Stability of unruptured intracranial aneurysms in the anterior circulation: nomogram models for risk assessment

A Decision Tree Model to Help Treatment Decision-Making for Unruptured Intracranial Aneurysms: A Multi-center, Long-Term Follow-up Study in a Large Chinese Cohort

Chinese population have a high prevalence of unruptured intracranial aneurysm (UIA). Clinical and imaging risk factors predicting UIA growth or rupture are poorly understood in the Chinese population due to the lack of large-scale longitudinal studies, and the treatment decision for UIA patients was challenging. Develop a decision tree (DT) model for UIA instability, and validate its performance in multi-center studies. Single-UIA patients from two prospective, longitudinal multicenter cohort studies were analyzed, and set as the development cohort and validation cohort. The primary endpoint was UIA instability (rupture, growth, or morphological change). A DT was established within the development cohort and validated within the validation cohort. The performance of clinicians in identifying unstable UIAs before and after the help of the DT was compared using the area under curve (AUC). The development cohort included 1270 patients with 1270 UIAs and a follow-up duration of 47.2 ± 15.5 months. Aneurysm instability occurred in 187 (14.7%) patients. Multivariate Cox analysis revealed hypertension (hazard ratio [HR], 1.54; 95%CI, 1.14-2.09), aspect ratio (HR, 1.22; 95%CI, 1.17-1.28), size ratio (HR, 1.31; 95%CI, 1.23-1.41), bifurcation configuration (HR, 2.05; 95%CI, 1.52-2.78) and irregular shape (HR, 4.30; 95%CI, 3.19-5.80) as factors of instability. In the validation cohort (n = 106, 12 was unstable), the DT model incorporating these factors was highly predictive of UIA instability (AUC, 0.88 [95%CI, 0.79-0.97]), and superior to existing UIA risk scales such as PHASES and ELAPSS (AUC, 0.77 [95%CI, 0.67-0.86] and 0.76 [95%CI, 0.66-0.86], P < 0.001). Within all 1376 single-UIA patients, the use of the DT significantly improved the accuracy of junior neurosurgical clinicians to identify unstable UIAs (AUC from 0.63 to 0.82, P < 0.001). The DT incorporating hypertension, aspect ratio, size ratio, bifurcation configuration and irregular shape was able to predict UIA instability better than existing clinical scales in Chinese cohorts. CLINICAL TRIAL REGISTRATION: IARP-CP cohort were included (unique identifier: ChiCTR1900024547. Published July 15, 2019. Completed December 30, 2020), with 100-Project phase-I cohort (unique identifier: NCT04872842, Published May 5, 2021. Completed November 8, 2022) as the development cohort. The 100-Project phase-II cohort (unique identifier: NCT05608122. Published November 8, 2022) as the validation cohort.

Serum Interleukin-1 Levels Are Associated with Intracranial Aneurysm Instability

Serum interleukin-1 (IL-1) are possibly indicative of the inflammation in the intracranial aneurysm (IA) wall. This study aimed to investigate whether IL-1 could discriminate the unstable IAs (ruptured intracranial aneurysms (RIAs) and symptomatic unruptured intracranial aneurysms (UIAs)) from stable, asymptomatic UIAs. IA tissues and blood samples from 35 RIA patients and 35 UIA patients were collected between January 2017 and June 2020 as the derivation cohort. Blood samples from 211 patients with UIAs were collected between January 2021 and June 2022 as the validation cohort (including 63 symptomatic UIAs). Blood samples from 35 non-cerebral-edema meningioma patients (non-inflammatory control) and 19 patients with unknown-cause subarachnoid hemorrhage (hemorrhagic control) were also collected. IL-1β and IL-1.ra (IL-1 receptor antagonist) were measured in serum and IA tissues, and the IL-1 ratio was calculated as log10 (IL-1.ra/IL-1β). Based on the derivation cohort, multivariate logistic analysis showed that IL-1β (odds ratio, 1.48, P = 0.001) and IL-1.ra (odds ratio, 0.74, P = 0.005) were associated with RIAs. The IL-1 ratio showed an excellent diagnostic accuracy for RIAs (c-statistic, 0.91). Histological analysis confirmed the significant correlation of IL-1 between serum and aneurysm tissues. IL-1 ratio could discriminate UIAs from non-inflammatory controls (c-statistic, 0.84), and RIAs from hemorrhagic controls (c-statistic, 0.95). Based on the validation cohort, the combination of IL-1 ratio and PHASES score had better diagnostic accuracy for symptomatic UIAs than PHASES score alone (c-statistic, 0.88 vs 0.80, P < 0.001). Serum IL-1 levels correlate with aneurysm tissue IL-1 levels and unstable aneurysm status, and could serve as a potential biomarker for IA instability.

Nomograms for assessing the rupture risk of anterior choroid artery aneurysms based on clinical, morphological, and hemodynamic features

Background and purpose

A notable prevalence of subarachnoid hemorrhage is evident among patients with anterior choroidal artery aneurysms in clinical practice. To evaluate the risk of rupture in unruptured anterior choroidal artery aneurysms, we conducted a comprehensive analysis of risk factors and subsequently developed two nomograms.

Methods

A total of 120 cases of anterior choroidal artery aneurysms (66 unruptured and 54 ruptured) from 4 medical institutions were assessed utilizing computational fluid dynamics (CFD) and digital subtraction angiography (DSA). The training set, consisting of 98 aneurysms from 3 hospitals, was established, with an additional 22 cases from the fourth hospital forming the external validation set. Statistical differences between the two data sets were thoroughly compared. The significance of 9 clinical baseline characteristics, 11 aneurysm morphology parameters, and 4 hemodynamic parameters concerning aneurysm rupture was evaluated within the training set. Candidate selection for constructing the nomogram models involved regression analysis and variance inflation factors. Discrimination, calibration, and clinical utility of the models in both training and validation sets were assessed using area under curves (AUC), calibration plots, and decision curve analysis (DCA). The DeLong test, net reclassification index (NRI), and integrated discrimination improvement (IDI) were employed to compare the effectiveness of classification across models.

Results

Two nomogram models were ultimately constructed: model 1, incorporating clinical, morphological, and hemodynamic parameters (C + M + H), and model 2, relying primarily on clinical and morphological parameters (C + M). Multivariate analysis identified smoking, size ratio (SR), normalized wall shear stress (NWSS), and average oscillatory shear index (OSIave) as optimal candidates for model development. In the training set, model 1 (C + M + H) achieved an AUC of 0.795 (95% CI: 0.706 ~ 0.884), demonstrating a sensitivity of 95.6% and a specificity of 54.7%. Model 2 (C + M) had an AUC of 0.706 (95% CI: 0.604 ~ 0.808), with corresponding sensitivity and specificity of 82.4 and 50.3%, respectively. Similarly, AUCs for models 1 and 2 in the external validation set were calculated to be 0.709 and 0.674, respectively. Calibration plots illustrated a consistent correlation between model evaluations and real-world observations in both sets. DCA demonstrated that the model incorporating hemodynamic parameters offered higher clinical benefits. In the training set, NRI (0.224, p = 0.007), IDI (0.585, p = 0.002), and DeLong test (change = 0.089, p = 0.008) were all significant. In the external validation set, NRI, IDI, and DeLong test statistics were 0.624 (p = 0.063), 0.572 (p = 0.044), and 0.035 (p = 0.047), respectively.

Conclusion

Multidimensional nomograms have the potential to enhance risk assessment and patient-specific treatment of anterior choroidal artery aneurysms. Validated by an external cohort, the model incorporating clinical, morphological, and hemodynamic features may provide improved classification of rupture states.

The markers and risk stratification model of intracranial aneurysm instability in a large Chinese cohort

Intracranial aneurysm is the leading cause of nontraumatic subarachnoid hemorrhage. Evaluating the unstable (rupture and growth) risk of aneurysms is helpful to guild decision-making for unruptured intracranial aneurysms (UIA). This study aimed to develop a model for risk stratification of UIA instability. The UIA patients from two prospective, longitudinal multicenter Chinese cohorts recruited from January 2017 to January 2022 were set as the derivation cohort and validation cohort. The primary endpoint was UIA instability, comprising aneurysm rupture, growth, or morphology change, during a 2-year follow-up. Intracranial aneurysm samples and corresponding serums from 20 patients were also collected. Metabolomics and cytokine profiling analysis were performed on the derivation cohort (758 single-UIA patients harboring 676 stable UIAs and 82 unstable UIAs). Oleic acid (OA), arachidonic acid (AA), interleukin 1β (IL-1β), and tumor necrosis factor-α (TNF-α) were significantly dysregulated between stable and unstable UIAs. OA and AA exhibited the same dysregulated trends in serums and aneurysm tissues. The feature selection process demonstrated size ratio, irregular shape, OA, AA, IL-1β, and TNF-α as features of UIA instability. A machine-learning stratification model (instability classifier) was constructed based on radiological features and biomarkers, with high accuracy to evaluate UIA instability risk (area under curve (AUC), 0.94). Within the validation cohort (492 single-UIA patients harboring 414 stable UIAs and 78 unstable UIAs), the instability classifier performed well to evaluate the risk of UIA instability (AUC, 0.89). Supplementation of OA and pharmacological inhibition of IL-1β and TNF-α could prevent intracranial aneurysms from rupturing in rat models. This study revealed the markers of UIA instability and provided a risk stratification model, which may guide treatment decision-making for UIAs.

m6A regulator–mediated RNA methylation modification patterns and immune microenvironment infiltration characterization in patients with intracranial aneurysms

Background

The role of epigenetic modulation in immunity is receiving increased recognition—particularly in the context of RNA N6-methyladenosine (m6A) modifications. Nevertheless, it is still uncertain whether m6A methylation plays a role in the onset and progression of intracranial aneurysms (IAs). This study aimed to establish the function of m6A RNA methylation in IA, as well as its correlation with the immunological microenvironment.

Methods

Our study included a total of 97 samples (64 IA, 33 normal) in the training set and 60 samples (44 IA, 16 normal) in the validation set to systematically assess the pattern of RNA modifications mediated by 22 m6A regulators. The effects of m6A modifications on immune microenvironment features, i.e., immune response gene sets, human leukocyte antigen (HLA) genes, and infiltrating immune cells were explored. We employed Lasso, machine learning, and logistic regression for the purpose of identifying an m6A regulator gene signature of IA with external data validation. For the unsupervised clustering analysis of m6A modification patterns in IA, consensus clustering methods were employed. Enrichment analysis was used to assess immune response activity along with other functional pathways. The identification of m6A methylation markers was identified based on a protein–protein interaction network and weighted gene co-expression network analysis.

Results

We identified an m6A regulator signature of IGFBP2, IGFBP1, IGF2BP2, YTHDF3, ALKBH5, RBM15B, LRPPRC, and ELAVL1, which could easily distinguish individuals with IA from healthy individuals. Unsupervised clustering revealed three m6A modification patterns. Gene enrichment analysis illustrated that the tight junction, p53 pathway, and NOTCH signaling pathway varied significantly in m6A modifier patterns. In addition, the three m6A modification patterns showed significant differences in m6A regulator expression, immune microenvironment, and bio-functional pathways. Furthermore, macrophages, activated T cells, and other immune cells were strongly correlated with m6A regulators. Eight m6A indicators were discovered—each with a statistically significant correlation with IA—suggesting their potential as prognostic biological markers.

Conclusion

Our study demonstrates that m6A RNA methylation and the immunological microenvironment are both intricately correlated with the onset and progression of IA. The novel insight into patterns of m6A modification offers a foundation for the development of innovative treatment approaches for IA.

Human "live cadaver" neurovascular model for proximal and distal mechanical thrombectomy in stroke

BACKGROUND

Preclinical testing platforms that accurately replicate complex human cerebral vasculature are critical to advance neurointerventional knowledge, tools, and techniques. Here, we introduced and validated a human "live cadaveric" head-and-neck neurovascular model optimized for proximal and distal vascular occlusion and recanalization techniques.

METHODS

Human cadaveric head-and-neck specimens were cannulated bilaterally in the jugular veins, carotid, and vertebral arteries. Specimens were then coupled with modular glass models of the aorta and extracranial carotid arteries, as well as radial and femoral access ports. Intracranial physiological flow was simulated using a flow-delivery system and blood-mimicking fluid. Baseline anatomy, histological, and mechanical properties of cerebral arteries were compared with those of fresh specimens. Radiopaque clot analogs were embolized to replicate proximal and distal arterial occlusions, followed by thrombectomy. Experienced interventionalists scored the model on different aspects.

RESULTS

Compared with counterpart fresh human arteries, formalin-fixed arteries showed similar mechanical properties, including maximum stretch, increased tensile strength/stiffness, and friction coefficients were also not significantly different. On histology, minimal endothelial damage was noted in arteries after 3 months of light fixation, otherwise the arterial wall maintained the structural integrity. Contrast angiographies showed no micro- or macro-vasculature obstruction. Proximal and distal occlusions created within the middle cerebral arteries were consistently obtained and successfully recanalized. Additionally, interventionists scored the model highly realistic, indicating great similarity to patients' vasculature.

CONCLUSIONS

The human "live cadaveric" neurovascular model accurately replicates the anatomy, mechanics, and hemodynamics of cerebral vasculature and allows the performance of neurointerventional procedures equivalent to those done in patients.