Dataset Information

Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.

ABSTRACT: PURPOSE:Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient gender and age. METHODS:Cross-sectional data from 1061 patients were used for image-based computational fluid dynamics and shape characterization of 1631 aneurysms for training an aneurysm rupture probability model using logistic group Lasso regression. The model's discrimination and calibration were internally validated based on the area under the curve (AUC) of the receiver operating characteristic and calibration plots. RESULTS:The final model retained 11 hemodynamic and 12 morphological variables, aneurysm location, as well as patient age and gender. An adverse hemodynamic environment characterized by a higher maximum oscillatory shear index, higher kinetic energy and smaller low shear area as well as a more complex aneurysm shape, male gender and younger age were associated with an increased rupture risk. The corresponding AUC of the model was 0.86 (95% CI [0.85, 0.86], after correction for optimism 0.84). CONCLUSION:The model combining variables from various domains was able to discriminate between ruptured and unruptured aneurysms with an AUC of 86%. Internal validation indicated potential for the application of this model in clinical practice after evaluation with longitudinal data.

SUBMITTER: Detmer FJ

PROVIDER: S-EPMC6328054 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.

Detmer Felicitas J FJ Chung Bong Jae BJ Mut Fernando F Slawski Martin M Hamzei-Sichani Farid F Putman Christopher C Jiménez Carlos C Cebral Juan R JR

International journal of computer assisted radiology and surgery 20180809 11

<h4>Purpose</h4>Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient ...[more]

PMID: 30094777

Similar Datasets

Project description:Background and objectiveIntracranial 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.MethodsA 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.ResultsThe 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.ConclusionThere 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.

Project description:BackgroundRecurrence of intracranial aneurysms after endovascular coiling is a serious clinical concern.ObjectiveWe hypothesized that recurrence is associated with aneurysm morphology and flow, as well as the coil intervention and the induced flow modifications.MethodsWe collected 52 primary-coiling aneurysm cases that were either occluded (n=34) or recurrent (n=18) at >1 year follow-up. We created aneurysm models from pre-coiling digital subtraction angiographic images, calculated aneurysm morphology, simulated pre-coiling hemodynamics, modeled coil deployment, and obtained post-coiling hemodynamics for each case. We performed univariable analysis on 26 morphologic, treatment-specific, and hemodynamic parameters to distinguish between recurrent and occluded groups, and multivariable analysis to identify independently significant parameters associated with recurrence. Univariable analysis was also performed on ruptured and unruptured aneurysm subcohorts separately to investigate if they shared specific significant parameters.ResultsRecurrence was associated with pre-coiling aneurysm morphologic and flow parameters including larger size (maximum dimension and volume), larger neck (diameter, area, and neck-to-parent-artery ratio), and higher flow momentum and kinetic energy. Recurrence was also associated with lower coil packing (packing density and uncoiled volume), higher post-treatment flow (velocity, momentum, and kinetic energy), lower post-treatment washout time, and higher post-treatment impingement force at the neck. Multivariable analysis identified two aneurysmal characteristics (neck diameter and pre-coiling flow kinetic energy), one coil packing parameter (uncoiled volume), and one post-treatment hemodynamic parameter (flow momentum) that were independently associated with recurrence. In ruptured aneurysms, recurrence was associated with larger neck (diameter and area), whereas in unruptured aneurysms, recurrence was associated with larger size (maximum dimension and volume). In both subcohorts, recurrence was associated with higher post-coiling flow momentum and kinetic energy.ConclusionRecurrence at >1 year after coil treatment is associated with intrinsic aneurysm characteristics, coiling itself, and flow changes induced by coiling. Larger aneurysm size and neck, less coil packing, and higher intra-aneurysmal flow before and after coiling predict recurrence.

Project description:Background: The circle of Willis is a network of arteries allowing blood supply to the brain. Bulging of these arteries leads to formation of intracranial aneurysm (IA). Subarachnoid hemorrhage (SAH) due to IA rupture is among the leading causes of disability in the western world. The formation and rupture of IAs is a complex pathological process not completely understood. In the present study, we have precisely measured aneurysmal wall thickness and its uniformity on histological sections and investigated for associations between IA wall thickness/uniformity and commonly admitted risk factors for IA rupture. Methods: Fifty-five aneurysm domes were obtained at the Geneva University Hospitals during microsurgery after clipping of the IA neck. Samples were embedded in paraffin, sectioned and stained with hematoxylin-eosin to measure IA wall thickness. The mean, minimum, and maximum wall thickness as well as thickness uniformity was measured for each IA. Clinical data related to IA characteristics (ruptured or unruptured, vascular location, maximum dome diameter, neck size, bottleneck factor, aspect and morphology), and patient characteristics [age, smoking, hypertension, sex, ethnicity, previous SAH, positive family history for IA/SAH, presence of multiple IAs and diagnosis of polycystic kidney disease (PKD)] were collected. Results: We found positive correlations between maximum dome diameter or neck size and IA wall thickness and thickness uniformity. PKD patients had thinner IA walls. No associations were found between smoking, hypertension, sex, IA multiplicity, rupture status or vascular location, and IA wall thickness. No correlation was found between patient age and IA wall thickness. The group of IAs with non-uniform wall thickness contained more ruptured IAs, women and patients harboring multiple IAs. Finally, PHASES and ELAPSS scores were positively correlated with higher IA wall heterogeneity. Conclusion: Among our patient and aneurysm characteristics of interest, maximum dome diameter, neck size and PKD were the three factors having the most significant impact on IA wall thickness and thickness uniformity. Moreover, wall thickness heterogeneity was more observed in ruptured IAs, in women and in patients with multiple IAs. Advanced medical imaging allowing in vivo measurement of IA wall thickness would certainly improve personalized management of the disease and patient care.

Dataset Information

Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.

Publications

Development and internal validation of an aneurysm rupture probability model based on patient characteristics and aneurysm location, morphology, and hemodynamics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets