess these promising new imaging marker parameters for predicting aneurysm instability in longitudinal cohorts of patients with IA.

On the Importance of Including Cohesive Zone Models in Modelling Mixed-Mode Aneurysm Rupture

INTRODUCTION

The precise mechanism of rupture in abdominal aortic aneurysms (AAAs) has not yet been uncovered. The phenomenological failure criterion of the coefficient of proportionality between von Mises stress and tissue strength does not account for any mechanistic foundation of tissue fracture. Experimental studies have shown that arterial failure is a stepwise process of fibrous delamination (mode II) and kinking (mode I) between layers. Such a mechanism has not previously been considered for AAA rupture.

METHODS

In the current study we consider both von Mises stress in the wall, in addition to interlayer tractions and delamination using cohesive zone models. Firstly, we present a parametric investigation of the influence of a range of AAA anatomical features on the likelihood of elevated interlayer traction and delamination.

RESULTS

We observe in several cases that the location of peak von Mises stress and tangential traction coincide. Our simulations also reveal however, that peak von Mises and intramural tractions are not coincident for aneurysms with Length/Radius less than 2 (short high-curvature aneurysms) and for aneurysms with symmetric intraluminal thrombus (ILT). For an aneurysm with (L/R = 2.0), the peak σ vm moves slightly towards the origin while the peak T t is near the peak bulge with a separation distance of ~ 17 mm. Additionally, we present three patient-specific AAA models derived directly from CT scans, which also illustrate that the location of von Mises stress does not correlate with the point of interlayer delamination.

CONCLUSION

This study suggests that incorporating cohesive zone models into clinical based FE analyses may capture a greater proportion of ruptures in-silico.

Emergence of Precision Medicine Within Neurological Surgery: Promise and Opportunity

Within neurosurgery, it has always been important to individualize patient care. In recent years, however, technological advances have brought a new dimension to personalized care as developing methods, including next-generation sequencing, have enabled us to molecularly profile pathologies with increasing scale and resolution. In this review, the authors discuss the history and advances in precision medicine and neurosurgery, focusing both on neuro-oncology, as well as its extension to other neurosurgical subspecialties. They highlight the important roles of neurosurgeons in past work and future work, with the extension of tissue collection and precision medicine principles to additional sample types and disease indications.

Risk factors and predictive indicators of rupture in cerebral aneurysms

Cerebral aneurysms are abnormal dilations of blood vessels in the brain that have the potential to rupture, leading to subarachnoid hemorrhage and other serious complications. Early detection and prediction of aneurysm rupture are crucial for effective management and prevention of rupture-related morbidities and mortalities. This review aims to summarize the current knowledge on risk factors and predictive indicators of rupture in cerebral aneurysms. Morphological characteristics such as aneurysm size, shape, and location, as well as hemodynamic factors including blood flow patterns and wall shear stress, have been identified as important factors influencing aneurysm stability and rupture risk. In addition to these traditional factors, emerging evidence suggests that biological and genetic factors, such as inflammation, extracellular matrix remodeling, and genetic polymorphisms, may also play significant roles in aneurysm rupture. Furthermore, advancements in computational fluid dynamics and machine learning algorithms have enabled the development of novel predictive models for rupture risk assessment. However, challenges remain in accurately predicting aneurysm rupture, and further research is needed to validate these predictors and integrate them into clinical practice. By elucidating and identifying the various risk factors and predictive indicators associated with aneurysm rupture, we can enhance personalized risk assessment and optimize treatment strategies for patients with cerebral aneurysms.

Risk analysis of intracranial aneurysm rupture based on the arterial segment of origin

Background and objective

The rupture risk of intracranial aneurysms (IAs) is related to their arterial origin, but whether the different segments of the artery have different risks and act as independent risk factors is still unknown. Our study aimed to investigate the rupture risk of IAs in different arterial segments in a large Chinese cohort.

Methods

Imaging and clinical data of consecutive patients with IAs diagnosed by Computed Tomography angiography (CTA) from January 2013 to December 2022 were collected. Two neuroradiologists independently identified ruptured and unruptured IAs based on imaging and medical records. The internal carotid artery (ICA), middle cerebral artery (MCA), anterior cerebral artery (ACA), vertebral artery (VA), and posterior cerebral artery (PCA) were segmented according to the Bouthillier and Fischer segmentation methods. Stenoses of the proximal parent vessel were evaluated and documented. The Institutional Review Board (IRB) at Beijing Tiantan Hospital approved this retrospective study.

Results

A total of 3,837 aneurysms {median size 3.5 mm [interquartile range (IQR) 2.6-5.1 mm]; 532 ruptured} were included in this study from 2,968 patients [mean age: 57 years (IQR 50-64); male patients: 1,153]. Ruptured aneurysms were most commonly located in the posterior inferior cerebellar artery (PICA) (52.9%), anterior communicating artery (ACoA) (33.8%), other locations (33.3%), ACA (22.4%), and basilar artery (BA) (21.4%). The locations with the highest likelihood of rupture were the C7 ICA (21.3%), M2 MCA (24.0%), distal MCA (25.0%), and A2 ACA (28.1%). IAs originating from the C7 (p < 0.001), dM1 (p = 0.022), and dA1 (p = 0.021) segments were independent risk factors for rupture. IAs without stenosis of the proximal parent vessel were associated with a higher risk of rupture (p = 0.023).

Conclusion

There are unique associations between the origins of aneurysms from various arterial segments. Aneurysms originating from the anterior communicating artery (ACoA), BA, PICA, A2, dA, C7, and M2 indicate a higher risk of rupture. Aneurysms originating from C4, C5, and C6 indicate a lower risk of rupture. C7 IAs, ACoA IAs, and PICA IAs seem to be independent risk factors.

Knowledge domain and emerging trends in the rupture risk of intracranial aneurysms research from 2004 to 2023

BACKGROUND

Intracranial aneurysms (IAs) pose significant health risks, attributable to their potential for sudden rupture, which can result in severe outcomes such as stroke and death. Despite extensive research, the variability of aneurysm behavior, with some remaining stable for years while others rupture unexpectedly, remains poorly understood.

AIM

To employ bibliometric analysis to map the research landscape concerning risk factors associated with IAs rupture.

METHODS

A systematic literature review of publications from 2004 to 2023 was conducted, analyzing 3804 documents from the Web of Science Core Collection database, with a focus on full-text articles and reviews in English. The analysis encompassed citation and co-citation networks, keyword bursts, and temporal trends to delineate the evolution of research themes and collaboration patterns. Advanced software tools, CiteSpace and VOSviewer, were utilized for comprehensive data visualization and trend analysis.

RESULTS

Analysis uncovered a total of 3804 publications on IA rupture risk factors between 2006 and 2023. Research interest surged after 2013, peaking in 2023. The United States led with 28.97% of publications, garnering 37706 citations. Notable United States-China collaborations were observed. Capital Medical University produced 184 publications, while Utrecht University boasted a citation average of 69.62 per publication. "World Neurosurgery" published the most papers, contrasting with "Stroke", the most cited journal. The PHASES score from "Lancet Neurology" emerged as a vital rupture risk prediction tool. Early research favored endovascular therapy, transitioning to magnetic resonance imaging and flow diverters. "Subarachnoid hemorrhage" stood out as a recurrent keyword.

CONCLUSION

This study assesses global IA research trends and highlights crucial gaps, guiding future investigations to improve preventive and therapeutic approaches.

Clinical relevance of critical plasma homocysteine levels in predicting rupture risk for small and medium-sized intracranial aneurysms

Plasma homocysteine (Hcy) has been globally recognized as an independent risk factor for various neurovascular diseases. In this study, the authors investigated the relationship between critical Hcy concentration and the risk of rupture in intracranial aneurysms (IAs). This study collected data from 423 patients with both ruptured and unruptured IAs. We compared demographic data, vascular rupture risk factors, and laboratory test results between the two groups. Multivariable logistic regression analysis was employed to determine the correlation between critical plasma Hcy levels and the risk of rupture in small to medium-sized IAs. A total of 330 cases of ruptured intracranial aneurysms (RIA) and 93 cases of unruptured intracranial aneurysms (UIA) were included. Univariate analysis revealed statistically significant differences between the ruptured and unruptured groups in terms of hypertension, hyperlipidemia, plasma Hcy levels, and IA morphology (all P < 0.05). Multivariable logistic regression analysis indicated that hypertension (odds ratio [OR] 0.504; 95% confidence interval [CI] 0.279-0.911; P = 0.023), hyperlipidemia (OR 1.924; 95% CI 1.079-3.429; P = 0.027), and plasma Hcy levels (OR 1.420; 95% CI 1.277-1.578; P < 0.001) were independently associated with the rupture of small to medium-sized IAs, all with statistical significance (P < 0.05). Our study suggests that critical plasma Hcy levels are an independent risk factor for increased rupture risk in small to medium-sized intracranial aneurysms. Therefore, reducing plasma Hcy levels may be considered a valuable strategy to mitigate the risk of intracranial vascular abnormalities rupture and improve patient prognosis.

A Decision Tree Model to Help Treatment Decision-Making for Unruptured Intracranial Aneurysms: A Multi-center, Long-Term Follow-up Study in a Large Chinese Cohort

Chinese population have a high prevalence of unruptured intracranial aneurysm (UIA). Clinical and imaging risk factors predicting UIA growth or rupture are poorly understood in the Chinese population due to the lack of large-scale longitudinal studies, and the treatment decision for UIA patients was challenging. Develop a decision tree (DT) model for UIA instability, and validate its performance in multi-center studies. Single-UIA patients from two prospective, longitudinal multicenter cohort studies were analyzed, and set as the development cohort and validation cohort. The primary endpoint was UIA instability (rupture, growth, or morphological change). A DT was established within the development cohort and validated within the validation cohort. The performance of clinicians in identifying unstable UIAs before and after the help of the DT was compared using the area under curve (AUC). The development cohort included 1270 patients with 1270 UIAs and a follow-up duration of 47.2 ± 15.5 months. Aneurysm instability occurred in 187 (14.7%) patients. Multivariate Cox analysis revealed hypertension (hazard ratio [HR], 1.54; 95%CI, 1.14-2.09), aspect ratio (HR, 1.22; 95%CI, 1.17-1.28), size ratio (HR, 1.31; 95%CI, 1.23-1.41), bifurcation configuration (HR, 2.05; 95%CI, 1.52-2.78) and irregular shape (HR, 4.30; 95%CI, 3.19-5.80) as factors of instability. In the validation cohort (n = 106, 12 was unstable), the DT model incorporating these factors was highly predictive of UIA instability (AUC, 0.88 [95%CI, 0.79-0.97]), and superior to existing UIA risk scales such as PHASES and ELAPSS (AUC, 0.77 [95%CI, 0.67-0.86] and 0.76 [95%CI, 0.66-0.86], P < 0.001). Within all 1376 single-UIA patients, the use of the DT significantly improved the accuracy of junior neurosurgical clinicians to identify unstable UIAs (AUC from 0.63 to 0.82, P < 0.001). The DT incorporating hypertension, aspect ratio, size ratio, bifurcation configuration and irregular shape was able to predict UIA instability better than existing clinical scales in Chinese cohorts. CLINICAL TRIAL REGISTRATION: IARP-CP cohort were included (unique identifier: ChiCTR1900024547. Published July 15, 2019. Completed December 30, 2020), with 100-Project phase-I cohort (unique identifier: NCT04872842, Published May 5, 2021. Completed November 8, 2022) as the development cohort. The 100-Project phase-II cohort (unique identifier: NCT05608122. Published November 8, 2022) as the validation cohort.

Integrating PointNet-Based Model and Machine Learning Algorithms for Classification of Rupture Status of IAs

BACKGROUND

The rupture of intracranial aneurysms (IAs) would result in subarachnoid hemorrhage with high mortality and disability. Predicting the risk of IAs rupture remains a challenge.

METHODS

This paper proposed an effective method for classifying IAs rupture status by integrating a PointNet-based model and machine learning algorithms. First, medical image segmentation and reconstruction algorithms were applied to 3D Digital Subtraction Angiography (DSA) imaging data to construct three-dimensional IAs geometric models. Geometrical parameters of IAs were then acquired using Geomagic, followed by the computation of hemodynamic clouds and hemodynamic parameters using Computational Fluid Dynamics (CFD). A PointNet-based model was developed to extract different dimensional hemodynamic cloud features. Finally, five types of machine learning algorithms were applied on geometrical parameters, hemodynamic parameters, and hemodynamic cloud features to classify and recognize IAs rupture status. The classification performance of different dimensional hemodynamic cloud features was also compared.

RESULTS

The 16-, 32-, 64-, and 1024-dimensional hemodynamic cloud features were extracted with the PointNet-based model, respectively, and the four types of cloud features in combination with the geometrical parameters and hemodynamic parameters were respectively applied to classify the rupture status of IAs. The best classification outcomes were achieved in the case of 16-dimensional hemodynamic cloud features, the accuracy of XGBoost, CatBoost, SVM, LightGBM, and LR algorithms was 0.887, 0.857, 0.854, 0.857, and 0.908, respectively, and the AUCs were 0.917, 0.934, 0.946, 0.920, and 0.944. In contrast, when only utilizing geometrical parameters and hemodynamic parameters, the accuracies were 0.836, 0.816, 0.826, 0.832, and 0.885, respectively, with AUC values of 0.908, 0.922, 0.930, 0.884, and 0.921.

CONCLUSION

In this paper, classification models for IAs rupture status were constructed by integrating a PointNet-based model and machine learning algorithms. Experiments demonstrated that hemodynamic cloud features had a certain contribution weight to the classification of IAs rupture status. When 16-dimensional hemodynamic cloud features were added to the morphological and hemodynamic features, the models achieved the highest classification accuracies and AUCs. Our models and algorithms would provide valuable insights for the clinical diagnosis and treatment of IAs.

Serum Interleukin-1 Levels Are Associated with Intracranial Aneurysm Instability

Serum interleukin-1 (IL-1) are possibly indicative of the inflammation in the intracranial aneurysm (IA) wall. This study aimed to investigate whether IL-1 could discriminate the unstable IAs (ruptured intracranial aneurysms (RIAs) and symptomatic unruptured intracranial aneurysms (UIAs)) from stable, asymptomatic UIAs. IA tissues and blood samples from 35 RIA patients and 35 UIA patients were collected between January 2017 and June 2020 as the derivation cohort. Blood samples from 211 patients with UIAs were collected between January 2021 and June 2022 as the validation cohort (including 63 symptomatic UIAs). Blood samples from 35 non-cerebral-edema meningioma patients (non-inflammatory control) and 19 patients with unknown-cause subarachnoid hemorrhage (hemorrhagic control) were also collected. IL-1β and IL-1.ra (IL-1 receptor antagonist) were measured in serum and IA tissues, and the IL-1 ratio was calculated as log10 (IL-1.ra/IL-1β). Based on the derivation cohort, multivariate logistic analysis showed that IL-1β (odds ratio, 1.48, P = 0.001) and IL-1.ra (odds ratio, 0.74, P = 0.005) were associated with RIAs. The IL-1 ratio showed an excellent diagnostic accuracy for RIAs (c-statistic, 0.91). Histological analysis confirmed the significant correlation of IL-1 between serum and aneurysm tissues. IL-1 ratio could discriminate UIAs from non-inflammatory controls (c-statistic, 0.84), and RIAs from hemorrhagic controls (c-statistic, 0.95). Based on the validation cohort, the combination of IL-1 ratio and PHASES score had better diagnostic accuracy for symptomatic UIAs than PHASES score alone (c-statistic, 0.88 vs 0.80, P < 0.001). Serum IL-1 levels correlate with aneurysm tissue IL-1 levels and unstable aneurysm status, and could serve as a potential biomarker for IA instability.

Assessment of intracranial aneurysm rupture risk using a point cloud-based deep learning model

Background and Purpose: Precisely assessing the likelihood of an intracranial aneurysm rupturing is critical for guiding clinical decision-making. The objective of this study is to construct and validate a deep learning framework utilizing point clouds to forecast the likelihood of aneurysm rupturing. Methods: The dataset included in this study consisted of a total of 623 aneurysms, with 211 of them classified as ruptured and 412 as unruptured, which were obtained from two separate projects within the AneuX morphology database. The HUG project, which included 124 ruptured aneurysms and 340 unruptured aneurysms, was used to train and internally validate the model. For external validation, another project named @neurIST was used, which included 87 ruptured and 72 unruptured aneurysms. A standardized method was employed to isolate aneurysms and a segment of their parent vessels from the original 3D vessel models. These models were then converted into a point cloud format using open3d package to facilitate training of the deep learning network. The PointNet++ architecture was utilized to process the models and generate risk scores through a softmax layer. Finally, two models, the dome and cut1 model, were established and then subjected to a comprehensive comparison of statistical indices with the LASSO regression model built by the dataset authors. Results: The cut1 model outperformed the dome model in the 5-fold cross-validation, with the mean AUC values of 0.85 and 0.81, respectively. Furthermore, the cut1 model beat the morphology-based LASSO regression model with an AUC of 0.82. However, as the original dataset authors stated, we observed potential generalizability concerns when applying trained models to datasets with different selection biases. Nevertheless, our method outperformed the LASSO regression model in terms of generalizability, with an AUC of 0.71 versus 0.67. Conclusion: The point cloud, as a 3D visualization technique for intracranial aneurysms, can effectively capture the spatial contour and morphological aspects of aneurysms. More structural features between the aneurysm and its parent vessels can be exposed by keeping a portion of the parent vessels, enhancing the model's performance. The point cloud-based deep learning model exhibited good performance in predicting rupture risk while also facing challenges in generalizability.

Risk factors and management of intraprocedural rupture during coil embolization of unruptured intracranial aneurysms: role of balloon guiding catheter

Introduction

Intraprocedural rupture (IPR) is a serious complication of endovascular coil embolization of unruptured intracranial aneurysms (UIAs). Although outcomes after IPR are poor, methods to prevent subsequent neurological deterioration have not yet been investigated. We evaluated the risk factors and management strategies for IPR, particularly the role of balloon guiding catheters (BGCs) in rapid hemostasis.

Methods

We retrospectively reviewed all UIA cases treated with coil embolization at three institutions between 2003 and 2021, focusing on preoperative radiological data, operative details, and outcomes.

Results

In total, 2,172 aneurysms were treated in 2026 patients. Of these, 19 aneurysms in 19 patients (0.8%) ruptured during the procedure. Multivariate analysis revealed that aneurysms with a bleb (OR: 3.03, 95% CI: 1.21 to 7.57, p = 0.017), small neck size (OR: 0.56, 95% CI: 0.37 to 0.85, p = 0.007), and aneurysms in the posterior communicating artery (PcomA) (OR: 4.92, 95% CI: 1.19 to 20.18, p = 0.027) and anterior communicating artery (AcomA) (OR: 12.08, 95% CI: 2.99 to 48.79, p < 0.001) compared with the internal carotid artery without PcomA were significantly associated with IPR. The incidence of IPR was similar between the non-BGC and BGC groups (0.9% vs. 0.8%, p = 0.822); however, leveraging BGC was significantly associated with lower morbidity and mortality rates after IPR (0% vs. 44%, p = 0.033).

Discussion

The incidence of IPR was relatively low. A bleb, small aneurysm neck, and location on PcomA and AcomA are independent risk factors for IPR. The use of BGC may prevent fatal clinical deterioration and achieve better clinical outcomes in patients with IPR.

Risk Factors and Location of Intracranial Aneurysm Rupture in a Consecutive Chinese Han Population

OBJECTIVE

The aim of the present study was to retrospectively analyze and investigate the clinical data of 704 cases of ruptured intracranial aneurysms (RIAs) and unruptured intracranial aneurysms (UIAs). The risk factors predicting aneurysm rupture were explored from the perspective of the clinical characteristics of intracranial aneurysm (IA).

METHODS

The clinical data of 704 patients with RIAs (494 patients) and UIAs (210 patients) admitted to the Department of Neurosurgery of Tianjin Medical University General Hospital and Tianjin Fifth Central Hospital between January 2016 and May 2022 were analyzed. A detailed analysis of sex, age, history, personal history, drug intake, and site of aneurysm occurrence was performed. Age was analyzed in segments and strata, and parameters with significant differences in the preliminary analysis results were analyzed by logistic regression to predict factors associated with the risk of aneurysm rupture.

RESULTS

Among 494 patients with RIA (70.2%) and 210 patients with UIA (29.8%), the logistic regression showed that IA location appeared to be the most significant factor associated with RIA (OR, 95% CI: internal carotid artery (ICA), reference; anterior communicating artery,27.864,12.548-61.878; posterior communicating artery,12.408,6.658-23.124; anterior cerebral artery,5.804,2.333-14.440; middle cerebral artery,9.284,4.599-18.744; posterior circulation arteries, 4.224,2.011-8.871). Age was not a significant factor associated with RIA in the model and Hyperlipidemia (OR: 0.365; 95% CI: 0.171-0.779), Atherosclerosis (OR: 0.277; 95% CI: 0.172-0.446) and Multiple aneurysms (OR: 0.275; 95% CI: 0.177-0.425) patients were less likely to have RIA.IA location and age were the best predictors of RIA using the model.

CONCLUSIONS

The present findings indicated that hyperlipidemia and atherosclerosis have a protective effect on aneurysm rupture, and different anatomical sites of IA may be risk factors for the occurrence of IA rupture. Among the anatomical sites of IA, the anterior communicating artery and posterior communicating artery have a higher fracture risk.

Multimodal exploration of the intracranial aneurysm wall

PURPOSE

Intracranial aneurysms (IAs) are pathological changes of the intracranial vessel wall, although clinical image data can only show the vessel lumen. Histology can provide wall information but is typically restricted to ex vivo 2D slices where the shape of the tissue is altered.

METHODS

We developed a visual exploration pipeline for a comprehensive view of an IA. We extract multimodal information (like stain classification and segmentation of histologic images) and combine them via 2D to 3D mapping and virtual inflation of deformed tissue. Histological data, including four stains, micro-CT data and segmented calcifications as well as hemodynamic information like wall shear stress (WSS), are combined with the 3D model of the resected aneurysm.

RESULTS

Calcifications were mostly present in the tissue part with increased WSS. In the 3D model, an area of increased wall thickness was identified and correlated to histology, where the Oil red O (ORO) stained images showed a lipid accumulation and the alpha-smooth muscle actin (aSMA) stained images showed a slight loss of muscle cells.

CONCLUSION

Our visual exploration pipeline combines multimodal information about the aneurysm wall to improve the understanding of wall changes and IA development. The user can identify regions and correlate how hemodynamic forces, e.g. WSS, are reflected by histological structures of the vessel wall, wall thickness and calcifications.

New morphological parameter for intracranial aneurysms and rupture risk prediction based on artificial neural networks

BACKGROUND

Numerous studies have evaluated the rupture risk of intracranial aneurysms using morphological parameters because of their good predictive capacity. However, the limitation of current morphological parameters is that they do not always allow evaluation of irregularities of intracranial aneurysms. The purpose of this study is to propose a new morphological parameter that can quantitatively describe irregularities of intracranial aneurysms and to evaluate its performance regarding rupture risk prediction.

METHODS

In a retrospective study, conventional morphological parameters (aspect ratio, bottleneck ratio, height-to-width ratio, volume to ostium ratio, and size ratio) and a newly proposed morphological parameter (mass moment of inertia) were calculated for 125 intracranial aneurysms (80 unruptured and 45 ruptured aneurysms). Additionally, hemodynamic parameters (wall shear stress and strain) were calculated using computational fluid dynamics and fluid-structure interaction. Artificial neural networks trained with each parameter were used for rupture risk prediction.

RESULTS

All components of the mass moment of inertia (Ixx, Iyy, and Izz) were significantly higher in ruptured cases than in unruptured cases (p values for Ixx, Iyy, and Izz were 0.032, 0.047, and 0.039, respectively). When the conventional morphological and hemodynamic parameters as well as the mass moment of inertia were considered together, the highest performance for rupture risk prediction was obtained (sensitivity 96.3%; specificity 85.7%; area under the receiver operating characteristic curve 0.921).

CONCLUSIONS

The mass moment of inertia would be a useful parameter for evaluating aneurysm irregularity and hence its risk of rupture. The new approach described here may help clinicians to predict the risk of aneurysm rupture more effectively.

Predictive Model Evaluating Risk of Hemorrhage in Intracranial Aneurysms: Analysis from Prospectively Collected HEAT Trial Database

OBJECTIVE

We analyzed the data of patients enrolled in the Hydrogel Endovascular Aneurysm Treatment (HEAT) trial to develop and validate a model to predict the risk of aneurysmal hemorrhage.

METHODS

Analysis included data from 600 patients enrolled for the HEAT trial and included single saccular aneurysms of 3-14 mm size. Baseline characteristics were compared between patients with ruptured and unruptured aneurysms. Regression analysis was performed in the training set to identify significant risk factors and was validated in the validation dataset. The complete dataset was used to formulate a scoring model in which positive and negative predictors were assigned 1 and -1 points, respectively.

RESULTS

Data from 593 patients were analyzed in which 169 (28.5%) patients had ruptured aneurysms. The training (n = 297) and validation dataset (n = 296) had a comparable proportion of ruptured aneurysms (29.3% and 27.7%). Dome-to-neck ratio >2.5 (odds ratio [OR] 3.66), irregular shape (OR 3.79), daughter sac (OR 5.89), and anterior and posterior communicating artery locations (OR 3.32 and 3.56, respectively) had a higher rupture rate. Use of aspirin was associated with lower risk of hemorrhage (OR 0.16). The area under the curve from the receiver operating curve analysis was 0.88, 0.87, and 0.87 in the training, validation, and combined data set, respectively. The scoring model created a score of -1 to 2, yielding an of aneurysmal hemorrhage probability from 1.5% (score -1) to 70% (score 2).

CONCLUSIONS

This prospective study identifies dome-to-neck ratio >2.5, irregular shape, presence of daughter sac, absence of aspirin use, and aneurysm location at anterior communicating and posterior communicating artery as factors associated with increased risk of hemorrhagic presentation in small- to medium-sized intracranial aneurysms. Our model provides an estimate of rupture risk based on the presence or absence of these factors.

Morphological characteristics of brain aneurysms among age groups

BACKGROUND

Patient's age is an important factor in determining the risk of aneurysm rupture. However, there is limited data on how aneurysm morphology differs among age groups. We studied morphological characteristics of brain aneurysms among age groups in a large cohort.

METHODS

Aneurysms from the Stroke Thrombectomy and Aneurysm Registry (STAR) were analyzed. The following parameters were included: location, size, neck, width, height, aspect ratio, and regular versus irregular morphology. The risk of rupture presentation was estimated using logistic regression.

RESULTS

A total of 1407 unruptured and 607 ruptured saccular aneurysms were included. The most common locations of ruptured aneurysms in patients younger than 70 years-old were the middle cerebral artery (MCA) and the anterior communicating artery (ACOM). The most common location of ruptured aneurysms in patients older than 70 years-old were the posterior communicating artery (PCOM) and ACOM. The size of unruptured aneurysms increased with age (p < .001). Conversely, the size of ruptured aneurysms was similar among age groups (p = .142). Unruptured and ruptured aneurysms became more irregular at presentation with older age (p < .001 and p .025, respectively). Irregular morphology and location were associated with rupture status across all age groups in multivariate regression.

CONCLUSIONS

Younger patients have small unruptured and ruptured aneurysms, and ruptured aneurysms are mostly located in the MCA and ACOM. Older patients have larger and more irregular unruptured aneurysms, and ruptured aneurysms are mostly located in the PCOM and ACOM. An irregular morphology increases the risk of rupture in all age groups.

StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm

Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality and morbidity, may outweigh the benefits of aneurysmal occlusion in some cases. Hence, there is a critical need for developing techniques that assist physicians in assessing the risk of aneurysm rupture to determine which aneurysms require treatment. However, a reliable IA rupture risk prediction technique is currently unavailable. To address this issue, this study proposes a novel approach for aneurysm segmentation and multidisciplinary rupture prediction using 2D Digital Subtraction Angiography (DSA) images. The proposed method involves training a fully connected convolutional neural network (CNN) to segment aneurysm regions in DSA images, followed by extracting and fusing different features using a multidisciplinary approach, including deep features, geometrical features, Fourier descriptor, and shear pressure on the aneurysm wall. The proposed method also adopts a fast correlation-based filter approach to drop highly correlated features from the set of fused features. Finally, the selected fused features are passed through a Decision Tree classifier to predict the rupture severity of the associated aneurysm into four classes: Mild, Moderate, Severe, and Critical. The proposed method is evaluated on a newly developed DSA image dataset and on public datasets to assess its generalizability. The system's performance is also evaluated on DSA images annotated by expert neurosurgeons for the rupture risk assessment of the segmented aneurysm. The proposed system outperforms existing state-of-the-art segmentation methods, achieving an 85 % accuracy against annotated DSA images for the risk assessment of aneurysmal rupture.

Impact of Morphological Factors on the Future Growth of Unruptured Posterior Communicating Artery Aneurysms

BACKGROUND

No previous study has established the factors associated with intracranial aneurysm growth using imaging data obtained before the appearance of morphological changes. Therefore, we investigated the factors related to future aneurysm growth in posterior communicating artery (Pcom) aneurysms.

METHODS

Using a longitudinal database of intracranial aneurysm cases, we reviewed the findings for consecutive patients with unruptured Pcom aneurysms admitted to our institute from 2012 to 2021. Magnetic resonance images obtained over time were used to evaluate aneurysm growth. Aneurysms showing growth over time (group G) and unchanged aneurysms (group U) were compared in terms of background data and morphological factors.

RESULTS

93 Pcom aneurysms (group G: 25 aneurysms, 25%; group U: 68 aneurysms, 75%) were eligible for the present study. Six aneurysm rupture events occurred in group G (24%). Among morphological factors, Pcom diameter (1.2 ± 0.3 mm vs. 0.8 ± 0.7 mm, P < 0.01), bleb formation (group G: 39% vs. group U: 10%; odds ratio, 5.6; P = 0.01), and the lateral projection of the dome (group G: 52% vs. group U: 13%; odds ratio, 3.2; P = 0.023) were significantly different between the 2 groups. The sensitivity and specificity of a cutoff Pcom diameter of 0.73 mm for predicting enlargement were 96% and 53%, respectively.

CONCLUSIONS

Pcom diameter, bleb formation, and lateral dome projection were associated with growth of Pcom aneurysms. Aneurysms with these risk factors require careful follow-up imaging, which may facilitate early detection of aneurysm growth and prevention of rupture through therapeutic interventions.

Automatic risk prediction of intracranial aneurysm on CTA image with convolutional neural networks and radiomics analysis

BACKGROUND

Intracranial aneurysm (IA) is a nodular protrusion of the arterial wall caused by the localized abnormal enlargement of the lumen of a brain artery, which is the primary cause of subarachnoid hemorrhage. Accurate rupture risk prediction can effectively aid treatment planning, but conventional rupture risk estimation based on clinical information is subjective and time-consuming.

METHODS

We propose a novel classification method based on the CTA images for differentiating aneurysms that are prone to rupture. The main contribution of this study is that the learning-based method proposed in this study leverages deep learning and radiomics features and integrates clinical information for a more accurate prediction of the risk of rupture. Specifically, we first extracted the provided aneurysm regions from the CTA images as 3D patches with the lesions located at their centers. Then, we employed an encoder using a 3D convolutional neural network (CNN) to extract complex latent features automatically. These features were then combined with radiomics features and clinical information. We further applied the LASSO regression method to find optimal features that are highly relevant to the rupture risk information, which is fed into a support vector machine (SVM) for final rupture risk prediction.

RESULTS

The experimental results demonstrate that our classification method can achieve accuracy and AUC scores of 89.78% and 89.09%, respectively, outperforming all the alternative methods.

DISCUSSION

Our study indicates that the incorporation of CNN and radiomics analysis can improve the prediction performance, and the selected optimal feature set can provide essential biomarkers for the determination of rupture risk, which is also of great clinical importance for individualized treatment planning and patient care of IA.

Alcohol flushing syndrome is significantly associated with intracranial aneurysm rupture in the Chinese Han population

Objective

Although alcohol flushing syndrome (AFS) has been associated with various diseases, its association with intracranial aneurysm rupture (IAR) is unclear. We aimed to examine this association in the Chinese Han population.

Methods

We retrospectively reviewed Chinese Han patients with intracranial aneurysms who were evaluated and treated at our institution between January 2020 and December 2021. AFS was determined using a semi-structured telephone interview. Clinical data and aneurysm characteristics were assessed. Univariate and multivariate logistic regression were conducted to determine independent factors associated with aneurysmal rupture.

Results

A total of 1,170 patients with 1,059 unruptured and 236 ruptured aneurysms were included. The incidence of aneurysm rupture was significantly higher in patients without AFS (p &lt; 0.001). Meanwhile, there was a significantly difference between the AFS and non-AFS group in habitual alcohol consumption (10.5 vs. 27.2%, p &lt; 0.001). In the univariate analyses, AFS [odds ratio (OR) 0.49; 95% confidence interval (CI), 0.34–0.72] was significantly associated with IAR. In the multivariate analysis, AFS was an independent predictor of IAR (OR 0.50; 95%, CI, 0.35–0.71). Multivariate analysis revealed that AFS was an independent predictor of IAR in both habitual (OR 0.11; 95% CI, 0.03–0.45) and non-habitual drinkers (OR 0.69; 95% CI, 0.49–0.96).

Conclusion

Alcohol flushing syndrome may be a novel clinical marker to assess the risk of IAR. The association between AFS and IAR exists independently of alcohol consumption. Further single nucleotide polymorphism testing and molecular biology studies are warranted.

Differences Between Ruptured Aneurysms With and Without Blebs: Mechanistic Implications

PURPOSE

Blebs are known risk factors for intracranial aneurysm (IA) rupture. We analyzed differences between IAs that ruptured with blebs and those that ruptured without developing blebs to identify distinguishing characteristics among them and suggest possible mechanistic implications.

METHODS

Using image-based models, 25 hemodynamic and geometric parameters were compared between ruptured IAs with and without blebs (n = 673), stratified by location. Hemodynamic and geometric differences between bifurcation and sidewall aneurysms and for aneurysms at five locations were also analyzed.

RESULTS

Ruptured aneurysms harboring blebs were exposed to higher flow conditions than aneurysms that ruptured without developing blebs, and this was consistent across locations. Bifurcation aneurysms were exposed to higher flow conditions than sidewall aneurysms. They had larger maximum wall shear stress (WSS), more concentrated WSS distribution, and larger numbers of critical points than sidewall aneurysms. Additionally, bifurcation aneurysms were larger, more elongated, and had more distorted shapes than sidewall aneurysms. Aneurysm morphology was associated with aneurysm location (p < 0.01). Flow conditions were different between aneurysm locations.

CONCLUSION

Aneurysms at different locations are likely to develop into varying morphologies and thus be exposed to diverse flow conditions that may predispose them to follow distinct pathways towards rupture with or without bleb development. This could explain the diverse rupture rates and bleb presence in aneurysms at different locations.

Rupture risk prediction of cerebral aneurysms using a novel convolutional neural network-based deep learning model

BACKGROUND

Cerebral aneurysms should be treated before rupture because ruptured aneurysms result in serious disability. Therefore, accurate prediction of rupture risk is important and has been estimated using various hemodynamic factors.

OBJECTIVE

To suggest a new way to predict rupture risk in cerebral aneurysms using a novel deep learning model based on hemodynamic parameters for better decision-making about treatment.

METHODS

A novel convolutional neural network (CNN) model was used for rupture risk prediction retrospectively of 123 aneurysm cases. To include the effect of hemodynamic parameters into the CNN, the hemodynamic parameters were first calculated using computational fluid dynamics and fluid-structure interaction. Then, they were converted into images for training the CNN using a novel approach. In addition, new data augmentation methods were devised to obtain sufficient training data. A total of 53,136 images generated by data augmentation were used to train and test the CNN.

RESULTS

The CNNs trained with wall shear stress (WSS), strain, and combination images had area under the receiver operating characteristics curve values of 0.716, 0.741, and 0.883, respectively. Based on the cut-off values, the CNN trained with WSS (sensitivity: 0.5, specificity: 0.79) or strain (sensitivity: 0.74, specificity: 0.71) images alone was not highly predictive. However, the CNN trained with combination images of WSS and strain showed a sensitivity and specificity of 0.81 and 0.82, respectively.

CONCLUSION

CNN-based deep learning algorithm using hemodynamic factors, including WSS and strain, could be an effective tool for predicting rupture risk in cerebral aneurysms with good predictive accuracy.

Analysis of the wall thickness of intracranial aneurysms: Can computational fluid dynamics detect the translucent areas of saccular intracranial aneurysms and predict the rupture risk preoperatively?

Background and purpose

The translucent area on the surface of intracranial aneurysms (IAs) is associated with rupture risk. In the present study, the Polyflow module of the Ansys software was used to simulate and analyze the thickness of the aneurysm wall to detect whether it was "translucent" and to assess the rupture risk.

Methods

Forty-five patients with 48 IAs who underwent microsurgery were retrospectively reviewed. The medical records, radiographic data, and intraoperative images of the patients were collected. The image data were analyzed using computational fluid dynamics (CFD) simulations to explore the relationship between the simulated thickness of the aneurysm wall, the translucent area, and the rupture point of the real aneurysm's surface to predict the rupture risk and provide a certain reference basis for clinical treatment.

Results

The Polyflow simulation revealed that the location of the minimum extreme point of the simulated aneurysm wall thickness was consistent with the translucent area or rupture point on the surface of the real aneurysm. There was a downward trend in the correlation between the change rate (I_S) in the wall area and volume during aneurysm growth and rupture. Ruptured aneurysms have a greater inhomogeneity coefficient I_δ than the unruptured ones. In the unruptured group, translucent aneurysms also had greater inhomogeneity coefficients I_δ and more significant thickness changes (multiple I_BA) than non-translucent ones.

Conclusions

The Ansys software Polyflow module could detect whether the unruptured aneurysms were translucent and predict the rupture risk and rupture point.

Clinical trial registration

https://clinicaltrials.gov/, Identifier, NCT03133624.

Deep learning-based semantic vessel graph extraction for intracranial aneurysm rupture risk management

PURPOSE

Intracranial aneurysms are vascular deformations in the brain which are complicated to treat. In clinical routines, the risk assessment of intracranial aneurysm rupture is simplified and might be unreliable, especially for patients with multiple aneurysms. Clinical research proposed more advanced analysis of intracranial aneurysm, but requires many complex preprocessing steps. Advanced tools for automatic aneurysm analysis are needed to transfer current research into clinical routine.

METHODS

We propose a pipeline for intracranial aneurysm analysis using deep learning-based mesh segmentation, automatic centerline and outlet detection and automatic generation of a semantic vessel graph. We use the semantic vessel graph for morphological analysis and an automatic rupture state classification.

RESULTS

The deep learning-based mesh segmentation can be successfully applied to aneurysm surface meshes. With the subsequent semantic graph extraction, additional morphological parameters can be extracted that take the whole vascular domain into account. The vessels near ruptured aneurysms had a slightly higher average torsion and curvature compared to vessels near unruptured aneurysms. The 3D surface models can be further employed for rupture state classification which achieves an accuracy of 83.3%.

CONCLUSION

The presented pipeline addresses several aspects of current research and can be used for aneurysm analysis with minimal user effort. The semantic graph representation with automatic separation of the aneurysm from the parent vessel is advantageous for morphological and hemodynamical parameter extraction and has great potential for deep learning-based rupture state classification.

Dexmedetomidine alleviates inflammatory response and oxidative stress injury of vascular smooth muscle cell via α2AR/GSK-3β/MKP-1/NRF2 axis in intracranial aneurysm

Vascular smooth muscle cell (VSMC) phenotypic modulation regulates the initiation and progression of intracranial aneurysm (IA). Dexmedetomidine (DEX) is suggested to play neuroprotective roles in patients with craniocerebral injury. Therefore, we investigated the biological functions of DEX and its mechanisms against IA formation and progression in the current study. The rat primary VSMCs were isolated from Sprague-Dawley rats. IA and superficial temporal artery (STA) tissue samples were obtained from patients with IA. Flow cytometry was conducted to identify the characteristics of isolated VSMCs. Hydrogen peroxide (H₂O₂) was used to mimic IA-like conditions in vitro. Cell viability was detected using CCK-8 assays. Wound healing and Transwell assays were performed to detect cell motility. ROS production was determined by immunofluorescence using DCFH-DA probes. Western blotting and RT-qPCR were carried out to measure gene expression levels. Inflammation responses were determined by measuring inflammatory cytokines. Immunohistochemistry staining was conducted to measure α₂-adrenergic receptor levels in tissue samples. DEX alleviated the H₂O₂-induced cytotoxicity, attenuated the promoting effects of H₂O₂ on cell malignancy, and protected VSMCs against H₂O₂-induced oxidative damage and inflammation response. DEX regulated the GSK-3β/MKP-1/NRF2 pathway via the α2AR. DEX alleviates the inflammatory responses and oxidative damage of VSMCs by regulating the GSK-3β/MKP-1/NRF2 pathway via the α2AR in IA.

Preventive Approaches in Women's Neurology: Prepartum, Pregnancy, and Postpartum

Women's neurology is the subspecialty within neurology concerned with the distinct healthcare needs of women. In this article, we review current literature and expert management strategies regarding disease-specific neurologic concerns of women, with an emphasis on issues related to contraception, pregnancy, and lactation. Health conditions that we discuss in this article include epilepsy, headache, stroke, multiple sclerosis, and Chiari I malformation. Current findings on neurologic disease in women suggest that many women with neurologic disease can safely manage their disease during pregnancy and have healthy children, though pregnancy planning is important in many conditions to mitigate risks and effective contraceptive management is important when pregnancy prevention is desired.

Risk factors for aneurysm rupture among Kazakhs: findings from a national tertiary

BACKGROUND

Rupture of intracranial aneurysms (RIA) leads to subarachnoid hemorrhage (SAH) with severe consequences. Although risks for RIA are established, the results vary between ethnic groups and were never studied in Kazakhstan. This study aimed to establish the risk factors of RIA in the Kazakh population.  METHODS: Retrospective analysis of 762 patients with single IAs, who attended the neurosurgical center from 2008 until 2018, was conducted. Demographic characteristics, such as age, sex, smoking status, and hypertension were considered. Descriptive and bivariate analyses were performed. A multivariable logistic regression model was built to identify factors correlated with RIA.

RESULTS

The mean age of participants was 48.49 ± 0.44 years old. The majority (68.37%) of IAs have ruptured. Of the ruptured aneurysms, 43.76% were < 6 mm, and 38.39% were located on the anterior cerebral and anterior communicating arteries (ACA). Logistic regression model indicates younger age group (16-40 years), smoking, having stage 3 hypertension, smaller IA size and its location on ACA increase the odds of rupture.

CONCLUSIONS

This study has revealed that younger, smoking patients with stage 3 arterial hypertension are at higher risk for RIA. Small aneurysms (< 6 mm) and location on ACA had increased odds of rupture, while larger aneurysms on internal carotid arteries had lower odds.

Stability of unruptured intracranial aneurysms in the anterior circulation: nomogram models for risk assessment

OBJECTIVE

The probable stability of the lesion is critical in guiding treatment decisions in unruptured intracranial aneurysms (IAs). The authors aimed to develop multidimensional predictive models for the stability of unruptured IAs.

METHODS

Patients with unruptured IAs in the anterior circulation were prospectively enrolled and regularly followed up. Clinical data were collected, IA morphological features were assessed, and adjacent hemodynamic features were quantified with patient-specific computational fluid dynamics modeling. Based on multivariate logistic regression analyses, nomograms incorporating these factors were developed in a primary cohort (patients enrolled between January 2017 and February 2018) to predict aneurysm rupture or growth within 2 years. The predictive accuracies of the nomograms were compared with the population, hypertension, age, size, earlier rupture, and site (PHASES) and earlier subarachnoid hemorrhage, location, age, population, size, and shape (ELAPSS) scores and validated in the validation cohort (patients enrolled between March and October 2018).

RESULTS

Among 231 patients with 272 unruptured IAs in the primary cohort, hypertension, aneurysm location, irregular shape, size ratio, normalized wall shear stress average, and relative resident time were independently related to the 2-year stability of unruptured IAs. The nomogram including clinical, morphological, and hemodynamic features (C+M+H nomogram) had the highest predictive accuracy (c-statistic 0.94), followed by the nomogram including clinical and morphological features (C+M nomogram; c-statistic 0.89), PHASES score (c-statistic 0.68), and ELAPSS score (c-statistic 0.58). Similarly, the C+M+H nomogram had the highest predictive accuracy (c-statistic 0.94) in the validation cohort (85 patients with 97 unruptured IAs).

CONCLUSIONS

Hemodynamics have predictive values for 2-year stability of unruptured IAs treated conservatively. Multidimensional nomograms have significantly higher predictive accuracies than conventional risk prediction scores.

Evaluating the impact of personalized rehabilitation nursing management in the perioperative nursing of patients with intracranial aneurysm: A protocol for systematic review and meta-analysis

BACKGROUND

Patients who suffer from aneurysmal subarachnoid hemorrhage continue to die at a high rate, despite large geographical and risk factor-related variability in death rates. Hemorrhagic stroke has a greater death rate than ischemic stroke, which is often permanent, although patients who survive have less impairment than those who do not. Because of this, nurses must offer appropriate nursing care throughout the perioperative period for patients suffering from this prevalent neurological condition. Patients with intracranial aneurysms (IA) will be the subjects of this research, which will be carried out to thoroughly investigate the effect of tailored rehabilitative nurse treatment throughout the perioperative period.

METHODS

The influence of customized rehabilitative nurse management in the perioperative nursing of patients with IA has been studied in both randomized controlled trials and observation studies, according to the authors. From the time of the database's creation until February 2022, information about studies will be gathered from 3 Chinese databases (Wanfang, China National Knowledge Infrastructure, and Chinese BioMedical database) and 4 English databases (PubMed, EMBASE, Cochrane Library, and CINAHL database). After the data extraction and risk of bias evaluation of the included studies are completed, the data synthesis will be carried out using the RevMan 5.3 program. Egger's regression test and funnel plots will be used to determine whether or not there is any publication bias. The I2 statistics will be used to determine the degree of heterogeneity. A sensitivity analysis will be conducted to determine the robustness as well as stability of our results and conclusions.

RESULTS

This research is anticipated to offer high-quality evidence of tailored rehabilitative nurse treatment in the perioperative nursing of patients with IA.

CONCLUSION

Results of this research will synthesize the current data to determine whether or not tailored rehabilitation nursing treatment may enhance the surgical recovery of patients with IA.

Homocysteine Levels Are Associated With the Rupture of Intracranial Aneurysms

Background

Homocysteine (Hcy) levels may be associated with the development of intracranial aneurysms (IAs). However, whether it increases the risk of rupture of IAs is unknown. This study aimed to determine the association between homocysteine levels and IA rupture.

Methods

We retrospectively reviewed patients with IAs and subarachnoid hemorrhage (SAH) at our hospital between January 2019 and May 2021. Clinical data, including Hcy levels and IA images, were assessed. The association between Hcy level and IA rupture was investigated using multivariate logistic regression analyses in patients with IAs and SAH.

Results

A total of 589 patients were included. 546 patients with IAs, including 331 UIA (Unruptured IA) and 215 RIA (Ruptured IA). The average age was 57.43 ± 10.86 years old, and 67.03% were women. Among them, all 215 RIAs lead to SAH. In addition, we also enrolled 43 non-aneurysmal subarachnoid hemorrhage (Na-SAH) patients. The average age was 54.12 ± 10.55 years old, and 53.48% were female. After adjusting for confounders in the multivariate model, Hcy levels were correlated with the rupture of IA (odds ratio [OR] 1.069; 95% confidence interval [CI] 1.025–1.114, p = 0.002) and a-SAH (OR 1.083; 95% CI 1.002–1.170, p = 0.046).

Conclusion

Hcy levels were associated with IA rupture. These findings provide novel insights into IAs rupture, and future studies are needed to confirm this relationship.

“Atypical” Mild Clinical Presentation in Elderly Patients With Ruptured Intracranial Aneurysm: Causes and Clinical Characteristics

Objective

Thunderclap-like severe headache or consciousness disturbance is the common “typical” clinical presentation after aneurysmal subarachnoid hemorrhage (aSAH); however, a slowly developing “atypical” clinical pattern, with mild headache, vomiting, or dizziness, is frequently noted in elderly patients. The aim of this study was to evaluate the clinical characteristics of this “atypical” subgroup, as well as related factors associated with the presence of these mild symptoms.

Methods

The data of 176 elderly patients (≥70 years old) with ruptured intracranial aneurysms (IAs) treated at our center from January 2016 to January 2020 were retrospectively collected and analyzed. The patients were divided into “typical” and “atypical” groups based on their initial and development of clinical symptoms after the diagnosis of aSAH. Intergroup differences were analyzed, and factors related to the presence of these two clinical patterns were explored through multiple logistic regression analyses.

Results

Despite significant admission delay (P &lt; 0.001) caused by mild initial symptoms with slow development, patients in the “atypical” group achieved better clinical prognosis, as indicated by a significantly higher favourable outcome ratio and lower death rate upon discharge and at different time points during the 1-year follow-up, than the “typical” group (P &lt; 0.05). Multiple logistic regression analysis revealed that modified Fisher grade III-IV (OR = 11.182, P = 0.003), brain atrophy (OR = 10.010, P = 0.001), a larger lesion diameter (OR = 1.287, P &lt; 0.001) and current smoking (OR = 5.728, P &lt; 0.001) were independently associated with the presence of “typical” symptoms. Aneurysms with wide necks (OR = 0.013, P &lt; 0.001) were independently associated with the presence of “atypical” symptoms.

Conclusions

“Atypical” presentations, with mild clinical symptoms and slow development, were commonly recorded in elderly patients after the onset of aSAH. Despite the prolonged admission delay, these “atypical” patients achieved better clinical outcomes than those with “typical” symptoms. Modified Fisher grade (III-IV), current smoking, brain atrophy and larger lesion diameter were factors predictive of “typical” symptoms, while aneurysms with wide necks were independently associated with “atypical” symptoms.

Impinging Flow Induces Expression of Monocyte Chemoattractant Protein-1 in Endothelial Cells Through Activation of the c-Jun N-terminal Kinase/c-Jun/p38/c-Fos Pathway

OBJECTIVE

Monocyte chemoattractant protein-1 (MCP-1) is an important regulator of the formation and development of intracranial aneurysms. This study explored the molecular mechanisms underlying the induction of MCP-1 and related inflammatory factors in human umbilical vein endothelial cells (HUVECs) under hemodynamic conditions.

METHODS

A modified T chamber was used to simulate fluid flow at the bifurcation of the artery and wall shear stress on HUVECs in vitro. Changes in HUVECs were analyzed in response to impinging flow. And HUVECs without impinging flow were used as the control group. Protein expression levels of extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), p38, activator protein-1, and MCP-1 were detected by Western blot, and the messenger RNA expression levels of MCP-1, interleukin (IL)-1β, and IL-6 were determined by quantitative reverse transcription polymerase chain reaction.

RESULTS

Under impinging flow, the phosphorylation levels of ERK, JNK, and p38, as well as the protein levels of MCP-1, c-Jun, and c-Fos, increased. The messenger RNA expression of MCP-1, IL-1β, and IL-6 also increased in HUVECs. Pretreatment of the HUVECs with inhibitors of JNK and p38 significantly attenuated the increased expression of MCP-1, IL-1β, and IL-6, while ERK inhibitors had no obvious effect.

CONCLUSIONS

Under impinging flow, MCP-1 and inflammatory factors are regulated through the JNK/c-Jun/p38/c-Fos pathway and participate in EC inflammation.

Geometric and Morphologic Features of Ruptured Intracranial Aneurysms Associated with Methamphetamine Use

BACKGROUND

Methamphetamine (MA) use is associated with poor outcomes after aneurysmal subarachnoid hemorrhage (aSAH). MA exerts both hemodynamic and inflammatory effects, but whether these manifest with altered intracranial aneurysm (IA) remodeling is unknown. The objective of this study was to compare IA geometric and morphologic features in patients with and without MA detected on urine toxicology (Utox) at presentation.

METHODS

160 consecutive patients with SAH and Utox at time of admission were retrospectively reviewed. Geometric-morphologic IA characteristics were assessed by blinded neuroradiologists. Studied features were maximum sac diameter, location, size, ellipsoid volume, aspect ratio, size ratio, volume: neck ratio, dome: neck ratio, bottleneck factor, morphology (saccular, fusiform/dissecting, blister, mycotic), and presence of bleb, vasculopathy, or additional unruptured IA.

RESULTS

Of 139/160 patients with aSAH, 23/139 (16.5%) were Utox MA+ There was no difference in aneurysm subtype frequency, presence of bleb, vasculopathy, or presence an additional (unruptured) aneurysm with trend toward posterior circulation location and higher Hunt and Hess grade (p = 0.09 for both) in MA+ group. Maximum IA sac diameter, ellipsoid volume, dome-neck ratio, and size ratio were similar between groups. Only the aspect ratio (AR) differed between groups (MA+ = 2.20 vs. MA- = 1.74, p = 0.02). The AR remained a significant predictor of Utox MA+ in a multiple logistic regression analysis (odds ratio 1.87, 95% confidence interval 1.06-3.39).

CONCLUSIONS

Active use of methamphetamine is independently associated with larger AR in patients with ruptured IA. This may indicate hazardous remodeling due to hemodynamic and/or inflammatory changes.

Risk factors for intracranial aneurysm rupture in pediatric patients

BACKGROUND

Intracranial aneurysm (IA) rupture in pediatric patients is a rare but fatal condition. Although risk factors for aneurysm rupture in adults have been well documented, they remain unknown in pediatric patients.

METHODS

Data for 94 pediatric patients with IAs were retrospectively analyzed. The patients were divided into ruptured and unruptured groups. Risk factors for aneurysm rupture were analyzed through univariable and multiple logistic regression analyses. Typical patients with risk factors were described.

RESULTS

Univariable analyses showed that the unruptured group had significantly higher percentages of giant aneurysms (43.2% vs 12.3%, P = 0.002), wide-neck aneurysms (67.6% vs 29.8%, P = 0.001), and aneurysms located in the internal carotid artery (40.5% vs 3.5%, P < 0.001), while the ruptured group had significantly higher percentages of patients younger than 5 years old (28.1% vs 5.4%, P = 0.013) and aneurysms located in the anterior cerebral artery (24.6% vs 5.4%, P = 0.032), posterior cerebral artery (14.0% vs 0%, P = 0.045), and distal arterial region (DAR) (46.8% vs 27.0%, P < 0.001). Multiple logistic regression analysis confirmed that age 0-5 years (OR = 6.844, P = 0.042) and IAs located in the DAR (OR = 4.162, P = 0.029) were independently related to an increased risk of rupture. Wide-necked aneurysms (OR = 0.235, P = 0.047) were independently associated with a lower risk of rupture.

CONCLUSIONS

Among pediatric patients, age younger than 5 years and lesions located in the DAR are independent risk factors for IA rupture, while an IA with a wide neck acts as a protective factor.

Detection and analysis of cerebral aneurysms based on X-ray rotational angiography - the CADA 2020 challenge

The Cerebral Aneurysm Detection and Analysis (CADA) challenge was organized to support the development and benchmarking of algorithms for detecting, analyzing, and risk assessment of cerebral aneurysms in X-ray rotational angiography (3DRA) images. 109 anonymized 3DRA datasets were provided for training, and 22 additional datasets were used to test the algorithmic solutions. Cerebral aneurysm detection was assessed using the F2 score based on recall and precision, and the fit of the delivered bounding box was assessed using the distance to the aneurysm. The segmentation quality was measured using the Jaccard index and a combination of different surface distance measures. Systematic errors were analyzed using volume correlation and bias. Rupture risk assessment was evaluated using the F2 score. 158 participants from 22 countries registered for the CADA challenge. The U-Net-based detection solutions presented by the community show similar accuracy compared to experts (F2 score 0.92), with a small number of missed aneurysms with diameters smaller than 3.5 mm. In addition, the delineation of these structures, based on U-Net variations, is excellent, with a Jaccard score of 0.92. The rupture risk estimation methods achieved an F2 score of 0.71. The performance of the detection and segmentation solutions is equivalent to that of human experts. The best results are obtained in rupture risk estimation by combining different image-based, morphological, and computational fluid dynamic parameters using machine learning methods. Furthermore, we evaluated the best methods pipeline, from detecting and delineating the vessel dilations to estimating the risk of rupture. The chain of these methods achieves an F2-score of 0.70, which is comparable to applying the risk prediction to the ground-truth delineation (0.71).

Quantitative angiography prognosis of intracranial aneurysm treatment failure using parametric imaging and distal vessel analysis

PURPOSE

Data-driven methods based on x-ray angiographic parametric imaging (API) have been successfully used to provide prognosis for intracranial aneurysm (IA) treatment outcome. Previous studies have mainly focused on embolization devices where the flow pattern visualization is in the aneurysm dome; however, this is not possible in IAs treated with endovascular coils due to high x-ray attenuation of the devices. To circumvent this challenge, we propose to investigate whether flow changes in the parent artery distal to the coil-embolized IAs could be used to achieve the same accuracy of surgical outcome prognosis.

METHODS

Eighty digital subtraction angiography sequences were acquired from patients with IA embolized with coils. Five API parameters were recorded from a region of interest (ROI) placed distal to the IA neck in the main artery. Average API values were recorded and pre-treatment values. A supervised machine learning algorithm was trained to provide a six-month post procedure binary outcome (occluded/not occluded). Receiver operating characteristic (ROC) analysis was used to assess the accuracy of the method.

RESULTS

Use of API parameters with data driven methods yielded an area under the ROC curve of 0.77 ±0.11 and accuracy of 78.6%. Single parameter-based analysis yielded accuracies which were suboptimal for clinical acceptance.

CONCLUSIONS

We determined that data-driven method based on API analysis of flow in the parent artery of IA treated with coils provide clinically acceptable accuracy for the prognosis of six months occlusion outcome.

Vessel Wall Magnetic Resonance Imaging in Cerebrovascular Diseases

Cerebrovascular diseases are a leading cause of disability and death worldwide. The definition of stroke etiology is mandatory to predict outcome and guide therapeutic decisions. The diagnosis of pathological processes involving intracranial arteries is especially challenging, and the visualization of intracranial arteries’ vessel walls is not possible with routine imaging techniques. Vessel wall magnetic resonance imaging (VW-MRI) uses high-resolution, multiparametric MRI sequences to directly visualize intracranial arteries walls and their pathological alterations, allowing a better characterization of their pathology. VW-MRI demonstrated a wide range of clinical applications in acute cerebrovascular disease. Above all, it can be of great utility in the differential diagnosis of atherosclerotic and non-atherosclerotic intracranial vasculopathies. Additionally, it can be useful in the risk stratification of intracranial atherosclerotic lesions and to assess the risk of rupture of intracranial aneurysms. Recent advances in MRI technology made it more available, but larger studies are still needed to maximize its use in daily clinical practice.