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Introduction: Understanding the relationship between aneurysm wall enhancement (AWE), wall shear stress (WSS), and wall tension (WT) across different brain aneurysm compartments may improve the assessment of rupture risk and vessel wall dynamics. Our comprehensive analysis aimed to evaluate these characteristics across different brain aneurysm compartments., Methods: Patients with intracranial aneurysms underwent 3-T high-resolution magnetic resonance imaging (MRI). T1-weighted images were obtained before and after administering gadolinium (Gd) contrast. 3D segmentations of the aneurysms were generated using 3D Slicer. AWE was quantified based on the signal intensity of the aneurysm wall on T1+Gd images. Finite element analysis calculated WT, while computational fluid dynamics assessed WSS metrics, including time-averaged wall shear stress (TAWSS), wall shear stress gradient (WSSG), and oscillatory shear index (OSI). AWE, WT, and WSS metrics were compared among aneurysms compartments and aneurysms stratified by size, aspect ratio (AR), and size ratio (SR)., Results: AWE was elevated in aneurysms with greater size and AR. WT and OSI were higher in aneurysms with larger sizes and higher AR and SR. Aneurysm necks exhibited higher WT, TAWSS, and WSSG compared to the aneurysm body. Irregular aneurysms displayed lower TAWSS, WSSG, and higher OSI in areas of high AWE. The bleb had the highest AWE and lowest WT and WSSG, while necks showed the lowest AWE and highest WT and WSSG., Conclusion: Aneurysm necks typically exhibit high WT and WSS, while the body often shows low WSS. Blebs express elevated AWE alongside diminished WSS and WT which potentially increases rupture risk KEY POINTS: Question Areas of high wall enhancement in irregular aneurysms are characterized by low wall sheer stress and high oscillatory sheer index. Findings High risk structures such as daughter sacs exhibit the highest wall enhancement and lowest wall sheer stress. Clinical relevance Comprehensive morphomechanical and wall enhancement analysis of brain aneurysms have the potential to offer valuable new insights into aneurysm biology., Competing Interests: Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Doctor Edgar Samaniego. Conflict of interest: The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. Statistics and biometry: No complex statistical methods were necessary for this paper. Informed consent: Written informed consent was waived by the Institutional Review Board because of the retrospective nature of the study. Ethical approval: Institutional Review Board approval was obtained – (IRB: 201803866). Study subjects or cohorts overlap: None study subjects or cohorts have been previously reported. Methodology: Retrospective Observational Performed at one institution, (© 2025. The Author(s), under exclusive licence to European Society of Radiology.)

Aneurysm wall enhancement (AWE) has the potential to be used as an imaging biomarker for the risk stratification of intracranial aneurysms (IAs). Radiomics provides a refined approach to quantify and further characterize AWE's textural features. This study examines the performance of AWE quantification combined with clinical information in detecting symptomatic IAs. Ninety patients harboring 104 IAs (29 symptomatic and 75 asymptomatic) underwent high-resolution magnetic resonance imaging (HR-MRI). The assessment of AWE was performed using two different methods: 3D-AWE mapping and composite radiomics-based score (RadScore). The dataset was split into training and testing subsets. The testing set was used to build two different nomograms using each modality of AWE assessment combined with patients' clinical information and aneurysm morphological data. Finally, each nomogram was evaluated on an independent testing set. A total of 22 radiomic features were significantly different between symptomatic and asymptomatic IAs. The 3D-AWE mapping nomogram achieved an area under the curve (AUC) of 0.77 (63% accuracy, 78% sensitivity, and 58% specificity). The RadScore nomogram exhibited a better performance, achieving an AUC of 0.83 (77% accuracy, 89% sensitivity, and 73% specificity). The comprehensive analysis of IAs with the quantification of AWE data through radiomic analysis, patient clinical information, and morphological aneurysm metrics achieves a high accuracy in detecting symptomatic IA status., Competing Interests: Declarations. Ethical Approval: Institutional Review Board number 202310190 was obtained for this retrospective analysis. Informed consent was not required for the study. Conflict of Interest: The authors declare no competing interests. Disclosures: SSV, AS, DJO, ES, SS, AG: None EIL: Board Membership: Stryker, NeXtGen Biologics, MedX Health, Cog-nition Medical, EndoStream; Consultancy: Claret Medical, GLG Con-sulting, Guidepoint, Imperative Care, Medtronic, Rebound Therapeu-tics, StimMed; Employment: University at Buffalo Neurosurgery Inc;Expert Testimony: renders medical/legal opinions as an expert witness;Stock/Stock Options: NeXtGen Biologics, Cognition Medical, RapidMedical, Claret Medical, Imperative Care, Rebound Therapeutics,StimMed AHS: inancial interest/investor/stock options/ownership: Adona Medical, Inc., Amnis Therapeutics, BlinkTBI, Inc.,Boston Scientific Corp. (for purchase of Claret Medical), BuffaloTechnology Partners, Inc., Cardinal Consultants, LLC, CerebrotechMedical Systems, Inc., Cognition Medical, Endostream Medical,Ltd, Imperative Care, Inc., International Medical Distribution Part-ners, Neurovascular Diagnostics, Inc., Q’Apel Medical, Inc., RadicalCatheter Technologies, Inc., Rebound Therapeutics Corp. (purchased2019 by Integra Lifesciences, Corp.), Rist Neurovascular, Inc., SenseDiagnostics, Inc., Serenity Medical, Inc., Silk Road Medical, Spin-naker Medical, Inc., StimMed, Synchron, Three Rivers Medical, Inc.,Vastrax, LLC, VICIS, Inc., Viseon, Inc.; consultant/advisory board:Amnis Therapeutics, Boston Scientific, Canon Medical Systems USA,Inc., Cerebrotech Medical Systems, Inc., Cerenovus, Corindus, Inc.,Endostream Medical, Ltd, Imperative Care, Inc., Integra LifeSciencesCorp., Medtronic, MicroVention, Minnetronix Neuro, Inc., North-west University—DSMB Chair for HEAT Trial, Penumbra, Q’ApelMedical, Inc., Rapid Medical, Rebound Therapeutics Corp., SerenityMedical, Inc., Silk Road Medical, StimMed, Stryker, Three RiversMedical, Inc., VasSol, W.L. Gore & Associates; national PI/steeringcommittees: Cerenovus LARGE trial and ARISE II trial, MedtronicSWIFT PRIME and SWIFT DIRECT trials, MicroVention FRED Trialand CONFIDENCE study, MUSC POSITIVE trial, Penumbra 3D Sep-arator trial, COMPASS trial, INVEST trial; research grants: co-inves-tigator, NIH/NINDS 1R01NS091075 Virtual Intervention of Intracra-nial Aneurysms; role: co-principal investigator, NIH-NINDS R21NS109575-01 Optimizing Approaches to Endovascular Therapy ofAcute Ischemic Stroke VMT: Financial interest/investor/stockoptions/ownership: Neurovascular Diagnostics, Inc., QAS.AI, Inc.;Consultant/advisory board: Canon Medical Systems USA; Researchgrants: Principal investigator, National Science Foundation Award No.1746694 and NIH NINDS award R43 NS115314-0; awardee of a Brain Aneurysm Foundation grant, a Center for Advanced Technology grant, and a Cummings Foundation grant EAS: Consultant for Medtronic, Microvention, Cerenovus, iSchemaView, and Rapid Medical, (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Despite advancements in acute management, morbidity rates for subarachnoid hemorrhage (SAH) remain high. Therefore, it is imperative to utilize standardized outcome scales in SAH research for evaluating new therapies effectively. This review offers a comprehensive overview of prevalent scales and clinical outcomes used in SAH assessment, accompanied by recommendations for their application and prognostic accuracy. Standardized terminology and diagnostic criteria should be employed when reporting pathophysiological outcomes such as symptomatic vasospasm and delayed cerebral ischemia. Furthermore, integrating clinical severity scales like the World Federation of Neurosurgical Societies scale and modified Fisher score into clinical trials is advised to evaluate their prognostic significance, despite their limited correlation with outcomes. The modified Rankin score is widely used for assessing functional outcomes, while the Glasgow outcome scale-extended version is suitable for broader social and behavioral evaluations. Avoiding score dichotomization is crucial to retain valuable information. Cognitive and behavioral outcomes, though frequently affected in patients with favorable neurological outcomes, are often overlooked during follow-up outpatient visits, despite their significant impact on quality of life. Comprehensive neuropsychological evaluations conducted by trained professionals are recommended for characterizing cognitive function, with the Montreal Cognitive Assessment serving as a viable screening tool. Additionally, integrating psychological inventories like the Beck Depression and Anxiety Inventory, along with quality-of-life scales such as the Stroke-Specific Quality of Life Scale, can effectively assess behavioral and quality of life outcomes in SAH studies., Competing Interests: Declarations. Conflict of Interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Emerging evidence indicates that aneurysmal subarachnoid hemorrhage (aSAH) elicits a response from both innate and adaptive immune systems. An upregulation of CD8 + CD161 + cells has been observed in the cerebrospinal fluid (CSF) after aSAH, yet the precise role of these cells in the context of aSAH is unkown. CSF samples from patients with aSAH and non-aneurysmal SAH (naSAH) were analyzed. Single-cell RNA sequencing (scRNAseq) was performed on CD8 + CD161 + sorted samples from aSAH patients. Cell populations were identified using "clustering." Gene expression levels of ten previously described genes involved in inflammation were quantified from aSAH and naSAH samples using RT-qPCR. The study focused on the following genes: CCL5, CCL7, APOE, SPP1, CXCL8, CXCL10, HMOX1, LTB, MAL, and HLA-DRB1. Gene clustering analysis revealed that monocytes, NK cells, and T cells expressed CD8 + CD161 + in the CSF of patients with aSAH. In comparison to naSAH samples, aSAH samples exhibited higher mRNA levels of CXCL10 (median, IQR = 90, 16-149 vs. 0.5, 0-6.75, p = 0.02). A trend towards higher HMOX1 levels was also observed in aSAH (median, IQR = 12.6, 9-17.6 vs. 2.55, 1.68-5.7, p = 0.076). Specifically, CXCL10 and HMOX1 were expressed by the monocyte subpopulation. Monocytes, NK cells, and T cells can potentially express CD8 + CD161 + in patients with aSAH. Notably, monocytes show high levels of CXCL10. The elevated expression of CXCL10 in aSAH compared to naSAH indicates its potential significance as a target for future studies., Competing Interests: Declarations. Ethics Approval: The Institutional Review Board of the University of Iowa approved this study under IRASH (IRB ID number: 201902739). Informed Consent: Informed Consent was acquired for every patient under supervision of the Institutional Review Board of the University of Iowa. Competing Interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Blebs significantly increase rupture risk of intracranial aneurysms. Radiomic analysis offers a robust characterization of the aneurysm wall. However, the unique radiomic profile of various compartments, including blebs, remains unexplored. Likewise, the correlation between these imaging markers and fluid/mechanical metrics is yet to be investigated. To address this, we analyzed the radiomic features (RFs) of bleb-containing aneurysms and their relationship with wall tension and shear stress metrics, aiming to enhance risk assessment., Methods: Aneurysms were imaged using high-resolution magnetic resonance imaging (MRI). A T1 and a T1 after contrast (T1+Gd) sequences were acquired. 3D models of aneurysm bodies and blebs were generated, and RFs were extracted. Aneurysms with and without blebs were matched based on location and size for analysis. Univariate regression models and Spearman's correlations were used to establish associations between bleb-dependent RFs and mechanical/fluid dynamics metrics., Results: Eighteen aneurysms with blebs were identified. Fifty-five RFs were significantly different between blebs and body within the same aneurysms. Of these RFs, 9% (5/55) were first-order, and 91% (50/55) were second-order features. After aneurysms with and without blebs were matched for location and size, five RFs 5% (5/93) were significantly different. Forty-one out of the 55 RFs different between bleb and body sac of the primary aneurysm were moderately and strongly correlated with mechanical and fluid dynamics metrics., Conclusion: Aneurysm blebs exhibit distinct radiomic profiles compared with the main body of the aneurysm sac. The variability in bleb wall characteristics may arise from differing mechanical stresses and localized hemodynamics. Leveraging radiomic profiling could help identify regions with a heightened risk of rupture., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The volume of hemorrhage is a crucial factor in predicting outcomes following aneurysmal subarachnoid hemorrhage (aSAH). Although grading scales such as the Fisher score are widely used, they can lead to inaccuracies in quantifying the total blood volume because of their reliance on visual assessment. We analyzed a large cohort of patients with aSAH with a semiautomated software for the precise quantification of hemorrhage volume. The primary aim is to identify clear thresholds that correlate with the likelihood of complications after aSAH, thereby enhancing the predictive accuracy and improving patient management strategies., Methods: A semiautomated algorithm was developed to analyze noncontrast computed tomography scans of patients with aSAH. The algorithm categorized tissues into blood, gray matter, white matter, and cerebrospinal fluid, isolating the blood for volume quantification. Receiver operating curve analysis was done to establish thresholds for vasospasm, acute hydrocephalus, shunt-dependent hydrocephalus (SDHC), and death within 7 days., Results: A total of 500 patients with aSAH and their respective aneurysms were analyzed. Hemorrhage volume was significantly higher in patients with vasospasm (21.7 [10.9-41.4] vs. 10.7 [4.2-26.9], p < 0.001), acute hydrocephalus (22.7 [9.2-41.8] vs. 5.1 [2.1-13.5], p < 0.001), SDHC (23.8 [11.3-40.7] vs. 11.7 [4.1-28.2], p < 0.001), and those who died before 7 days (52.8 [34.6-90.6] mL vs. 14.8 [5.0-32.4] mL, p < 0.001) compared with their counterparts. Notably, specific hemorrhage thresholds were identified for each complication: 15.16 mL for vasospasm (65% sensitivity and 60% specificity), 9.95 mL for acute hydrocephalus (74% sensitivity and 69% specificity), 16.76 mL for SDHC (63% sensitivity and 60% specificity), and 33.84 mL for death within 7 days (79% sensitivity and 77% specificity)., Conclusions: Semiautomated blood volume quantification tools could aid in stratifying complication risk after aSAH. Established thresholds for hemorrhage volume related to complications could be used in clinical practice to aid in management decisions., (© 2024. Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society.)

Background and Purpose: The determination of Aneurysm wall enhancement (AWE) by human readers on visual inspection alone is subjective and prone to error. A three-dimensional (3D) method for quantifying the aneurysm wall's signal intensity (SI) enables objective determination of AWE. Inter-reader agreement and agreement between subjective and objective determination of AWE were assessed in this study., Materials and Methods: Patients with saccular intracranial aneurysms (IAs) were imaged with high-resolution MRI. Subjective assessment: Two internal adjudicators visually determined AWE if the degree of enhancement was equal to or higher than the pituitary stalk. An experienced internal neuroradiologist resolved disagreements. This internal adjudication was compared with an external adjudication to assess inter-rater agreement among centers. Objective assessment: The distribution of SI across the aneurysm wall after normalizing the SI to the corpus callosum was determined with an in-house code. The normalized mean SI on post-contrast T1 MRI was defined as 3D-circumferential AWE (3D-CAWE). If the 3D-CAWE value was higher than one, an IA was defined as objectively "enhancing." Inter-rater agreement was analyzed with kappa coefficients. Inter-technique agreement between subjective and objective assessment was performed using kappa statistics. Univariate regressions were performed to identify which morphological characteristics influenced subjective adjudication of enhancement., Results: A total of 113 IAs were analyzed. The agreement of the internal assessment was moderate (k = 0.63), 49.5% of IAs (56) were classified as "enhancing" and 50.5% (57) as "non-enhancing" after consensus. Inter-rater agreement between internal and external adjudication was weak (k = 0.52) for the presence of AWE. There was no agreement between the subjective assessment of AWE and objective 3D-CAWE (k = 0.16, p 0.02). Subjective assessment was less likely to reliably adjudicate enhancement when assessing multiple aneurysms (OR 0.4, 95% CI 0.16 -0.97, p 0.04) and IAs larger than > 7 mm (OR 0.22, 95% CI 0.09 -0.55, p 0.002) despite being objectively "non-enhancing"., Conclusions: Subjective adjudication of AWE has poor inter-rater agreement, and no agreement with an objective 3D method of determining AWE. It is also less likely than objective quantification to identify enhancement in aneurysms larger than 7 mm or when multiple aneurysms are present. Objective 3D quantification, such as the technique used in this study, should therefore be considered when assessing AWE, especially in patients with multiple aneurysms and aneurysms larger than 7 mm in size., Abbreviations: 3D, three-dimensional; 3D-CAWE, three-dimensional circumferential aneurysm wall enhancement; AWE, aneurysm wall enhancement; Gd, gadolinium; HR-MRI, high resolution MRI; HR 3D T1 VWI, high-resolution 3D T1 weighted black blood vessel wall imaging; IA, intracranial aneurysm; SI, signal intensity., Competing Interests: The authors declare no conflicts of interest related to the content of this article., (© 2024 by American Journal of Neuroradiology.)

Introduction: High-resolution magnetic resonance imaging (HR-MRI) allows for detailed visualization of intracranial atherosclerotic plaques. Radiomics can be used as a tool for objective quantification of the plaque's characteristics. We analyzed the radiomics features (RFs) obtained from 7 T HR-MRI of patients with intracranial atherosclerotic disease (ICAD) to determine distinct characteristics of culprit and non-culprit plaques., Methods: Patients with stroke due to ICAD underwent HR-MRI. Culprit plaques in the vascular territory of the stroke were identified. Degree of stenosis, area degree of stenosis and plaque burden were calculated. A three-dimensional segmentation of the plaque was performed, and RFs were obtained. A machine learning model for prediction and identification of culprit plaques using significantly different RFs was evaluated., Results: The study included 33 patients with ICAD as stroke etiology. Univariate analysis revealed 24 RFs in pre-contrast MRI, 21 in post-contrast MRI, 13 RFs that were different between pre and post contrast MRIs. Additionally, six shape-based RFs significantly differed from culprit and non-culprit plaques. The random forest model achieved an accuracy rate of 81% (88% sensitivity and 75% specificity) in identifying culprit plaques in the independent testing dataset. This model successfully identified the culprit plaques in all patients during the testing phase., Discussion: Symptomatic plaques had a distinct signature RFs compared to other plaques within the same subject. A machine learning model built with RFs successfully identified the symptomatic atherosclerotic plaques in most cases. Radiomics is a promising tool for stratification of plaques in patients with ICAD.

The treatment of intracranial aneurysms is dictated by its risk of rupture in the future. Several clinical and radiological risk factors for aneurysm rupture have been described and incorporated into prediction models. Despite the recent technological advancements in aneurysm imaging, linear length and visible irregularity with a bleb are the only radiological measure used in clinical prediction models. The purpose of this article is to summarize both the standard imaging techniques, including their limitations, and the advanced techniques being used experimentally to image aneurysms. It is expected that as our understanding of advanced techniques improves, and their ability to predict clinical events is demonstrated, they become an increasingly routine part of aneurysm assessment. It is important that neurovascular specialists understand the spectrum of imaging techniques available., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Aneurysm wall enhancement (AWE) has the potential to be used as an imaging biomarker for the risk stratification of intracranial aneurysms (IAs). Radiomics provides a refined approach to quantify and further characterize AWE's textural features. This study examines the performance of AWE quantification combined with clinical information in detecting symptomatic IAs., Methods: Ninety patients harboring 104 IAs (29 symptomatic and 75 asymptomatic) underwent high-resolution magnetic resonance imaging (HR-MRI). The assessment of AWE was performed using two different methods: 3D-AWE mapping and composite radiomics-based score (RadScore). The dataset was split into training and testing subsets. The testing set was used to build two different nomograms using each modality of AWE assessment combined with patients' demographic information and aneurysm morphological data. Finally, each nomogram was evaluated on an independent testing set., Results: A total of 22 radiomic features were significantly different between symptomatic and asymptomatic IAs. The 3D-AWE Mapping nomogram achieved an area under the curve (AUC) of 0.77 (63% accuracy, 78% sensitivity and 58% specificity). The RadScore nomogram exhibited a better performance, achieving an AUC of 0.83 (77% accuracy, 89% sensitivity and 73% specificity)., Conclusions: Combining AWE quantification through radiomic analysis with patient demographic data in a clinical nomogram achieved high accuracy in detecting symptomatic IAs.