Association Between Serum Homocysteine Concentration, Aneurysm Wall Inflammation, and Aneurysm Symptoms in Intracranial Fusiform Aneurysm.

RATIONALE AND OBJECTIVES: The pathophysiology of fusiform intracranial aneurysm (FIA) involves inflammatory processes, and homocysteine plays a role in the inflammatory processes in the vessel wall. Moreover, aneurysm wall enhancement (AWE) has emerged as a new imaging biomarker of aneurysm wall inflammatory pathologies. To investigate the pathophysiological mechanisms of aneurysm wall inflammation and FIA instability, we aimed to determine the associations between the homocysteine concentration, AWE, and FIAs' related symptoms. MATERIALS AND METHODS: We retrospectively reviewed the data of 53 patients with FIA who underwent both high-resolution magnetic resonance imaging and serum homocysteine concentration measurement. FIAs' related symptoms were defined as ischemic stroke or transient ischemic attack, cranial nerve compression, brainstem compression, and acute headache. The contrast ratio of the signal intensity of the aneurysm wall to the pituitary stalk (CRstalk) was used to indicate AWE. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to determine how well the independent factors could predict FIAs' related symptoms. Predictors of CRstalk were also investigated. Spearman's correlation coefficient was used to identify the potential associations between these predictors. RESULTS: Fifty-three patients were included, of whom 23 (43.4%) presented with FIAs' related symptoms. After adjusting for baseline differences in the multivariate logistic regression analysis, the CRstalk (odds ratio [OR]=3.207, P = .023) and homocysteine concentration (OR=1.344, P = .015) independently predicted FIAs' related symptoms. The CRstalk was able to differentiate between FIAs with and without symptoms (area under the ROC curve [AUC]=0.805), with an optimal cutoff value of 0.76. The homocysteine concentration could also differentiate between FIAs with and without symptoms (AUC=0.788), with an optimal cutoff value of 13.13. The combination of the CRstalk and homocysteine concentration had a better ability to identify symptomatic FIAs (AUC=0.857). Male sex (OR=0.536, P = .018), FIAs' related symptoms (OR=1.292, P = .038), and homocysteine concentration (OR=1.254, P = .045) independently predicted the CRstalk. CONCLUSION: A higher serum homocysteine concentration and greater AWE indicate FIA instability. Serum homocysteine concentration may be a useful biomarker of FIA instability; however, this needs to be verified in future studies.

Light-Augmented Multi-ion Interaction in MXene Membrane for Simultaneous Water Treatment and Osmotic Power Generation.

The mixing of wastewater and natural water releases abundant osmotic energy. Harvesting this energy could significantly reduce the energy and economic cost of water treatment, leading to sustainable wastewater treatment technology. Yet, such energy harvesting is highly challenging because it requires a material that is highly permeable to nontoxic ions while rejecting toxic ions in wastewater to reach high power density and prevent environmental pollution. In this work, we demonstrate that a light-augmented biomimetic multi-ion interaction in an MXene membrane can simultaneously realize high permeability of Na+ ions for enhanced osmotic power generation and high selectivity to heavy metal ions up to a ratio of 2050 for wastewater treatment. The Na+ permeability is enhanced by the photothermal effect of the MXene membrane. The transport of heavy metal ions, however, is suppressed because, under angstrom-confinement, heavy metal ions are strongly electrostatically repelled by the increased number of permeating Na+ ions. As a result, the membrane can stably generate osmotic power from simulated industrial wastewater, and the power density can be enhanced by 4 times under light illumination of approximate 1 sun intensity. This work highlights the importance of multi-ion interaction for the transport properties of ionic materials, which remains rarely investigated and poorly understood in previous studies.

A deep learning framework for intracranial aneurysms automatic segmentation and detection on magnetic resonance T1 images.

OBJECTIVES: To design a deep learning-based framework for automatic segmentation and detection of intracranial aneurysms (IAs) on magnetic resonance T1 images and test the robustness and performance of framework. METHODS: A retrospective diagnostic study was conducted based on 159 IAs from 136 patients who underwent the T1 images. Among them, 127 cases were randomly selected for training and validation, and 32 cases were used to assess the accuracy and consistency of our algorithm. We developed and assembled three convolutional neural networks for the segmentation and detection of IAs. The segmentation and detection performance of the model were compared with the ground truth, and various metrics were calculated at the voxel level, IAs level, and patient level to show the performance of our framework. RESULTS: Our assembled model achieved overall Dice, voxel-level sensitivity, specificity, balanced accuracy, and F1 score of 0.802, 0.874, 0.9998, 0.937, and 0.802, respectively. A coincidence greater than 0.7 between the aneurysms predicted by the model and the ground truth was considered as a true positive. For IAs detection, the sensitivity reached 90.63% with 0.58 false positives per case. The volume of IAs segmented by our model showed a high agreement and consistency with the volume of IAs labeled by experts. CONCLUSION: The deep learning framework is achievable and robust for IAs segmentation and detection. Our model offers more clinical application opportunities compared to digital subtraction angiography (DSA)-based, CTA-based, and MRA-based methods. CLINICAL RELEVANCE STATEMENT: Our deep learning framework effectively detects and segments intracranial aneurysms using clinical routine T1 sequences, showing remarkable effectiveness and offering great potential for improving the detection of latent intracranial aneurysms and enabling early identification. KEY POINTS: •There is no segmentation method based on clinical routine T1 images. Our study shows that the proper deep learning framework can effectively localize the intracranial aneurysms. •The T1-based segmentation and detection method is more universal than other angiography-based detection methods, which can potentially reduce missed diagnoses caused by the absence of angiography images. •The deep learning framework is robust and has the potential to be applied in a clinical setting.

Statins may Decrease Aneurysm wall Enhancement of Unruptured Fusiform Intracranial Aneurysms: A high-resolution 3T MRI Study.

Inflammation plays an integral role in the formation, growth, and progression to rupture of unruptured intracranial aneurysms. Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) has emerged as a surrogate biomarker of vessel wall inflammation and unruptured intracranial aneurysm instability. We investigated the correlation between anti-inflammatory drug use and three-dimensional AWE of fusiform intracranial aneurysms (FIAs). We retrospectively analyzed consecutive patients with FIAs in our database who underwent 3T HR-MRI at three Chinese centers. FIAs were classified as fusiform-type, dolichoectatic-type, or transitional-type. AWE was objectively defined using the aneurysm-to-pituitary stalk contrast ratio in three-dimensional space by determining the contrast ratio of the average signal intensity in the aneurysmal wall and pituitary stalk on post-contrast T1-weighted images. Data on aneurysm size, morphology, and location, as well as patient demographics and comorbidities, were collected. Univariate and multivariate logistic regression analyses were performed to determine factors independently associated with AWE of FIAs on HR-MRI. In total, 127 FIAs were included. In multivariate analysis, statin use (ß = -0.236, P = 0.007) was the only independent factor significantly associated with decreased AWE. In the analysis of three FIA subtypes, the fusiform and transitional types were significantly associated with statin use (rs = -0.230, P = 0.035; and rs = -0.551, P = 0.010; respectively). It establishes an incidental correlation between the use of statins daily for ≥ 6 months and decreased AWE of FIAs. The findings also indicate that the pathophysiology may differ among the three FIA subtypes.

Two-Dimensional Sodium Channels with High Selectivity and Conductivity for Osmotic Power Generation from Wastewater.

Conducting target ions rapidly while rejecting rival ions efficiently is challenging yet highly demanded for ion separation related applications. Two-dimensional (2D) channels are widely used for ion separation, but highly selective 2D channels generally suffer from a relatively low ionic conductivity. Here we report that the 2D vermiculite channels have a Na+ conductivity higher than bulk and at the same time reject heavy metal ions with a selectivity of a few hundreds. Such performance is attributed to the highly electronegative crystal surface and the extremely narrow channel (0.2 nm high), as also supported by the ab initio molecular dynamics simulation. We demonstrate that the highly selective and conductive sodium channels can be utilized to harvest osmotic power from industrial wastewater, achieving a power density of more than 20 W m-2 while preventing pollution from waste heavy metal ions. This work provides a strategy for wastewater utilization as well as treatment. Moreover, the investigation suggests the possibility to break the ionic permeability-selectivity trade-off by combining Ångstrom-scale confinement with proper surface engineering, which could lead to applications that are challenging for previous materials.

Janus carbon nitride membrane for robust and enhanced nanofluidic power generation from wastewater.

Nanofluidic membranes have shown great promise in harvesting osmotic power. Yet, previous studies extensively focused on osmotic energy released by the mixing of seawater and river water, while there exist many other osmotic energy sources, such as the mixing of wastewater with other water. However, harvesting the osmotic power of wastewater is highly challenging because it requires the membranes to have environmental remediation capabilities to avoid pollution and biofouling, which has not been satisfied by previous nanofluidic materials. In this work, we demonstrate that a Janus carbon nitride membrane can be used for simultaneous power generation and water purification. The Janus structure of the membrane generates asymmetric band structure and therefore a built-in electric field, facilitating electron-hole separation. As a result, the membrane shows strong photocatalytic capability, which efficiently degrades organic pollutants and kills microorganisms. In particular, the built-in electric field also facilitates ionic transport, significantly promoting the osmotic power density up to 30 W/m2 under simulated sunlight illumination. The power generation performance can be robustly kept with or without the presence of pollutants. This study will shed light on the development of multi-functional power generation materials for the comprehensive utilization of industrial wastewater as well as domestic sewage.

Three-dimensional aneurysm wall enhancement in fusiform intracranial aneurysms is associated with aneurysmal symptoms.

Background and purpose: Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) is a potential biomarker for evaluating unstable aneurysms. Fusiform intracranial aneurysms (FIAs) frequently have a complex and curved structure. We aimed to develop a new three-dimensional (3D) aneurysmal wall enhancement (AWE) characterization method to enable comprehensive FIA evaluation and to investigate the ability of 3D-AWE to predict symptomatic FIA. Methods: We prospectively recruited patients with unruptured FIAs and received 3 T HR-MRI imaging from September 2017 to January 2019. 3D models of aneurysms and parent arteries were generated. Boundaries of the FIA were determined using 3D vessel diameter measurements. Dmax was the greatest diameter in the cross-section, while Lmax was the length of the centerline of the aneurysm. Signal intensity of the FIA was normalized to the pituitary stalk and then mapped onto the 3D model, then the average enhancement (3D-AWEavg), maximum enhancement (3D-AWEmax), enhancement area (AWEarea), and enhancement ratio (AWEratio) were calculated as AWE indicators, and the surface area of the entire aneurysm (Aarea) was also calculated. Areas with high AWE were defined as those with a value >0.9 times the signal intensity of the pituitary stalk. Multivariable logistic regression analyses were performed to determine independent predictors of aneurysm-related symptoms. FIA subtypes were defined as fusiform, dolichoectasia, and transitional. Differences between the three FIA subtypes were also examined. Results: Forty-seven patients with 47 FIAs were included. Mean patient age was 55 ± 12.62 years and 74.5% were male. Twenty-nine patients (38.3%) were symptomatic. After adjusting for baseline differences in age, hypertension, Lmax, and FIA subtype, the multivariate logistics regression models showed that 3D-AWEavg (odds ratio [OR], 4.029; p = 0.019), 3D-AWEmax (OR, 3.437; p = 0.022), AWEarea (OR, 1.019; p = 0.008), and AWEratio (OR, 2.490; p = 0.045) were independent predictors of aneurysm-related symptoms. Dmax and Aarea were larger and 3D-AWEavg, 3D-AWEmax, AWEarea, and AWEratio were higher with the transitional subtype than the other two subtypes. Conclusion: The new 3D AWE method, which enables the use of numerous new metrics, can predict symptomatic FIAs. Different 3D-AWE between the three FIA subtypes may be helpful in understanding the pathophysiology of FIAs.

Systemic immune-inflammation index is associated with aneurysmal wall enhancement in unruptured intracranial fusiform aneurysms.

Introduction: Inflammation plays a key role in the progression of intracranial aneurysms. Aneurysmal wall enhancement (AWE) correlates well with inflammatory processes in the aneurysmal wall. Understanding the potential associations between blood inflammatory indices and AWE may aid in the further understanding of intracranial aneurysm pathophysiology. Methods: We retrospectively reviewed 122 patients with intracranial fusiform aneurysms (IFAs) who underwent both high-resolution magnetic resonance imaging and blood laboratory tests. AWE was defined as a contrast ratio of the signal intensity of the aneurysmal wall to that of the pituitary stalk ≥ 0.90. The systemic immune-inflammation (SII) index (neutrophils × platelets/lymphocytes) was calculated from laboratory data and dichotomized based on whether or not the IFA had AWE. Aneurysmal symptoms were defined as sentinel headache or oculomotor nerve palsy. Multivariable logistic regression and receiver operating characteristic curve analyses were performed to determine how well the SII index was able to predict AWE and aneurysmal symptoms. Spearman's correlation coefficients were used to explore the potential associations between variables. Results: This study included 95 patients, of whom 24 (25.3%) presented with AWE. After adjusting for baseline differences in neutrophil to lymphocyte ratios, leukocytes, and neutrophils in the multivariable logistic regression analysis, smoking history (P = 0.002), aneurysmal symptoms (P = 0.047), maximum diameter (P = 0.048), and SII index (P = 0.022) all predicted AWE. The SII index (P = 0.038) was the only independent predictor of aneurysmal symptoms. The receiver operating characteristic curve analysis revealed that the SII index was able to accurately distinguish IFAs with AWE (area under the curve = 0.746) and aneurysmal symptoms (area under the curve = 0.739). Discussion: An early elevation in the SII index can independently predict AWE in IFAs and is a potential new biomarker for predicting IFA instability.

Aneurysm wall enhancement, atherosclerotic proteins, and aneurysm size may be related in unruptured intracranial fusiform aneurysms.

OBJECTIVE: This cross-sectional study aimed to investigate the associations between aneurysm wall enhancement (AWE), atherosclerotic protein levels, and aneurysm size in unruptured intracranial fusiform aneurysms (IFAs). METHODS: Patients with IFAs underwent high-resolution magnetic resonance imaging (HR-MRI) and atherosclerotic protein examinations from May 2015 to December 2021 were collected. A CRstalk (signal intensity [SI] of IFA wall/SI of pituitary stalk) > 0.60 was considered to indicate AWE. Atherosclerotic protein data was obtained from the peripheral blood. Aneurysmal characteristics included the maximal diameter of the cross-section (Dmax), location, type of IFA, presence of mural thrombus, and mural clots. Statistical analyses were performed with univariate analysis, logistic regression analysis, and Spearman's correlation coefficient. RESULTS: Seventy-one IFAs from 71 patients were included in the study. Multivariate analysis revealed statin use (OR = 0.189, p = 0.026) and apolipoprotein B (Apo-B) level (OR = 6.019, p = 0.026) were the independent predictors of AWE in IFAs. In addition, statin use (OR = 0.813, p = 0.036) and Apo-B level (OR = 1.610, p = 0.003) were also the independent predictors of CRstalk. Additionally, we found that CRstalk and AWE were significantly positively associated with Dmax (rs = 0.409 and 0.349, respectively; p < 0.001 and p = 0.003, respectively). CONCLUSIONS: There may be correlations between AWE, atherosclerotic protein levels, and aneurysm size in patients with IFAs. Apo-B and statin use were independent predictors of AWE in IFAs, which have the potential to be new therapeutic targets for IFAs. KEY POINTS: • There may be correlations between aneurysm wall enhancement, atherosclerotic protein levels in the peripheral blood, and aneurysm size in patients with intracranial fusiform aneurysms. • Apolipoprotein B and statin use were independent predictors of aneurysm wall enhancement in intracranial fusiform aneurysms.

Inflow Angle Impacts Morphology, Hemodynamics, and Inflammation of Side-wall Intracranial Aneurysms.

BACKGROUND: Aneurysm inflow angle has been shown to be associated with hemodynamic changes by computational fluid dynamics. However, these studies were based on single aneurysm model and were limited to side-wall aneurysms. PURPOSE: To investigate the association between inflow angle and morphology, hemodynamic, and inflammation of intracranial side-wall and bifurcation aneurysms. STUDY TYPE: Prospective. POPULATION: A total of 62 patients (aged 58.34 ± 12.39, 44 female) with 59 unruptured side-wall aneurysms and 17 unruptured bifurcation aneurysms were included. FIELD STRENGTH/SEQUENCE: A 3.0 T; 3D fast field echo sequence (TOF-MRA); free-breathing, 3D radio-frequency-spoiled, multi-shot turbo field echo sequence (4D-flow MRI); 3D black-blood T1-weighted volumetric turbo spin echo acquisition sequence (T1 -VISTA) ASSESSMENT: Two neuroradiologists assessed the inflow angle and size for intracranial aneurysms in 3D space with TOF-MRA images. The average and maximum inflow velocity (Vavg-IA , Vmax-IA ), blood flow (Flowavg-IA , Flowmax-IA ), and average wall shear stress (WSSavg-IA ) for aneurysms were assessed from 4D-flow MRI in regions of interest drawn by two neuroradiologists. The aneurysmal wall enhancement (AWE) grades between precontrast and postcontrast T1 -VISTA images were evaluated by three neuroradiologists. STATISTICAL TESTS: Kruskal-Wallis H test, χ2 test, Pearson's correlation coefficient, scatter plots and regression lines, multivariate logistic regression analysis (partial correlation r) were performed. A P < 0.05 was considered statistically significant. RESULTS: The WSSavg-IA (0.52 ± 0.34 vs. 0.27 ± 0.22) and AWE grades (1.38 ± 1.04 vs. 2.02 ± 0.68) between the two inflow angle subgroups of side-wall aneurysms were significantly different. The aneurysm size (rs  = 0.31), WSSavg-IA (rs  = -0.45), and AWE grades (rs  = 0.45) were significantly correlated with inflow angle in side-wall aneurysms. While in bifurcation aneurysms, there were no significant associations between inflow angle and size (P = 0.901), Vavg-IA (P = 0.699), Vmax-IA (P = 0.482), Flowavg-IA (P = 0.550), Flowmax-IA (P = 0.689), WSSavg-IA (P = 0.573), and AWE grades (P = 0.872). DATA CONCLUSION: A larger aneurysm size, a lower WSS and a higher AWE grade were correlated with a larger inflow angle in side-wall aneurysms. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Independent predictors and risk score for intraprocedural rupture during endovascular treatment of small ruptured intracranial aneurysms (<5 mm).

Background and purpose: Intraprocedural rupture (IPR) is a devastating complication of endovascular treatment (EVT). Small-sized and ruptured aneurysms are independent predictors of IPR, which presents a technical challenge during EVT. We aimed to develop a score to quantify the individual patient risk of IPR in the EVT of small (<5 mm) ruptured aneurysms (SRAs). Methods: A retrospective review was conducted to interrogate databases prospectively maintained at two academic institutions in China from January 2009 to October 2016. We collected intraoperative angiograms and medical records to identify independent predictors of IPR using univariate and multivariable analyses. A risk score for IPR was derived using multivariable logistic regression analyses. Results: Of the 290 enrolled patients, IPR occurred in 16 patients (5.5%). The univariate analysis showed that the rate of IPR was significantly higher in patients having aneurysms with a small basal outpouching (SBO), in patients having aneurysms concomitant with adjacent moderate atherosclerotic stenosis (ACAMAS), and in former or current smokers. Multivariate analyses showed that SBO [odds ratio (OR): 3.573; 95% confidence interval (CI): 1.078-11.840; p = 0.037], vascular eloquence (VE; OR: 3.780; 95% CI: 1.080-13.224; p = 0.037), and ACAMAS (OR: 6.086; 95% CI: 1.768-20.955; p = 0.004) were significantly and independently associated with IPR. A three-point risk score (S-V-A) was derived to predict IPR [SBO (yes = 1), VE (yes = 1), and ACAMAS (yes = 1)]. Conclusions: Intraprocedural rupture occurred in 5.5% of the patients during EVT of SRA. SBO, VE, and ACAMAS were independent risk factors of IPR in the EVT of SRA. Based on these variables, the S-V-A score may be useful in predicting IPR daily, but more confirmation studies are required.

Comparisons between cross-section and long-axis-section in the quantification of aneurysmal wall enhancement of fusiform intracranial aneurysms in identifying aneurysmal symptoms.

Background: To investigate the quantification of aneurysmal wall enhancement (AWE) in fusiform intracranial aneurysms (FIAs) and to compare AWE parameters based on different sections of FIAs in identifying aneurysm symptoms. Methods: Consecutive patients were prospectively recruited from February 2017 to November 2019. Aneurysm-related symptoms were defined as sentinel headache and oculomotor nerve palsy. All patients underwent high resolution magnetic resonance imaging (HR-MRI) protocol, including both pre and post-contrast imaging. CRstalk (signal intensity of FIAs' wall divided by pituitary infundibulum) was evaluated both in the cross-section (CRstalk-cross) and the long-axis section (CRstalk-long) of FIAs. Aneurysm characteristics include the maximal diameter of the cross-section (D max), the maximal length of the long-axis section (L max), location, type, and mural thrombus. The performance of parameters for differentiating symptomatic and asymptomatic FIAs was obtained and compared by a receiver operating characteristic (ROC) curve. Results: Forty-three FIAs were found in 43 patients. Eighteen (41.9%) patients who presented with aneurysmal symptoms were classified in the symptomatic group. In univariate analysis, male sex (P = 0.133), age (P = 0.013), FIAs type (P = 0.167), mural thrombus (P = 0.130), L max (P = 0.066), CRstalk-cross (P = 0.027), and CRstalk-long (P = 0.055) tended to be associated with aneurysmal symptoms. In the cross-section model of multivariate analysis, male (P = 0.038), age (P = 0.018), and CRstalk-cross (P = 0.048) were independently associated with aneurysmal symptoms. In the long-axis section model of multivariate analysis, male (P = 0.040), age (P = 0.010), CRstalk-long (P = 0.046), and L max (P = 0.019) were independently associated with aneurysmal symptoms. In the combination model of multivariate analysis, male (P = 0.027), age (P = 0.011), CRstalk-cross (P = 0.030), and L max (P = 0.020) were independently associated with aneurysmal symptoms. CRstalk-cross has the highest accuracy in predicting aneurysmal symptoms (AUC = 0.701). The combination of CRstalk-cross and L max exhibited the highest performance in discriminating symptomatic from asymptomatic FIAs (AUC = 0.780). Conclusion: Aneurysmal wall enhancement is associated with symptomatic FIAs. CRstalk-cross and L max were independent risk factors for aneurysmal symptoms. The combination of these two factors may improve the predictive performance of aneurysmal symptoms and may also help to stratify the instability of FIAs in future studies.

Quantification of aneurysm wall enhancement in intracranial fusiform aneurysms and related predictors based on high-resolution magnetic resonance imaging: a validation study.

Background: Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) has emerged as a new imaging biomarker of intracranial aneurysm instability. Objective: To determine a standard method of AWE quantification for predicting fusiform intracranial aneurysms (FIAs) stability by comparing the sensitivity of each parameter in identifying symptomatic FIAs. The predictors of AWE and FIA types were also identified. Methods: We retrospectively analyzed consecutive fusiform aneurysm patients who underwent HR-MRI from two centers. The aneurysm-to-pituitary stalk contrast ratio (CRstalk), aneurysm enhancement ratio, and aneurysm enhancement index were extracted, and their sensitivities in discriminating aneurysm symptoms were compared using the receiver-operating characteristic curve. Morphological parameters of fusiform aneurysm were extracted based on 3D vessel model. Uni- and multivariate analyses of related predictors for AWE, CRstalk, and FIA types were performed, respectively. Results: Overall, 117 patients (mean age, 53.3 ± 11.7 years; male, 75.2%) with 117 FIAs underwent HR-MRI were included. CRstalk with the maximum signal intensity (CRstalk-max) had the highest sensitivity in identifying symptomatic FIAs with an area under the curve value (0.697) and a cut-off value of 0.90. The independent predictors of AWE were aneurysm symptoms [(odds ratio) OR = 3.754, p = 0.003], aspirin use (OR = 0.248, p = 0.037), and the maximum diameter of the cross-section (OR = 1.171, p = 0.043). The independent predictors of CRstalk-max were aneurysm symptoms (OR = 1.289, p = 0.003) and posterior circulation aneurysm (OR = 1.314, p = 0.001). Transitional-type showed higher rates of hypertension and mural thrombus over both dolichoectatic- and fusiform-type FIAs. Conclusion: CRstalk-max may be the most reliable parameter to quantify AWE to distinguish symptomatic FIAs. It also has the potential to identify unstable FIAs. Several factors contribute to the complex pathophysiology of FIAs and need further validation in a larger cohort.

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.