Small Aneurysms with Low PHASES Scores Account for Most Subarachnoid Hemorrhage Cases

Nomogram-based geometric and hemodynamic parameters for predicting the growth of small untreated intracranial aneurysms

Previous studies have shown that the growth status of intracranial aneurysms (IAs) predisposes to rupture. This study aimed to construct a nomogram for predicting the growth of small IAs based on geometric and hemodynamic parameters. We retrospectively collected the baseline and follow-up angiographic images (CTA/ MRA) of 96 small untreated saccular IAs, created patient-specific vascular models and performed computational fluid dynamics (CFD) simulations. Geometric and hemodynamic parameters were calculated. A stepwise Cox proportional hazards regression analysis was employed to construct a nomogram. IAs were stratified into low-, intermediate-, and high-risk groups based on the total points from the nomogram. Receiver operating characteristic (ROC) analysis, calibration curves, decision curve analysis (DCA) and Kaplan-Meier curves were evaluated for internal validation. In total, 30 untreated saccular IAs were grown (31.3%; 95%CI 21.8%-40.7%). The PHASES, ELAPSS, and UIATS performed poorly in distinguishing growth status. Hypertension (hazard ratio [HR] 4.26, 95%CI 1.61-11.28; P = 0.004), nonsphericity index (95%CI 4.10-25.26; P = 0.003), max relative residence time (HR 1.01, 95%CI 1.00-1.01; P = 0.032) were independently related to the growth status. A nomogram was constructed with the above predictors and achieved a satisfactory prediction in the validation cohort. The log-rank test showed significant discrimination among the Kaplan-Meier curves of different risk groups in the training and validation cohorts. A nomogram consisting of geometric and hemodynamic parameters presented an accurate prediction for the growth status of small IAs and achieved risk stratification. It showed higher predictive efficacy than the assessment tools.

Optimal PHASES Scoring for Risk Stratification of Surgically Treated Unruptured Aneurysms

OBJECTIVE

The PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, Site) score was developed to facilitate risk stratification for management of unruptured intracranial aneurysms (UIAs). This study aimed to identify the optimal PHASES score cutoff for predicting neurologic outcomes in patients with surgically treated aneurysms.

METHODS

All patients who underwent microneurosurgical treatment for UIA at a large quaternary center from January 1, 2014, to December 31, 2020, were retrospectively reviewed. Inclusion criteria included a modified Rankin Scale (mRS) score of ≤2 at admission. The primary outcome was 1-year mRS score, with a "poor" neurologic outcome defined as an mRS score >2.

RESULTS

In total, 375 patients were included in the analysis. The mean (SD) PHASES score for the entire study population was 4.47 (2.67). Of 375 patients, 116 (31%) had a PHASES score ≥6, which was found to maximize prediction of poor neurologic outcome. Patients with PHASES scores ≥6 had significantly higher rates of poor neurologic outcome than patients with PHASES scores <6 at discharge (58 [50%] vs. 90 [35%], P = 0.005) and follow-up (20 [17%] vs. 18 [6.9%], P = 0.002). After adjusting for age, Charlson Comorbidity Index score, nonsaccular aneurysm, and aneurysm size, PHASES score ≥6 remained a significant predictor of poor neurologic outcome at follow-up (odds ratio, 2.75; 95% confidence interval, 1.42-5.36, P = 0.003).

CONCLUSIONS

In this retrospective analysis, a PHASES score ≥6 was associated with significantly greater proportions of poor outcome, suggesting that awareness of this threshold in PHASES scoring could be useful in risk stratification and UIA management.

Nomograms for assessing the rupture risk of anterior choroid artery aneurysms based on clinical, morphological, and hemodynamic features

Background and purpose

A notable prevalence of subarachnoid hemorrhage is evident among patients with anterior choroidal artery aneurysms in clinical practice. To evaluate the risk of rupture in unruptured anterior choroidal artery aneurysms, we conducted a comprehensive analysis of risk factors and subsequently developed two nomograms.

Methods

A total of 120 cases of anterior choroidal artery aneurysms (66 unruptured and 54 ruptured) from 4 medical institutions were assessed utilizing computational fluid dynamics (CFD) and digital subtraction angiography (DSA). The training set, consisting of 98 aneurysms from 3 hospitals, was established, with an additional 22 cases from the fourth hospital forming the external validation set. Statistical differences between the two data sets were thoroughly compared. The significance of 9 clinical baseline characteristics, 11 aneurysm morphology parameters, and 4 hemodynamic parameters concerning aneurysm rupture was evaluated within the training set. Candidate selection for constructing the nomogram models involved regression analysis and variance inflation factors. Discrimination, calibration, and clinical utility of the models in both training and validation sets were assessed using area under curves (AUC), calibration plots, and decision curve analysis (DCA). The DeLong test, net reclassification index (NRI), and integrated discrimination improvement (IDI) were employed to compare the effectiveness of classification across models.

Results

Two nomogram models were ultimately constructed: model 1, incorporating clinical, morphological, and hemodynamic parameters (C + M + H), and model 2, relying primarily on clinical and morphological parameters (C + M). Multivariate analysis identified smoking, size ratio (SR), normalized wall shear stress (NWSS), and average oscillatory shear index (OSIave) as optimal candidates for model development. In the training set, model 1 (C + M + H) achieved an AUC of 0.795 (95% CI: 0.706 ~ 0.884), demonstrating a sensitivity of 95.6% and a specificity of 54.7%. Model 2 (C + M) had an AUC of 0.706 (95% CI: 0.604 ~ 0.808), with corresponding sensitivity and specificity of 82.4 and 50.3%, respectively. Similarly, AUCs for models 1 and 2 in the external validation set were calculated to be 0.709 and 0.674, respectively. Calibration plots illustrated a consistent correlation between model evaluations and real-world observations in both sets. DCA demonstrated that the model incorporating hemodynamic parameters offered higher clinical benefits. In the training set, NRI (0.224, p = 0.007), IDI (0.585, p = 0.002), and DeLong test (change = 0.089, p = 0.008) were all significant. In the external validation set, NRI, IDI, and DeLong test statistics were 0.624 (p = 0.063), 0.572 (p = 0.044), and 0.035 (p = 0.047), respectively.

Conclusion

Multidimensional nomograms have the potential to enhance risk assessment and patient-specific treatment of anterior choroidal artery aneurysms. Validated by an external cohort, the model incorporating clinical, morphological, and hemodynamic features may provide improved classification of rupture states.

Three-Dimensional Morphological Change of Intracranial Aneurysms Before and Around Rupture

BACKGROUND AND OBJECTIVES

Patients with an unruptured intracranial aneurysm often undergo periodic imaging to detect potential aneurysm growth, which is associated with an increased rupture risk. Because prediction of rupture based on growth is moderate, morphological changes have gained interest as a risk factor for rupture. We studied 3-dimensional-quantified morphological changes over time during radiological monitoring before rupture and around rupture.

METHODS

In this retrospective observational study, we identified aneurysms that ruptured during follow-up, with imaging available for at least 2 time points before rupture and one after rupture. For each time point, we obtained 8 morphological parameters: 2-dimensional size, volume, surface area, compactness 1 and 2, sphericity, elongation, and flatness. Morphological changes before rupture and around rupture were log-transformed, scaled, and analyzed with linear mixed-effects models.

RESULTS

We included 16 aneurysms in 16 patients who were imaged between 2004 and 2021. In the time period before rupture (median follow-up duration 1200 days, IQR 736-1340), 3 size-related morphological parameters increased: 2-dimensional size (estimated mean change 0.44, 95% CI 0.24-0.65), volume (estimated mean change 0.34, 95% CI 0.12-0.56), and surface area (0.33, 95% CI 0.11-0.54). In the period around rupture (median follow-up duration 407 days, IQR 148-719), these parameters further increased. In addition, 5 morphological parameters (compactness 1 and 2, sphericity, elongation, and flatness) decreased around rupture but not before rupture.

CONCLUSION

Change in aneurysm volume and surface area may be novel risk factors for rupture. Because most morphological parameters changed around but not before rupture, morphological changes during these 2 periods should be regarded as different processes. This implies that postrupture morphology should not be used as a surrogate for prerupture morphology in rupture prediction models.

Clinical and Morphological Factors for Ruptured Anterior Communicating Artery Aneurysms

Introduction

The anterior communicating artery (ACoA) aneurysm, the most frequent cerebral aneurysm to rupture, carries a significant clinical burden, yet the factors influencing its rupture are limited in Indonesia. This study aims to determine the clinical and morphological features associated with ruptured ACoA compared to non-AcoA aneurysms among Indonesians.

Patients and Methods

We retrospectively reviewed our center's aneurysm patient registry from January 2019 to December 2022, and compared the clinical and morphological features between ruptured ACoA aneurysms and ruptured aneurysms elsewhere with univariate and multivariate analyses.

Results

Of the 292 patients with 325 ruptured aneurysms, 89 were from ACoA. The mean age of patients was 54.99 years, with female preponderance in the non-ACoA group (non-ACoA: 73.31%, ACoA: 46.07%). On univariate analysis, ages ≥60 [ages 60-69: OR = 0.311 (0.111-0.869), p=0.026; ages ≥70: OR = 0.215 (0.056-0.819), p=0.024], female gender [OR = 0.311 (0.182-0.533), p<0.001], and smoking [OR=2.069 (1.036-4.057), p=0.022] exhibited significant association with ruptured ACoA aneurysm. On multivariate analysis, only the female gender was independently associated with ruptured ACoA aneurysm (aOR 0.355 [0.436-1.961], p=0.001).

Conclusion

In our study, ruptured ACoA aneurysm was inversely associated with advanced age, female gender, presence of daughter aneurysm, and directly associated with smoking. After multivariate adjustment, the female gender showed an independent association with ruptured ACoA aneurysm.

Qualitative and quantitative wall enhancement associated with unstable intracranial aneurysms: a meta-analysis

Background

Unstable intracranial aneurysms (UIAs) are more likely to rupture and cause serious consequences. Evaluating the stability of unruptured aneurysms facilitates clinical management stratification.

Purpose

To compare and evaluate the predictive performance of qualitative and quantitative wall enhancement (aneurysmal wall enhancement [AWE], circumferential aneurysmal wall enhancement [CAWE], wall enhancement ratio [WER]) on high-resolution magnetic resonance imaging (MRI) of the vessel wall to predict the presence of UIA.

Material and Methods

Original articles describing the depiction of aneurysmal wall enhancement on 3.0-T or 1.5-T high-resolution vessel wall imaging were retrieved from the Web of Science, Medline/PubMed, the Cochrane Library, and EMBASE databases up to 15 February 2022. The combined sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated, and meta-regression analysis was performed.

Results

In total, 12 original articles involving 1619 intracranial aneurysms (IAs) were included. The combined sensitivity and specificity of AWE, CAWE, and WER were 91% and 67%, 59% and 83%, and 86% and 75%, respectively, in the diagnosis of UIA. The summary AUC values of these items were, in order from high to low, 0.88 (WER), 0.84 (AWE), and 0.77 (CAWE), and the differences among them were significant ( z = 2.976, P = 0.003 and z = 2.950, P = 0.003). The meta-regression analysis identified average size and 2D/3D magnetic imaging technology as possible sources of heterogeneity.

Conclusion

Qualitative and quantitative wall enhancement showed moderate accuracy in predicting UIA, and WER had the highest accuracy among them in this meta-analysis. Two covariates were found to explain the heterogeneity.

SMART Registry: Safety and Performance of the Penumbra SMART COIL System for Patients With Intracranial Aneurysms 4 mm and Smaller

BACKGROUND

The Penumbra SMART COIL System includes a novel generation of embolic coils composed of complex and WAVE shape properties with varying levels of softness.

OBJECTIVE

To assess safety and efficacy of the SMART COIL System through a 1-year follow-up in patients with small intracranial aneurysms.

METHODS

This subset analysis of the SMART Registry, a prospective, multicenter study, includes patients with small intracranial aneurysms (≤4 mm) treated with the SMART COIL System. Registry end points include retreatment rates through 1 year, procedural device-related serious adverse events, and adequate occlusion postprocedure.

RESULTS

Of 905 enrolled patients with aneurysms, 172 (19.0%) had small (≤4 mm) aneurysms (75.6% female; mean age 57.2 ± 13.4 years). 30.8% (53/172) of small aneurysms were ruptured, of which 50.9% (27/53) had Hunt and Hess ≥3. 79.5% (132/166) were wide-necked. Stent-assisted coiling and balloon-assisted coiling were performed in 37.2% (64/172) and 22.1% (38/172) of patients, respectively. The mean packing density for very small aneurysms was 44.9 (SD 25.23). Raymond Class I and Class II were achieved in 89.5% (154/172) postprocedure and 97.2% (137/141) at 1 year. The retreatment rate through 1 year was 5.6% (8/142), and the recanalization rate was 7.1% (10/141). The periprocedural device-related serious adverse event rate was 2.9% (5/172). Intraprocedural aneurysm rupture occurred in 0.8% of patients.

CONCLUSION

This analysis suggests that the SMART COIL System is safe and efficacious in small aneurysms with satisfactory occlusion rates and low rates of rupture or rerupture. At 1 year, patients had low retreatment rates and good clinical outcomes.

The majority of ruptured aneurysms are small with low rupture risk scores

BACKGROUND

Understanding the rupture risk of unruptured intracranial aneurysms has important clinical implications given the morbidity and mortality associated with subarachnoid hemorrhage (SAH). The ISUIA, UCAS, and PHASES studies provide rupture risk calculations.

OBJECTIVE

We apply the risk calculations to a series ruptured intracranial aneurysms to assess the rupture risk for each aneurysm (had they been discovered in the unruptured state).

METHODS

This is a retrospective study of 246 patients with SAH from a ruptured saccular aneurysm. The ISUIA, UCAS, and PHASES calculators were applied to each patient/aneurysm to demonstrate a theoretical annual risk of rupture dichotomized by aneurysm location.

RESULTS

The average diameter of the aneurysms was 5.5 ± 3.1 mm. Three quarters (75%) of the aneurysms measured <7 mm and 48.8% were <5 mm. The anterior communicating artery (Acomm) was the most common location of rupture (24.7%). Posterior communicating artery aneurysms (Pcomm) were the third most common at 16.2%. The average ISUIA 1-year rupture risk was 0.46 ± 0.008%. The average UCAS 1-year rupture risk was 0.93% ± 0.01. The annualPHASESrupture risk was0.32 ± 0.004%. The highest risk locations were the vertebral artery (up to 10.3% per year) and superior cerebellar artery (up to 2.7% per year). On average, Acomm aneurysms had 1 year risk no higher than 1.1% and Pcomm aneurysms no higher than 1.2% per year.

CONCLUSION

We observed that in a small retrospective series of ruptured aneurysms, the majority were <7 mm and that the theoretical rupture risk of these aneurysms, had they been discovered in the unruptured state, is low (<1% per year). Our study has a number of limitations and these results should be validated in a larger multicenter study.

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.

Predicting the rupture status of small middle cerebral artery aneurysms using random forest modeling

Objective

Small intracranial aneurysms are increasingly being detected; however, a prediction model for their rupture is rare. Random forest modeling was used to predict the rupture status of small middle cerebral artery (MCA) aneurysms with morphological features.

Methods

From January 2009 to June 2020, we retrospectively reviewed patients with small MCA aneurysms (<7 mm). The aneurysms were randomly split into training (70%) and internal validation (30%) cohorts. Additional independent datasets were used for the external validation of 78 small MCA aneurysms from another four hospitals. Aneurysm morphology was determined using computed tomography angiography (CTA). Prediction models were developed using the random forest and multivariate logistic regression.

Results

A total of 426 consecutive patients with 454 small MCA aneurysms (<7 mm) were included. A multivariate logistic regression analysis showed that size ratio (SR), aspect ratio (AR), and daughter dome were associated with aneurysm rupture, whereas aneurysm angle and multiplicity were inversely associated with aneurysm rupture. The areas under the receiver operating characteristic (ROC) curves (AUCs) of random forest models using the five independent risk factors in the training, internal validation, and external validation cohorts were 0.922, 0.889, and 0.92, respectively. The random forest model outperformed the logistic regression model (p = 0.048). A nomogram was developed to assess the rupture of small MCA aneurysms.

Conclusion

Random forest modeling is a good tool for evaluating the rupture status of small MCA aneurysms and may be considered for the management of small aneurysms.

Unruptured cerebral aneurysm risk stratification: Background, current research, and future directions in aneurysm assessment

Background:

The optimal management of unruptured cerebral aneurysms is widely debated in the medical field. Rapid technology advances, evolving understanding of underlying pathophysiology, and shifting practice patterns have made the cerebrovascular field particularly dynamic in recent years. Despite progress, there remains a dearth of large randomized studies to help guide the management of these controversial patients.

Methods:

We review the existing literature on the natural history of unruptured cerebral aneurysms and highlight ongoing research aimed at improving our ability to stratify risk in these patients.

Results:

Landmark natural history studies demonstrated the significance of size, location, and other risk factors for aneurysm rupture, but prior studies have significant limitations. We have begun to understand the underlying pathophysiology behind aneurysm formation and rupture and are now applying new tools such as flow dynamics simulations and machine learning to individualize rupture risk stratification.

Conclusion:

Prior studies have identified several key risk factors for aneurysmal rupture, but have limitations. New technology and research methods have enabled us to better understanding individual rupture risk for patients with unruptured cerebral aneurysms.

Thin Slice Unenhanced Brain CT Can Detect Aneurysms Larger than 7 mm

Purpose:

To evaluate the detection rate of intracranial aneurysms on reconstructed thin slice non enhanced CT (NECT) scans.

Methods:

NECT scans from 34 patients with 35 aneurysms and 35 individuals without aneurysms were collected. Thin slice maximum intensity projections of the NECT scans were reconstructed. One observer evaluated the native images twice with a time interval of six month between both passes with respect to the prevalence and location of an aneurysm. The size and location of the aneurysms were evaluated in corresponding CT-Angiography and Time of flight datasets. A logit regression analysis was performed with size and location as dependent variables. 2 × 2 tables were constructed. The sensitivity and false negative rate were calculated for aneurysms with 0–6.9 mm, 7–9.9 mm and 10–20 mm and the under the curve (AUC) was calculated.

Results:

The overall detection rate of the aneurysms was 63% for the first pass and 66% for the second pass in the reconstructed NECT scans. The detection rate of aneurysms is size dependent. The sensitivity to detect aneurysms with a size of 0–6.9 mm was 0.09 and 0.03, for aneurysms with a size of 7–9.9. mm was 0.8 and 0.7 and for aneurysms with a size of 10–20 mm was 0.92 for both passes.

The AUC was 0.77 for the first pass and 0.78 for the second pass.

Conclusions:

NECT scans can be used to detect a significant proportion of intracranial aneurysms larger than 7 mm if properly displayed and reconstructed. These patients should receive further vascular imaging to prevent future aneurysm related subarachnoid hemorrhage.

Endovascular Biopsy of Vertebrobasilar Aneurysm in Patient With Polyarteritis Nodosa

Background and Purpose: The management of unruptured intracranial aneurysms remains controversial. The decisions to treat are heavily informed by estimated risk of bleeding. However, these estimates are imprecise, and better methods for stratifying the risk or tailoring treatment strategy are badly needed. Here, we demonstrate an initial proof-of-principle concept for endovascular biopsy to identify the key molecular pathways and gene expression changes associated with aneurysm formation. We couple this technique with single cell RNA sequencing (scRNAseq) to develop a roadmap of the pathogenic changes of a dolichoectatic vertebrobasilar aneurysm in a patient with polyarteritis nodosa.

Methods: Endovascular biopsy and fluorescence activated cell sorting was used to isolate the viable endothelial cells (ECs) using the established techniques. A single cell RNA sequencing (scRNAseq) was then performed on 24 aneurysmal ECs and 23 patient-matched non-aneurysmal ECs. An integrated panel of bioinformatic tools was applied to determine the differential gene expression, enriched signaling pathways, and cell subpopulations hypothesized to drive disease pathogenesis.

Results: We identify a subset of 7 (29%) aneurysm-specific ECs with a distinct gene expression signature not found in the patient-matched control ECs. A gene set enrichment analysis identified these ECs to have increased the expression of genes regulating the leukocyte-endothelial cell adhesion, major histocompatibility complex (MHC) class I, T cell receptor recycling, tumor necrosis factor alpha (TNFα) response, and interferon gamma signaling. A histopathologic analysis of a different intracranial aneurysm that was later resected yielded a diagnosis of polyarteritis nodosa and positive staining for TNFα.

Conclusions: We demonstrate feasibility of applying scRNAseq to the endovascular biopsy samples and identify a subpopulation of ECs associated with cerebral aneurysm in polyarteritis nodosa. Endovascular biopsy may be a safe method for deriving insight into the disease pathogenesis and tailoring the personalized treatment approaches to intracranial aneurysms.

Machine Learning and Intracranial Aneurysms: From Detection to Outcome Prediction

Machine learning (ML) is a rapidly rising research tool in biomedical sciences whose applications include segmentation, classification, disease detection, and outcome prediction. With respect to traditional statistical methods, ML algorithms have the potential to learn and improve their predictive performance when fed with large data sets without the need of being specifically programmed. In recent years, this technology has been increasingly applied for tackling clinical issues in intracranial aneurysm (IA) research. Several studies attempted to provide reliable models for enhanced aneurysm detection. Convolutional neural networks trained with variable degrees of human interaction on data from diverse imaging modalities showed high sensitivity in aneurysm detection tasks, also outperforming expert image analysis. Algorithms were also shown to differentiate ruptured from unruptured IAs, with however limited clinical relevance. For prediction of rupture and stability assessment, ML was preliminarily shown to achieve better performance compared to conventional statistical methods and existing risk scores. ML-based complication and functional outcome prediction in the event of SAH have been more extensively reported, in contrast with periprocedural outcome investigation in unruptured IA patients. ML has the potential to be a game changer in IA patient management. Currently clinical translation of experimental results is limited.

Intracranial aneurysm wall enhancement as an indicator of instability: a systematic review and meta-analysis

BACKGROUND AND PURPOSE

Aneurysm wall enhancement (AWE) of intracranial aneurysms on magnetic resonance imaging has been described in previous studies as a surrogate marker of instability. With this study, an updated literature overview and summary risk estimates of the association between AWE and different specific outcomes (i.e., rupture, growth or symptomatic presentation) for both cross-sectional and longitudinal studies are provided.

METHODS

The PRISMA guideline was followed and a search was performed of PubMed and Embase to 1 January 2021 for studies that reported on AWE and aneurysm instability. In cross-sectional studies, AWE was compared between patients with stable and unstable aneurysms. In longitudinal studies, AWE of stable aneurysms was assessed at baseline after which patients were followed longitudinally. Risk ratios were calculated for longitudinal studies, prevalence ratios for cross-sectional studies and then the ratios were pooled in a random-effects meta-analysis. Also, the performance of AWE to differentiate between stable and unstable aneurysms was evaluated.

RESULTS

Twelve studies were included with a total of 1761 aneurysms. In cross-sectional studies, AWE was positively associated with rupture (prevalence ratio 11.47, 95% confidence interval [CI] 4.05-32.46) and growth or symptomatic presentation (prevalence ratio 4.62, 95% CI 2.85-7.49). Longitudinal studies demonstrated a positive association between AWE and growth or rupture (risk ratio 8.00, 95% CI 2.14-29.88). Assessment of the performance of AWE showed high sensitivities, mixed specificities, low positive predictive values and high negative predictive values.

CONCLUSIONS

Although AWE is positively associated with aneurysm instability, current evidence mostly supports the use of its absence as a surrogate marker of aneurysm stability.

Growth of unruptured aneurysms: A meta-analysis of natural history and endovascular studies

The growth of unruptured intracranial aneurysms (UIAs) is a strong predictor of rupture. Clinical observations suggest that some UIAs might grow faster after endovascular treatment than untreated UIAs. There are no head-to-head comparisons of incidence rates of UIAs thus far.

METHODS

We searched PubMed, Embase and Google Scholar for relevant articles from the inception of the databases to March 2020. We pooled and compared the incidence rates for the growth of aneurysms from natural history studies and endovascular treatment studies. Generalized linear models were used for confounder adjustment for the prespecified confounders age, size and location.

RESULTS

Twenty-five studies (10 describing growth in natural history and 15 reporting growth after endovascular therapy) considering 6325 aneurysms were included in the meta-analysis. The median size of aneurysms was 3.7 mm in the natural history studies and 6.4 mm in endovascular treatment studies (p = 0.001). The pooled incidence rate (IR) of growth was significantly higher in endovascular treatment studies (IR 52 per 1000 person-years, with a 95% confidence interval (CI) 36-79) compared to natural history studies (IR 28 per 1000 person-years, 95% CI 17 - 46, p-value < 0.01) after adjustment for confounders.

CONCLUSION

Our results suggest that the incidence rate of cerebral aneurysm growth might be higher after endovascular therapy than the incidence rates reported in natural history studies. These results should be viewed in light of the risk of bias of the individual studies and the risk of ecological bias.

PHASES score and treatment scoring with cigarette smoking in the long-term prediction of rupturing of unruptured intracranial aneurysms

OBJECTIVE

Treatment indications in unruptured intracranial aneurysms (UIAs) are challenging because of the lack of prospective natural history studies without treatment selection and the decreasing incidence of aneurysm rupture. The purpose of this study was to test whether the population, hypertension, age, size of aneurysm, earlier aneurysm rupture, site of aneurysm (PHASES) score obtained from an individual-based meta-analysis could predict the long-term rupture risk of UIAs.

METHODS

The series included 142 patients of working age with UIAs diagnosed before 1979, when these were not treated but were followed up until the first rupture, death, or the last contact. PHASES scores were recorded for all patients by using the baseline variables and compared with the new treatment score obtained from a recent cohort, consisting of age, smoking status, and aneurysm size and location.

RESULTS

Of the 142 patients, 34 had an aneurysm rupture during a total follow-up of 3064 person-years. The median time between diagnosis and an aneurysm rupture was 10.6 years. The PHASES score at baseline was higher in those with an aneurysm rupture than in the others (5.3 ± 2.3 vs 4.2 ± 2.2, p = 0.012), and the difference relative to the new treatment score was 5.3 ± 2.4 versus 3.0 ± 2.2 (p < 0.001). The receiver operating characteristic curve of the PHASES score for predicting rupture showed a fair area under the curve (0.674, 95% CI 0.558-0.790) where the optimal cutoff point was obtained at ≥ 6 versus < 6 points for sensitivity (0.500) and specificity (0.811). The area under the curve of the new score was 0.755 (95% CI 0.657-0.853), with the optimal cutoff point at ≥ 5 versus < 5 points for sensitivity (0.607) and specificity (0.789).

CONCLUSIONS

The PHASES and the new scores predicted the long-term aneurysm rupture risk moderately well, with the latter, which also included smoking, being slightly better and easier in clinical practice. The findings suggest that treatment decisions about UIAs in patients of working age can be done with an improved cost-effectiveness.

Morphology-based radiomics signature: a novel determinant to identify multiple intracranial aneurysms rupture

We aimed to develop and validate a morphology-based radiomics signature nomogram for assessing the risk of intracranial aneurysm (IA) rupture. A total of 254 aneurysms in 105 patients with subarachnoid hemorrhage and multiple intracranial aneurysms from three centers were retrospectively reviewed and randomly divided into the derivation and validation cohorts. Radiomics morphological features were automatically extracted from digital subtraction angiography and selected by the least absolute shrinkage and selection operator algorithm to develop a radiomics signature. A radiomics signature-based nomogram was developed by incorporating the signature and traditional morphological features. The performance of calibration, discrimination, and clinical usefulness of the nomogram was assessed. Ten radiomics morphological features were selected to build the radiomics signature model, which showed better discrimination with an area under the curve (AUC) equal to 0.814 and 0.835 in the derivation and validation cohorts compared with 0.747 and 0.666 in the traditional model, which only include traditional morphological features. When radiomics signature and traditional morphological features were combined, the AUC increased to 0.842 and 0.849 in the derivation and validation cohorts, thus showing better performance in assessing aneurysm rupture risk. This novel model could be useful for decision-making and risk stratification for patients with IAs.

Shape related features of intracranial aneurysm are associated with rupture status in a large Chinese cohort

BACKGROUND

To investigate the prevalence of small ruptured saccular intracranial aneurysms (sIA) in a Chinese cohort and to identify factors associated with rupture status of sIAs.

METHODS

Consecutive patients with confirmed sIAs by DSA from January 2015 to July 2019 were included. Demographic and aneurysmal features, including maximal diameter, location, irregularity (lobulated or with blebs), and aspect ratio (AR, defined as height divided by neck width) were recorded and analyzed. Mixed effect logistic regression was used in multivariate analysis.

RESULTS

We analyzed 1514 sIAs in a Chinese cohort of 1216 patients, including 651 ruptured and 863 unruptured sIAs. Median aneurysm size was 5.7 mm for ruptured aneurysms, with 66.1% <7 mm in maximal diameter, and 40.2% measuring <5 mm. The median PHASES score of ruptured sIAs was 5. In multivariate analysis, male sex, hypertension, locations other than the internal carotid artery, irregularity (lobulated or with blebs), and higher AR were independently associated with rupture status (OR for irregularity, 2.88, 95% CI 2.20 to 3.77, p<0.001; OR for AR, 1.12, 95% CI 1.01 to 1.24, p=0.036). However, maximal diameter was not significantly associated with rupture status (p=0.72).

CONCLUSIONS

In this cohort, ruptured sIAs were frequently smaller than 7 mm. Shape related features, such as irregularity and higher AR, were associated with the ruptured status of sIAs, irrespective of diameter. PHASES seems to be inadequate in sIA risk stratification. Shape related parameters may be further investigated in prospective studies.

External Validation of the PHASES Score in Patients with Multiple Intracranial Aneurysms

OBJECTIVES

This study sought to assess whether the Population, Hypertension, Age, Size, Earlier Subarachnoid Hemorrhage, Site (PHASES) score can do risk stratification of patients with multiple aneurysms (MIAs).

MATERIAL AND METHODS

Patients between January 1, 2016 and January 1, 2019 were recruited retrospectively. The PHASES score was applied to assess the theoretical risk of IA rupture. For patients-level analyses, four modes of the application of the score were used: largest IA PHASES score, highest PHASES score, sum PHASES score, and mean PHASES score.

RESULTS

A total of 701 patients with 1673 IAs were included in this study. At aneurysm-level analysis, the average PHASES score was 3.0 ± 3.0 points, with 2.8 ± 3.0 points and 4.1 ± 2.9 points in the unruptured and ruptured groups, respectively (p < 0.001). At the patient-level analysis, for the largest IA PHASES score, the areas under the curves (AUC) was 0.572. The discrimination performance of the largest IA PHASES score decreases as IA number increases, with AUCs were 0.597, 0.518, and 0.450 in the 2 IAs, 3 IAs and, 4 or more IAs subgroups, respectively. For highest PHASES score, sum PHASES score, and mean PHASES score, the AUCs were 0.577, 0.599, and 0.619, respectively.

CONCLUSIONS

In this study, PHASES score only serve as a weak tool in decision-making settings for MIAs patients; as such, more accurate models should be developed for MIAs patients and the cumulative effect of MIA may should be considered.

High-Resolution Vessel Wall Magnetic Resonance Imaging of Small Unruptured Intracranial Aneurysms

Background: We decided to investigate whether aneurysm wall enhancement (AWE) on high-resolution vessel wall magnetic resonance imaging (HR VW-MRI) coexists with the conventional risk factors for aneurysm rupture. Methods: We performed HR VW-MRI in 46 patients with 64 unruptured small intracranial aneurysms. Patient demographics and clinical characteristics were recorded. The PHASES score was calculated for each aneurysm. Results: Of the 64 aneurysms, 15 (23.4%) showed wall enhancement on post-contrast HR VW-MRI. Aneurysms with wall enhancement had significantly larger size (p = 0.001), higher dome-to-neck ratio (p = 0.024), and a more irregular shape (p = 0.003) than aneurysms without wall enhancement. The proportion of aneurysms with wall enhancement was significantly higher in older patients (p = 0.011), and those with a history of prior aneurysmal SAH. The mean PHASES score was significantly higher in aneurysms with wall enhancement (p < 0.000). The multivariate logistic regression analysis revealed that aneurysm irregularity and the PHASES score are independently associated with the presence of AWE. Conclusions: Aneurysm wall enhancement on HR VW-MRI coexists with the conventional risk factors for aneurysm rupture.

Qualitative and Quantitative Wall Enhancement on Magnetic Resonance Imaging Is Associated With Symptoms of Unruptured Intracranial Aneurysms

BACKGROUND AND PURPOSE

Aneurysmal wall enhancement (AWE) on vessel wall magnetic resonance imaging (VW-MRI) has been described as a new imaging biomarker of unstable unruptured intracranial aneurysms (UIAs). Previous studies of symptomatic UIAs are limited due to small sample sizes and lack of AWE quantification. Our study aims to investigate whether qualitative and quantitative assessment of AWE can differentiate symptomatic and asymptomatic UIAs.

METHODS

Consecutive patients with UIAs were prospectively recruited for vessel wall magnetic resonance imaging at 3T from October 2014 to October 2019. UIAs were categorized as symptomatic if presenting with sentinel headache or oculomotor nerve palsy directly related to the aneurysm. Evaluation of wall enhancement included enhancement pattern (0=none, 1=focal, and 2=circumferential) and quantitative wall enhancement index (WEI). Univariate and multivariate analyses were used to identify the parameters associated with symptoms.

RESULTS

Two hundred sixty-seven patients with 341 UIAs (93 symptomatic and 248 asymptomatic) were included in this study. Symptomatic UIAs more frequently showed circumferential AWE than asymptomatic UIAs (66.7% versus 17.3%, P<0.001), as well as higher WEI (median [interquartile range], 1.3 [1.0-1.9] versus 0.3 [0.1-0.9], P<0.001). In multivariate analysis, both AWE pattern and WEI were independent factors associated with symptoms (odds ratio=2.03 across AWE patterns [95% CI, 1.21-3.39], P=0.01; odds ratio=3.32 for WEI [95% CI, 1.51-7.26], P=0.003). The combination of AWE pattern and WEI had an area under the curve of 0.91 to identify symptomatic UIAs, with a sensitivity of 95.7% and a specificity of 73.4%.

CONCLUSIONS

In a large cohort of UIAs with vessel wall magnetic resonance imaging, both AWE pattern and WEI were independently associated with aneurysm-related symptoms. The qualitative and quantitative features of AWE can potentially be used to identify unstable intracranial aneurysms.

From 2D to 4D Phase-Contrast MRI in the Neurovascular System: Will It Be a Quantum Jump or a Fancy Decoration?

Considering the crosstalk between the flow and vessel wall, hemodynamic assessment of the neurovascular system may offer a well-integrated solution for both diagnosis and management by adding prognostic significance to the standard CT/MR angiography. 4D flow MRI or time-resolved 3D velocity-encoded phase-contrast MRI has long been promising for the hemodynamic evaluation of the great vessels, but challenged in clinical studies for assessing intracranial vessels with small diameter due to long scan times and low spatiotemporal resolution. Current accelerated MRI techniques, including parallel imaging with compressed sensing and radial k-space undersampling acquisitions, have decreased scan times dramatically while preserving spatial resolution. 4D flow MRI visualized and measured 3D complex flow of neurovascular diseases such as aneurysm, arteriovenous shunts, and atherosclerotic stenosis using parameters including flow volume, velocity vector, pressure gradients, and wall shear stress. In addition to the noninvasiveness of the phase contrast technique and retrospective flow measurement through the wanted windows of the analysis plane, 4D flow MRI has shown several advantages over Doppler ultrasound or computational fluid dynamics. The evaluation of the flow status and vessel wall can be performed simultaneously in the same imaging modality. This article is an overview of the recent advances in neurovascular 4D flow MRI techniques and their potential clinical applications in neurovascular disease. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.