Dataset Information

Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters.

ABSTRACT:

Introduction

A multitude of approaches have been postulated for assessing the risk of intracranial aneurysm rupture. However, the amount of potential predictive factors is not applicable in clinical practice and they are rejected in favor of the more practical PHASES score. For the subgroup of multiple intracranial aneurysms (MIAs), the PHASES score might severely underestimate the rupture risk, as only the aneurysm with the largest diameter is considered for risk evaluation.

Methods

In this study, we investigated 38 patients harboring a total number of 87 MIAs with respect to their morphological and hemodynamical characteristics. For the determination of the best suited parameters regarding their predictive power for aneurysm rupture, we conducted three phases of statistical evaluation. The statistical analysis aimed to identify parameters that differ significantly between ruptured and unruptured aneurysms, show smallest possible correlations among each other and have a high impact on rupture risk prediction.

Results

Significant differences between ruptured and unruptured aneurysms were found in 16 out of 49 parameters. The lowest correlation were found for gamma, aspect ratio (AR1), aneurysm maximal relative residence time (Aneurysm_RRT_max) and aneurysm mean relative residence time. The data-driven parameter selection yielded a significant correlation of only two parameters (AR1 and the Aneurysm_RRT_max) with rupture state (area under curve?=?0.75).

Conclusion

A high number of established morphological and hemodynamical parameters seem to have no or only low effect on prediction of aneurysm rupture in patients with MIAs. For best possible rupture risk assessment of patients with MIAs, only the morphological parameter AR1 and the hemodynamical parameter Aneurysm_RRT_max need to be included in the prediction model.

SUBMITTER: Neyazi B

PROVIDER: S-EPMC7739206 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters.

Neyazi Belal B Swiatek Vanessa M VM Skalej Martin M Beuing Oliver O Stein Klaus-Peter KP Hattingen Jörg J Preim Bernhard B Berg Philipp P Saalfeld Sylvia S Sandalcioglu I Erol IE

Therapeutic advances in neurological disorders 20201214

<h4>Introduction</h4>A multitude of approaches have been postulated for assessing the risk of intracranial aneurysm rupture. However, the amount of potential predictive factors is not applicable in clinical practice and they are rejected in favor of the more practical PHASES score. For the subgroup of multiple intracranial aneurysms (MIAs), the PHASES score might severely underestimate the rupture risk, as only the aneurysm with the largest diameter is considered for risk evaluation.<h4>Methods< ...[more]

PMID: 33403004

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Project description:Objective: The aim of the present study is to investigate the potential morphological and hemodynamic risk factors related to intracranial aneurysms (IAs) rupture and establish a system to stratify the risk of IAs rupture to help the clinical decision-making. Methods: Patients admitted to our hospital for single-IAs were selected from January 2012 and January 2018. A propensity score matching was conducted to match patients. The morphological parameters were obtained from high solution CTA images, and the hemodynamic parameters were obtained in accordance with the outcomes of computational fluid dynamics (CFDs) simulation. Differences in the morphologic and hemodynamic parameters were compared. The significant parameters were selected to establish a novel scoring system (Intracranial Aneurysm Rupture Score, IARS). The comparison was drawn between the discriminating accuracy of IARS and the Rupture Resemblance Score (RRS) system to verify the value of IARS. Then, a group of patients with unruptured IAs was stratified into the high risk and low risk groups by IARS and RRS system separately and was followed up for 18-27 months to verify the value of IARS. The outcome of different stratifications was compared. Results: The matching process yielded 167 patients in each group. Differences of statistical significance were found in aneurysm length (p = 0.001), perpendicular height (H) (p < 0.001), aspect ratio (AR) (p < 0.001), size ratio (SR) (p < 0.001), deviated angle (DA) (p < 0.001), normalized average wall shear stress (NWSSa) (p < 0.001), wall shear stress gradient (WSSG) (p < 0.001), low shear area ratio (LSAR) (p = 0.01), and oscillatory shear index (OSI) (p = 0.01). Logistic regression analysis further demonstrated that SR, DA, NWSSa, LSAR, and OSI were the independent risk factors of IAs rupture. SR, DA, LSAR, and OSI were finally selected to establish the IARS. Our present IARS showed a higher discriminating value (AUC 0.81 vs. 0.77) in comparison with the RRS (SR, NWSSa, and OSI). After follow-up, seven patients were subject to IAs rupture. 5/26 in high risk group stratified by IARS, yet 7/57 in high risk group stratified by RRS. The accuracy of IARS was further verified (19.2% vs. 12.3%, AUC for the IARS and the RRS was 0.723 and 0.673, respectively). Conclusion: SR, DA, NWSSa, LSAR, and OSI were considered the independent risk factors of IAs rupture. Our novel IARS showed higher accuracy in discriminating IA rupture in comparison with RRS.

Project description:Background and purposeA 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.MethodsA 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.ResultsTwo 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.ConclusionMultidimensional 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.

Dataset Information

Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters.

Introduction

Methods

Results

Conclusion

Publications

Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters.

Similar Datasets

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