Comparison of Unruptured Intracranial Aneurysm Treatment Score and PHASES Score in Subarachnoid Hemorrhage Patients With Multiple Intracranial Aneurysms

Sensitivity of the Unruptured Intracranial Aneurysm Treatment Score (UIATS) to detect aneurysms at high-risk of rupture: Retrospective analysis in a cohort of 346 patients with a proven subarachnoid hemorrhage

INTRODUCTION

The aim of this study was to assess the capability of the Unruptured Intracranial Aneurysm Treatment Score (UIATS) to discriminate unruptured intracranial aneurysms (UIAs) at high risk for subarachnoid hemorrhage (aSAH).

MATERIAL AND METHOD

During the period from January 2012 to December 2022, we included all consecutive adult patients admitted to our institution for an aSAH caused by the rupture of a saccular IA. The patient-related, aneurysm-related and treatment-related risk factors considered by UIATS were retrieved from medical records. After UIATS calculation for all ruptured IAs in the cohort, patients were categorized as "true positives (TP)" if UIATS would have (appropriately) oriented the management toward treatment, whereas patients for whom the UIATS would have (inappropriately) recommended observation were categorized as "false negatives (FN)". Patients for whom UIATS was inconclusive were categorized as "undetermined (UND)". Sensitivity of the UIATS (Se UIATS) was calculated by using the following formula: TP/(TP + FN).

RESULTS

A total of 346 patients (253 women, 73%; mean age = 56 ± 1.45 years) were incorporated into the final analysis. There were 140 T P (40%), 79 F N (23%) and 127 UND (37%), leading to a Se UIATS of 63.9% (CI 58.3-69.5). Cumulatively, the UIATS failed to provide an appropriate recommendation in 60% of the entire cohort.

CONCLUSION

By retrospectively applying the UIATS in a cohort of ruptured IAs, our study emphasizes how vulnerable the UIATS can be. Even if the UIATS suggests conservative management, clinicians should inform patients that there is still a small risk of rupture.

Time-of-Flight MRA of Intracranial Aneurysms with Interval Surveillance, Clinical Segmentation and Annotations

Intracranial aneurysms (IAs) are present in 2-6% of the global population and can be catastrophic upon rupture with a mortality rate of 30-50%. IAs are commonly detected through time-of-flight magnetic resonance angiography (TOF-MRA), however, this data is rarely available for research and training purposes. The provision of imaging resources such as TOF-MRA images is imperative to develop new strategies for IA detection, rupture prediction, and surgical training. To support efforts in addressing data availability bottlenecks, we provide an open-access TOF-MRA dataset comprising 63 patients, of which 24 underwent interval surveillance imaging by TOF-MRA. Patient scans were evaluated by a neuroradiologist, providing aneurysm and vessel segmentations, clinical annotations, 3D models, in addition to 3D Slicer software environments containing all this data for each patient. This dataset is the first to provide interval surveillance imaging for supporting the understanding of IA growth and stability. This dataset will support computational and experimental research into IA dynamics and assist surgical and radiology training in IA treatment.

Optimizing Patient Care: A Multicentric Study on the Clinical Impact of Sim&Size™ Simulation Software in Intracranial Aneurysm Treatment With Pipeline Embolization Devices

BACKGROUND

To determine the clinical effects (stent size, and number of stents used) of the Sim&Size™ simulation software on the endovascular treatment of unruptured saccular intracranial aneurysms with Pipeline Embolization Devices (PED).

METHODS

This study is a retrospective analytical multicenter study of patients treated with PED (Flex and Flex with SHIELD) for intracranial aneurysm in FOSCAL clinic and CHU de Montpellier.

RESULTS

The study included 253 patients, of which 75 were treated in Colombia and 178 were treated in France. The majority of patients were women (83.8%), with a median age of 57.48 years, and had large vessel location (88.1%), with most aneurysms located in the ICA paraclinoid segment (56.8%). Patients in the group with Sim&Size™ simulation had shorter stents than those without simulation (15.62 mm versus 17.36 mm, P-value = 0.001). Also, a lower proportion of these patients required more than one stent (1.4% versus 7.3%, P-value = 0.022). There were 7 complications reported in the group that used the Sim&Size™ simulation software, compared to 9 complications in the group that did not use the software.

CONCLUSIONS

Using Sim&Size™ simulation software for endovascular treatment of patients with intracranial aneurysms using PED reduces the stent length and decreasing the number of devices needed per treatment.

Application of zone classification in multiple intracranial aneurysmal subarachnoid hemorrhage treatment strategies

Background

The options of surgical approach and treatment stage are two challenging treatment strategy issues with multiple intracranial aneurysmal subarachnoid hemorrhage (MIA-SAH).

Methods

We retrospectively analyzed data from patients with MIA-SAH who underwent surgery in our center between January 1, 2014 and September 1, 2022. To define "zone classification", the cranial cavity was divided into four zones by the planes of cerebral falx and tentorium cerebelli. Aneurysms isolated to one zone were defined as zone classification I; those crossing two zones were defined as zone classification II; those crossing three zones were defined as zone classification III; and those crossing four zones were defined as zone classification IV. General and aneurysmal-related characteristics of patients with different zone classifications were collected and compared between two surgical approaches. Multivariate logistic regression analysis was used to identify factors independently associated with multistage treatment options.

Results

A total of 226 patients with 523 aneurysms were included. The proportion of patients undergoing endovascular treatment increased with higher zone classification (I: 85.4%; II: 94.0%; III: 100.0%; IV: 100.0%). The proportion of patients receiving one-stage treatment decreased with higher zone classification (I: 60.2%; II: 33.6%; III: 0.0%; IV: 0.0%). Compared with patients undergoing microsurgical clipping, more patients undergoing endovascular treatment had zone classification II-IV (56.9% vs. 31.8%, p = 0.025). Zone classification II-IV (odds ratio [OR] = 3.821, 95% confidence interval [CI]: 2.041-7.154, p < 0.001), endovascular treatment (OR = 8.756, 95% CI: 2.589-29.609, p < 0.001), and size of all unruptured aneurysms <3 mm (OR = 4.531, 95% CI: 2.315-8.871, p < 0.001) were each independently associated with multistage treatment.

Conclusions

Zone classification provides a new idea in MIA-SAH treatment strategies, especially regarding surgical approach and treatment stage options.

Sex differences in patients with and without high-risk factors associated with aneurysmal subarachnoid hemorrhage

BACKGROUND

Controversy remains regarding the appropriate screening for intracranial aneurysms or for the treatment of aneurysmal subarachnoid hemorrhage (aSAH) for patients without known high-risk factors for rupture. This study aimed to assess how sex affects both aSAH presentation and outcomes for aSAH treatment.

METHOD

A retrospective cohort study was conducted of all patients treated at a single institution for an aSAH during a 12-year period (August 1, 2007-July 31, 2019). An analysis of women with and without high-risk factors was performed, including a propensity adjustment for a poor neurologic outcome (modified Rankin Scale [mRS] score > 2) at follow-up.

RESULTS

Data from 1014 patients were analyzed (69% [n = 703] women). Women were significantly older than men (mean ± SD, 56.6 ± 14.1 years vs 53.4 ± 14.2 years, p < 0.001). A significantly lower percentage of women than men had a history of tobacco use (36.6% [n = 257] vs 46% [n = 143], p = 0.005). A significantly higher percentage of women than men had no high-risk factors for aSAH (10% [n = 70] vs 5% [n = 16], p = 0.01). The percentage of women with an mRS score > 2 at the last follow-up was significantly lower among those without high-risk factors (34%, 24/70) versus those with high-risk factors (53%, 334/633) (p = 0.004). Subsequent propensity-adjusted analysis (adjusted for age, Hunt and Hess grade, and Fisher grade) found no statistically significant difference in the odds of a poor outcome for women with or without high-risk factors for aSAH (OR = 0.7, 95% CI = 0.4-1.2, p = 0.18).

CONCLUSIONS

A higher percentage of women versus men with aSAH had no known high-risk factors for rupture, supporting more aggressive screening and management of women with unruptured aneurysms.

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.

Unruptured intracranial aneurysms: Why should we focus on small aneurysms? A comprehensive update of recent findings

Intracranial aneurysms (IAs) are a significant public health concern because they have the potential to cause deva-stating consequences, including death and disability. Despite advances in diagnostic and treatment modalities, the outcomes for patients with aneurysmal subarachnoid haemorrhage (aSAH) remain poor, with high rates of rebleeding, vasospasm, and cerebral ischaemia. IAs are a significant risk factor for aSAH, and it is estimated that up to 3% of the general population have IAs. Recent studies using novel imaging modalities have shown that the prevalence of IAs may be much higher, with 6.6% of adults aged 40-84 years having intradural saccular IAs ≥ 2 mm. The risk of rupture for IAs is difficult to predict, and the decision to treat them invasively is based on a balance between the estimated rupture risk and the procedural risks of the treatment. However, the mortality and morbidity rates among patients treated for IAs can be as high as 5%. There is a need for clear guidelines on the treatment of IAs, and this review aims to provide an update on recent findings in this area. To achieve this goal, the authors identified and summarized recent, high-impact studies on IAs. The review focuses on the diagnostic and treatment options for IAs, as well as the risks associated with these interventions. The authors also provide an overview of the natural history of IAs and discuss the challenges and uncertainties in managing these patients.

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.

Evaluation of unruptured aneurysm scoring systems and ratios in subarachnoid hemorrhage patients with multiple intracranial aneurysms

Background

This study aims to appraise aneurysm scores and ratios' ability to discriminate between ruptured aneurysms and unruptured intracranial aneurysms (UIAs) in subarachnoid hemorrhage (SAH) patients harboring multiple intracranial aneurysms (MICAs). We, then, investigate the most frequent risk factors associated with MICAs.

Methods

We retrospectively applied unruptured intracranial aneurysm treatment score (UIATS) and population hypertension age size of aneurysm earlier SAH from another aneurysm site of aneurysm (PHASES) score, aspect, and dome-to-neck ratio to the 59 consecutive spontaneous SAH patients with MICAs admitted between January 2000 and December 2015 to the Department of Neurosurgery of the University Hospital Center "Hôpital des Spécialités" of Rabat (Morocco). Patients with at least two intracranial aneurysms (IAs) confirmed on angiography were included in the study.

Results

Fifty-nine patients were harboring 128 IAs. The most frequent patient-level risk factors were arterial hypertension (AHT) 30.5 % (n = 18) and smoking status 22.0 % (n = 13). A PHASES score recommended treatment in 52 of 60 ruptured aneurysms and in six of 68 UIAs with a sensitivity of 31.67% and a specificity of 76.47%. UIATS recommended treatment in 26 of 62 ruptured aneurysms and in 35 of 55 UIAs with a sensitivity of 41.9% and a specificity of 63.6%. Aspect ratio recommended treatment in 60 of 60 ruptured aneurysms and in 63 of 68 UIAs with a sensitivity of 100% and a specificity of 88.24%. Dome-to-neck ratio recommended treatment in 45 of 60 ruptured aneurysms and in 48 of 68 UIAs with a sensitivity of 80% and a specificity of 63.24%. The aspect ratio (area under the curve [AUC] = 0.953) AUC > 0.8 has a higher discriminatory power between ruptured aneurysms and UIAs.

Conclusion

AHT and smoking status were the most common risk factors for intracranial multiple aneurysms and the aspect ratio and PHASES score were the most powerful discrimination tools between ruptured aneurysms and the UIAs.

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.

Toward Grading Subarachnoid Hemorrhage Risk Prediction: A Machine Learning-Based Aneurysm Rupture Score

OBJECTIVE

Existing approaches neither provide an accurate prediction of subarachnoid hemorrhage (SAH) nor offer a quantitative comparison among a group of its risk factors. To evaluate the population, hypertension, age, size, earlier subarachnoid hemorrhage, and location (PHASES) and unruptured intracranial aneurysm treatment score (UIATS) scores and develop an Artificial Intelligence-based 5-year and lifetime aneurysmal rupture criticality prediction (ARCP) score for a set of risk factors.

METHODS

We design various location-specific and ensemble learning models to develop lifetime rupture risk, employ the longitudinal data to develop a linear regression-based model to predict an aneurysm's growth score, and use the Apriori algorithm to identify risk factors strongly associated with SAH. We develop ARCP by integrating output of Apriori algorithm and ML models and compare with PHASES and UIATS scores along with the scores of a multidisciplinary team of neurosurgeons.

RESULTS

The PHASES and UIATS scores show sensitivities of 22% and 35% and specificities of 76% and 79%, respectively. Location-specific models show precision and recall of 93% and 90% for the middle cerebral artery, 83% and 80% for the anterior communicating artery, and 80% and 80% for the supraclinoid internal carotid artery, respectively. The ensemble method shows both precision and recall of 80%. The validation of the models shows that ARCP performs better than our control group of neurosurgeons. Data-driven knowledge produces comparisons among 61 risk factor combinations, 11 ranked minor, 8 moderate, and 41 severe, and 1 of which is a critical factor.

CONCLUSIONS

The PHASES and UIATS are weak predictors, and the ARCP score can identify, and grade, risk factors associated with SAH.

Identification of ruptured intracranial aneurysms using the aneurysm-specific prediction score in patients with multiple aneurysms with subarachnoid hemorrhages- a Chinese population based external validation study

Background

For patients with aneurysmal subarachnoid hemorrhages (SAHs) and multiple intracranial aneurysms (MIAs), a simple and fast imaging method that can identify ruptured intracranial aneurysms (RIAs) may have great clinical value. We sought to use the aneurysm-specific prediction score to identify RIAs in patients with MIAs and evaluate the aneurysm-specific prediction score.

Methods

Between May 2018 and May 2021, 134 patients with 290 MIAs were retrospectively analyzed. All patients had an SAH due to IA rupture. CT angiography (CTA) was used to assess the maximum diameter, shape, and location of IAs to calculate the aneurysm-specific prediction score. Then, the aneurysm-specific prediction score was applied to RIAs in patients with MIAs.

Results

The IAs with the highest aneurysm-specific prediction scores had not ruptured in 17 (12.7%) of the 134 patients with 290 MIAs. The sensitivity, specificity, false omission rate, diagnostic error rate, and diagnostic accuracy of the aneurysm-specific prediction score were higher than those of the maximum diameter, shape, and location of IAs.

Conclusions

The present study suggests that the aneurysm-specific prediction score has high diagnostic accuracy in identifying RIAs in patients with MIAs and SAH, but that it needs further evaluation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02727-w.

Machine Learning for Rupture Risk Prediction of Intracranial Aneurysms: Challenging the PHASES Score in Geographically Constrained Areas

Intracranial aneurysms represent a potentially life-threatening condition and occur in 3–5% of the population. They are increasingly diagnosed due to the broad application of cranial magnetic resonance imaging and computed tomography in the context of headaches, vertigo, and other unspecific symptoms. For each affected individual, it is utterly important to estimate the rupture risk of the respective aneurysm. However, clinically applied decision tools, such as the PHASES score, remain insufficient. Therefore, a machine learning approach assessing the rupture risk of intracranial aneurysms is proposed in our study. For training and evaluation of the algorithm, data from a single neurovascular center was used, comprising 446 aneurysms (221 ruptured, 225 unruptured). The machine learning model was then compared with the PHASES score and proved superior in accuracy (0.7825), F1-score (0.7975), sensitivity (0.8643), specificity (0.7022), positive predictive value (0.7403), negative predictive value (0.8404), and area under the curve (0.8639). The frequency distributions of the predicted rupture probabilities and the PHASES score were analyzed. A symmetry can be observed between the rupture probabilities, with a symmetry axis at 0.5. A feature importance analysis reveals that the body mass index, consumption of anticoagulants, and harboring vessel are regarded as the most important features when assessing the rupture risk. On the other hand, the size of the aneurysm, which is weighted most in the PHASES score, is regarded as less important. Based on our findings we discuss the potential role of the model for clinical practice in geographically confined aneurysm patients.