Ghoche, Maged T.

BACKGROUND AND OBJECTIVES: Aneurysm risk prediction remains an imprecise science that places patients at risk for either over or undertreatment. Machine learning (ML) models may improve clinical practice by adding precision to risk assessment. This study aims to comprehensively assess the current landscape of ML applications in predicting the risk of aneurysm rupture and compare the performance with the widely used PHASES score. METHODS: A systematic review of PubMed, Scopus, and Web of Science was conducted. All studies using ML tools to predict the rupture risk of intracranial aneurysms were included. Meta-analysis was conducted with consideration to the ML algorithms and compared with the PHASES score. RESULTS: Thirty-six studies involving 22 462 patients were included in the final analysis. ML techniques, including 124 models using 25 algorithms, were employed. Among various ML models, while they had comparable diagnostic performance, deep learning exhibited a slightly better performance profile (sensitivity = 0.792, specificity = 0.788, and accuracy = 0.778 in external validation). Based on our analysis, ML, regardless of the algorithm, provides comparable sensitivity (0.743 vs 0.771, P = .60) and higher specificity (0.763 vs 0.507, P < .01) compared with the PHASES score. Consistently, pooling the area under the receiver operating characteristic curve (AUC) for 60 ML models and 5 PHASES score data, ML models exhibited higher AUC (0.84 vs 0.64, P < .01). Using hemodynamic parameters as input for models improved specificity ( P < .01) in the test sets without any significant changes in the sensitivity. The later improvement was not observed in the external validation sets. CONCLUSION: ML techniques have the potential to enhance the prediction of intracranial aneurysm rupture compared with traditional approaches, like the PHASES score. Incorporating hemodynamic parameters may further enhance the accuracy of ML models. Feature prospective studies are required to validate the utility of ML models for clinical integration.

OBJECTIVE Patients with autosomal dominant polycystic kidney disease (ADPKD) have been identified to have a significantly increased risk of developing intracranial aneurysms (IAs). These patients are diagnosed at younger ages and are also at increased risk for IA rupture. The objective of this systematic review and meta-analysis was to identify risk factors associated with IA detection during screening of asymptomatic ADPKD patients. METHODS The authors searched for studies reporting the prevalence of IA among patients with ADPKD screened using MRA, CTA, or DSA on PubMed, Embase, Google Scholar, Scopus, Web of Science, Cochrane Database of Systematic Reviews, and ClinicalTrials.gov prior to August 2023 by using individualized standardized search strategies. Eligibility of all retrieved studies was assessed according to the PRISMA guidelines. Risk of bias of the included observational studies was assessed using the Newcastle-Ottawa Scale. Meta-analysis was performed using a random-effects model. RESULTS Twenty-four observational studies involving 5907 patients with ADPKD were identified for quantitative analysis. The authors observed an overall prevalence of IA of 12.6%. They identified several risk factors for IA with statistically significantly increased odds for unruptured IA (UIA) detection, including female sex (18 studies, OR 1.63, 95% CI 1.37–1.94, I 2 = 0%), family history of either IA or subarachnoid hemorrhage (SAH) (12 studies, OR 2.17, 95% CI 1.68–2.81, I 2 = 0%), family history of SAH (3 studies, OR 2.67, 95% CI 1.25–5.71, I 2 = 66.0%), stage 3 or greater chronic kidney disease (CKD) (4 studies, OR 2.55, 95% CI 1.84–3.54, I 2 = 0%), and hypertension (13 studies, OR 1.41, 95% CI 1.04–1.91, I 2 = 34%). Age > 45 years, family history of ADPKD, smoking status, and presence of liver cysts did not reach statistical significance as risk factors during this meta-analysis. CONCLUSIONS The results of the authors’ meta-analysis suggest increased risk of UIA detection in screening of ADPKD patients who are female, have a family history of IA or SAH, have hypertension, or have moderate or more severe CKD. Given the increased prevalence of IA in ADPKD patients with these risk factors, these patients may stand to benefit from screening for IA early in treatment or at time of diagnosis, even if neurologically asymptomatic.

OBJECTIVE While the relationship between smoking and subarachnoid hemorrhage is well established, data regarding the probability of detecting unruptured intracranial aneurysms (UIAs) in smokers remain sparse. The aim of this systematic review and meta-analysis is to provide a comprehensive understanding of the relationship between smoking and the likelihood of identifying UIAs in healthy asymptomatic patients who underwent brain imaging for indications unrelated to UIAs. METHODS A systematic review was conducted following the PRISMA guidelines. The PubMed and Scopus databases were searched for studies published before March 2024 that reported on the presence of UIAs in healthy asymptomatic patients who had undergone brain imaging for indications unrelated to UIAs. Three independent reviewers assessed the eligibility of all retrieved studies. Risk of bias for the included observational studies was assessed using the methodological index for non-randomized studies. Data on UIA prevalence, smoking status, and patient and aneurysm characteristics were extracted. The association between smoking and the presence of UIA was studied. A prevalence proportional meta-analysis was conducted across the included studies. A meta-analysis was performed with a random-effects model by using summary statistics from the included studies. RESULTS Six studies involving 47,788 patients who had undergone brain imaging were identified for quantitative analysis. The pooled UIA prevalence in the sample was 3.07% (95% CI 2.27%–4.16%). Patients who smoked had higher rates of aneurysm detection than the patients who did not smoke (pooled prevalence of 2.96%, 95% CI 2.68%–3.27% vs 2.23%, 95% CI 2.08%–2.39%). Although the relation between the two was not statistically significant (p = 0.06), smoking was associated with higher odds for UIA detection, yielding an OR of 1.34 (95% CI 1.07–1.67) with an I 2 value of 53%. CONCLUSIONS This study suggests a potentially higher risk of UIAs in patients who smoked than in those who never smoked. However, the results of this meta-analysis revealed that smoking was not statistically associated with higher UIA detection. This result could be explained by the limited number of studies published on this topic. If these findings reach statistical significance in future larger studies, it could justify revising guidelines to include cigarette smokers in intracranial aneurysm screening.

BACKGROUND: Smoking and observed growth of intracranial aneurysms are known risk factors for rupture. The mechanism by which smoking increases this risk is not completely elucidated. Furthermore, an association between smoking and aneurysm growth has not been clearly defined in the literature. We hypothesize that smoking is associated with aneurysm growth, which, in turn, may serve as one of the mechanisms by which smoking drives rupture risk. METHODS: We report a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Using the R software, we performed a meta-analysis to investigate the association between smoking and the growth of unruptured intracranial aneurysms. Studies on familial aneurysms and genetic syndromes known to increase the risk of aneurysms were excluded. RESULTS: Eighteen observational studies were included with a total of 3535 patients and 4289 aneurysms with a mean follow-up period ranging from 17 to 226 months. The mean age among the studies ranged from 38.4 to 73.9 years; 74% of patients were female. Ever-smoking status (odds ratio, 1.10 [95% CI, 0.87–1.38]) and current smoking status (odds ratio, 1.43 [95% CI, 0.84–2.43]) did not show a statistically significant association with growth of intracranial aneurysms. Patients currently smoking did not have a statistically significant association with the growth of intracranial aneurysms (odds ratio, 1.18 [95% CI, 0.72–1.93]) compared with patients without a smoking history. No significant association was found in patients who previously smoked compared with patients who never smoked (odds ratio, 1.46 [95% CI, 0.88–2.43]). CONCLUSIONS: Smoking is not clearly associated with the growth of unruptured intracranial aneurysms, despite trends being observed, there is no statistical association. The mechanism by which smoking increases rupture risk might not be growth. In patients for whom observation is recommended, the absence of growth over time in the setting of smoking history does not, therefore, imply protection from rupture.