Wall enhancement characteristics of vertebrobasilar nonsaccular aneurysms and their relationship to symptoms

Association Between Serum Homocysteine Concentration, Aneurysm Wall Inflammation, and Aneurysm Symptoms in Intracranial Fusiform Aneurysm

RATIONALE AND OBJECTIVES

The pathophysiology of fusiform intracranial aneurysm (FIA) involves inflammatory processes, and homocysteine plays a role in the inflammatory processes in the vessel wall. Moreover, aneurysm wall enhancement (AWE) has emerged as a new imaging biomarker of aneurysm wall inflammatory pathologies. To investigate the pathophysiological mechanisms of aneurysm wall inflammation and FIA instability, we aimed to determine the associations between the homocysteine concentration, AWE, and FIAs' related symptoms.

MATERIALS AND METHODS

We retrospectively reviewed the data of 53 patients with FIA who underwent both high-resolution magnetic resonance imaging and serum homocysteine concentration measurement. FIAs' related symptoms were defined as ischemic stroke or transient ischemic attack, cranial nerve compression, brainstem compression, and acute headache. The contrast ratio of the signal intensity of the aneurysm wall to the pituitary stalk (CRstalk) was used to indicate AWE. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to determine how well the independent factors could predict FIAs' related symptoms. Predictors of CRstalk were also investigated. Spearman's correlation coefficient was used to identify the potential associations between these predictors.

RESULTS

Fifty-three patients were included, of whom 23 (43.4%) presented with FIAs' related symptoms. After adjusting for baseline differences in the multivariate logistic regression analysis, the CRstalk (odds ratio [OR]=3.207, P = .023) and homocysteine concentration (OR=1.344, P = .015) independently predicted FIAs' related symptoms. The CRstalk was able to differentiate between FIAs with and without symptoms (area under the ROC curve [AUC]=0.805), with an optimal cutoff value of 0.76. The homocysteine concentration could also differentiate between FIAs with and without symptoms (AUC=0.788), with an optimal cutoff value of 13.13. The combination of the CRstalk and homocysteine concentration had a better ability to identify symptomatic FIAs (AUC=0.857). Male sex (OR=0.536, P = .018), FIAs' related symptoms (OR=1.292, P = .038), and homocysteine concentration (OR=1.254, P = .045) independently predicted the CRstalk.

CONCLUSION

A higher serum homocysteine concentration and greater AWE indicate FIA instability. Serum homocysteine concentration may be a useful biomarker of FIA instability; however, this needs to be verified in future studies.

Statins may Decrease Aneurysm wall Enhancement of Unruptured Fusiform Intracranial Aneurysms: A high-resolution 3T MRI Study

Inflammation plays an integral role in the formation, growth, and progression to rupture of unruptured intracranial aneurysms. Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) has emerged as a surrogate biomarker of vessel wall inflammation and unruptured intracranial aneurysm instability. We investigated the correlation between anti-inflammatory drug use and three-dimensional AWE of fusiform intracranial aneurysms (FIAs). We retrospectively analyzed consecutive patients with FIAs in our database who underwent 3T HR-MRI at three Chinese centers. FIAs were classified as fusiform-type, dolichoectatic-type, or transitional-type. AWE was objectively defined using the aneurysm-to-pituitary stalk contrast ratio in three-dimensional space by determining the contrast ratio of the average signal intensity in the aneurysmal wall and pituitary stalk on post-contrast T1-weighted images. Data on aneurysm size, morphology, and location, as well as patient demographics and comorbidities, were collected. Univariate and multivariate logistic regression analyses were performed to determine factors independently associated with AWE of FIAs on HR-MRI. In total, 127 FIAs were included. In multivariate analysis, statin use (β = -0.236, P = 0.007) was the only independent factor significantly associated with decreased AWE. In the analysis of three FIA subtypes, the fusiform and transitional types were significantly associated with statin use (rs = -0.230, P = 0.035; and rs = -0.551, P = 0.010; respectively). It establishes an incidental correlation between the use of statins daily for ≥ 6 months and decreased AWE of FIAs. The findings also indicate that the pathophysiology may differ among the three FIA subtypes.

Three-dimensional aneurysm wall enhancement in fusiform intracranial aneurysms is associated with aneurysmal symptoms

Background and purpose

Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) is a potential biomarker for evaluating unstable aneurysms. Fusiform intracranial aneurysms (FIAs) frequently have a complex and curved structure. We aimed to develop a new three-dimensional (3D) aneurysmal wall enhancement (AWE) characterization method to enable comprehensive FIA evaluation and to investigate the ability of 3D-AWE to predict symptomatic FIA.

Methods

We prospectively recruited patients with unruptured FIAs and received 3 T HR-MRI imaging from September 2017 to January 2019. 3D models of aneurysms and parent arteries were generated. Boundaries of the FIA were determined using 3D vessel diameter measurements. D_max was the greatest diameter in the cross-section, while L_max was the length of the centerline of the aneurysm. Signal intensity of the FIA was normalized to the pituitary stalk and then mapped onto the 3D model, then the average enhancement (3D-AWE_avg), maximum enhancement (3D-AWE_max), enhancement area (AWE_area), and enhancement ratio (AWE_ratio) were calculated as AWE indicators, and the surface area of the entire aneurysm (A_area) was also calculated. Areas with high AWE were defined as those with a value >0.9 times the signal intensity of the pituitary stalk. Multivariable logistic regression analyses were performed to determine independent predictors of aneurysm-related symptoms. FIA subtypes were defined as fusiform, dolichoectasia, and transitional. Differences between the three FIA subtypes were also examined.

Results

Forty-seven patients with 47 FIAs were included. Mean patient age was 55 ± 12.62 years and 74.5% were male. Twenty-nine patients (38.3%) were symptomatic. After adjusting for baseline differences in age, hypertension, L_max, and FIA subtype, the multivariate logistics regression models showed that 3D-AWE_avg (odds ratio [OR], 4.029; p = 0.019), 3D-AWE_max (OR, 3.437; p = 0.022), AWE_area (OR, 1.019; p = 0.008), and AWE_ratio (OR, 2.490; p = 0.045) were independent predictors of aneurysm-related symptoms. D_max and A_area were larger and 3D-AWE_avg, 3D-AWE_max, AWE_area, and AWE_ratio were higher with the transitional subtype than the other two subtypes.

Conclusion

The new 3D AWE method, which enables the use of numerous new metrics, can predict symptomatic FIAs. Different 3D-AWE between the three FIA subtypes may be helpful in understanding the pathophysiology of FIAs.

Aneurysm wall enhancement, hemodynamics, and morphology of intracranial fusiform aneurysms

Background and objective

Intracranial fusiform aneurysms (IFAs) are considered to have a complex pathophysiology process and poor natural history. The purpose of this study was to investigate the pathophysiological mechanisms of IFAs based on the characteristics of aneurysm wall enhancement (AWE), hemodynamics, and morphology.

Methods

A total of 21 patients with 21 IFAs (seven fusiform types, seven dolichoectatic types, and seven transitional types) were included in this study. Morphological parameters of IFAs were measured from the vascular model, including the maximum diameter (Dmax), maximum length (Lmax), and centerline curvature and torsion of fusiform aneurysms. The three-dimensional (3D) distribution of AWE in IFAs was obtained based on high-resolution magnetic resonance imaging (HR-MRI). Hemodynamic parameters including time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), gradient oscillatory number (GON), and relative residence time (RRT) were extracted by computational fluid dynamics (CFD) analysis of the vascular model, and the relationship between these parameters and AWE was investigated.

Results

The results showed that Dmax (p = 0.007), Lmax (p = 0.022), enhancement area (p = 0.002), and proportion of enhancement area (p = 0.006) were significantly different among three IFA types, and the transitional type had the largest Dmax, Lmax, and enhancement area. Compared with the non-enhanced regions of IFAs, the enhanced regions had lower TAWSS but higher OSI, GON, and RRT (p < 0.001). Furthermore, Spearman’s correlation analysis showed that AWE was negatively correlated with TAWSS, but positively correlated with OSI, GON, and RRT.

Conclusion

There were significant differences in AWE distributions and morphological features among the three IFA types. Additionally, AWE was positively associated with the aneurysm size, OSI, GON, and RRT, while negatively correlated with TAWSS. However, the underlying pathological mechanism of the three fusiform aneurysm types needs to be further studied.

Aneurysm wall enhancement, atherosclerotic proteins, and aneurysm size may be related in unruptured intracranial fusiform aneurysms

OBJECTIVE

This cross-sectional study aimed to investigate the associations between aneurysm wall enhancement (AWE), atherosclerotic protein levels, and aneurysm size in unruptured intracranial fusiform aneurysms (IFAs).

METHODS

Patients with IFAs underwent high-resolution magnetic resonance imaging (HR-MRI) and atherosclerotic protein examinations from May 2015 to December 2021 were collected. A CR_stalk (signal intensity [SI] of IFA wall/SI of pituitary stalk) > 0.60 was considered to indicate AWE. Atherosclerotic protein data was obtained from the peripheral blood. Aneurysmal characteristics included the maximal diameter of the cross-section (D_max), location, type of IFA, presence of mural thrombus, and mural clots. Statistical analyses were performed with univariate analysis, logistic regression analysis, and Spearman's correlation coefficient.

RESULTS

Seventy-one IFAs from 71 patients were included in the study. Multivariate analysis revealed statin use (OR = 0.189, p = 0.026) and apolipoprotein B (Apo-B) level (OR = 6.019, p = 0.026) were the independent predictors of AWE in IFAs. In addition, statin use (OR = 0.813, p = 0.036) and Apo-B level (OR = 1.610, p = 0.003) were also the independent predictors of CR_stalk. Additionally, we found that CR_stalk and AWE were significantly positively associated with D_max (r_s = 0.409 and 0.349, respectively; p < 0.001 and p = 0.003, respectively).

CONCLUSIONS

There may be correlations between AWE, atherosclerotic protein levels, and aneurysm size in patients with IFAs. Apo-B and statin use were independent predictors of AWE in IFAs, which have the potential to be new therapeutic targets for IFAs.

KEY POINTS

• There may be correlations between aneurysm wall enhancement, atherosclerotic protein levels in the peripheral blood, and aneurysm size in patients with intracranial fusiform aneurysms. • Apolipoprotein B and statin use were independent predictors of aneurysm wall enhancement in intracranial fusiform aneurysms.

Systemic immune-inflammation index is associated with aneurysmal wall enhancement in unruptured intracranial fusiform aneurysms

Introduction

Inflammation plays a key role in the progression of intracranial aneurysms. Aneurysmal wall enhancement (AWE) correlates well with inflammatory processes in the aneurysmal wall. Understanding the potential associations between blood inflammatory indices and AWE may aid in the further understanding of intracranial aneurysm pathophysiology.

Methods

We retrospectively reviewed 122 patients with intracranial fusiform aneurysms (IFAs) who underwent both high-resolution magnetic resonance imaging and blood laboratory tests. AWE was defined as a contrast ratio of the signal intensity of the aneurysmal wall to that of the pituitary stalk ≥ 0.90. The systemic immune-inflammation (SII) index (neutrophils × platelets/lymphocytes) was calculated from laboratory data and dichotomized based on whether or not the IFA had AWE. Aneurysmal symptoms were defined as sentinel headache or oculomotor nerve palsy. Multivariable logistic regression and receiver operating characteristic curve analyses were performed to determine how well the SII index was able to predict AWE and aneurysmal symptoms. Spearman's correlation coefficients were used to explore the potential associations between variables.

Results

This study included 95 patients, of whom 24 (25.3%) presented with AWE. After adjusting for baseline differences in neutrophil to lymphocyte ratios, leukocytes, and neutrophils in the multivariable logistic regression analysis, smoking history (P = 0.002), aneurysmal symptoms (P = 0.047), maximum diameter (P = 0.048), and SII index (P = 0.022) all predicted AWE. The SII index (P = 0.038) was the only independent predictor of aneurysmal symptoms. The receiver operating characteristic curve analysis revealed that the SII index was able to accurately distinguish IFAs with AWE (area under the curve = 0.746) and aneurysmal symptoms (area under the curve = 0.739).

Discussion

An early elevation in the SII index can independently predict AWE in IFAs and is a potential new biomarker for predicting IFA instability.

Comparisons between cross-section and long-axis-section in the quantification of aneurysmal wall enhancement of fusiform intracranial aneurysms in identifying aneurysmal symptoms

Background

To investigate the quantification of aneurysmal wall enhancement (AWE) in fusiform intracranial aneurysms (FIAs) and to compare AWE parameters based on different sections of FIAs in identifying aneurysm symptoms.

Methods

Consecutive patients were prospectively recruited from February 2017 to November 2019. Aneurysm-related symptoms were defined as sentinel headache and oculomotor nerve palsy. All patients underwent high resolution magnetic resonance imaging (HR-MRI) protocol, including both pre and post-contrast imaging. CR_stalk (signal intensity of FIAs' wall divided by pituitary infundibulum) was evaluated both in the cross-section (CR_{stalk−cross}) and the long-axis section (CR_stalk−long) of FIAs. Aneurysm characteristics include the maximal diameter of the cross-section (D_max), the maximal length of the long-axis section (L_max), location, type, and mural thrombus. The performance of parameters for differentiating symptomatic and asymptomatic FIAs was obtained and compared by a receiver operating characteristic (ROC) curve.

Results

Forty-three FIAs were found in 43 patients. Eighteen (41.9%) patients who presented with aneurysmal symptoms were classified in the symptomatic group. In univariate analysis, male sex (P = 0.133), age (P = 0.013), FIAs type (P = 0.167), mural thrombus (P = 0.130), L_max (P = 0.066), CR_{stalk−cross} (P = 0.027), and CR_stalk−long (P = 0.055) tended to be associated with aneurysmal symptoms. In the cross-section model of multivariate analysis, male (P = 0.038), age (P = 0.018), and CR_{stalk−cross} (P = 0.048) were independently associated with aneurysmal symptoms. In the long-axis section model of multivariate analysis, male (P = 0.040), age (P = 0.010), CR_stalk−long (P = 0.046), and L_max (P = 0.019) were independently associated with aneurysmal symptoms. In the combination model of multivariate analysis, male (P = 0.027), age (P = 0.011), CR_{stalk−cross} (P = 0.030), and L_max (P = 0.020) were independently associated with aneurysmal symptoms. CR_{stalk−cross} has the highest accuracy in predicting aneurysmal symptoms (AUC = 0.701). The combination of CR_{stalk−cross} and L_max exhibited the highest performance in discriminating symptomatic from asymptomatic FIAs (AUC = 0.780).

Conclusion

Aneurysmal wall enhancement is associated with symptomatic FIAs. CR_{stalk−cross} and L_max were independent risk factors for aneurysmal symptoms. The combination of these two factors may improve the predictive performance of aneurysmal symptoms and may also help to stratify the instability of FIAs in future studies.

Quantification of aneurysm wall enhancement in intracranial fusiform aneurysms and related predictors based on high-resolution magnetic resonance imaging: a validation study

Background:

Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) has emerged as a new imaging biomarker of intracranial aneurysm instability.

Objective:

To determine a standard method of AWE quantification for predicting fusiform intracranial aneurysms (FIAs) stability by comparing the sensitivity of each parameter in identifying symptomatic FIAs. The predictors of AWE and FIA types were also identified.

Methods:

We retrospectively analyzed consecutive fusiform aneurysm patients who underwent HR-MRI from two centers. The aneurysm-to-pituitary stalk contrast ratio (CR_stalk), aneurysm enhancement ratio, and aneurysm enhancement index were extracted, and their sensitivities in discriminating aneurysm symptoms were compared using the receiver-operating characteristic curve. Morphological parameters of fusiform aneurysm were extracted based on 3D vessel model. Uni- and multivariate analyses of related predictors for AWE, CR_stalk, and FIA types were performed, respectively.

Results:

Overall, 117 patients (mean age, 53.3 ± 11.7 years; male, 75.2%) with 117 FIAs underwent HR-MRI were included. CR_stalk with the maximum signal intensity (CR_stalk-max) had the highest sensitivity in identifying symptomatic FIAs with an area under the curve value (0.697) and a cut-off value of 0.90. The independent predictors of AWE were aneurysm symptoms [(odds ratio) OR = 3.754, p = 0.003], aspirin use (OR = 0.248, p = 0.037), and the maximum diameter of the cross-section (OR = 1.171, p = 0.043). The independent predictors of CR_stalk-max were aneurysm symptoms (OR = 1.289, p = 0.003) and posterior circulation aneurysm (OR = 1.314, p = 0.001). Transitional-type showed higher rates of hypertension and mural thrombus over both dolichoectatic- and fusiform-type FIAs.

Conclusion:

CR_stalk-max may be the most reliable parameter to quantify AWE to distinguish symptomatic FIAs. It also has the potential to identify unstable FIAs. Several factors contribute to the complex pathophysiology of FIAs and need further validation in a larger cohort.

Insights into the pathogenesis of cerebral fusiform aneurysms: high-resolution MRI and computational analysis

BACKGROUND

Intracranial fusiform aneurysms are complex and poorly characterized vascular lesions. High-resolution magnetic resonance imaging (HR-MRI) and computational morphological analysis may be used to characterize cerebral fusiform aneurysms.

OBJECTIVE

To use advanced imaging and computational analysis to understand the unique pathophysiology, and determine possible underlying mechanisms of instability of cerebral fusiform aneurysms.

METHODS

Patients with unruptured intracranial aneurysms prospectively underwent imaging with 3T HR-MRI at diagnosis. Aneurysmal wall enhancement was objectively quantified using signal intensity after normalization of the contrast ratio (CR) with the pituitary stalk. Enhancement between saccular and fusiform aneurysms was compared, as well as enhancement characteristics of fusiform aneurysms. The presence of microhemorrhages in fusiform aneurysms was determined with quantitative susceptibility mapping (QSM). Three distinct types of fusiform aneurysms were analyzed with computational fluid dynamics (CFD) and finite element analysis (FEA).

RESULTS

A total of 130 patients with 160 aneurysms underwent HR-MRI. 136 aneurysms were saccular and 24 were fusiform. Fusiform aneurysms had a significantly higher CR and diameter than saccular aneurysms. Enhancing fusiform aneurysms exhibited more enhancement of reference vessels than non-enhancing fusiform aneurysms. Ten fusiform aneurysms underwent QSM analysis, and five aneurysms showed microhemorrhages. Microhemorrhage-positive aneurysms had a larger volume, diameter, and greater enhancement than aneurysms without microhemorrhage. Three types of fusiform aneurysms exhibited different CFD and FEA patterns.

CONCLUSION

Fusiform aneurysms exhibited more contrast enhancement than saccular aneurysms. Enhancing fusiform aneurysms had larger volume and diameter, more enhancement of reference vessels, and more often exhibited microhemorrhage than non-enhancing aneurysms. CFD and FEA suggest that various pathophysiological processes determine the formation and growth of fusiform aneurysms.

Black-Blood Contrast in Cardiovascular MRI

MRI is a versatile technique that offers many different options for tissue contrast, including suppressing the blood signal, so‐called black‐blood contrast. This contrast mechanism is extremely useful to visualize the vessel wall with high conspicuity or for characterization of tissue adjacent to the blood pool. In this review we cover the physics of black‐blood contrast and different techniques to achieve blood suppression, from methods intrinsic to the imaging readout to magnetization preparation pulses that can be combined with arbitrary readouts, including flow‐dependent and flow‐independent techniques. We emphasize the technical challenges of black‐blood contrast that can depend on flow and motion conditions, additional contrast weighting mechanisms (T₁, T₂, etc.), magnetic properties of the tissue, and spatial coverage. Finally, we describe specific implementations of black‐blood contrast for different vascular beds.