Imaging Modalities for Intracranial Aneurysm: More Than Meets the Eye

Imaging of Intracranial Aneurysms: A Review of Standard and Advanced Imaging Techniques

The treatment of intracranial aneurysms is dictated by its risk of rupture in the future. Several clinical and radiological risk factors for aneurysm rupture have been described and incorporated into prediction models. Despite the recent technological advancements in aneurysm imaging, linear length and visible irregularity with a bleb are the only radiological measure used in clinical prediction models. The purpose of this article is to summarize both the standard imaging techniques, including their limitations, and the advanced techniques being used experimentally to image aneurysms. It is expected that as our understanding of advanced techniques improves, and their ability to predict clinical events is demonstrated, they become an increasingly routine part of aneurysm assessment. It is important that neurovascular specialists understand the spectrum of imaging techniques available.

Kissing Aneurysms of the Anterior Communicating Artery Treated With Surgical Clipping: A Case Report and Literature Review

Intracranial "kissing" aneurysms are rare vascular conditions described as two anatomically adjacent aneurysms originating from either the same or different arteries, with their walls pressed together. Two-dimensional angiography was formerly considered the gold standard for diagnosis, with the three-dimensional rotational type now offering more insightful details about vascular discrepancies. The treatment of anterior communicating artery (AcoA) "kissing" aneurysms poses significant challenges, with surgical clipping proving difficult due to their deep midline location or the bilateral anterograde arterial supply. However, advancements in endovascular coil embolization, such as dual-volume reconstruction, can assist in diagnosis. This study presents the case of a 50-year-old patient who was diagnosed with "kissing" aneurysms of the AcoA. The patient underwent surgical clipping and showed no pathological follow-up findings. The surgical intervention often provides a more direct and effective approach. This case contributes to the body of knowledge surrounding the management of this complex disease.

The relationship between symptomatic status and aneurysm wall enhancement characteristics of single unruptured intracranial aneurysm

OBJECTIVE

We aimed to analyze the aneurysm wall enhancement (AWE) characteristics of a single unruptured intracranial aneurysm (UIA) and observe the relationship between the symptoms of a single UIA and the aneurysm wall.

METHODS

In our hospital, 85 patients diagnosed with a single UIA using computed tomography angiography (CTA) were retrospectively analyzed. The patients were divided into symptomatic and asymptomatic groups, including 46 asymptomatic and 39 symptomatic aneurysms. High-resolution magnetic resonance imaging of the vascular wall (HR-MR-VWI) was utilized to ascertain the presence, degree, and extent of AWE and thick-wall enhancement. In addition to AWE characteristics, morphological parameters of aneurysms, such as maximal size, shape, height, neck width, aspect ratio (AR), and size ratio (SR), were scanned using CTA. The differences in the parameters of a single UIA between the two groups were compared. An investigation explored the correlation between the symptom status of a single UIA and AWE.

RESULTS

We observed a correlation between symptom status and maximal size, height, and neck width for a single UIA, the presence or absence of AWE, and the levels and boundaries of AWE and thick-wall reinforcement. This study found that the AWE range was independently correlated with symptom status in the multivariate regression analysis.

CONCLUSION

A larger AWE range was an independent risk factor for the onset of symptoms in a single UIA.

Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images

Intracranial aneurysm is a high-risk disease, with imaging playing a crucial role in their diagnosis and treatment. The rapid advancement of artificial intelligence in imaging technology holds promise for the development of AI-based radiomics predictive models. These models could potentially enable the automatic detection and diagnosis of intracranial aneurysms, assess their status, and predict outcomes, thereby assisting in the creation of personalized treatment plans. In addition, these techniques could improve diagnostic efficiency for physicians and patient prognoses. This article aims to review the progress of artificial intelligence radiomics in the study of intracranial aneurysms, addressing the challenges faced and future prospects, in hopes of introducing new ideas for the precise diagnosis and treatment of intracranial aneurysms.

Constrained estimation of intracranial aneurysm surface deformation using 4D-CTA

BACKGROUND AND OBJECTIVE

Intracranial aneurysms are relatively common life-threatening diseases, and assessing aneurysm rupture risk and identifying the associated risk factors is essential. Parameters such as the Oscillatory Shear Index, Pressure Loss Coefficient, and Wall Shear Stress are reliable indicators of intracranial aneurysm development and rupture risk, but aneurysm surface irregular pulsation has also received attention in aneurysm rupture risk assessment.

METHODS

The present paper proposed a new approach to estimate aneurysm surface deformation. This method transforms the estimation of aneurysm surface deformation into a constrained optimization problem, which minimizes the error between the displacement estimated by the model and the sparse data point displacements from the four-dimensional CT angiography (4D-CTA) imaging data.

RESULTS

The effect of the number of sparse data points on the results has been discussed in both simulation and experimental results, and it shows that the proposed method can accurately estimate the surface deformation of intracranial aneurysms when using sufficient sparse data points.

CONCLUSIONS

Due to a potential association between aneurysm rupture and surface irregular pulsation, the estimation of aneurysm surface deformation is needed. This paper proposed a method based on 4D-CTA imaging data, offering a novel solution for the estimation of intracranial aneurysm surface deformation.

The geometric evolution of aortic dissections: Predicting surgical success using fluctuations in integrated Gaussian curvature

Clinical imaging modalities are a mainstay of modern disease management, but the full utilization of imaging-based data remains elusive. Aortic disease is defined by anatomic scalars quantifying aortic size, even though aortic disease progression initiates complex shape changes. We present an imaging-based geometric descriptor, inspired by fundamental ideas from topology and soft-matter physics that captures dynamic shape evolution. The aorta is reduced to a two-dimensional mathematical surface in space whose geometry is fully characterized by the local principal curvatures. Disease causes deviation from the smooth bent cylindrical shape of normal aortas, leading to a family of highly heterogeneous surfaces of varying shapes and sizes. To deconvolute changes in shape from size, the shape is characterized using integrated Gaussian curvature or total curvature. The fluctuation in total curvature (δK) across aortic surfaces captures heterogeneous morphologic evolution by characterizing local shape changes. We discover that aortic morphology evolves with a power-law defined behavior with rapidly increasing δK forming the hallmark of aortic disease. Divergent δK is seen for highly diseased aortas indicative of impending topologic catastrophe or aortic rupture. We also show that aortic size (surface area or enclosed aortic volume) scales as a generalized cylinder for all shapes. Classification accuracy for predicting aortic disease state (normal, diseased with successful surgery, and diseased with failed surgical outcomes) is 92.8±1.7%. The analysis of δK can be applied on any three-dimensional geometric structure and thus may be extended to other clinical problems of characterizing disease through captured anatomic changes.

Detection Rates and Trends of Asymptomatic Unruptured Intracranial Aneurysms From 2005 to 2019

BACKGROUND AND OBJECTIVES

The trend in detection rates of asymptomatic unruptured intracranial aneurysms (UIAs) on brain computed tomography angiography/magnetic resonance angiography (CTA/MRA) is not well established. Our objective was to evaluate time trends in asymptomatic UIA detection rates on brain CTA/MRA between 2005 and 2019.

METHODS

We conducted a retrospective study of all brain computed tomography/magnetic resonance scans (n = 288 336 scans in 130 621 patients) performed between January 2005 and December 2019 at a tertiary referral hospital. Patients who underwent brain CTA/MRA examinations were included (n = 81 261 scans in 48 037 patients). The annual detection rate of new UIA cases was calculated based on the first brain CTA/MRA imaging. Detection rates were compared between three periods and across different age groups.

RESULTS

The number of first CTA/MRA examinations increased significantly from 2005 to 2009 (n = 12 190 patients) to 2010-2014 (n = 14 969 patients) and 2015-2019 (n = 20 878 patients) ( P < .001). The UIA detection rate also increased significantly from 1.7% in 2005-2009 to 2.5% in 2010-2014 and 3.4% in 2015-2019 ( P < .001). The UIA detection rate increased significantly from 2010-2014 to 2015-2019 (relative risk [RR], 1.33; 95% CI, 1.17-1.51), particularly in patients aged 60-69 years (RR, 1.29; 95% CI, 1.01-1.63), 70-79 years (RR, 1.71; 95% CI, 1.30-2.25), and >79 years (RR, 2.33; 95% CI, 1.56-3.47). Furthermore, the detection rate of <5-mm UIAs increased from 2010-2014 to 2015-2019 (RR, 1.51; 95% CI, 1.28-1.77).

CONCLUSION

The detection rate of asymptomatic UIAs, particularly in elderly patients, has increased significantly over the past 15 years, coinciding with the increased use of CTA/MRA imaging. Furthermore, the size of the identified UIAs has decreased. These findings raise concerns about the management strategies for UIAs, indicating the need for further research.

Ruptured Intracranial Aneurysm in a 60-Day-Old Infant: An Extreme Case

The prevalence of aneurysms in children is low when compared to adults, being even rarer in the first year of life. They can be secondary to infections, traumatic brain injury, autoimmune diseases, or connective tissue diseases. Dissecting etiology is rare. A 60-day-old female infant, previously healthy, presented to the emergency department (ED) with irritability and loss of appetite since the preceding day, a fever of one-hour duration, and vomiting. Laboratory analysis revealed a hemoglobin level of 6.5 g/dL, without elevation of inflammatory markers. In the ED, she experienced two episodes, with a one-hour interval, of clonic movements of the upper eyelid and right upper limb, along with conjugate gaze deviation to the same side, which resolved after intravenous diazepam. Levetiracetam was initiated after the second episode. The anterior fontanelle became progressively tense. Brain computed tomography (CT) showed a voluminous intraparenchymal and subarachnoid hemorrhage with an aneurysm at the bifurcation of the left middle cerebral artery (MCA). Initially, an endovascular approach was tried but was not successful due to technical problems. Consequently, a Vaso-CT scan was performed that confirmed a dissecting aneurysm/pseudoaneurysm (8 mm × 10 mm × 10 mm) of the left MCA, originating from the upper wall of the M1 segment. Next, she underwent microsurgical exclusion of the aneurysm using microclips. Post-surgery brain CT showed acute ischemia in the entire MCA region. Follow-up angiography showed complete exclusion of the aneurysm. She evolved to grade 3 monoparesis of the upper limb at the six-month interval follow-up, which has been gradually improving with physical rehabilitation. The next-generation sequencing (NGS) panel for aneurysms and arterial dissections did not detect any pathogenic variants. Clinical presentation of cerebral aneurysms in infants can be subtle, and a high index of suspicion is required in cases of irritability, altered consciousness, seizures, bulging fontanelle, and motor deficits. Early detection is of utmost importance as it is associated with moderate mortality. Surgical treatment with the use of clips proved to be effective in this case.

Comparative Study of the Diagnostic Value of Zero-Echo-Time Magnetic Resonance Angiography With Time-of-Flight Magnetic Resonance Angiography for Intracranial Aneurysm

OBJECTIVE

Intracranial aneurysm (IAN) is a class of cerebrovascular diseases with a serious threat to patients, and an accurate diagnosis of IAN is very important for both selection of the appropriate therapy and prediction of the prognosis. This study aimed to evaluate the diagnostic values of zero-echo-time magnetic resonance angiography (ZTE-MRA) and time-of-flight magnetic resonance angiography (TOF-MRA) in patients with IAN.

METHODS

Digital subtraction angiography, ZTE-MRA, and TOF-MRA were performed in 18 patients diagnosed with IAN. The images of ZTE-MRA and TOF-MRA were compared for image quality, qualitative diagnosis, detailed diagnosis, number of thrombi, and residual aneurysm lumen, with digital subtraction angiography as the reference.

RESULTS

Zero-echo-time MRA and TOF-MRA did not show a significant difference in image quality or detailed information (including aneurysm size, growth direction, and angle with the aneurysm-carrying vessel) ( P > 0.05). However, ZTE-MRA showed advantages over TOF-MRA in terms of qualitative diagnosis (sensitivity and specificity), intra-aneurismal thrombus detection, and residual aneurysm lumen detection after embolization ( P < 0.05).

CONCLUSIONS

Compared with TOF-MRA, ZTE-MRA showed greater diagnostic value for IAN patients in terms of qualitative diagnosis, as well as the detection of intra-aneurysm thrombi and residual aneurysm lumen after embolization.

Comparative Study of Automated Algorithms for Brain Arteriovenous Malformation Nidus Extent Identification Using 3DRA

PURPOSE

When performing a brain arteriovenous malformation (bAVMs) intervention, computer-assisted analysis of bAVMs can aid clinicians in planning precise therapeutic alternatives. Therefore, we aim to assess currently available methods for bAVMs nidus extent identification over 3DRA. To this end, we establish a unified framework to contrast them over the same dataset, fully automatising the workflows.

MATERIALS AND METHODS

We retrospectively collected contrast-enhanced 3DRA scans of patients with bAVMs. A segmentation network was used to automatically acquire the brain vessels segmentation for each case. We applied the nidus extent identification algorithms over each of the segmentations, computing overlap measurements against manual nidus delineations.

RESULTS

We evaluated the methods over a private dataset with 22 3DRA scans of individuals with bAVMs. The best-performing alternatives resulted in [Formula: see text] and [Formula: see text] dice coefficient values.

CONCLUSIONS

The mathematical morphology-based approach showed higher robustness through inter-case variability. The skeleton-based approach leverages the skeleton topomorphology characteristics, while being highly sensitive to anatomical variations and the skeletonisation method employed. Overall, nidus extent identification algorithms are also limited by the quality of the raw volume, as the consequent imprecise vessel segmentation will hinder their results. Performance of the available alternatives remains subpar. This analysis allows for a better understanding of the current limitations.

Machine learning and reduced order modelling for the simulation of braided stent deployment

Endoluminal reconstruction using flow diverters represents a novel paradigm for the minimally invasive treatment of intracranial aneurysms. The configuration assumed by these very dense braided stents once deployed within the parent vessel is not easily predictable and medical volumetric images alone may be insufficient to plan the treatment satisfactorily. Therefore, here we propose a fast and accurate machine learning and reduced order modelling framework, based on finite element simulations, to assist practitioners in the planning and interventional stages. It consists of a first classification step to determine a priori whether a simulation will be successful (good conformity between stent and vessel) or not from a clinical perspective, followed by a regression step that provides an approximated solution of the deployed stent configuration. The latter is achieved using a non-intrusive reduced order modelling scheme that combines the proper orthogonal decomposition algorithm and Gaussian process regression. The workflow was validated on an idealized intracranial artery with a saccular aneurysm and the effect of six geometrical and surgical parameters on the outcome of stent deployment was studied. We trained six machine learning models on a dataset of varying size and obtained classifiers with up to 95% accuracy in predicting the deployment outcome. The support vector machine model outperformed the others when considering a small dataset of 50 training cases, with an accuracy of 93% and a specificity of 97%. On the other hand, real-time predictions of the stent deployed configuration were achieved with an average validation error between predicted and high-fidelity results never greater than the spatial resolution of 3D rotational angiography, the imaging technique with the best spatial resolution (0.15 mm). Such accurate predictions can be reached even with a small database of 47 simulations: by increasing the training simulations to 147, the average prediction error is reduced to 0.07 mm. These results are promising as they demonstrate the ability of these techniques to achieve simulations within a few milliseconds while retaining the mechanical realism and predictability of the stent deployed configuration.

Imaging of intracranial aneurysms in animals: a systematic review of modalities

Intracranial aneurysm (IA) animal models are paramount to study IA pathophysiology and to test new endovascular treatments. A number of in vivo imaging modalities are available to characterize IAs at different stages of development in these animal models. This review describes existing in vivo imaging techniques used so far to visualize IAs in animal models. We systematically searched for studies containing in vivo imaging of induced IAs in animal models in PubMed and SPIE Digital library databases between 1 January 1945 and 13 July 2022. A total of 170 studies were retrieved and reviewed in detail, and information on the IA animal model, the objective of the study, and the imaging modality used was collected. A variety of methods to surgically construct or endogenously induce IAs in animals were identified, and 88% of the reviewed studies used surgical methods. The large majority of IA imaging in animals was performed for 4 reasons: basic research for IA models, testing of new IA treatment modalities, research on IA in vivo imaging of IAs, and research on IA pathophysiology. Six different imaging techniques were identified: conventional catheter angiography, computed tomography angiography, magnetic resonance angiography, hemodynamic imaging, optical coherence tomography, and fluorescence imaging. This review presents and discusses the advantages and disadvantages of all in vivo IA imaging techniques used in animal models to help future IA studies finding the most appropriate IA imaging modality and animal model to answer their research question.

Advanced cross-sectional imaging of cerebral aneurysms

While the rupture rate of cerebral aneurysms is only 1% per year, ruptured aneurysms are associated with significant morbidity and mortality, while aneurysm treatments have their own associated risk of morbidity and mortality. Conventional markers for aneurysm rupture include patient-specific and aneurysm-specific characteristics, with the development of scoring systems to better assess rupture risk. These scores, however, rely heavily on aneurysm size, and their accuracy in assessing risk in smaller aneurysms is limited. While the individual risk of rupture of small aneurysms is low, due to their sheer number, the largest proportion of ruptured aneurysms are small aneurysms. Conventional imaging techniques are valuable in characterizing aneurysm morphology; however, advanced imaging techniques assessing the presence of inflammatory changes within the aneurysm wall, hemodynamic characteristics of blood flow within aneurysm sacs, and imaging visualization of irregular aneurysm wall motion have been used to further determine aneurysm instability that otherwise cannot be characterized by conventional imaging techniques. The current manuscript reviews conventional imaging techniques and their value and limitations in cerebral aneurysm characterization, and evaluates the applications, value and limitations of advanced aneurysm imaging and post-processing techniques including intracranial vessel wall MRA, 4D-flow, 4D-CTA, and computational fluid dynamic simulations.