Retrospective application of risk scores to ruptured intracranial aneurysms: would they have predicted the risk of bleeding?

Evaluation of PHASES Score for Predicting Rupture of Intracranial Aneurysms: Significance of Aneurysm Size

BACKGROUND

Recent data have identified that certain risk factors for rupture differ between small and larger intracranial aneurysms (IAs). Such differing risk factors make up 5 out of the 6 predictor variables used in the PHASES score, which raises the question on whether IA size has a significant effect on the score's performance.

METHODS

Patients who were diagnosed with an IA incidentally or due to a subarachnoid hemorrhage between 2015 and 2023 were selected for potential inclusion. The median IA size of the cohort was chosen as the cutoff point to categorize small and large (6 mm). The PHASES score was calculated for all patients, and a receiver operating characteristic curve analysis was performed to evaluate the classification accuracy of PHASES in predicting rupture for small and large IAs.

RESULTS

A total of 677 IAs were included. Among the IAs, 400 (58.9%) presented as UIAs and 279 (41.0%) as subarachnoid hemorrhage. The average PHASES score was 2.9 and 6.5 for small (n = 322) and large (n = 355) IAs, respectively. The PHASES score performed significantly lower for predicting rupture in smaller IAs (area under the curve: 0.634) compared with the larger (area under the curve: 0.741) (P = 0.00083).

CONCLUSIONS

PHASES was shown to underperform on small IAs. The decision to treat small unruptured IAs remains highly controversial, and the development of a new score to estimate the annual rupture rate while accounting for IA morphology is of great need. Our findings can help encourage future researchers to develop such a score.

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.

Predictors for Rupture of Small (<7mm) Intracranial Aneurysms: A Systematic Review and Meta-Analysis

INTRODUCTION

Identifying predictors for rupture of small intracranial aneurysms (sIAs) have become a growing topic in the literature given the relative paucity of data on their natural history. The authors performed a meta-analysis to identify reliable predictors.

METHODS

PubMed, Scopus, and Web of Science were used to systematically extract references which involved at least 10 IAs <7mm which including a control group experiencing no rupture. All potential predictors reported in the literature were evaluated in the meta-analysis.

RESULTS

Fifteen studies yielding 4,739 sIAs were included in the meta-analysis. Four studies were prospective and 11 were retrospective. Univariate analysis identified 7 predictors which contradicted or are absent in the current scoring systems, while allowing to perform subgroup analysis for further reliability: patient age (MD -1.97, 95%CI -3.47-0.48; P = 0.01), the size ratio (MD 0.40, 95%CI 0.26-0.53; P < 0.00001), the aspect ratio (MD 0.16, 95%CI 0.11-0.22; P < 0.00001), bifurcation point (OR 3.76, 95%CI 2.41-5.85; P < 0.00001), irregularity (OR 2.95, 95%CI 1.91-4.55; P < 0.00001), the pressure loss coefficient (MD -0.32, 95%CI -0.52-0.11; P = 0.002), wall sheer stress (Pa) (MD -0.16, 95%CI -0.28-0.03; P = 0.01). All morphology related predictors listed above have been confirmed as independent predictors via multivariable analysis among the individual studies.

CONCLUSIONS

Morphology related predictors are superior to the classic patient demographic predictors present in most scoring systems. Given that morphology predictors take time to measure, our findings may be of great interest to developers seeking to incorporate artificial intelligence into the treatment decision-making process.

Retrospective Application of Risk Scores to Unruptured Anterior Communicating Artery Aneurysms

BACKGROUND

Treatment decisions for unruptured intracranial aneurysms (UIAs) pose a challenge for neurosurgeons, prompting the development of clinical scales assessing hemorrhage risk to provide management guidance. This study compares recommendations from the PHASES and UIA treatment scores (UIATS) applied to anterior communicating artery (AComA) UIAs against real-world management.

METHODS

While UIATS recommends management, for PHASES, an aneurysm with score of 10 or more was considered "high-risk". Analysis involved assessing the concordance in each group alongside comparison to real-word management.

RESULTS

Among 129 patients, 46.5% were observed and 53.5% were treated. PHASES scores were significantly higher in the treatment group (p = 0.00002), and UIATS recommendations correlated with real-world decisions (p < 0.001). We observed no difference in the frequencies of UIATS recommendations between high- and low-risk groups. When comparing the UIATS and PHASES, 33% of high-risk aneurysms received a UIATS conservative management recommendation. In 39% of high-risk aneurysms, the UIATS recommendation was not definitive. Conversely, 27% of low-risk aneurysms obtained a UIATS UIA repair recommendation. Overall, concordance between PHASES and UIATS was 32%.

CONCLUSIONS

Significant discordance in therapeutic suggestions underscores the predominant influence of center experience and individual assessments. Future studies should refine and validate decision-making strategies, potentially exploring alternative applications or developing tailored scales.

Trends in the Age of Patients Treated for Unruptured Intracranial Aneurysms from 1990 to 2020

BACKGROUND

The decision for treatment for unruptured intracranial aneurysms (UIAs) is often difficult. Innovation in endovascular devices have improved the benefit-to-risk profile especially for elderly patients; however, the treatment guidelines from the past decade often recommend conservative management. It is unknown how these changes have affected the overall age of the patients selected for treatment. Herein, we aimed to study potential changes in the average age of the patients that are being treated over time.

METHODS

A systematic search of the literature was performed to identify all studies describing the age of the UIAs that were treated by any modality. Scatter diagrams with trend lines were used to plot the age of the patients treated over time and assess the presence of a potential significant trend via statistical correlation tests.

RESULTS

A total of 280 studies including 83,437 UIAs treated between 1987 and 2021 met all eligibility criteria and were entered in the analysis. Mean age of the patients was 55.5 years, and 70.7% were female. There was a significant increasing trend in the age of the treated patients over time (Spearman r: 0.250; P < 0.001), with a 1-year increase in the average age of the treated patients every 5 years since 1987.

CONCLUSIONS

The present study indicates that based on the treated UIA patient data published in the literature, older UIAs are being treated over time. This trend is likely driven by safer treatments while suggesting that re-evaluation of certain UIA treatment decision scores may be of great interest.

Prospective assessment of aneurysmal rupture risk scores in patients with subarachnoid hemorrhage: a multicentric cohort

PURPOSE

The natural evolution of unruptured intracranial aneurysms (UIA) is indeed difficult to predict at the individual level.

OBJECTIVE

In a large prospective multicentric European cohort, we aimed to evaluate whether the PHASES, UCAS, and ELPASS scores in patients with aneurysmal subarachnoid hemorrhage would have predicted a high risk of aneurysmal rupture or growth.

METHODS

Academic centers treating patients with intracranial aneurysms were invited to prospectively collect de-identified data from all patients admitted at their institution for a subarachnoid hemorrhage-related to intracranial aneurysmal rupture between January 1 and March 31, 2021 through a trainee-led research collaborative network. Each responding center was provided with an electronic case record form (CRF) which collected all the elements of the PHASES, ELAPSS, and UCAS scores.

RESULTS

A total of 319 patients with aneurysmal subarachnoid hemorrhage were included at 17 centers during a 3-month period. One hundred eighty-three aneurysms (57%) were less than 7 mm. The majority of aneurysms were located on the anterior communicating artery (n = 131, 41%). One hundred eighty-four patients (57%), 103 patients (32%), and 58 (18%) were classified as having a low risk of rupture or growth, according to the PHASES, UCAS, and ELAPSS scores, respectively.

CONCLUSION

In a prospective study of European patients with aneurysmal subarachnoid hemorrhage, we showed that 3 common risk-assessment tools designed for patients with unruptured intracranial aneurysms would have not identified most patients to be at high or intermediate risk for rupture, questioning their use for decision-making in the setting of unruptured aneurysms.

Timing and outcome of bystanders treatment in patients with subarachnoid hemorrhage associated with multiple aneurysms

In case of subarachnoid hemorrhage (SAH) associated with multiple intracranial aneurysms (MIAs), the main goal of acute treatment is securing the source of bleeding (index aneurysm). Indications and timing of bystanders treatment are instead still debated as the risk of new SAHs in patients harboring MIAs is not yet established. However, even if technically feasible, a simultaneous management of all aneurysms remains questionable, especially for safety issues. We retrospectively reviewed our last 5-year experience with SAH patients harboring MIAs entered in a clinic-radiological monitoring for bystanders follow-up in order to evaluate the occurrence of morphological changes, bleeding events, and safety and efficacy of a delayed treatment. We included 39 patients with mean age of 59.5 ± 12.2 years who survived a SAH. Among them, 14 underwent treatment, whereas 25 continued follow-up. The mean time between index and bystanders treatment was 14.3 ± 19.2 months. Patients undergoing bystanders treatment were mainly female and in general younger than patients undergoing observation. No cases of growth or bleeding were observed among bystanders within the two groups during the follow-up, which was longer than 1 year for the intervention group, and almost 40 months for the observation group. No major complications and mRS modifications were observed after bystanders treatment. Our data seem to suggest that within the short follow-up, intervention and observation seem to be likewise safe for bystander aneurysms, showing at the same time that a delayed management presents a similar risk profile of treating unruptured aneurysms in patients with no previous history of SAH.

Circumferential wall enhancement with contrast ratio measurement in unruptured intracranial aneurysm for aneurysm instability

BACKGROUND

Aneurysm wall enhancement on high-resolution vessel wall imaging (HR-VWI) may represent vessel wall inflammation for unruptured intracranial aneurysms (UIAs). Further evidence for the role of circumferential aneurysm wall enhancement (CAWE) in evaluating the instability of UIAs is required, especially in small aneurysms (<7 mm).

METHODS

We analyzed patients with saccular UIAs who prospectively underwent HR-VWI on a 3.0 T MRI scanner in our center from September 2017 to August 2021. The presence of AWE was identified and quantitatively measured using the aneurysm-to-pituitary stalk contrast ratio (CRstalk) with maximal signal intensity value. The PHASES and ELAPSS scores were used to assess the risk of aneurysm rupture and growth. We evaluated the association of CAWE and CRstalk value with intracranial aneurysm instability.

RESULTS

One hundred patients with 109 saccular UIAs were included in this study. Eighty-three UIAs (76.1%) had a size smaller than 7 mm. PHASES and ELAPSS scores were significantly higher in UIAs with CAWE than in UIAs without CAWE (p < .01). The association of CAWE with PHASES and ELAPSS scores remained in small UIAs (<7 mm). The optimal cutoff value of CRstalk for CAWE was 0.5. PHASES and ELAPSS scores were significantly higher in UIAs with CRstalk ≥0.5 than in UIAs with CRstalk <0.5 (p < .01).

CONCLUSIONS

CAWE on HR-VWI is a valuable imaging marker for aneurysm instability in UIAs. CRstalk value ≥0.5 may be associated with a higher risk of intracranial aneurysm rupture and growth.

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.

Risk factors for the progression of unruptured intracranial aneurysms in patients followed by CT/MR angiography

Background

The progression of an unruptured intracranial aneurysm (UIA) is associated with a higher rupture risk. The aim of this study was to identify the risk factors for the progression of UIAs among Chinese adults and compare them with the ELAPSS (Earlier subarachnoid hemorrhage, IA Location, Age, Population, IA Size and Shape) score.

Methods

Four hundred thirty-eight consecutive patients with 491 UIAs were followed and reviewed retrospectively from August 2011 to November 2019. Follow-up images of the UIAs were used to determine changes in IA size and shape. Patients and IAs were divided into non-progression and progression groups. In addition to the clinical characteristics of the patients, the features of the IAs (e.g., size and shape) were evaluated by computed tomography angiography (CTA) or magnetic resonance angiography (MRA). Independent risk factors for UIA progression were studied using multiple Cox proportional hazards regression analysis. In addition, the diagnostic value of the ELAPSS score for the prediction of UIA progression was calculated.

Results

Seventy-two IAs in 68 patients progressed during a mean follow-up time of 24.2±19.68 months. IAs located at the bifurcation [odds ratio (OR) 2.600], with an irregular shape (OR 2.981) or having a high aspect ratio (AR, OR 2.430) were correlated with progression. Based on these three factors, the threshold value of our predictive score was 0.5, and the area under the curve (AUC), sensitivity and specificity were 0.756, 93.1% and 40.6%, respectively, while the AUC, sensitivity and specificity of the ELAPSS score were 0.711, 55.6%, and 75.2%, respectively.

Conclusions

IAs located at the bifurcation, with an irregular shape and with an elevated AR are risk factors for UIA progression in the Chinese population. Our predictive score is of great value in predicting the risk of UIA progression.

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.

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.