Assessing the Hemodynamics in Residual Cavities of Intracranial Aneurysm after Coil Embolization with Combined Computational Flow Dynamics and Silent Magnetic Resonance Angiography

Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization

PURPOSE

To enhance the performance of machine learning (ML) models for the post-embolization recanalization of cerebral aneurysms, we evaluated the impact of hemodynamic feature derivation and selection method on six ML algorithms.

METHODS

We utilized computational fluid dynamics (CFD) to simulate hemodynamics in 66 cerebral aneurysms from 65 patients, including 57 stable and nine recanalized aneurysms. We derived a total of 107 features for each aneurysm, encompassing four clinical features, 12 morphological features, and 91 hemodynamic features. To investigate the influence of feature derivation and selection methods on the ML models, we employed two derivation methods, simplified and fully derived, in combination with four selection methods: all features, statistically significant analysis, stepwise multivariate logistic regression analysis (stepwise-LR), and recursive feature elimination (RFE). Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) on both the training and testing datasets.

RESULTS

The AUROC values on the testing dataset exhibited a wide-ranging spectrum, spanning from 0.373 to 0.863. Fully derived features and the RFE selection method demonstrated superior performance in intra-model comparisons. The multi-layer perceptron (MLP) model, trained with RFE-selected fully derived features, achieved the best performance on the testing dataset, with an AUROC value of 0.863 (95% CI: 0.684- 1.000).

CONCLUSION

Our study demonstrated the importance of feature derivation and selection in determining the performance of ML models. This enabled the development of accurate decision-making models without the need to invade the patient.

Determination of Significant Three-Dimensional Hemodynamic Features for Postembolization Recanalization in Cerebral Aneurysms Through Explainable Artificial Intelligence

BACKGROUND

Recanalization poses challenges after coil embolization in cerebral aneurysms. Establishing predictive models for postembolization recanalization is important for clinical decision making. However, conventional statistical and machine learning (ML) models may overlook critical parameters during the initial selection process.

METHODS

In this study, we automated the identification of significant hemodynamic parameters using a PointNet-based deep neural network (DNN), leveraging their three-dimensional spatial features. Further feature analysis was conducted using saliency mapping, an explainable artificial intelligence (XAI) technique. The study encompassed the analysis of velocity, pressure, and wall shear stress in both precoiling and postcoiling models derived from computational fluid dynamics simulations for 58 aneurysms.

RESULTS

Velocity was identified as the most pivotal parameter, supported by the lowest P value from statistical analysis and the highest area under the receiver operating characteristic curves/precision-recall curves values from the DNN model. Moreover, visual XAI analysis showed that robust injection flow zones, with notable impingement points in precoiling models, as well as pronounced interplay between flow dynamics and the coiling plane, were important three-dimensional features in identifying the recanalized aneurysms.

CONCLUSIONS

The combination of DNN and XAI was found to be an accurate and explainable approach not only at predicting postembolization recanalization but also at discovering unknown features in the future.

Standardized viscosity as a source of error in computational fluid dynamic simulations of cerebral aneurysms

BACKGROUND

Computational fluid dynamics (CFD) simulations are a powerful tool for studying cerebral aneurysms, capable of evaluating hemodynamics in a way that is infeasible with imaging alone. However, the difficulty of incorporating patient-specific information and inherent obstacles of in vivo validation have limited the clinical usefulness of CFD of cerebral aneurysms. In this work we investigate the effect of using standardized blood viscosity values in CFD simulations of cerebral aneurysms when compared to simulations of the same aneurysms using patient-specific viscosity values derived from hematocrit measurements.

PURPOSE

The objective of this work is to determine the level of error, on average, that is, caused by using standardized values of viscosity in CFD simulations of cerebral aneurysms. By quantifying this error, we demonstrate the need for incorporating patient-specific viscosity in future CFD investigations of cerebral aneurysms.

METHODS

CFD simulations of forty-one cerebral aneurysms were conducted using patient-specific boundary conditions. For each aneurysm two simulations were conducted, one utilizing patient-specific blood viscosity derived from hematocrit measurements and another using a standardized value for blood viscosity. Hemodynamic parameters such as wall shear stress (WSS), wall shear stress gradient (WSSG), and the oscillatory shear index (OSI) were calculated for each of the simulations for each aneurysm. Paired t-tests for differences in the time-averaged maps of these hemodynamic parameters between standardized and patient-specific viscosity simulations were conducted for each aneurysm. Bland-Altman analysis was used to examine the cohort-wide changes in the hemodynamic parameters. Subjects were broken into two groups, those with higher than standard viscosity and those with lower than standard viscosity. An unpaired t-test was used to compare the percent change in WSS, WSSG, and OSI between patient-specific and standardized viscosity simulations for the two cohorts. The percent changes in hemodynamic parameters were correlated against the direction and magnitude of percent change in viscosity, aneurysm size, and aneurysm location. For all t-tests, a Bonferroni-corrected significance level of 0.0167 was used.

RESULTS

63.2%, 41.5%, and 48.7% of aneurysms showed statistically significant differences between patient-specific and standardized viscosity simulations for WSS, WSSG, and OSI respectively. No statistically significant difference was found in the percent changes in WSS, WSSG, and OSI between the group with higher than standard viscosity and those with lower than standard viscosity, indicating an increase in viscosity can cause either an increase or decrease in each of the hemodynamic parameters. On a study-wide level no significant bias was found in either direction for WSS, WSSG, or OSI between the simulation groups due to the bidirectional effect of changing viscosity. No correlation was found between percent change of viscosity and percent change of WSS, WSSG, or OSI, meaning an after-the-fact correction for patient-specific viscosity is not feasible.

CONCLUSION

Standardizing viscosity values in CFD of cerebral aneurysms has a large and unpredictable impact on the calculated WSS, WSSG, and OSI when compared to CFD simulations of the same aneurysms using a patient-specific viscosity. We recommend implementing hematocrit-based patient-specific blood viscosity values for all CFD simulations of cerebral aneurysms.

Fluid dynamic analysis in predicting the recanalization of intracranial aneurysms after coil embolization - A study of spatiotemporal characteristics

Purpose

Hemodynamics 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.

Methods

Hemodynamics 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).

Results

Different 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.

Conclusion

Our 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.

Progression from Early Minor Recanalization to Major Recanalization in Ruptured Intracranial Aneurysms After Successful Coil Embolization: Risk Factors and Proposal of a Novel Predicting Variable

BACKGROUND

The risk factors for the progression from early minor recanalization to major recanalization are not well established. Herein, we evaluated ruptured intracranial aneurysms (IAs) with minor recanalization within 1 year of coiling and their progression to major recurrence.

METHODS

We retrospectively reviewed our database of coiled IAs and searched for ruptured saccular IAs that were successfully embolized without residual sacs. We selected IAs with minor recanalization confirmed on radiological studies within 1 year of coil embolization. All the IA cases had a follow-up period longer than 36 months based on the radiological results.

RESULTS

Minor recanalization occurred in 45 IAs within 1 year of coil embolization. Among them, 14 IAs (31.1%) progressed to major recanalization, and 31 remained stable. Progression to major recanalization was detected 12 months after minor recanalization in 2 patients, 24 months in 7 patients, and 36 months in 5 patients. Moreover, the progression to major recanalization occurred more frequently in IAs at the posterior location (P = 0.024, odds ratio 11.20) and IAs with a proportional forced area > 9 mm2 (P = 0.002, odds ratio 17.13), which was a newly proposed variable in the present study.

CONCLUSIONS

Our results showed that approximately one third of the ruptured IAs with early minor recanalization after coiling progressed to major recanalization within 3 years. Physicians should focus on the progression of ruptured IAs from minor to major recanalization, especially those with a posterior circulation location and a proportional forced area >9 mm2.

Hemodynamic differences of posterior communicating artery aneurysms between adult and fetal types of posterior cerebral artery

BACKGROUND

The recanalization of posterior communicating artery (PCoA) aneurysms after endovascular treatment has been analyzed by various factors. However, the differences between adult and fetal types of posterior cerebral artery (PCA) have not been fully investigated. The main aim of this study was to investigate hemodynamic differences of PCoA aneurysms between adult and fetal types using computational fluid dynamics (CFD).

METHODS

Fifty-five PCoA aneurysms were evaluated by 3D CT angiography and divided into unruptured aneurysms with adult-type or fetal-type PCAs (19 cases, UA group; 9 cases, UF group) and ruptured aneurysms with adult-type or fetal-type PCAs (17 cases, RA group; 10 cases, RF group). These native aneurysms were analyzed by CFD regarding morphological and hemodynamic characteristics. To evaluate simulated endovascular treatment of aneurysms, CFD was performed using porous media modeling.

RESULTS

Morphologically, the RA group had significantly smaller parent artery diameter (2.91 mm vs. 3.49 mm, p=0.005) and higher size ratio (2.54 vs. 1.78, p=0.023) than the RF group. CFD revealed that the UA group had significantly lower oscillatory shear index (OSI) (0.0032 vs. 0.0078, p=0.004) than the UF group and that the RA group had lower WSS (3.09 vs. 11.10, p=0.001) and higher OSI (0.014 vs. 0.006, p=0.031) than the RF group, while the RF group presented significantly higher intra-aneurysmal flow velocity (0.19 m/s vs. 0.061 m/s, p=0.002) than the RA group. Porous media modeling of simulated treatment revealed higher residual flow volume in the fetal-type groups.

CONCLUSIONS

These results suggested that PCoA aneurysms with fetal-type PCAs had different morphological features and hemodynamic characteristics compared with those with adult-type PCAs, leading to high risks of recanalization.

The current landscape of intracranial aneurysms in Africa: management outcomes, challenges, and strategies-a narrative review

Intracranial aneurysms (IAs) pose complex and potentially life-threatening challenges in Africa, where limited resources, restricted access to specialised healthcare facilities, and disparities in healthcare provision amplify the difficulties of management. Timely diagnosis and treatment are pivotal in preventing complications, including subarachnoid haemorrhage. Treatment options encompass observation, surgical clipping, endovascular coiling, and flow diversion. Positive outcomes observed in IA management in Africa include high survival rates, favourable functional outcomes, successful treatment techniques, and the absence of complications in some cases. However, negative outcomes such as postoperative complications, reduced quality of life, perioperative mortality, and the risk of recurrence persist. Challenges in IA management encompass limited access to diagnostic tools, a scarcity of specialised healthcare professionals, and an unequal distribution of services. Addressing these challenges requires interventions focused on improving access to diagnostic tools, expanding the number of trained professionals, and establishing specialised IA treatment centres. Collaboration, research, and capacity-building efforts hold significant importance in improving patient outcomes and reducing disparities in IA management across Africa.

Improving the accuracy of computational fluid dynamics simulations of coiled cerebral aneurysms using finite element modeling

Cerebral aneurysms are a serious clinical challenge, with ∼half resulting in death or disability. Treatment via endovascular coiling significantly reduces the chances of rupture, but the techniquehas failure rates of ∼20 %. This presents a pressing need to develop a method fordetermining optimal coildeploymentstrategies. Quantification of the hemodynamics of coiled aneurysms using computational fluid dynamics (CFD) has the potential to predict post-treatment outcomes, but representing the coil mass in CFD simulations remains a challenge. We use the Finite Element Method (FEM) for simulating patient-specific coil deployment for n = 4 ICA aneurysms for which 3D printed in vitro models were also generated, coiled, and scanned using ultra-high resolution synchrotron micro-CT. The physical and virtual coil geometries were voxelized onto a binary structured grid and porosity maps were generated for geometric comparison. The average binary accuracy score is 0.8623 and the average error in porosity map is 4.94 %. We then conduct patient-specific CFD simulations of the aneurysm hemodynamics using virtual coils geometries, micro-CT generated oil geometries, and using the porous medium method to represent the coil mass. Hemodynamic parameters including Neck Inflow Rate (Qneck) and Wall Shear Stress (WSS) were calculated for each of the CFD simulations. The average relative error in Qneck and WSS from CFD using FEM geometry were 6.6 % and 21.8 % respectively, while the error from CFD using a porous media approximation resulted in errors of 55.1 % and 36.3 % respectively; demonstrating a marked improvement in the accuracy of CFD simulations using FEM generated coil geometries.

Risk Factors for Recurrence of Intracranial Aneurysm After Coil Embolization: A Meta-Analysis

Intracranial aneurysm is a severe cerebral disorder involving complicated risk factors and endovascular coiling is a common therapeutic selection for intracranial aneurysm. The recurrence is a clinical challenge in intracranial aneurysms after coil embolization. With this study, we provided a meta-analysis of the risk factors for the recurrence of intracranial aneurysm after coil embolization. Nine studies were included with a total of 1,270 studies that were retrieved from the database. The sample size of patients with intracranial aneurysms ranged from 241 to 3,530, and a total of 9,532 patients were included in the present meta-analysis. The intracranial aneurysms that occurred in middle cerebral artery (MCA) (OR = 1.09, 95% CI: 1.03–1.16, P = 0.0045) and posterior circulation (OR = 2.01, 95% CI: 1.55–2.60, P = 0.000) presented the significantly higher risk of recurrence after coil embolization. Meanwhile, intracranial aneurysms of size > 7 mm (OR = 5.38, 95%CI: 3.76–7.70, P = 0.000) had a significantly higher risk of recurrence after coil embolization. Moreover, ruptured aneurysm (OR = 2.86, 95% CI: 2.02–4.04, P = 0.000) and subarachnoid hemorrhage (SAH) (OR = 1.57, 95% CI: 1.20–2.06, P = 0.001) was positively correlated with the risk of recurrence after coil embolization. In conclusion, this meta-analysis identified the characteristics of intracranial aneurysms with MCA, posterior circulation, size > 7 mm, ruptured aneurysm, and SAH as the risk factors of recurrence after coil embolization for intracranial aneurysms.

Computational fluid dynamics (CFD) analysis in a ruptured vertebral artery dissecting aneurysm implanted by Pipeline when recurrent after LVIS-assisted coiling treatment: Case report and review of the literatures

BACKGROUNDS

Hemodynamics plays an important role in the natural history of the process of rupture and recurrence of intracranial aneurysms. This study aimed to investigate the role of hemodynamics for recurrence in a vertebral artery dissecting aneurysm (VADA).

METHODS

A patient with a ruptured VADA firstly treated by low-profile visualized intraluminal support (LVIS)-assisted coiling, and was implanted with a Pipeline Embolization Device (PED) after aneurysm recurrence. Finite element analysis and computational fluid dynamics simulations were conducted in 6 serial imaging procedures, and the calculated hemodynamics was correlated with aneurysm recurrence.

RESULTS

Wall shear stress (WSS) was not effectively suppressed, resulting in aneurysm recurrence with initial entry tear to occur above the protuberance after 7 months of LVIS stent-assisted coiling. With the implantation of PED, WSS, inflow stream and velocity at the aneurysm neck significantly decreased. During the 3-month follow-up after PED deployment, there was significant shrinkage of the sac and the blood flow in the sac was reduced considerably. The 27-month follow-up after PED deployment indicated the aneurysm was stable.

CONCLUSIONS

The present case study suggests that insufficient suppression of high WSS and high inflow velocity at the neck of the parent artery, especially near the posterior inferior cerebellar artery, might be associated with aneurysm recurrence.