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Risk Factors for Recanalization after Coil Embolization.

ABSTRACT: The aim of our study was to identify risk factors for recanalization 6 months after coil embolization using clinical data followed by computational fluid dynamics (CFD) analysis. Firstly, clinical data of 184 patients treated with coil embolization were analyzed retrospectively. Secondly, aneurysm models for high/low recanalization risk were generated based on ROC curves and their cut-off points. Afterward, CFD was utilized to validate the results. In multivariable analysis, aneurysm filling during the first embolization was an independent risk factor whilst packing density was a protective factor of recanalization after 6 months in patients with aSAH. For patients with unruptured aneurysms, packing density was found to be a protective factor whilst the aneurysm neck size was an independent risk factor. Complex flow pattern and multiple vortices were associated with aneurysm shape and were characteristic of the high recanalization risk group. Statistical analysis suggested that there are various factors influencing recanalization risk. Once certain values of morphometric parameters are exceeded, a complex flow with numerous vortices occurs. This phenomenon was revealed due to CFD investigations that validated our statistical research. Thus, the complex flow pattern itself can be treated as a relevant recanalization predictor.

SUBMITTER: Wisniewski K

PROVIDER: S-EPMC8398571 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Risk Factors for Recanalization after Coil Embolization.

Wiśniewski Karol K Tyfa Zbigniew Z Tomasik Bartłomiej B Reorowicz Piotr P Bobeff Ernest J EJ Posmyk Bartłomiej J BJ Hupało Marlena M Stefańczyk Ludomir L Jóźwik Krzysztof K Jaskólski Dariusz J DJ

Journal of personalized medicine 20210814 8

The aim of our study was to identify risk factors for recanalization 6 months after coil embolization using clinical data followed by computational fluid dynamics (CFD) analysis.<h4>Methods</h4>Firstly, clinical data of 184 patients treated with coil embolization were analyzed retrospectively. Secondly, aneurysm models for high/low recanalization risk were generated based on ROC curves and their cut-off points. Afterward, CFD was utilized to validate the results.<h4>Results</h4>In multivariable ...[more]

PMID: 34442437

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Project description:ObjectiveOutcomes of stent-assisted coil embolization (SACE) have not been well established in the setting of vertebrobasilar dissecting aneurysms (VBDAs) due to the low percentage of cases that need treatment and the array of available therapeutic options. Herein, we presented clinical and radiographic results of SACE in patients with VBDAs.Materials and methodsA total of 47 patients (M:F, 30:17; mean age ± SD, 53.7 ± 12.6 years), with a VBDA who underwent SACE between 2008 and 2014 at two institutions were evaluated retrospectively. Medical records and radiologic data were analyzed to assess the outcome of SACE procedures. Cox proportional hazards regression analysis was conducted to determine the factors that were associated with aneurysmal recanalization after SACE.ResultsStent-assisted coil embolization technically succeeded in all patients. Three cerebellar infarctions occurred on postembolization day 1, week 2, and month 2, but no other procedure-related complications developed. Immediately following SACE, 25 aneurysms (53.2%) showed no contrast filling into the aneurysmal sac. During a mean follow-up of 20.2 months, 37 lesions (78.7%) appeared completely occluded, whereas 10 lesions showed recanalization, 5 of which required additional embolization. Overall recanalization rate was 12.64% per lesion-year, and mean postoperative time to recanalization was 18 months (range, 3-36 months). In multivariable analysis, major branch involvement (hazard ratio [HR]: 7.28; p = 0.013) and the presence of residual sac filling (HR: 8.49, p = 0.044) were identified as statistically significant independent predictors of recanalization. No bleeding was encountered in follow-up monitoring.ConclusionStent-assisted coil embolization appears feasible and safe for treatment of VBDAs. Long-term results were acceptable in a majority of patients studied, despite a relatively high rate of incomplete occlusion immediately after SACE. Major branch involvement and coiled aneurysms with residual sac filling may predispose to recanalization.

Project description:PurposeHemodynamics play a key role in the management of cerebral aneurysm recanalization after coil embolization; however, the most reliable hemodynamic parameter remains unknown. Previous studies have explored the use of both spatiotemporally averaged and maximal definitions for hemodynamic parameters, based on computational fluid dynamics (CFD) analysis, to build predictive models for aneurysmal recanalization. In this study, we aimed to assess the influence of different spatiotemporal characteristics of hemodynamic parameters on predictive performance.MethodsHemodynamics were simulated using CFD for 66 cerebral aneurysms from 65 patients. We evaluated 14 types of spatiotemporal definitions for two hemodynamic parameters in the pre-coiling model and five in virtual post-coiling model (VM) created by cutting the aneurysm from the pre-coiling model. A total of 91 spatiotemporal hemodynamic features were derived and utilized to develop univariate predictor (UP) and multivariate logistic regression (LR) models. The model's performance was assessed using two metrics: the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC).ResultsDifferent spatiotemporal hemodynamic features exhibited a wide range of AUROC values ranging from 0.224 to 0.747, with 22 feature pairs showing a significant difference in AUROC value (P-value <0.05), despite being derived from the same hemodynamic parameter. PDave,q1 was identified as the strongest UP with AUROC/AUPRC values of 0.747/0.385, yielding sensitivity and specificity value of 0.889 and 0.614 at the optimal cut-off value, respectively. The LR model further improved the prediction performance, having AUROC/AUPRC values of 0.890/0.903. At the optimal cut-off value, the LR model achieved a specificity of 0.877, sensitivity of 0.719, outperforming the UP model.ConclusionOur research indicated that the characteristics of hemodynamic parameters in terms of space and time had a significant impact on the development of predictive model. Our findings suggest that LR model based on spatiotemporal hemodynamic features could be clinically useful in predicting recanalization after coil embolization in patients, without the need for invasive procedures.

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Risk Factors for Recanalization after Coil Embolization.

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Risk Factors for Recanalization after Coil Embolization.

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