Low Wall Shear Stress Is Independently Associated With the Rupture Status of Middle Cerebral Artery Aneurysms

Geometrical Factors Affect Wall Shear Stress in Saccular Aneurysms of the Infrarenal Abdominal Aorta

BACKGROUND

Low wall shear stress (WSS) is predictive of aortic aneurysm growth and rupture. Yet, estimating WSS in a clinical setting is impractical, whereas measuring aneurysm geometry is feasible. This study investigates the association between saccular aneurysm geometry of the infrarenal aorta and WSS.

METHODS

Starting with a nonaneurysmal, patient-specific, computational fluid dynamics model of the aorta, saccular aneurysms of varying geometry were created by incrementally increasing the neck width and sac depth from 1 cm to 4 cm. The aspect ratio (the ratio between sac depth and neck width) varied between 0.25 and 4. The peak WSS, time-averaged WSS (TAWSS), and oscillatory shear index (OSI) were measured within the aneurysm sac.

RESULTS

Decreasing the neck width from 4 cm to 1 cm decreased the peak WSS by 69% and the TAWSS by 83%. Increasing the sac depth from 1 cm to 4 cm decreased the peak WSS by 55% and the OSI by 37%. The aspect ratio was negatively correlated to peak WSS (Rs -0.85; P < 0.001).

CONCLUSIONS

In saccular aneurysms of the infrarenal aorta, a smaller neck width, deeper aneurysm sac, and larger aspect ratio are associated with lower peak WSS.

Radiomic profiling of high-risk aneurysms with blebs: an exploratory study

BACKGROUND

Blebs significantly increase rupture risk of intracranial aneurysms. Radiomic analysis offers a robust characterization of the aneurysm wall. However, the unique radiomic profile of various compartments, including blebs, remains unexplored. Likewise, the correlation between these imaging markers and fluid/mechanical metrics is yet to be investigated. To address this, we analyzed the radiomic features (RFs) of bleb-containing aneurysms and their relationship with wall tension and shear stress metrics, aiming to enhance risk assessment.

METHODS

Aneurysms were imaged using high-resolution magnetic resonance imaging (MRI). A T1 and a T1 after contrast (T1+Gd) sequences were acquired. 3D models of aneurysm bodies and blebs were generated, and RFs were extracted. Aneurysms with and without blebs were matched based on location and size for analysis. Univariate regression models and Spearman's correlations were used to establish associations between bleb-dependent RFs and mechanical/fluid dynamics metrics.

RESULTS

Eighteen aneurysms with blebs were identified. Fifty-five RFs were significantly different between blebs and body within the same aneurysms. Of these RFs, 9% (5/55) were first-order, and 91% (50/55) were second-order features. After aneurysms with and without blebs were matched for location and size, five RFs 5% (5/93) were significantly different. Forty-one out of the 55 RFs different between bleb and body sac of the primary aneurysm were moderately and strongly correlated with mechanical and fluid dynamics metrics.

CONCLUSION

Aneurysm blebs exhibit distinct radiomic profiles compared with the main body of the aneurysm sac. The variability in bleb wall characteristics may arise from differing mechanical stresses and localized hemodynamics. Leveraging radiomic profiling could help identify regions with a heightened risk of rupture.

Combining Machine-Measured Morphometric, Geometric, and Hemodynamic Factors to Predict the Risk of Aneurysm Rupture at the Middle Cerebral Artery Bifurcation

BACKGROUND

Middle Cerebral Artery Bifurcation Aneurysm (MbifA) is associated with a high risk of rupture and poor overall prognosis in patients once it ruptures. Morphological, geometric, and hemodynamic parameters have been identified as factors contributing to the rupture of intracranial aneurysms. However, there are no studies that combine these 3 types of parameters to specifically target MbifA rupture.

METHODS

This study enrolled all patients with MbifAs diagnosed at our treatment center from 1 April 2021 to 31 July 2023 who met the study criteria. All patients underwent digital subtraction angiography examination to obtain 3D rotational angiography data. We imported the complete image data into the Aneurysm/Artery Reconstruction and Analysis machine to obtain 13 morphological parameters (Dneck, Ddome, Height, Dmax, Dartery, aspect ratio [AR], size ratio, dome-neck-ratio [DNR], height-artery-ratio, bottleneck factor, Inflow Angle, Incline Angle, Arterial Angle), 5 geometric parameters (V,S,undulation index [UI], ellipticity index [EI],nonsphericity index [NSI]), and 5 hemodynamic parameters (wall shear stress [WSS], the maximum WSS, the parent artery WSS, the normalized WSS [NWSS], oscillatory shear index [OSI]). All the above significant parameters were tested by univariate and multivariate analyses to find out the independent discriminatory factors.

RESULTS

A total of 49 MbifAs (16 ruptured and 33 unruptured) from 44 patients were included in the study. Height (P = 0.033), AR (P = 0.007), DNR (P = 0.011), EI (P = 0.042), NSI(P = 0.030), UI(P = 0.027), WSS(P = 0.033), and NWSS(P = 0.002) were all associated with MbifA rupture in univariate analyses, but only NWSS was an independent risk factor (P = 0.036, OR = 0.046, 95% CI: 0.003-0.815) in multivariate logistic regression analysis.

CONCLUSIONS

Height, AR, DNR, EI, UI, NSI, WSS, and NWSS may be correlated with MbifA rupture, but only NWSS was an independent risk factor. A lower NWSS was associated with a higher risk of MbifA rupture. No significant differences were observed in the angle parameters, including the Inflow Angle, between ruptured and unruptured MbifAs. OSI was significantly increased at the dome of the aneurysm but the mean OSI was not found to be associated with MbifA rupture.

Numerical simulation of flow behavior in basilar bifurcation computed tomography angiography

In this study, a moving boundary deformation model based on four-dimensional computed tomography angiography (4D-CTA) with high temporal resolution is constructed, and blood flow dynamics of cerebral aneurysms are investigated by numerical simulation. A realistic moving boundary deformation model of a cerebral aneurysm was constructed based on 4D-CTA in each phase. Four hemodynamic factors (wall shear stress [WSS], wall shear stress divergence [WSSD], oscillatory shear index [OSI], and residual residence time [RRT]) were obtained from numerical simulations, and these factors were evaluated in basilar artery aneurysms. Comparison of the rigid body condition and the moving boundary condition investigating the relationship between wall displacement and hemodynamic factors clarified that the spatial-averaged WSS and maximum WSSD considering only the aneurysmal dome has a large difference between conditions during the peak systole, and there were also significant differences in OSI and RRT.

C5a-C5AR1 axis as a potential trigger of the rupture of intracranial aneurysms

Recent studies have indicated the involvement of neutrophil-mediated inflammatory responses in the process leading to intracranial aneurysm (IA) rupture. Receptors mediating neutrophil recruitment could thus be therapeutic targets of unruptured IAs. In this study, complement C5a receptor 1 (C5AR1) was picked up as a candidate that may cause neutrophil-dependent inflammation in IA lesions from comprehensive gene expression profile data acquired from rat and human samples. The induction of C5AR1 in IA lesions was confirmed by immunohistochemistry; the up-regulations of C5AR1/C5ar1 stemmed from infiltrated neutrophils, which physiologically express C5AR1/C5ar1, and adventitial fibroblasts that induce C5AR1/C5ar1 in human/rat IA lesions. In in vitro experiments using NIH/3T3, a mouse fibroblast-like cell line, induction of C5ar1 was demonstrated by starvation or pharmacological inhibition of mTOR signaling by Torin1. Immunohistochemistry and an experiment in a cell-free system using recombinant C5 protein and recombinant Plasmin indicated that the ligand of C5AR1, C5a, could be produced through the enzymatic digestion by Plasmin in IA lesions. In conclusion, we have identified a potential contribution of the C5a-C5AR1 axis to neutrophil infiltration as well as inflammatory responses in inflammatory cells and fibroblasts of IA lesions. This cascade may become a therapeutic target to prevent the rupture of IAs.

Assessing the risk of intracranial aneurysm rupture using computational fluid dynamics: a pilot study

Objective

This study compared 2 representative cases with ruptured aneurysms to explore the role of hemodynamic and morphological parameters in evaluating the rupture risk of intracranial aneurysms (IAs).

Methods

CTA and 3-dimensional rotational angiography (3DRA) of 3 IAs in 2 patients were retrospectively analyzed in this study. Hemodynamics and morphological parameters were compared between a ruptured IA and an unruptured IA in case1, and between before and after aneurysm rupture in case 2.

Results

In case 1, the ruptured aneurysm had larger morphological parameters including size ratio (SR), aspect ratio (AR), aneurysm vessel angle (θF), Aneurysm inclination angle (θA), Undulation index (UI), Ellipticity index (EI), and Non-sphericity Index (NSI) than the unruptured aneurysm. And oscillatory shear index (OSI) is also larger. Higher rupture resemblance score (RRS) was shown in the ruptured aneurysm. In case 2, the aneurysm had one daughter sac after 2 years. Partial morphological and hemodynamic parameters including SR, AR, θF, θA, UI, EI, NSI, OSI, and relative residence time (RRT) increased, and normalized wall shear stress (NWSS) was significantly reduced. RRS increased during this period.

Conclusion

SR and OSI may have predictive values for the risk of intracranial aneurysm rupture. It is possible that WSS Changes before and after IA rupture, yet the influence of high or low WSS on growth and rupture of IA remains unclear. RRS is promising to be used in the clinical assessment of the rupture risk of IAs and to guide the formulation of treatment plans.

Aneurysmal Inflow Rate Coefficient Predicts Ultra-early Rebleeding in Ruptured Intracranial Aneurysms: Preliminary Report of a Computational Fluid Dynamics Study

Rebleeding from a ruptured intracranial aneurysm has poor outcomes. Although numerous factors are associated with rebleeding, studies on computational fluid dynamics (CFD) on hemodynamic parameters associated with early rebleeding are scarce. In particular, no report of rebleeding in ultra-early phase exists. We aimed to elucidate the specific hemodynamic parameters associated with ultra-early rebleeding using CFD. In this study, the rebleeding group included patients with aneurysmal subarachnoid hemorrhage (aSAH) that rebled within 6 h from the onset. The control group included patients without rebleeding, observed for >10 h following the initial rupture. Clinical images after initial rupture and before rebleeding were used to build 3D vessel models for hemodynamic analysis focusing on the following parameters: time-averaged wall shear stress (WSS), normalized WSS, low shear area, oscillatory shear index, relative residence time, pressure loss coefficient, and aneurysmal inflow rate coefficient (AIRC). Five and 15 patients in the rebleeding and control groups, respectively, met the inclusion criteria. The World Federation of Neurosurgical Surgeons grade was significantly higher in the rebleeding group (p = 0.0088). Hemodynamic analysis showed significantly higher AIRC in the rebleeding group (p = 0.042). The other parameters were not significantly different between groups. There were no significant differences or correlations between SAH severity and AIRC. AIRC was identified as a hemodynamic parameter associated with ultra-early rebleeding of ruptured intracranial aneurysms. Thus, AIRC calculation may enable the prediction of ultra-early rebleeding.

Study of Typical Ruptured and Unruptured Intracranial Aneurysms Based on Fluid-Structure Interaction

BACKGROUND

Most intracranial aneurysms (IAs) will be abnormal bulges on the walls of intracranial arteries that result from the dynamic interaction of geometric morphology, hemodynamics, and pathophysiology. Hemodynamics plays a key role in the origin, development, and rupture of IAs. In the past, hemodynamic studies of IAs were mostly based on the rigid wall hypothesis of computational fluid dynamics, and the influence of arterial wall deformation was ignored. We used fluid-structure interaction (FSI) to study the features of ruptured aneurysms, because it can solve this problem very well and the simulation will be more realistic.

METHODS

A total of 12 IAs, 8 ruptured and 4 unruptured, at the middle cerebral artery bifurcation were studied using FSI to better identify the characteristics of ruptured IAs. We studied the differences in the hemodynamic parameters, including the flow pattern, wall shear stress (WSS), oscillatory shear index (OSI), and displacement and deformation of the arterial wall.

RESULTS

Ruptured IAs had a larger low WSS area and more complex, concentrated, and unstable flow. Also, the OSI was higher. In addition, the displacement deformation area at the ruptured IA was more concentrated and larger.

CONCLUSIONS

A large aspect ratio; a large height/width ratio; complex, unstable, and concentrated flow patterns with small impact areas; a large low WSS region; large WSS fluctuation, high OSI; and large displacement of the aneurysm dome could be risk factors associated with aneurysm rupture. If similar cases are encountered when simulation is used in the clinic, priority should be given to diagnosis and treatment.

An Analysis of Landmark Articles Regarding Aneurysms of the Middle Cerebral Artery

OBJECTIVE

Aneurysms located on the middle cerebral artery (MCA) range from 22% to 31.5% in prevalence of all aneurysms in the anterior cerebral circulation. This bibliometric analysis summarizes the most cited articles on MCA aneurysms and highlights the landmark publications that contributed to evidence-based practice.

METHODS

In the execution of this bibliometric-based review article, the Scopus database was used to perform a title-specific, keyword-based search for all publications until August 2022. The keyword "(middle cerebral artery OR MCA) AND aneurysm" was used. Our results were arranged in descending order based on the citation count of the article. The 100 most cited articles were selected for analysis. Parameters included the following: title, citation count, citations per year, authors, specialty of first author, institution, country of origin, publishing journal, Source Normalized Impact per Paper, and Hirsch index.

RESULTS

The keyword-based search showed that 1206 articles on MCA aneurysms were published up to August 2022. The top 100 articles were published between 1940 and 2019. The top 100 most cited articles collected a total of 6232 citations with an average of 62.3 citations per article. The rate of self-citations accounted for an average of 5.75% of the total number of citations.

CONCLUSIONS

The bibliometric analysis provides a quantitative overview of how medical literature and interventions are analyzed in academic medicine. In the present study, we evaluated the global trends in research regarding MCA aneurysms by finding the top 100 most cited articles.

Mean arterial pressure-aneurysm neck ratio predicts the rupture risk of intracranial aneurysm by reflecting pressure at the dome

Background and purpose

The unruptured intracranial aneurysm (UIA) has high disability and mortality rate after rupture, it is particularly important to assess the risk of UIA and to carry out individualized treatment. The objective of this research is to introduce a novel parameter to predict the rupture risk of UIA.

Methods

A total of 649 patients with 964 intracranial aneurysms in our center were enrolled. A novel parameter named mean arterial pressure-aneurysmal neck ratio (MAPN) was defined. Ten baseline clinical features and twelve aneurysm morphological characteristics were extracted to generate the MAPN model. The discriminatory performance of the MAPN model was compared with the PHASES score and the UCAS score.

Results

In hemodynamic analysis, MAPN was positively correlated with wall shear stress and aneurysm top pressure, with Pearson correlation coefficients of 0.887 and 0.791, respectively. The MAPN was larger in the ruptured group (36.62 ± 18.96 vs. 28.38 ± 14.58, P < 0.001). The area under the curve (AUC) of the MAPN was superior than the AUC of aspect ratio (AR) and the bottleneck factor (BN), they were 0.64 (P < 0.001; 95% CI, 0.588-0.692), 0.611 (P < 0.001; 95% CI, 0.559-0.663) and 0.607 (P < 0.001; 95% CI, 0.554-0.660), respectively. The MAPN model constructed by aneurysm size, aneurysm location, presence of secondary sacs and MAPN, demonstrated good discriminatory ability. The MAPN model exhibited superior performance compared with the UCAS score and the PHASES score (the AUC values were 0.799 [P < 0.001; 95% CI, 0.756-0.840], 0.763 [P < 0.001; 95% CI,0.719-0.807] and 0.741 [P < 0.001; 95% CI, 0.695-0.787], respectively; the sensitivities were 0.849, 0.758 and 0.753, respectively).

Conclusions

Research demonstrates the potential of MAPN to augment the clinical decision-making process for assessing the rupture risk of UIAs.

Low Wall Shear Stress and High Intra-aneurysmal Pressure are Associated with Ruptured Status of Vertebral Artery Dissecting Aneurysms

PURPOSE

The morphological and hemodynamic features of patients with vertebral artery dissecting aneurysms (VADAs) are yet unknown. This study sought to elucidate morphological and hemodynamic features of patients with ruptured and unruptured VADAs based on computed flow simulation.

METHODS

Fifty-two patients (31 unruptured and 21 ruptured VADAs) were admitted to two hospitals between March 2016 and October 2021. All VADAs were located in the intradural segment, and their clinical, morphological, and hemodynamic parameters were retrospectively analyzed. The hemodynamic parameters were determined through computational fluid dynamics simulations. Univariate statistical and multivariable logistic regression analyses were employed to select significantly different parameters and identify key factors. Receiver operating characteristic (ROC) analysis was used to assess the discrimination for each key factor.

RESULTS

Four hemodynamic parameters were observed to significantly differ between ruptured and unruptured VADAs, including wall shear stress (WSS), low shear area, intra-aneurysmal pressure (IAP), and relative residence time. However, no significant differences were observed in morphological parameters between ruptured and unruptured VADAs. Multivariable logistic regression analysis revealed that low WSS and high IAP were significantly observed in the ruptured VADAs and demonstrated adequate discrimination.

CONCLUSIONS

This research indicates significant hemodynamic differences, but no morphological differences were observed between ruptured and unruptured VADAs. The ruptured group had significantly lower WSS and higher IAP than the unruptured group. To further confirm the roles of low WSS and high IAP in the rupture of VADAs, large prospective studies and long-term follow-up of unruptured VADAs are required.

Computational Fluid Dynamics Analysis of Blood Flow Changes during the Growth of Saccular Abdominal Aortic Aneurysm

Computational fluid dynamics analysis of the growth process of saccular abdominal aortic aneurysm was performed. A 3D model of aortic aneurysm was created based on CT images. Properties in terms of wall shear stress, mean flow velocity, mean pressure, energy loss, and pressure loss coefficient were calculated using thermal fluid analysis software "ANSYS CFX." As the aneurysm expanded, the mean flow velocity decreased and the wall shear stress, mean pressure, energy loss, and pressure loss coefficient increased. Wall shear stress increased when the aneurysm was small, suggesting that is related to the development and growth of the aneurysm. (This is secondary publication from J Jpn Coll Angiol 2021; 61: 3-10.).

Investigation on the differences of hemodynamics in normal common carotid, subclavian, and common femoral arteries using the vector flow technique

OBJECTIVES

To investigate the feasibility of the vector flow imaging (V Flow) technique to measure peripheral arterial hemodynamic parameters, including wall shear stress (WSS) and turbulence index (Tur) in healthy adults, and compare the results in different arteries.

MATERIALS AND METHODS

Fifty-two healthy adult volunteers were recruited in this study. The maximum and mean values of WSS, and the Tur values at early-systole, mid-systole, late-systole, and early diastole for total 156 normal peripheral arteries [common carotid arteries (CCA), subclavian arteries (SCA), and common femoral arteries (CFA)] were assessed using the V Flow technique.

RESULTS

The mean WSS values for CCA, SCA, and CFA were (1.66 ± 0.68) Pa, (0.62 ± 0.30) Pa, and (0.56 ± 0.27) Pa, respectively. The mean Tur values for CCA, SCA, and CFA were (0.46 ± 1.09%), (20.7 ± 9.06%), and (24.63 ± 17.66%), respectively. The CCA and SCA, as well as the CCA and CFA, showed statistically significant differences in the mean WSS and the mean Tur (P < 0.01). The mean Tur values had a negative correlation with the mean WSS; the correlation coefficient between log(Tur) and WSS is -0.69 (P < 0.05).

CONCLUSION

V Flow technique is a simple, practical, and feasible quantitative imaging approach for assessing WSS and Tur in peripheral arteries. It has the potential to be a useful tool for evaluating atherosclerotic plaques in peripheral arteries. The results provide a new quantitative foundation for future investigations into diverse arterial hemodynamic parameters.

Reliability of using generic flow conditions to quantify aneurysmal haemodynamics: A comparison against simulations incorporating boundary conditions measured in vivo

BACKGROUND AND OBJECTIVES

Initiation, growth, and rupture of intracranial aneurysms are believed to be closely related to their local haemodynamic environment. While haemodynamics can be characterised by use of computational fluid dynamics (CFD), its reliability depends heavily upon accurate assumption of the boundary conditions. Herein, we compared the simulated aneurysmal haemodynamics obtained by use of generic boundary conditions against those obtained under flow conditions measured in vivo.

METHODS

We prospectively recruited 19 patients with intracranial aneurysms requiring 3-dimensional rotational angiography, during which blood pressure at the internal carotid artery was probed by catheter and flowrate measured by a dedicated software tool. Using these flow conditions measured in vivo, we quantified the aneurysmal haemodynamics for each patient by CFD, and then compared the results with those derived from a generic condition reported in the literature, in terms of the time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and percentage of the intra-aneurysmal flow (PIAF). In addition, the effects on aneurysmal haemodynamics of different outflow strategies (splitting method vs. Murray's Law) and simulation schemes (transient vs. steady-state) relative to each flow condition were also assessed.

RESULTS

Differences in the simulated TAWSS (-6.08 ± 10.64 Pa, p = 0.001), OSI (0.06 ± 0.13, p = 0.001), and PIAF (-0.05 ± 0.20, p = 0.012) between the patient-specific and generic boundary conditions were found to be statistically significant, in contrast to that in the RRT (49 ± 307 Pa^-1, p = 0.062). Outflow strategies did not yield statistically significant differences in any of the investigated parameters (all p > 0.05); rather, the resulting parameters were found to be in good correlations (all r > 0.71, p < 0.001). Difference between the aneurysmal TAWSS and the WSS derived from cycle-averaged flowrate condition was found to be minor (0.66 ± 1.36 Pa, p = 0.000), so was that between PIAFs obtained respectively from the transient and steady-state simulations (0.02 ± 0.05, p = 0.000).

CONCLUSIONS

Incorporating into simulation the patient-specific boundary conditions is critical for CFD to characterise aneurysmal haemodynamics, while outflow strategies may not introduce significant uncertainties. Steady-state simulation incorporating the cycle-averaged flow condition may produce unbiased WSS and PIAF compared to the transient analysis.

Subarachnoid Hemorrhage from Ruptured Internal Carotid Artery Aneurysm: Association with Arterial Tortuosity

OBJECTIVE

Many researchers have found a correlation between tortuous arteries and development of aneurysms in cerebral arteries. We decided to determine whether tortuosity of the internal carotid artery can be related to its aneurysm rupture.

METHODS

We retrospectively analyzed the internal carotid artery anatomy of 149 patients with internal carotid artery aneurysms. For each patient, we calculated relative length (RL), sum of angle metrics (SOAM), triangular index (TI), product of angle distance (PAD), and inflection count metrics (ICM).

RESULTS

A total of 33 patients (22.15%) had subarachnoid hemorrhage. These patients had significantly lower SOAM (0.31 ± 0.17 vs. 0.42 ± 0.21; P < 0.01), TI (0.27 ± 0.09 vs. 0.31 ± 0.11; P = 0.03) and ICM (0.25 ± 0.11 vs. 0.31 ± 0.17; P = 0.04). In multivariate logistic regression analysis, higher SOAM (odds ratio, 0.780; 95% confidence interval, 0.619-0.961; P = 0.025) remained independently associated with lower risk of internal carotid artery aneurysm rupture. In addition, we found significant positive correlation of aneurysm dome size with SOAM (R = 0.224; P = 0.013) and PAD (0.269; P < 0.01). Our study also showed that age (R = 0.252; P = 0.036), Glasgow Coma Scale score (R = -0.706; P < 0.01), and TI (R = -0.249; P = 0.042) were independently correlated with modified Rankin Scale score on discharge.

CONCLUSIONS

Lower tortuosity might be a protective factor against internal carotid artery aneurysm rupture and poor outcome after subarachnoid hemorrhage. Higher tortuosity is correlated with internal carotid artery aneurysm growth.

A web-based dynamic nomogram for rupture risk of posterior communicating artery aneurysms utilizing clinical, morphological, and hemodynamic characteristics

Background

Predicting rupture risk is important for aneurysm management. This research aimed to develop and validate a nomogram model to forecast the rupture risk of posterior communicating artery (PcomA) aneurysms.

Methods

Clinical, morphological, and hemodynamic parameters of 107 unruptured PcomA aneurysms and 225 ruptured PcomA aneurysms were retrospectively analyzed. The least absolute shrinkage and selection operator (LASSO) analysis was applied to identify the optimal rupture risk factors, and a web-based dynamic nomogram was developed accordingly. The nomogram model was internally validated and externally validated independently. The receiver operating characteristic (ROC) curve was used to assess the discrimination of nomogram, and simultaneously the Hosmer–Lemeshow test and calibration plots were used to assess the calibration. Decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical utility of nomogram additionally.

Results

Four optimal rupture predictors of PcomA aneurysms were selected by LASSO and identified by multivariate logistic analysis, including hypertension, aspect ratio (AR), oscillatory shear index (OSI), and wall shear stress (WSS). A web-based dynamic nomogram was then developed. The area under the curve (AUC) in the training and external validation cohorts was 0.872 and 0.867, respectively. The Hosmer–Lemeshow p > 0.05 and calibration curves showed an appropriate fit. The results of DCA and CIC indicated that the net benefit rate of the nomogram model is higher than other models.

Conclusion

Hypertension, high AR, high OSI, and low WSS were the most relevant risk factors for rupture of PcomA aneurysms. A web-based dynamic nomogram thus established demonstrated adequate discrimination and calibration after internal and external validation. We hope that this tool will provide guidance for the management of PcomA aneurysms.

A predictive hemodynamic model based on risk factors for ruptured mirror aneurysms

Objectives

To identify hemodynamic risk factors for intracranial aneurysm rupture and establish a predictive model to aid evaluation.

Methods

We analyzed the hemodynamic parameters of 91 pairs of ruptured mirror aneurysms. A conditional univariate analysis was used for the continuous variables. A conditional multivariate logistic regression analysis was performed to identify the independent risk factors. Differences where p < 0.05 were statistically significant. A predictive model was established based on independent risk factors. Odds ratios (ORs) were used to score points. The validation cohort consisted of 189 aneurysms. Receiver operating characteristic curves were generated to determine the cutoff values and area under the curves (AUCs) of the predictive model and independent risk factors.

Results

The conditional multivariate logistic analysis showed that the low shear area (LSA) (OR = 70.322, p = 0.044, CI = 1.112–4,445.256), mean combined hemodynamic parameter (CHP) (>0.087) (OR = 3.171, p = 0.034, CI = 1.089–9.236), and wall shear stress gradient (WSSG) ratio (>893.180) (OR = 5.740, p = 0.003, CI = 1.950–16.898) were independent risk factors. A prediction model was established: 23^*LSA + 1^*CHP mean (>0.087: yes = 1, no = 0) + 2 ^* WSSG ratio (>893.180: yes = 1, no = 0). The AUC values of the predictive model, LSA, mean CHP (>0.087), and WSSG ratio (>893.180) were 0.748, 0.700, 0.654, and 0.703, respectively. The predictive model and LSA cutoff values were 1.283 and 0.016, respectively. In the validation cohort, the predictive model, LSA, CHP (>0.087), and WSSG ratio (>893.180) were 0.736, 0.702, 0.689, and 0.706, respectively.

Conclusions

LSA, CHP (>0.087), and WSSG ratio (>893.180) were independent risk factors for aneurysm rupture. Our predictive model could aid practical evaluation.

Evaluation of aneurysm rupture risk based upon flowrate-independent hemodynamic parameters: a multi-center pilot study

BACKGROUND

Specifying generic flow boundary conditions in aneurysm hemodynamic simulations yields a great degree of uncertainty for the evaluation of aneurysm rupture risk. Herein, we proposed the use of flowrate-independent parameters in discriminating unstable aneurysms and compared their prognostic performance against that of conventional absolute parameters.

METHODS

This retrospective study included 186 aneurysms collected from three international centers, with the stable aneurysms having a minimum follow-up period of 24 months. The flowrate-independent aneurysmal wall shear stress (WSS) and energy loss (EL) were defined as the coefficients of the second-order polynomials characterizing the relationships between the respective parameters and the parent-artery flows. Performance of the flowrate-independent parameters in discriminating unstable aneurysms with the logistic regression, Adaboost, and support-vector machine (SVM) methods was quantified and compared against that of the conventional parameters, in terms of sensitivity, specificity, and area under the curve (AUC).

RESULTS

In discriminating unstable aneurysms, the proposed flowrate-independent EL achieved the highest sensitivity (0.833, 95% CI 0.586 to 0.964) and specificity (0.833, 95% CI 0.672 to 0.936) on the SVM, with the AUC outperforming the conventional EL by 0.133 (95% CI 0.039 to 0.226, p=0.006). Likewise, the flowrate-independent WSS outperformed the conventional WSS in terms of the AUC (difference: 0.137, 95% CI 0.033 to 0.241, p=0.010).

CONCLUSION

The flowrate-independent hemodynamic parameters surpassed their conventional counterparts in predicting the stability of aneurysms, which may serve as a promising set of hemodynamic metrics to be used for the prediction of aneurysm rupture risk when physiologically real vascular boundary conditions are unavailable.

Different Hemodynamic Characteristics and Resulting in Different Risks of Rupture Between Wide-Neck and Narrow-Neck Aneurysms

Objective

This study aimed to determine the ruptured rate and hemodynamic difference between wide-neck aneurysms (WNAs) and narrow-neck aneurysms (NNAs), as well as the hemodynamic parameters of risk factors for aneurysm rupture.

Methods

A total of 121 cases of intracranial aneurysms (IAs) were studied retrospectively between January 2019 and April 2021 at Renmin Hospital of Wuhan University. Intracranial aneurysms were classified into four types: ruptured wide-neck aneurysms (RWNAs), unruptured wide-neck aneurysms (UWNAs), ruptured narrow-neck aneurysms (RNNAs), and unruptured narrow-neck aneurysms (UNNAs). The Chi-square test was used to compare differences in rupture ratios. The clinical characteristics and hemodynamics were analyzed statistically to reveal the rupture risk factors. Moreover, significant parameters were subjected to binary logistic regression analysis to identify the independent predictive factors. The receiver operating characteristic (ROC) curve was performed to obtain cutoff values.

Results

WNAs ruptured more frequently than NNAs (P = 0.033). Ruptured intracranial aneurysms (RIAs) were characterized by significantly higher intra-aneurysmal pressure (IAP), wall shear stress (WSS), wall shear stress gradient (WSSG), and lower normalized wall shear stress (NWSS) than unruptured intracranial aneurysms (UIAs). RWNAs had higher IAP, WSS, and lower NWSS than UWNAs (P < 0.05). RNNAs had higher IAP, Streamwise WSSG and lower NWSS compared to UNNAs (P < 0.05). Binary logistic regression revealed that IAP and WSS were independent predictive risk factors for WNAs rupture, with cut-off values of 405.5 and 6.66 Pa, respectively. Also, IAP was an independent predictive risk factor for NNA rupture, with a cut-off value of 255.3 Pa.

Conclusions

Wide-neck aneurysms and narrow-neck aneurysms have diverse hemodynamics, which prompts a higher rupture ratio for WNAs. IAP could characterize the rupture risk in both WNAs and NNAs independently, but WSS could only predict the rupture risk in WNAs. This research might assist neurosurgeons with fostering a more sensible strategy for the treatment of IAs.

Association Between Aneurysmal Hemodynamics and Rupture Risk of Unruptured Intracranial Aneurysms

Background

Assessing rupture risk in patients with unruptured intracranial aneurysms (UIAs) remains challenging. Hemodynamics plays an important role in the natural history of intracranial aneurysms. This study aimed to compare aneurysmal hemodynamic features between patients with different rupture risk as determined by PHASES score.

Methods

We retrospectively examined 238 patients who harbored a solitary saccular UIA. Patients were stratified by rupture risk into low-, intermediate-, and high-risk groups according to PHASES score. Flow simulations were performed to compare differences in hemodynamics among the groups.

Results

Aneurysmal time-averaged wall shear stress (WSSa) and normalized WSS (WSSn) decreased progressively as PHASES score increased. WSSa and WSSn significantly differed among the low-, intermediate-, and high-risk groups (p < 0.001). WSSa was significantly lower in the high-risk group than the low-risk group (p < 0.001) and the intermediate-risk group (p = 0.004). WSSn was also significantly lower in the high-risk group than the low-risk group (p < 0.001) and the intermediate-risk group (p = 0.001).

Conclusions

Low WSS was significantly associated with higher risk of intracranial aneurysm rupture as determined by PHASES score, indicating that hemodynamics may play an important role in aneurysmal rupture. In the future, a multidimensional rupture risk prediction model that includes hemodynamic parameters should be investigated.

Hemodynamic impact of proximal anterior cerebral artery aneurysm: Mind the posteriorly projecting ones!

Intracranial aneurysm projected posteriorly is associated with high risk of aneurysm rupture. In order to investigate the biomechanical mechanisms for the adverse event, three-dimension intracranial cerebral aneurysms were constructed based on clinical data, and we numerically compared effect of location, position, size, and shape of aneurysm on hemodynamic conditions including velocity, pressure, and wall shear stress (WSS). The numerical results showed that the aneurysm projected posteriorly even at small sizes led to abnormal hemodynamic environment, which was featured by a local high pressure and stress concentration near aneurysm neck area. Moreover, the one located at the proximal A1 segment and ellipsoidal aneurysm would further worse local hemodynamic environment, causing high local stresses. These findings indicated the potential mechanical mechanism for high rupture rate of the aneurysms projected posteriorly, underscoring importance of early and accurate diagnosis and promptly treatment for improved the clinical outcome, even if these aneurysms are of small sizes.

Morphology-aware multi-source fusion-based intracranial aneurysms rupture prediction

OBJECTIVES

We proposed a new approach to train deep learning model for aneurysm rupture prediction which only uses a limited amount of labeled data.

METHOD

Using segmented aneurysm mask as input, a backbone model was pretrained using a self-supervised method to learn deep embeddings of aneurysm morphology from 947 unlabeled cases of angiographic images. Subsequently, the backbone model was finetuned using 120 labeled cases with known rupture status. Clinical information was integrated with deep embeddings to further improve prediction performance. The proposed model was compared with radiomics and conventional morphology models in prediction performance. An assistive diagnosis system was also developed based on the model and was tested with five neurosurgeons.

RESULT

Our method achieved an area under the receiver operating characteristic curve (AUC) of 0.823, outperforming deep learning model trained from scratch (0.787). By integrating with clinical information, the proposed model's performance was further improved to AUC = 0.853, making the results significantly better than model based on radiomics (AUC = 0.805, p = 0.007) or model based on conventional morphology parameters (AUC = 0.766, p = 0.001). Our model also achieved the highest sensitivity, PPV, NPV, and accuracy among the others. Neurosurgeons' prediction performance was improved from AUC=0.877 to 0.945 (p = 0.037) with the assistive diagnosis system.

CONCLUSION

Our proposed method could develop competitive deep learning model for rupture prediction using only a limited amount of data. The assistive diagnosis system could be useful for neurosurgeons to predict rupture.

KEY POINTS

• A self-supervised learning method was proposed to mitigate the data-hungry issue of deep learning, enabling training deep neural network with a limited amount of data. • Using the proposed method, deep embeddings were extracted to represent intracranial aneurysm morphology. Prediction model based on deep embeddings was significantly better than conventional morphology model and radiomics model. • An assistive diagnosis system was developed using deep embeddings for case-based reasoning, which was shown to significantly improve neurosurgeons' performance to predict rupture.

Combination of Morphological and Hemodynamic Parameters for Assessing the Rupture Risk of Intracranial Aneurysms: a Retrospective Study On Mirror Middle Cerebral Artery Aneurysms

Discordant findings were frequently reported by studies dedicated to exploring the association of morphological/hemodynamic factors with the rupture of intracranial aneurysms (IAs), probably owing to insufficient control of confounding factors. In this study, we aimed to minimize the influences of confounding factors by focusing IAs of interest on mirror aneurysms and, meanwhile, modeling IAs together with the cerebral arterial network to improve the physiological fidelity of hemodynamic simulation. 52 mirror aneurysms located at the middle cerebral artery (MCA) in 26 patients were retrospectively investigated. Numerical tests performed on two randomly selected patients demonstrated that over truncation of cerebral arteries proximal to the MCA during image-based model reconstruction led to uncertain changes in computed values of intra-aneurysmal hemodynamic parameters, which justified the minimal truncation strategy adopted in our study. Five morphological parameters (i.e., volume (V), height (H), dome area (DA), non-sphericity index (NSI), and size ratio (SR)) and two hemodynamic parameters (i.e., peak WSS (peakWSS), and pressure loss coefficient (PLc)) were found to differ significantly between the ruptured and unruptured aneurysms and proved by receiver operating characteristic (ROC) analysis to have potential value for differentiating the rupture status of aneurysm with the areas under curve (AUCs) ranging from 0.681 to 0.763. Integrating V, SR, peakWSS and PLc or some of them into regression models considerably improved the classification of aneurysms, elevating AUC up to 0.864, which indicates that morphological and hemodynamic parameters have complementary roles in assessing the risk of aneurysm rupture.

Case Report: Dynamic Changes in Hemodynamics During the Formation and Progression of Intracranial Aneurysms

Despite the devastating consequences of aneurysmal subarachnoid hemorrhage (SAH), the mechanisms underlying the formation, progression, and rupture of intracranial aneurysms (IAs) are complex and not yet fully clear. In a real-world situation, continuously observing the process of aneurysm development in humans appears unrealistic, which also present challenges for the understanding of the underlying mechanism. We reported the relatively complete course of IA development in two real patients. On this basis, computational fluid dynamics simulation (CFD) was performed to evaluate the changes in hemodynamics and analyze the mechanism underlying the formation, progression, and rupture of IAs. Our results suggested that the formation and progression of IAs can be a dynamic process, with constantly changing hemodynamic characteristics. CFD analysis based on medical imaging provides the opportunity to study the hemodynamic conditions over time. From these two rare cases, we found that concentrated high-velocity inflow jets, flows with vortex structures, extremely high WSS, and a very steep WSSG were correlated with the formation of IAs. Complex multi-vortex flows are possibly related to IAs prior to growth, and the rupture of IAs is possibly related to low WSS, extreme instability and complexity of flow patterns. Our findings provide unique insight into the theoretical hemodynamic mechanism underlying the formation and progression of IAs. Given the small sample size the findings of this study have to be considered preliminary and exploratory.

Morphological and Hemodynamic Characteristics Associated With the Rupture of Multiple Intracranial Aneurysms

Background and Purpose

The objective of this study was to identify the morphological and hemodynamic factors associated with the rupture of multiple intracranial aneurysms regardless of patient-related factors and establish a statistical model for aneurysm rupture risk assessment.

Methods

The digital subtraction angiography (DSA) data of 104 mirror intracranial aneurysms in 52 consecutive patients were retrospectively analyzed in this study. 21 morphological parameters and hemodynamic parameters were calculated by 3-dimensional reconstruction and computational fluid dynamics (CFD) simulation. Significant differences (p < 0.05) between the two groups were subsequently tested with the multivariate logistic regression to identify the independent risk factors. A prediction model was established based on the independent risk factors. The receiver operating characteristics (ROCs) were generated to estimate the prediction performance. A cohort of patients with multiple intracranial aneurysms admitted in our institute from January 2021 to October 2021 was introduced to verify the value of the model.

Results

Significant differences between the ruptured and unruptured aneurysms were found in 15 out of 19 parameters. Bleb formation, neck width, and size ratio were independent factors in the multivariate logistic regression. A prediction model based on the three independent risk factors was established: Odds = −1.495 – 0.707 × _(Neckwidth) + 3.061 × _{(Blebformation)} + 2.1 × _(SR) (bleb formation: Yes = 1, No = 0). The area under the curve (AUC) value of the model was 0.901. In the validation cohort, the prediction model showed satisfying performance in assessing multiple aneurysm rupture risk with a sensitivity of 100% and specificity of 88.46%.

Conclusion

Bleb formation, neck width, and size ratio were independently associated with aneurysm rupture status. The prediction model may help in identifying the aneurysm with high rupture risk.

Fluid-structure interaction simulation of tissue degradation and its effects on intra-aneurysm hemodynamics

Tissue degradation plays a crucial role in vascular diseases such as atherosclerosis and aneurysms. Computational modeling of vascular hemodynamics incorporating both arterial wall mechanics and tissue degradation has been a challenging task. In this study, we propose a novel finite element method-based approach to model the microscopic degradation of arterial walls and its interaction with blood flow. The model is applied to study the combined effects of pulsatile flow and tissue degradation on the deformation and intra-aneurysm hemodynamics. Our computational analysis reveals that tissue degradation leads to a weakening of the aneurysmal wall, which manifests itself in a larger deformation and a smaller von Mises stress. Moreover, simulation results for different heart rates, blood pressures and aneurysm geometries indicate consistently that, upon tissue degradation, wall shear stress increases near the flow-impingement region and decreases away from it. These findings are discussed in the context of recent reports regarding the role of both high and low wall shear stress for the progression and rupture of aneurysms.

Low Shear Stress at Baseline Predicts Expansion and Aneurysm-Related Events in Patients With Abdominal Aortic Aneurysm

BACKGROUND

Low shear stress has been implicated in abdominal aortic aneurysm (AAA) expansion and clinical events. We tested the hypothesis that low shear stress in AAA at baseline is a marker of expansion rate and future aneurysm-related events.

METHODS

Patients were imaged with computed tomography angiography at baseline and followed up every 6 months >24 months with ultrasound measurements of maximum diameter. From baseline computed tomography angiography, we reconstructed 3-dimensional models for automated computational fluid dynamics simulations and computed luminal shear stress. The primary composite end point was aneurysm repair and/or rupture, and the secondary end point was aneurysm expansion rate.

RESULTS

We included 295 patients with median AAA diameter of 49 mm (interquartile range, 43-54 mm) and median follow-up of 914 (interquartile range, 670-1112) days. There were 114 (39%) aneurysm-related events, with 13 AAA ruptures and 98 repairs (one rupture was repaired). Patients with low shear stress (<0.4 Pa) experienced a higher number of aneurysm-related events (44%) compared with medium (0.4-0.6 Pa; 27%) and high (>0.6 Pa; 29%) shear stress groups (P=0.010). This association was independent of known risk factors (adjusted hazard ratio, 1.72 [95% CI, 1.08-2.73]; P=0.023). Low shear stress was also independently associated with AAA expansion rate (β=+0.28 mm/y [95% CI, 0.02-0.53]; P=0.037).

CONCLUSIONS

We show for the first time that low shear stress (<0.4 Pa) at baseline is associated with both AAA expansion and future aneurysm-related events. Aneurysms within the lowest tertile of shear stress, versus those with higher shear stress, were more likely to rupture or reach thresholds for elective repair. Larger prospective validation trials are needed to confirm these findings and translate them into clinical management.

Middle cerebral arterial bifurcation aneurysms are associated with bifurcation angle and high tortuosity

PURPOSE

To investigate the association of middle cerebral artery (MCA) bifurcation aneurysms with bifurcation morphology.

MATERIALS AND METHODS

205 patients were enrolled, including 61 patients with MCA bifurcation aneurysms and 144 non-aneurysmal subjects. Aneurysmal cases were divided into types C (aneurysm neck on extension of the parent artery centerline) and D (deviating neck). The radius of the parent artery M1 (R_P) and bilateral branches (R_S and R_L, respectively), smaller (φ_S) and larger (φ_L) lateral angles, bifurcation angle, and arterial tortuosity from parent vessel to bilateral branches (T_S and T_L, respectively) were analyzed. Logistic regression and receiver operator characteristic (ROC) curve analysis were performed to identify risk factors and predictive values for MCA aneurysm presence and types.

RESULTS

In aneurysmal MCA bifurcations, bifurcating angle, T_S, T_L and R_L were significantly larger (P<0.01), while φ_S was significantly smaller (P<0.001) than those in controls. The bifurcation angle, T_S and LogitP were better morphological parameters for predicting MCA aneurysm presence with the AUC of 0.795, 0.932 and 0.951, respectively. Significant (P<0.05) differences were observed in the bifurcation angle, φ_L, R_P, R_L and T_L between types C and D aneurysmal bifurcations. T_L was an independent factor in discriminating types C from D aneurysms with an AUC of 0.802.

CONCLUSIONS

Bifurcation angle and arterial tortuosity from the parent artery to the branch forming a smaller angle with the parent artery have a higher value in distinguishing MCA aneurysmal from non-aneurysmal ones, and the tortuosity from the parent artery to the contralateral branch is the best indicator for distinguishing types C from D aneurysmal bifurcations.

Risk Factors for Pericallosal Artery Aneurysm Rupture Based on Morphological Computer-Assisted Semiautomated Measurement and Hemodynamic Analysis

Background: Although pericallosal artery aneurysms (PAAs) are relatively uncommon, accounting for only 1-9% of all intracranial aneurysms (IAs), they exhibit a considerably high propensity to rupture. Nevertheless, our current knowledge of the risk factors for PAA rupture is still very limited. To fill this gap, we investigated rupture risk factors for PAAs based on morphological computer-assisted semiautomated measurement (CASAM) and hemodynamic analysis. Methods: Patients with PAAs were selected from the IA database in our institute and their baseline data were collected. Morphological parameters were measured in all enrolled patients by applying CASAM. Computational fluid dynamics simulation (CFD) was performed to evaluate the hemodynamic difference between ruptured and unruptured PAAs. Results: From June 2017 to June 2020, among 2141 patients with IAs in our institute, 47 had PAAs (2.2%). Thirty-one patients (mean age 57.65 ± 9.97 years) with 32 PAAs (20 unruptured and 12 ruptured) were included in the final analysis. Comparing with unruptured PAAs, ruptured PAAs had significantly higher aspect ratio (AR), mean normalized wall shear stress (NWSS), and mean oscillatory shear index (OSI) values than the unruptured PAAs (all P < 0.05) in univariate analyses. Multivariable analysis showed that a high mean OSI was an independent risk factor for PAA rupture (OR = 6.45, 95% CI 1.37-30.32, P = 0.018). Conclusion: This preliminary study indicates that there are morphological and hemodynamic differences between ruptured and unruptured PAAs. In particular, a high mean OSI is an independent risk factor for PAA rupture. Further research with a larger sample size is warranted in the future.

Increased aneurysm wall permeability colocalized with low wall shear stress in unruptured saccular intracranial aneurysm

Aneurysm wall permeability has recently emerged as an in vivo marker of aneurysm wall remodeling. We sought to study the spatial relationship between hemodynamic forces derived from 4D-flow MRI and aneurysm wall permeability by DCE-MRI in a region-based analysis of unruptured saccular intracranial aneurysms (IAs). We performed 4D-flow MRI and DCE-MRI on patients with unruptured IAs of ≥ 5 mm to measure hemodynamic parameters, including wall shear stress (WSS), oscillatory shear index (OSI), WSS temporal (WSSGt) and spatial (WSSGs) gradient, and aneurysm wall permeability (K^trans) in different sectors of aneurysm wall defined by evenly distributed radial lines emitted from the aneurysm center. The spatial association between K^trans and hemodynamic parameters measured at the sector level was evaluated. Thirty-one patients were scanned. K^trans not only varied between aneurysms but also demonstrated spatial heterogeneity within an aneurysm. Among all 159 sectors, higher K^trans was associated with lower WSS, which was seen in both Spearman's correlation analysis (rho = - 0.18, p = 0.025) and linear regression analysis using generalized estimating equation to account for correlations between multiple sectors of the same aneurysm (regression coefficient = - 0.33, p = 0.006). Aneurysm wall permeability by DCE-MRI was shown to be spatially heterogenous in unruptured saccular IAs and associated with local WSS by 4D-flow MRI.

Moments of Intra-Dome Velocity Distribution as Robust Predictors of Rupture Status in Cerebral Aneurysms

BACKGROUND

Wall shear stress (WSS), the spatial gradient of flow velocity at luminal surface, has been employed for aneurysmal hemodynamic analysis, but it is sensitive to surface irregularities and noise. We devised a volumetric approach to evaluate discriminant power of intra-dome flow velocity distribution and modal analysis in rupture status determination compared with previously described WSS analysis.

METHODS

Catheter three-dimensional rotational angiographic datasets matched for volume were segmented in 20 sidewall aneurysms (10 ruptured), computational fluid dynamics simulations were performed, and velocity distributions were extracted from mesh-independent isometric sampling followed by moment analysis (mean, variance, skewness, and kurtosis). Univariate and multivariate analysis was used to evaluate discriminant performance of velocity moments. Sensitivity of velocity moments and WSS was evaluated to bleb presence and surface irregularity using digital bleb removal and surface noise addition.

RESULTS

Velocity moments of ruptured aneurysms showed higher skewness (2.45 ± 0.57 vs. 1.36 ± 0.82, P = 0.003) and kurtosis (11.83 ± 4.77 vs. 6.05 ± 4.65, P = 0.01) with lower mean (0.019 ± 0.01 vs. 0.038 ± 0.02, P = 0.03) compared with unruptured lesions; in multivariate modeling, skewness alone emerged as best predictor (area under the curve = 0.88). Bleb removal increased low WSS by 548%, and surface noise decreased it by 85.8% while having a smaller (<7%) effect on velocity skewness and kurtosis.

CONCLUSIONS

High aneurysm dome flow velocity skewness and kurtosis suggest an exponential distribution in ruptured lesions, with high peaks at low velocities, consistent with areas of slow flow. In contrast to WSS-based techniques, this approach is robust against surface variations, with promising improved rupture status discriminant performance that requires further validation in expanded future studies.

Aneurysm presence at the anterior communicating artery bifurcation is associated with caliber tapering of the A1 segment

OBJECTIVE

Vessel tapering results in blood flow acceleration at downstream bifurcations (firehose nozzle effect), induces hemodynamics predisposing to aneurysm initiation, and has been associated with middle cerebral artery (MCA) aneurysm presence and rupture status. The authors sought to determine if vessel caliber tapering is a generalizable predisposing factor by evaluating upstream A1 segment profiles in association with aneurysm presence in the anterior communicating artery (ACoA) complex, the most prevalent cerebral aneurysm location associated with a high rupture risk.

METHODS

Three-dimensional rotational angiographic studies were analyzed for 68 patients with ACoA aneurysms, 37 nonaneurysmal contralaterals, and 53 healthy bilateral controls (211 samples total). A1 segments were determined to be dominant, codominant, or nondominant based on flow and size. Equidistant cross-sectional orthogonal cuts were generated along the A1 centerline, and cross-sectional area (CSA) was evaluated proximally and distally, using intensity-invariant edge detection filtering. The relative tapering of the A1 segment was evaluated as the tapering ratio (distal/proximal CSA). Computational fluid dynamics was simulated on ACoA parametric models with and without tapering.

RESULTS

Aneurysms occurred predominantly on dominant (79%) and codominant (17%) A1 segments. A1 segments leading to unruptured ACoA aneurysms had significantly greater tapering compared to nonaneurysmal contralaterals (0.69 ± 0.13 vs 0.80 ± 0.17, p = 0.001) and healthy controls (0.69 ± 0.13 vs 0.83 ± 0.16, p < 0.001), regardless of dominance labeling. There was no statistically significant difference in tapering values between contralateral A1 and healthy A1 controls (0.80 ± 0.17 vs 0.83 ± 0.16, p = 0.56). Hemodynamically, A1 segment tapering induces high focal pressure, high wall shear stress, and high velocity at the ACoA bifurcation.

CONCLUSIONS

Aneurysmal, but not contralateral or healthy control, A1 segments demonstrated significant progressive vascular tapering, which is associated with aneurysmogenic hemodynamic conditions at the ACoA complex. Demonstration of the upstream tapering effect in the communicating ACoA segment is consistent with its prior detection in the noncommunicating MCA bifurcation, which together form more than 50% of intracranial aneurysms. The mechanistic characterization of this upstream vascular tapering phenomenon is warranted to understand its clinical relevance and devise potential therapeutic strategies.

Quantitative analysis of flow vortices: differentiation of unruptured and ruptured medium-sized middle cerebral artery aneurysms

BACKGROUND

Surgical intervention for unruptured intracranial aneurysms (IAs) carries inherent health risks. The analysis of "patient-specific" IA geometric and computational fluid dynamics (CFD) simulated wall shear stress (WSS) data has been investigated to differentiate IAs at high and low risk of rupture to help clinical decision making. Yet, outcomes vary among studies, suggesting that novel analysis could improve rupture characterization. The authors describe a CFD analytic method to assess spatiotemporal characteristics of swirling flow vortices within IAs to improve characterization.

METHODS

CFD simulations were performed for 47 subjects harboring one medium-sized (4-10 mm) middle cerebral artery (MCA) aneurysm with available 3D digital subtraction angiography data. Alongside conventional indices, quantified IA flow vortex spatiotemporal characteristics were applied during statistical characterization. Statistical supervised machine learning using a support vector machine (SVM) method was run with cross-validation (100 iterations) to assess flow vortex-based metrics' strength toward rupture characterization.

RESULTS

Relying solely on vortex indices for statistical characterization underperformed compared with established geometric characteristics (total accuracy of 0.77 vs 0.80) yet showed improvements over wall shear stress models (0.74). However, the application of vortex spatiotemporal characteristics into the combined geometric and wall shear stress parameters augmented model strength for assessing the rupture status of middle cerebral artery aneurysms (0.85).

CONCLUSIONS

This preliminary study suggests that the spatiotemporal characteristics of flow vortices within MCA aneurysms are of value to improve the differentiation of ruptured aneurysms from unruptured ones.

A data-driven model to identify high-risk aneurysms and guide management decisions: the Rupture Resemblance Score

OBJECTIVE

Previous studies have found that ruptured intracranial aneurysms (RIAs) have distinct morphological and hemodynamic characteristics, including higher size ratio and oscillatory shear index and lower wall shear stress. Unruptured intracranial aneurysms (UIAs) that possess similar characteristics to RIAs may be at a higher risk of rupture than those UIAs that do not. The authors previously developed the Rupture Resemblance Score (RRS), a data-driven computer model that can objectively gauge the similarity of UIAs to RIAs in terms of morphology and hemodynamics. The authors aimed to explore the clinical utility of RRS in guiding the management of UIAs, especially for challenging cases such as small UIAs.

METHODS

Between September 2018 and June 2019, the authors retrospectively collected consecutive challenging cases of incidentally identified UIAs that were discussed during their weekly multidisciplinary neurovascular conference. From patient 3D digital subtraction angiography, they reconstructed the aneurysm geometry and performed computer-assisted 3D morphology analysis and computational fluid dynamics simulation. They calculated RRS for every UIA case and compared it against the treatment decision made at the neurovascular conference as well as the recommendation based on the unruptured intracranial aneurysm treatment score (UIATS).

RESULTS

Forty-seven patients with 79 UIAs, 90% of which were < 7 mm in size, were included in this study. The mean RRS (range 0.0-1.0) was 0.24 ± 0.31. At the conferences, treatment was endorsed for 45 of the UIAs (57%). These cases had significantly higher RRSs than the 34 cases suggested for observation (0.33 ± 0.34 vs 0.11 ± 0.19, p < 0.001). The UIATS-based recommendations were "observation" for 24 UIAs (30%), "treatment" for 21 UIAs (27%), and "not definitive" for 34 UIAs (43%). These "not definitive" cases were stratified by RRS based on similarity to RIAs.

CONCLUSIONS

Although not a rupture predictor, RRS is a data-driven model that gauges the similarity of UIAs to RIAs in terms of morphology and hemodynamics. In cases in which the UIATS-based recommendation is not definitive, RRS provides additional stratification to assist the identification of high-risk UIAs. The current study highlights the clinical utility of RRS in a real-world setting as an adjunctive tool for the management of UIAs.

Morphological and Hemodynamic Changes during Cerebral Aneurysm Growth

Computational fluid dynamics (CFD) has grown as a tool to help understand the hemodynamic properties related to the rupture of cerebral aneurysms. Few of these studies deal specifically with aneurysm growth and most only use a single time instance within the aneurysm growth history. The present retrospective study investigated four patient-specific aneurysms, once at initial diagnosis and then at follow-up, to analyze hemodynamic and morphological changes. Aneurysm geometries were segmented via the medical image processing software Mimics. The geometries were meshed and a computational fluid dynamics (CFD) analysis was performed using ANSYS. Results showed that major geometry bulk growth occurred in areas of low wall shear stress (WSS). Wall shape remodeling near neck impingement regions occurred in areas with large gradients of WSS and oscillatory shear index. This study found that growth occurred in areas where low WSS was accompanied by high velocity gradients between the aneurysm wall and large swirling flow structures. A new finding was that all cases showed an increase in kinetic energy from the first time point to the second, and this change in kinetic energy seems correlated to the change in aneurysm volume.

Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study

BACKGROUND AND PURPOSE

Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic information based on machine learning techniques and to test the models in external validation datasets.

MATERIALS AND METHODS

From January 2010 to December 2016, five hundred four consecutive patients with only small aneurysms (<5 mm) detected by CTA and invasive cerebral angiography (or surgery) were retrospectively enrolled and randomly split into training (81%) and internal validation (19%) sets to derive and validate the proposed machine learning models (support vector machine, random forest, logistic regression, and multilayer perceptron). Hemodynamic parameters were obtained using computational fluid dynamics simulation. External validation was performed in other hospitals to test the models.

RESULTS

The support vector machine performed the best with areas under the curve of 0.88 (95% CI, 0.85-0.92) and 0.91 (95% CI, 0.74-0.98) in the training and internal validation datasets, respectively. Feature ranks suggested hemodynamic parameters, including stable flow pattern, concentrated inflow streams, and a small (<50%) flow-impingement zone, and the oscillatory shear index coefficient of variation, were the best predictors of aneurysm rupture. The support vector machine showed an area under the curve of 0.82 (95% CI, 0.69-0.94) in the external validation dataset, and no significant difference was found for the areas under the curve between internal and external validation datasets (P = .21).

CONCLUSIONS

This study revealed that machine learning had a good performance in predicting the rupture status of small aneurysms in both internal and external datasets. Aneurysm hemodynamic parameters were regarded as the most important predictors.

Age- and gender-dependent variability in the geometry of middle cerebral artery bifurcations

The goal of this study was to analyze trends in the geometric parameters of blood vessels with age in a randomly selected group of 200 computed tomography angiography studies of radiologically healthy individuals using dedicated statistical techniques. A quantitative description of cerebral vascular geometry with numerical parameters (bifurcation angle, branching angle, co-planarity index, average curvature, and average torsion) was proposed. The changes and variability in geometry were analyzed according to age. The bifurcation angle, branching angle, and average curvature increased with age, whereas the co-planarity index and average torsion decreased with age. For equal-diameter branches, women comparing to men presented lower bifurcation angles in the 4th decade of life, and lower values for the co-planarity index in the 3rd and 4th decades of life. In non-equal-diameter branches, the opposite relationship was observed for bifurcation angle in the 4th decade of life comparing both groups. All analyzed parameters showed clearly visible trends with patient age. Deviations in specific decades of life were detected; these deviations could be linked to the development of aneurysms in specific age groups.

Rupture Risk Assessment for Cerebral Aneurysm Using Interpretable Machine Learning on Multidimensional Data

Background: Assessment of cerebral aneurysm rupture risk is an important task, but it remains challenging. Recent works applying machine learning to rupture risk evaluation presented positive results. Yet they were based on limited aspects of data, and lack of interpretability may limit their use in clinical setting. We aimed to develop interpretable machine learning models on multidimensional data for aneurysm rupture risk assessment. Methods: Three hundred seventy-four aneurysms were included in the study. Demographic, medical history, lifestyle behaviors, lipid profile, and morphologies were collected for each patient. Prediction models were derived using machine learning methods (support vector machine, artificial neural network, and XGBoost) and conventional logistic regression. The derived models were compared with the PHASES score method. The Shapley Additive Explanations (SHAP) analysis was applied to improve the interpretability of the best machine learning model and reveal the reasoning behind the predictions made by the model. Results: The best machine learning model (XGBoost) achieved an area under the receiver operating characteristic curve of 0.882 [95% confidence interval (CI) = 0.838-0.927], significantly better than the logistic regression model (0.779; 95% CI = 0.729-0.829; P = 0.002) and the PHASES score method (0.758; 95% CI = 0.713-0.800; P = 0.001). Location, size ratio, and triglyceride level were the three most important features in predicting rupture. Two typical cases were analyzed to demonstrate the interpretability of the model. Conclusions: This study demonstrated the potential of using machine learning for aneurysm rupture risk assessment. Machine learning models performed better than conventional statistical model and the PHASES score method. The SHAP analysis can improve the interpretability of machine learning models and facilitate their use in a clinical setting.

Computational Fluid Dynamics for Cerebral Aneurysms in Clinical Settings

Hemodynamics is thought to play an important role in the pathogenesis of cerebral aneurysms and recent development of computer technology makes it possible to simulate blood flow using high-resolution 3D images within several hours. A lot of studies of computational fluid dynamics (CFD) for cerebral aneurysms were reported; therefore, application of CFD for cerebral aneurysms in clinical settings is reviewed in this article.CFD for cerebral aneurysms using a patient-specific geometry model was first reported in 2003 and it has been revealing that hemodynamics brings a certain contribution to understanding aneurysm pathology, including initiation, growth and rupture. Based on the knowledge of the state-of-the-art techniques, this review treats the decision-making process for using CFD in several clinical settings. We introduce our CFD procedure using digital imaging and communication in medicine (DICOM) datasets of 3D CT angiography or 3D rotational angiography. In addition, we review rupture status, hyperplastic remodeling of aneurysm wall, and recurrence of coiled aneurysms using the hemodynamic parameters such as wall shear stress (WSS), oscillatory shear index (OSI), aneurysmal inflow rate coefficient (AIRC), and residual flow volume (RFV).

A preliminary investigation of radiomics differences between ruptured and unruptured intracranial aneurysms

OBJECTIVES

Prediction of intracranial aneurysm rupture is important in the management of unruptured aneurysms. The application of radiomics in predicting aneurysm rupture remained largely unexplored. This study aims to evaluate the radiomics differences between ruptured and unruptured aneurysms and explore its potential use in predicting aneurysm rupture.

METHODS

One hundred twenty-two aneurysms were included in the study (93 unruptured). Morphological and radiomics features were extracted for each case. Statistical analysis was performed to identify significant features which were incorporated into prediction models constructed with a machine learning algorithm. To investigate the usefulness of radiomics features, three models were constructed and compared. The baseline model A was constructed with morphological features, while model B was constructed with addition of radiomics shape features and model C with more radiomics features. Multivariate analysis was performed for the ten most important variables in model C to identify independent risk factors. A simplified model based on independent risk factors was constructed for clinical use.

RESULTS

Five morphological features and 89 radiomics features were significantly associated with rupture. Model A, model B, and model C achieved the area under the receiver operating characteristic curve of 0.767, 0.807, and 0.879, respectively. Model C was significantly better than model A and model B (p < 0.001). Multivariate analysis identified two radiomics features which were used to construct the simplified model showing an AUROC of 0.876.

CONCLUSIONS

Radiomics signatures were different between ruptured and unruptured aneurysms. The use of radiomics features, especially texture features, may significantly improve rupture prediction performance.

KEY POINTS

• Significant radiomics differences exist between ruptured and unruptured intracranial aneurysms. • Radiomics shape features can significantly improve rupture prediction performance over conventional morphology-based prediction model. The inclusion of histogram and texture radiomics features can further improve the performance. • A simplified model with two variables achieved a similar level of performance as the more complex ones. Our prediction model can serve as a promising tool for the risk management of intracranial aneurysms.

Relationship Between Coronary Fractional Flow Reserve and Computational Fluid Dynamics Analysis in Moderate Stenosis of the Coronary Artery

Background: Fractional flow reserve (FFR) is used to evaluate the need for percutaneous coronary intervention (PCI) in cases of moderate stenosis of the coronary artery. Recently, diagnostic imaging support with computational fluid dynamics (CFD) analysis has been garnering attention. This study defines the relationship between FFR conducted for cardiac catheterization and CFD analyses conducted using coronary computed tomography (CT) for moderate stenosis, in addition to considering whether wall pressure (WP) and wall shear stress (WSS) can be used to evaluate ischemia.

Methods and Results: Cases in which FFR was measured via coronary CT and cardiac catheterization was performed within 3 months were collected retrospectively. In the CFD analysis, WP and WSS were calculated and compared with FFR. Three groups were created to compare results of CFD analysis and FFR values according to the location of the stenosis: the right coronary artery, the left anterior descending artery, and the left circumflex artery. There was a correlation between FFR and WSS according to CFD analysis for moderate stenosis of the coronary artery, with a cut-off value for treatment able to be calculated.

Conclusions: The results of this study suggest that ischemia can be evaluated by conducting CFD analysis (WSS) using coronary CT.

The biophysical role of hemodynamics in the pathogenesis of cerebral aneurysm formation and rupture

The pathogenesis of intracranial aneurysms remains complex and multifactorial. While vascular, genetic, and epidemiological factors play a role, nascent aneurysm formation is believed to be induced by hemodynamic forces. Hemodynamic stresses and vascular insults lead to additional aneurysm and vessel remodeling. Advanced imaging techniques allow us to better define the roles of aneurysm and vessel morphology and hemodynamic parameters, such as wall shear stress, oscillatory shear index, and patterns of flow on aneurysm formation, growth, and rupture. While a complete understanding of the interplay between these hemodynamic variables remains elusive, the authors review the efforts that have been made over the past several decades in an attempt to elucidate the physical and biological interactions that govern aneurysm pathophysiology. Furthermore, the current clinical utility of hemodynamics in predicting aneurysm rupture is discussed.

Computational fluid dynamics as a risk assessment tool for aneurysm rupture

OBJECTIVE

The authors reviewed the clinical role of computational fluid dynamics (CFD) in assessing the risk of intracranial aneurysm rupture.

METHODS

A literature review was performed to identify reports on CFD assessment of aneurysms using PubMed. The usefulness of various hemodynamic parameters, such as wall shear stress (WSS) and the Oscillatory Shear Index (OSI), and their role in aneurysm rupture risk analysis, were analyzed.

RESULTS

The authors identified a total of 258 published articles evaluating rupture risk, growth, and endovascular device assessment. Of these 258 articles, 113 matching for CFD and hemodynamic parameters that contribute to the risk of rupture (such as WSS and OSI) were identified. However, due to a lack of standardized methodology, controversy remains on each parameter's role.

CONCLUSIONS

Although controversy continues to exist on which risk factors contribute to predict aneurysm rupture, CFD can provide additional parameters to assess this rupture risk. This technology can contribute to clinical decision-making or evaluation of efficacy for endovascular methods and devices.

Computational and experimental investigation of particulate matter deposition in cerebral side aneurysms

Intracranial aneurysms frequently develop blood clots, plaque and inflammations, which are linked to enhanced particulate mass deposition. In this work, we propose a computational model for particulate deposition, that accounts for the influence of field forces, such as gravity and electrostatics, which produce an additional flux of particles perpendicular to the fluid motion and towards the wall. This field-mediated flux can significantly enhance particle deposition in low-shear environments, such as in aneurysm cavities. Experimental investigation of particle deposition patterns in in vitro models of side aneurysms, demonstrated the ability of the model to predict enhanced particle adhesion at these sites. Our results showed a significant influence of gravity and electrostatic forces (greater than 10%), indicating that the additional terms presented in our models may be necessary for modelling a wide range of physiological flow conditions and not only for ultra-low shear regions. Spatial differences between the computational model and the experimental results suggested that additional transport and fluidic mechanisms affect the deposition pattern within aneurysms. Taken together, the presented findings may enhance our understanding of pathological deposition processes at cardiovascular disease sites, and facilitate rational design and optimization of cardiovascular particulate drug carriers.

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

Arterial aneurysms are pathological dilations of blood vessels, which can be of clinical concern due to thrombosis, dissection, or rupture. Aneurysms can form throughout the arterial system, including intracranial, thoracic, abdominal, visceral, peripheral, or coronary arteries. Currently, aneurysm diameter and expansion rates are the most commonly used metrics to assess rupture risk. Surgical or endovascular interventions are clinical treatment options, but are invasive and associated with risk for the patient. For aneurysms in locations where thrombosis is the primary concern, diameter is also used to determine the level of therapeutic anticoagulation, a treatment that increases the possibility of internal bleeding. Since simple diameter is often insufficient to reliably determine rupture and thrombosis risk, computational hemodynamic simulations are being developed to help assess when an intervention is warranted. Created from subject-specific data, computational models have the potential to be used to predict growth, dissection, rupture, and thrombus-formation risk based on hemodynamic parameters, including wall shear stress, oscillatory shear index, residence time, and anomalous blood flow patterns. Generally, endothelial damage and flow stagnation within aneurysms can lead to coagulation, inflammation, and the release of proteases, which alter extracellular matrix composition, increasing risk of rupture. In this review, we highlight recent work that investigates aneurysm geometry, model parameter assumptions, and other specific considerations that influence computational aneurysm simulations. By highlighting modeling validation and verification approaches, we hope to inspire future computational efforts aimed at improving our understanding of aneurysm pathology and treatment risk stratification.