PHASES score applied to a prospective cohort of aneurysmal subarachnoid hemorrhage patients

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.

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.

Predictive value of IOM in clipping of unruptured intracranial aneurysms - A prospective study from the surgeon's point of view

Introduction

Intraoperative neuromonitoring (IOM) of motor/somatosensory evoked potentials is a well-established approach for reducing ischemic complications after aneurysm clipping.

Research question

To determine the predictive validity of IOM for postoperative functional outcome and its perceived added value for intraoperative real-time feedback of functional impairment in the surgical treatment of unruptured intracranial aneurysms (UIAs).

Material and methods

Prospective study of patients scheduled for elective clipping of UIAs between 02/2019-02/2021. Transcranial motor evoked potentials (tcMEP) were used in all cases, a significant decline was defined as loss of ≥50% in amplitude or 50% latency increase. Clinical data were correlated to postoperative deficits. A surgeon's questionnaire was conceived.

Results

47 patients were included, median age 57 years (range 26-76). IOM was successful in all cases. In 87.2%, IOM was stable throughout surgery, although 1 patient (2.4%) demonstrated a permanent postoperative neurological deficit. All patients with an intraoperatively reversible tcMEP-decline (12.7%) showed no surgery-related deficit, regardless of the decline duration (range 0.5-40.0 ​min; mean: 13.8). Temporary clipping (TC) was performed in 12 cases (25.5%), with a decline in amplitude in 4 patients. After clip-removal, all amplitudes returned to baseline. IOM provided the surgeon with a higher sense of security in 63.8%.

Discussion and conclusion

IOM remains invaluable during elective microsurgical clipping, particularly during TC of MCA and AcomA-aneurysms. It alerts the surgeon of impending ischemic injury and offers a way of maximizing the time frame for TC. IOM has highly increased surgeons' subjective feeling of security during the procedure.

RNA Expression Signatures of Intracranial Aneurysm Growth Trajectory Identified in Circulating Whole Blood

After detection, identifying which intracranial aneurysms (IAs) will rupture is imperative. We hypothesized that RNA expression in circulating blood reflects IA growth rate as a surrogate of instability and rupture risk. To this end, we performed RNA sequencing on 66 blood samples from IA patients, for which we also calculated the predicted aneurysm trajectory (PAT), a metric quantifying an IA's future growth rate. We dichotomized dataset using the median PAT score into IAs that were either more stable and more likely to grow quickly. The dataset was then randomly divided into training (n = 46) and testing cohorts (n = 20). In training, differentially expressed protein-coding genes were identified as those with expression (TPM > 0.5) in at least 50% of the samples, a q-value < 0.05 (based on modified F-statistics with Benjamini-Hochberg correction), and an absolute fold-change ≥ 1.5. Ingenuity Pathway Analysis was used to construct networks of gene associations and to perform ontology term enrichment analysis. The MATLAB Classification Learner was then employed to assess modeling capability of the differentially expressed genes, using a 5-fold cross validation in training. Finally, the model was applied to the withheld, independent testing cohort (n = 20) to assess its predictive ability. In all, we examined transcriptomes of 66 IA patients, of which 33 IAs were "growing" (PAT ≥ 4.6) and 33 were more "stable". After dividing dataset into training and testing, we identified 39 genes in training as differentially expressed (11 with decreased expression in "growing" and 28 with increased expression). Model genes largely reflected organismal injury and abnormalities and cell to cell signaling and interaction. Preliminary modeling using a subspace discriminant ensemble model achieved a training AUC of 0.85 and a testing AUC of 0.86. In conclusion, transcriptomic expression in circulating blood indeed can distinguish "growing" and "stable" IA cases. The predictive model constructed from these differentially expressed genes could be used to assess IA stability and rupture potential.

Profiling of Circulating Gene Expression Reveals Molecular Signatures Associated with Intracranial Aneurysm Rupture Risk

BACKGROUND

Following detection, rupture risk assessment for intracranial aneurysms (IAs) is critical. Towards molecular prognostics, we hypothesized that circulating blood RNA expression profiles are associated with IA risk.

METHODS

We performed RNA sequencing on 68 blood samples from IA patients. Here, patients were categorized as either high or low risk by assessment of aneurysm size (≥ 5 mm = high risk) and Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, Site (PHASES) score (≥ 1 = high risk). Modified F-statistics and Benjamini-Hochberg false discovery rate correction was performed on transcripts per million-normalized gene counts. Protein-coding genes expressed in ≥ 50% of samples with a q value < 0.05 and an absolute fold-change ≥ 2 were considered significantly differentially expressed. Bioinformatics in Ingenuity Pathway Analysis was performed to understand the biology of risk-associated expression profiles. Association was assessed between gene expression and risk via Pearson correlation analysis. Linear discriminant analysis models using significant genes were created and validated for classification of high-risk cases.

RESULTS

We analyzed transcriptomes of 68 IA patients. In these cases, 31 IAs were large (≥ 5 mm), while 26 IAs had a high PHASES score. Based on size, 36 genes associated with high-risk IAs, and two were correlated with the size measurement. Alternatively, based on PHASES score, 76 genes associated with high-risk cases, and nine of them showed significant correlation to the score. Similar ontological terms were associated with both gene profiles, which reflected inflammatory signaling and vascular remodeling. Prediction models based on size and PHASES stratification were able to correctly predict IA risk status, with > 80% testing accuracy for both.

CONCLUSIONS

Here, we identified genes associated with IA risk, as quantified by common clinical metrics. Preliminary classification models demonstrated feasibility of assessing IA risk using whole blood expression.

Proper ophthalmic artery aneurysms

Background

The ophthalmic segment of the internal carotid artery (ICA) represents a common site for cerebral aneurysms. However, aneurysms of the ophthalmic artery (OphA) itself represent rare lesions and have been associated with trauma and flow-related lesions such as arteriovenous fistulas or malformations. Here, we explore clinical and radiological features of four patients managed for five proper ophthalmic artery aneurysms (POAAs).

Methods

Patients undergoing diagnostic cerebral angiogram (DCA) between January 2018 and November 2021 with newly or previously identified POAA were retrospectively reviewed. Clinical and radiological data were analyzed to identify common and unique features.

Results

Four patients with identification of five POAA were identified. Three patients suffered traumatic brain injury with subsequent identification of POAA on DCA. Patient 1 presented with a traumatic carotid-cavernous-sinus fistula requiring transvenous coil embolization and second stage flow diversion of the ICA. Patient 2 suffered a gunshot wound with ICA compromise, ethmoidal dural arteriovenous fistula (dAVF) development with rapid growth of two POAAs eventually requiring Onyx embolization. Patient 3 was assaulted and DCA showed a POAA without any other cerebrovascular pathology. Patient 4 had undergone N-butyl cyanoacrylate embolization of an ethmoidal dAVF 13 years ago with the feeding OphA carrying a large POAA. Re-DCADCA was performed for a newly developed and unrelated transverse-sigmoid-sinus dAVF.

Conclusion

Management of POAAs poses a challenge to neurovascular surgeons since POAAs inherit a risk for visual deterioration or hemorrhage. DCA facilitates identification of coexisting cerebrovascular pathology. If clinically silent and not accompanied by cerebrovascular disease, observation appears reasonable.

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.

An accurate prognostic prediction for aneurysmal subarachnoid hemorrhage dedicated to patients after endovascular treatment

Background

Endovascular treatment for aneurysmal subarachnoid hemorrhage (aSAH) has high fatality and permanent disability rates. It remains unclear how the prognosis is determined by the complex interaction between clinical severity and aneurysm characteristics.

Objective

This study aimed to design an accurate prognostic prediction model for aSAH patients after endovascular treatment and elucidate the interaction between clinical severity and aneurysm characteristics.

Methods

We used a clinically homogeneous data set with 1029 aSAH patients who received endovascular treatment to develop prognostic models. Aneurysm characteristics were measured by variables, such as aneurysm size, neck size, and dome-to-neck ratio, while clinical severity on admission was measured by both comorbidities and neurological condition. In total, 18 clinical variables were used for prognostic prediction. Considering the imbalance between the favorable and the poor outcomes in this clinical population, both ensemble learning and deep reinforcement learning approaches were used for prediction.

Results

The random forest (RF) model was selected as the best approach for the prognostic prediction for all patients and also for patients with good-grade aSAH. Using an independent test data set, the model made accurate predictions (AUC = 0.869 ± 0.036, sensitivity = 0.709 ± 0.087, specificity = 0.805 ± 0.034) with the clinical severity on admission as a leading contributor to the prediction. For patients with good-grade aSAH, the RF model performed the best (AUC = 0.805 ± 0.034, sensitivity = 0.620 ± 0.172, specificity = 0.696 ± 0.043) with aneurysm characteristics as leading contributors. The classic scoring systems failed in this patient group (AUC < 0.600; sensitivity = 0.000, specificity = 1.000).

Conclusion

The proposed prognostic prediction model outperformed the classic scoring systems for patients with aSAH after endovascular treatment, especially when the classic scoring systems failed to make any informative prediction for patients with good-grade aSAH, who constitute the majority group (79%) of this clinical population.

Association Between Aneurysmal Hemodynamics and Rupture Risk of Unruptured Intracranial Aneurysms

Background

Assessing rupture risk in patients with unruptured intracranial aneurysms (UIAs) remains challenging. Hemodynamics plays an important role in the natural history of intracranial aneurysms. This study aimed to compare aneurysmal hemodynamic features between patients with different rupture risk as determined by PHASES score.

Methods

We retrospectively examined 238 patients who harbored a solitary saccular UIA. Patients were stratified by rupture risk into low-, intermediate-, and high-risk groups according to PHASES score. Flow simulations were performed to compare differences in hemodynamics among the groups.

Results

Aneurysmal time-averaged wall shear stress (WSSa) and normalized WSS (WSSn) decreased progressively as PHASES score increased. WSSa and WSSn significantly differed among the low-, intermediate-, and high-risk groups (p < 0.001). WSSa was significantly lower in the high-risk group than the low-risk group (p < 0.001) and the intermediate-risk group (p = 0.004). WSSn was also significantly lower in the high-risk group than the low-risk group (p < 0.001) and the intermediate-risk group (p = 0.001).

Conclusions

Low WSS was significantly associated with higher risk of intracranial aneurysm rupture as determined by PHASES score, indicating that hemodynamics may play an important role in aneurysmal rupture. In the future, a multidimensional rupture risk prediction model that includes hemodynamic parameters should be investigated.

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.

Intracranial aneurysm wall (in)stability-current state of knowledge and clinical perspectives

Intracranial aneurysm (IA), a local outpouching of cerebral arteries, is present in 3 to 5% of the population. Once formed, an IA can remain stable, grow, or rupture. Determining the evolution of IAs is almost impossible. Rupture of an IA leads to subarachnoid hemorrhage and affects mostly young people with heavy consequences in terms of death, disabilities, and socioeconomic burden. Even if the large majority of IAs will never rupture, it is critical to determine which IA might be at risk of rupture. IA (in)stability is dependent on the composition of its wall and on its ability to repair. The biology of the IA wall is complex and not completely understood. Nowadays, the risk of rupture of an IA is estimated in clinics by using scores based on the characteristics of the IA itself and on the anamnesis of the patient. Classification and prediction using these scores are not satisfying and decisions whether a patient should be observed or treated need to be better informed by more reliable biomarkers. In the present review, the effects of known risk factors for rupture, as well as the effects of biomechanical forces on the IA wall composition, will be summarized. Moreover, recent advances in high-resolution vessel wall magnetic resonance imaging, which are promising tools to discriminate between stable and unstable IAs, will be described. Common data elements recently defined to improve IA disease knowledge and disease management will be presented. Finally, recent findings in genetics will be introduced and future directions in the field of IA will be exposed.

Effect of Aneurysm and Patient Characteristics on Intracranial Aneurysm Wall Thickness

Background: The circle of Willis is a network of arteries allowing blood supply to the brain. Bulging of these arteries leads to formation of intracranial aneurysm (IA). Subarachnoid hemorrhage (SAH) due to IA rupture is among the leading causes of disability in the western world. The formation and rupture of IAs is a complex pathological process not completely understood. In the present study, we have precisely measured aneurysmal wall thickness and its uniformity on histological sections and investigated for associations between IA wall thickness/uniformity and commonly admitted risk factors for IA rupture.

Methods: Fifty-five aneurysm domes were obtained at the Geneva University Hospitals during microsurgery after clipping of the IA neck. Samples were embedded in paraffin, sectioned and stained with hematoxylin-eosin to measure IA wall thickness. The mean, minimum, and maximum wall thickness as well as thickness uniformity was measured for each IA. Clinical data related to IA characteristics (ruptured or unruptured, vascular location, maximum dome diameter, neck size, bottleneck factor, aspect and morphology), and patient characteristics [age, smoking, hypertension, sex, ethnicity, previous SAH, positive family history for IA/SAH, presence of multiple IAs and diagnosis of polycystic kidney disease (PKD)] were collected.

Results: We found positive correlations between maximum dome diameter or neck size and IA wall thickness and thickness uniformity. PKD patients had thinner IA walls. No associations were found between smoking, hypertension, sex, IA multiplicity, rupture status or vascular location, and IA wall thickness. No correlation was found between patient age and IA wall thickness. The group of IAs with non-uniform wall thickness contained more ruptured IAs, women and patients harboring multiple IAs. Finally, PHASES and ELAPSS scores were positively correlated with higher IA wall heterogeneity.

Conclusion: Among our patient and aneurysm characteristics of interest, maximum dome diameter, neck size and PKD were the three factors having the most significant impact on IA wall thickness and thickness uniformity. Moreover, wall thickness heterogeneity was more observed in ruptured IAs, in women and in patients with multiple IAs. Advanced medical imaging allowing in vivo measurement of IA wall thickness would certainly improve personalized management of the disease and patient care.

Development and validation of an institutional nomogram for aiding aneurysm rupture risk stratification

Rupture risk stratification is critical for incidentally detected intracranial aneurysms. Here we developed and validated an institutional nomogram to solve this issue. We reviewed the imaging and clinical databases for aneurysms from January 2015 to September 2018. Aneurysms were reconstructed and morphological features were extracted by the Pyradiomics in python. Multiple logistic regression was performed to develop the nomogram. The consistency of the nomogram predicted rupture risks and PHASES scores was assessed. The performance of the nomogram was evaluated by the discrimination, calibration, and decision curve analysis (DCA). 719 aneurysms were enrolled in this study. For each aneurysm, twelve morphological and nine clinical features were obtained. After logistic regression, seven features were enrolled in the nomogram, which were SurfaceVolumeRatio, Flatness, Age, Hyperlipemia, Smoker, Multiple aneurysms, and Location of the aneurysm. The nomogram had a positive and close correlation with PHASES score in predicting aneurysm rupture risks. AUCs of the nomogram in discriminating aneurysm rupture status was 0.837 in a separate testing set. The calibration curves fitted well and DCA demonstrated positive net benefits of the nomogram in guiding clinical decisions. In conclusion, Pyradiomics derived morphological features based institutional nomogram was useful for aneurysm rupture risk stratification.

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

Objective: Unruptured Intracranial Aneurysm (UIA) Treatment Score (UIATS) and PHASES score are used to inform treatment decision making for UIAs (treatment or observation). We assessed the ability of the scoring systems to discriminate between ruptured aneurysms and UIAs in a subarachnoid hemorrhage (SAH) cohort with multiple aneurysms. Methods: We retrospectively applied PHASES and UIATS scoring to the aneurysms of 40 consecutive patients with SAH and multiple intracranial aneurysms. Results: PHASES score discriminated better between ruptured aneurysms and UIAs than UIATS. PHASES scores and the difference between the UIATS subscores were higher for ruptured aneurysms compared with UIAs, which reached significance for the PHASES score. PHASES score estimated a low 5-year rupture risk in a larger proportion of the UIAs (≤0.7% in 62.3%, ≤1.7% in 98.4%) than of the ruptured aneurysms (≤0.7% in 22.5%, ≤1.7% in 82.5%). In the 40 ruptured aneurysms, UIATS provided recommendation for treatment in 11 (27.5%), conservative management in 14 (35.0%), and was inconclusive in 15 cases (37.5%). In the 61 UIAs, UIATS recommended treatment in 16 (26.2%), conservative management in 29 (47.5%), and was inconclusive in 16 (26.2%) cases. Conclusion: Similar to previous SAH cohorts, a significant proportion of the ruptured aneurysms exhibited a low-rupture risk. Nevertheless, PHASES score discriminated between ruptured aneurysms and UIAs in our cohort; the lower discriminatory power of UIATS was due to high weights of aneurysm-independent factors. We recommend careful integration of the scores for individual decision making. Large-scale prospective trials are required to establish score-based treatment strategies for UIAs.

Application of unruptured aneurysm scoring systems to a cohort of ruptured aneurysms: are we underestimating rupture risk?

The predictive values of current risk stratification scales such as the Unruptured Intracranial Aneurysm Treatment Score (UIATS) and the PHASES score are debatable. We evaluated these scores using a cohort of ruptured intracranial aneurysms to simulate their management recommendations had the exact same patients presented prior to rupture. A prospectively maintained database of ruptured saccular aneurysm patients presenting to our institution was used. The PHASES score was calculated for 992 consecutive patients presenting between January 2002 and December 2018, and the UIATS was calculated for 266 consecutive patients presenting between January 2013 and December 2018. A shorter period was selected for the UIATS cohort given the larger number of variables required for calculation. Clinical outcomes were compared between UIATS-recommended "observation" aneurysms and all other aneurysms. Out of 992 ruptured aneurysms, 54% had a low PHASES score (≤5). Out of the 266 ruptured aneurysms, UIATS recommendations were as follows: 68 (26%) "observation," 97 (36%) "treatment," and 101 (38%) "non-definitive." The UIATS conservative group of patients developed more SAH-related complications (78% vs. 65%, p=0.043), had a higher rate of non-home discharge (74% vs. 46%, p<0.001), and had a greater incidence of poor functional status (modified Rankin scale >2) after 12-18 months (68% vs. 51%, p=0.014). Current predictive scoring systems for unruptured aneurysms may underestimate future rupture risk and lead to more conservative management strategies in some patients. Patients that would have been recommended for conservative therapy were more likely to have a worse outcome after rupture.

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

As the incidental diagnosis of unruptured intracranial aneurysms has been increasing, several scores were developed to predict risk of rupture and growth to guide the management choice. We retrospectively applied these scores to a multicenter series of patients with subarachnoid hemorrhage to test whether they would have predicted the risk of bleeding in the event of aneurysm discovery previous to its rupture. Demographical, clinical, and radiological information of 245 adults were retrieved from two neurovascular centers' database. Data were pooled and PHASES, UCAS, and ELAPSS scores were retrospectively calculated for the whole population and their performances in identifying aneurysms at risk of rupture were compared. Mean PHASES, UCAS, and ELAPSS scores were 5.12 ± 3.08, 5.09 ± 2.62, and 15.88 ± 8.07, respectively. Around half (46%) of patients would have been assigned to the low- or very low-risk class (5-year rupture risk < 1%) in PHASES. Around 28% of patients would have been in a low-risk class, with a probability of 3-year rupture risk < 1% according to UCAS. Finally, ELAPSS score application showed a wider distribution among the risk classes, but a significant proportion of patients (45.5%) lie in the low- or intermediate-risk class for aneurysm growth. A high percentage of patients with ruptured aneurysms in this multicenter cohort would have been assigned to the lower risk categories for aneurysm growth and rupture with all the tested scores if they had been discovered before the rupture. Based on these observations, physicians should be careful about drawing therapeutic conclusions solely based on application of these scores.

Stability Assessment of Intracranial Aneurysms Using Machine Learning Based on Clinical and Morphological Features

Machine learning (ML) as a novel approach could help clinicians address the challenge of accurate stability assessment of unruptured intracranial aneurysms (IAs). We developed multiple ML models for IA stability assessment and compare their performances. We enrolled 1897 consecutive patients with unstable (n = 528) and stable (n = 1539) IAs. Thirteen patient-specific clinical features and eighteen aneurysm morphological features were extracted to generate support vector machine (SVM), random forest (RF), and feed-forward artificial neural network (ANN) models. The discriminatory performances of the models were compared with statistical logistic regression (LR) model and the PHASES score in IA stability assessment. Based on the receiver operating characteristic (ROC) curve and area under the curve (AUC) values for each model in the test set, the AUC values for RF, SVM, and ANN were 0.850 (95% CI 0.806-0.893), 0.858 (95 %CI 0.816-0.900), and 0.867 (95% CI 0.828-0.906), demonstrating good discriminatory ability. All ML models exhibited superior performance compared with the statistical LR and the PHASES score (the AUC values were 0.830 and 0.589, respectively; RF versus PHASES, P < 0.001; RF versus LR, P = 0.038). Important features contributing to the stability discrimination included three clinical features (location, sidewall/bifurcation type, and presence of symptoms) and three morphological features (undulation index, height-width ratio, and irregularity). These findings demonstrate the potential of ML to augment the clinical decision-making process for IA stability assessment, which may enable more optimal management for patients with IAs in the future.

Intracranial aneurysms at higher clinical risk for rupture demonstrate increased wall enhancement and thinning on multicontrast 3D vessel wall MRI

OBJECTIVE:

Identification of aneurysms at risk for rupture is important and challenging. We sought to evaluate if intracranial vessel wall (IVW) imaging characteristics of unruptured aneurysms correlate with clinical risk factors for rupture.

METHODS:

Patients with unruptured intracranial aneurysms were prospectively recruited and underwent a multi contrast 3D IVW protocol between April 6, 2016 and August 29, 2017. Two independent raters, blinded to aneurysm vulnerability, evaluated each aneurysm for wall enhancement, extent of enhancement in terms of the numbers of quadrants enhancing circumferentially, intensity of enhancement, and qualitative wall thinning. PHASES score was calculated for each aneurysm. Univariate logistic regression analysis was used to compare IVW characteristics between aneurysms at higher clinical risk for rupture (PHASES score > 3) and lower clinical risk for rupture (PHASES score ≤ 3).

RESULTS:

45 patients with 65 unruptured aneurysms were analyzed; 38 aneurysms with PHASES score > 3 (58%) and 27 aneurysms with PHASES score ≤ 3 (42%). Aneurysms with PHASES score > 3 were more likely to demonstrate enhancement (42.1% vs 14.8%, p = 0.022), greater extent of enhancement (mean: 2.9 vs 2.2 quadrants, p = 0.063), and wall thinning (9.2% vs 0%, p = 0.044). Inter-reader agreement was moderate-to-good for the presence (κ = 0.64), extent (κ = 0.64), and intensity of enhancement (κ = 0.60) but relatively low for wall thinning (κ = 0.25).

CONCLUSION:

Aneurysms at higher risk of rupture by PHASES score are more likely to demonstrate wall enhancement, more diffuse enhancement, and wall thinning on IVW.

ADVANCES IN KNOWLEDGE:

This study prospectively compares IVW-detected wall enhancement and thinning between unruptured aneurysms stratified into high and low risk groups by clinical scores (PHASES) of vulnerability.