Predicting the risk of rupture for vertebral aneurysm based on geometric features of blood vessels.
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SUBMITTER: Li S
PROVIDER: S-EPMC8355691 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundClinical and imaging surveillance practices following endovascular aneurysm repair (EVAR) for intact abdominal aortic aneurysm (AAA) vary considerably and compliance with recommended lifelong surveillance is poor. The aim of this study was to develop a dynamic prognostic model to enable stratification of patients at risk of future secondary aortic rupture or the need for intervention to prevent rupture (rupture-preventing reintervention) to enable the development of personalized surveillance intervals.MethodsBaseline data and repeat measurements of postoperative aneurysm sac diameter from the EVAR-1 and EVAR-2 trials were used to develop the model, with external validation in a cohort from a single-centre vascular database. Longitudinal mixed-effects models were fitted to trajectories of sac diameter, and model-predicted sac diameter and rate of growth were used in prognostic Cox proportional hazards models.ResultsSome 785 patients from the EVAR trials were included, of whom 155 (19·7 per cent) experienced at least one rupture or required a rupture-preventing reintervention during follow-up. An increased risk was associated with preoperative AAA size, rate of sac growth and the number of previously detected complications. A prognostic model using predicted sac growth alone had good discrimination at 2 years (C-index 0·68), 3 years (C-index 0·72) and 5 years (C-index 0·75) after operation and had excellent external validation (C-index 0·76-0·79). More than 5 years after operation, growth rates above 1 mm/year had a sensitivity of over 80 per cent and specificity over 50 per cent in identifying events occurring within 2 years.ConclusionSecondary sac growth is an important predictor of rupture or rupture-preventing reintervention to enable the development of personalized surveillance intervals. A dynamic prognostic model has the potential to tailor surveillance by identifying a large proportion of patients who may require less intensive follow-up.
| S-EPMC6175165 | biostudies-literature
Project description:ObjectivesAssessing the risk associated with unruptured intracranial aneurysms (IAs) is essential in clinical decision making. Several geometric risk parameters have been proposed for this purpose. However, performance of these parameters has been inconsistent. This study evaluates the performance and robustness of geometric risk parameters on two datasets and compare it to the uncertainty inherent in assessing these parameters and quantifies interparameter correlations.MethodsTwo datasets containing 244 ruptured and unruptured IA geometries from 178 patients were retrospectively analysed. IAs were stratified by anatomical region, based on the PHASES score locations. 37 geometric risk parameters representing four groups (size, neck, non-dimensional, and curvature parameters) were assessed. Analysis included standardised absolute group differences (SADs) between ruptured and unruptured IAs, ratios of SAD to median relative uncertainty (MRU) associated with the parameters, and interparameter correlation.ResultsThe ratio of SAD to MRU was lower for higher dimensional size parameters (ie, areas and volumes) than for one-dimensional size parameters. Non-dimensional size parameters performed comparatively well with regard to SAD and MRU. SAD was higher in the posterior anatomical region. Correlation of parameters was strongest within parameter (sub)groups and between size and curvature parameters, while anatomical region did not strongly affect correlation patterns.ConclusionNon-dimensional parameters and few parameters from other groups were comparatively robust, suggesting that they might generalise better to other datasets. The data on discriminative performance and interparameter correlations presented in this study may aid in developing and choosing robust geometric parameters for use in rupture risk models.
| S-EPMC9644336 | biostudies-literature
Project description:Hemorrhagic stroke accounts for 10-15% of all strokes and is strongly associated with mortality and morbidity worldwide, but its prevention and therapeutic interventions remain a major challenge. Here, we report the identification of miconazole as a hemorrhagic suppressor by a small-molecule screen in zebrafish. We found that a hypomorphic mutant fn40a, one of several known β-pix mutant alleles in zebrafish, had the major symptoms of brain hemorrhage, vessel rupture and inflammation as those in hemorrhagic stroke patients. A small-molecule screen with mutant embryos identified the anti-fungal drug miconazole as a potent hemorrhagic suppressor. Miconazole inhibited both brain hemorrhages in zebrafish and mesenteric hemorrhages in rats by decreasing matrix metalloproteinase 9 (MMP9)-dependent vessel rupture. Mechanistically, miconazole downregulated the levels of pErk and Mmp9 to protect vascular integrity in fn40a mutants. Therefore, our findings demonstrate that miconazole protects blood vessels from hemorrhages by downregulating the pERK-MMP9 axis from zebrafish to mammals and shed light on the potential of phenotype-based screens in zebrafish for the discovery of new drug candidates and chemical probes for hemorrhagic stroke.
| S-EPMC5374319 | biostudies-literature
Project description:ImportanceUnruptured intracranial aneurysms not undergoing preventive endovascular or neurosurgical treatment are often monitored radiologically to detect aneurysm growth, which is associated with an increase in risk of rupture. However, the absolute risk of aneurysm rupture after detection of growth remains unclear.ObjectiveTo determine the absolute risk of rupture of an aneurysm after detection of growth during follow-up and to develop a prediction model for rupture.Design, setting, and participantsIndividual patient data were obtained from 15 international cohorts. Patients 18 years and older who had follow-up imaging for at least 1 untreated unruptured intracranial aneurysm with growth detected at follow-up imaging and with 1 day or longer of follow-up after growth were included. Fusiform or arteriovenous malformation-related aneurysms were excluded. Of the 5166 eligible patients who had follow-up imaging for intracranial aneurysms, 4827 were excluded because no aneurysm growth was detected, and 27 were excluded because they had less than 1 day follow-up after detection of growth.ExposuresAll included aneurysms had growth, defined as 1 mm or greater increase in 1 direction at follow-up imaging.Main outcomes and measuresThe primary outcome was aneurysm rupture. The absolute risk of rupture was measured with the Kaplan-Meier estimate at 3 time points (6 months, 1 year, and 2 years) after initial growth. Cox proportional hazards regression was used to identify predictors of rupture after growth detection.ResultsA total of 312 patients were included (223 [71%] were women; mean [SD] age, 61 [12] years) with 329 aneurysms with growth. During 864 aneurysm-years of follow-up, 25 (7.6%) of these aneurysms ruptured. The absolute risk of rupture after growth was 2.9% (95% CI, 0.9-4.9) at 6 months, 4.3% (95% CI, 1.9-6.7) at 1 year, and 6.0% (95% CI, 2.9-9.1) at 2 years. In multivariable analyses, predictors of rupture were size (7 mm or larger hazard ratio, 3.1; 95% CI, 1.4-7.2), shape (irregular hazard ratio, 2.9; 95% CI, 1.3-6.5), and site (middle cerebral artery hazard ratio, 3.6; 95% CI, 0.8-16.3; anterior cerebral artery, posterior communicating artery, or posterior circulation hazard ratio, 2.8; 95% CI, 0.6-13.0). In the triple-S (size, site, shape) prediction model, the 1-year risk of rupture ranged from 2.1% to 10.6%.Conclusion and relevanceWithin 1 year after growth detection, rupture occurred in approximately 1 of 25 aneurysms. The triple-S risk prediction model can be used to estimate absolute risk of rupture for the initial period after detection of growth.
| S-EPMC8406207 | biostudies-literature
Project description:Background and objectiveThe rupture risk of intracranial aneurysms (IAs) is related to their arterial origin, but whether the different segments of the artery have different risks and act as independent risk factors is still unknown. Our study aimed to investigate the rupture risk of IAs in different arterial segments in a large Chinese cohort.MethodsImaging and clinical data of consecutive patients with IAs diagnosed by Computed Tomography angiography (CTA) from January 2013 to December 2022 were collected. Two neuroradiologists independently identified ruptured and unruptured IAs based on imaging and medical records. The internal carotid artery (ICA), middle cerebral artery (MCA), anterior cerebral artery (ACA), vertebral artery (VA), and posterior cerebral artery (PCA) were segmented according to the Bouthillier and Fischer segmentation methods. Stenoses of the proximal parent vessel were evaluated and documented. The Institutional Review Board (IRB) at Beijing Tiantan Hospital approved this retrospective study.ResultsA total of 3,837 aneurysms {median size 3.5 mm [interquartile range (IQR) 2.6-5.1 mm]; 532 ruptured} were included in this study from 2,968 patients [mean age: 57 years (IQR 50-64); male patients: 1,153]. Ruptured aneurysms were most commonly located in the posterior inferior cerebellar artery (PICA) (52.9%), anterior communicating artery (ACoA) (33.8%), other locations (33.3%), ACA (22.4%), and basilar artery (BA) (21.4%). The locations with the highest likelihood of rupture were the C7 ICA (21.3%), M2 MCA (24.0%), distal MCA (25.0%), and A2 ACA (28.1%). IAs originating from the C7 (p < 0.001), dM1 (p = 0.022), and dA1 (p = 0.021) segments were independent risk factors for rupture. IAs without stenosis of the proximal parent vessel were associated with a higher risk of rupture (p = 0.023).ConclusionThere are unique associations between the origins of aneurysms from various arterial segments. Aneurysms originating from the anterior communicating artery (ACoA), BA, PICA, A2, dA, C7, and M2 indicate a higher risk of rupture. Aneurysms originating from C4, C5, and C6 indicate a lower risk of rupture. C7 IAs, ACoA IAs, and PICA IAs seem to be independent risk factors.
| S-EPMC11371744 | biostudies-literature
Project description:Background and Purpose: Precisely assessing the likelihood of an intracranial aneurysm rupturing is critical for guiding clinical decision-making. The objective of this study is to construct and validate a deep learning framework utilizing point clouds to forecast the likelihood of aneurysm rupturing. Methods: The dataset included in this study consisted of a total of 623 aneurysms, with 211 of them classified as ruptured and 412 as unruptured, which were obtained from two separate projects within the AneuX morphology database. The HUG project, which included 124 ruptured aneurysms and 340 unruptured aneurysms, was used to train and internally validate the model. For external validation, another project named @neurIST was used, which included 87 ruptured and 72 unruptured aneurysms. A standardized method was employed to isolate aneurysms and a segment of their parent vessels from the original 3D vessel models. These models were then converted into a point cloud format using open3d package to facilitate training of the deep learning network. The PointNet++ architecture was utilized to process the models and generate risk scores through a softmax layer. Finally, two models, the dome and cut1 model, were established and then subjected to a comprehensive comparison of statistical indices with the LASSO regression model built by the dataset authors. Results: The cut1 model outperformed the dome model in the 5-fold cross-validation, with the mean AUC values of 0.85 and 0.81, respectively. Furthermore, the cut1 model beat the morphology-based LASSO regression model with an AUC of 0.82. However, as the original dataset authors stated, we observed potential generalizability concerns when applying trained models to datasets with different selection biases. Nevertheless, our method outperformed the LASSO regression model in terms of generalizability, with an AUC of 0.71 versus 0.67. Conclusion: The point cloud, as a 3D visualization technique for intracranial aneurysms, can effectively capture the spatial contour and morphological aspects of aneurysms. More structural features between the aneurysm and its parent vessels can be exposed by keeping a portion of the parent vessels, enhancing the model's performance. The point cloud-based deep learning model exhibited good performance in predicting rupture risk while also facing challenges in generalizability.
| S-EPMC10901972 | biostudies-literature
Project description:BackgroundAnterior cruciate ligament (ACL) graft rupture occurs at a high rate, especially in young athletes. The geometries of the tibial plateau and femoral intercondylar notch are risk factors for first-time ACL injury; however, little is known about the relationship between these geometries and risk of ACL graft rupture.HypothesisThe geometric risk factors for noncontact graft rupture are similar to those previously identified for first-time noncontact ACL injury, and sex-specific differences exist.Study designCase-control study; Level of evidence, 3.MethodsEleven subjects who suffered a noncontact ACL graft rupture and 44 subjects who underwent ACL reconstruction but did not experience graft rupture were included in the study. Using magnetic resonance imaging, the geometries of the tibial plateau subchondral bone, articular cartilage, meniscus, tibial spines, and femoral notch were measured. Risk factors associated with ACL graft rupture were identified using Cox regression.ResultsThe following were associated with increased risk of ACL graft injury in males: increased posterior-inferior-directed slope of the articular cartilage in the lateral tibial plateau measured at 2 locations (hazard ratio [HR] = 1.50, P = .029; HR = 1.39, P = .006), increased volume (HR = 1.45, P = .01) and anteroposterior length (HR = 1.34, P = .0023) of the medial tibial spine, and increased length (HR = 1.18, P = .0005) and mediolateral width (HR = 2.19, P = .0004) of the lateral tibial spine. In females, the following were associated with increased risk of injury: decreased volume (HR = 0.45, P = .02) and height (HR = 0.46, P = .02) of the medial tibial spine, decreased slope of the lateral tibial subchondral bone (HR = 0.72, P = .01), decreased height of the posterior horn of the medial meniscus (HR = 0.09, P = .001), and decreased intercondylar notch width at the anterior attachment of the ACL (HR = 0.72, P = .02).ConclusionThe geometric risk factors for ACL graft rupture are different for males and females. For females, a decreased femoral intercondylar notch width and a decreased height of the posterior medial meniscus were risk factors for ACL graft rupture that have also been found to be risk factors for first-time injury. There were no risk factors in common between ACL graft injury and first-time ACL injury for males.
| S-EPMC6604045 | biostudies-literature
Project description:Background: Intracranial aneurysm rupture is a devastating medical event with a high morbidity and mortality rate. Thus, timely detection and management are critical. The present study aimed to identify the aneurysm radiomics features associated with rupture and to build and evaluate a radiomics classification model of aneurysm rupture. Methods: Radiomics analysis was applied to CT angiography (CTA) images of 393 patients [152 (38.7%) with ruptured aneurysms]. Patients were divided at a ratio of 7:3 into retrospective training (n = 274) and prospective test (n = 119) cohorts. A total of 1,229 radiomics features were automatically calculated from each aneurysm. The feature number was systematically reduced, and the most important classifying features were selected. A logistic regression model was constructed using the selected features and evaluated on training and test cohorts. Radiomics score (Rad-score) was calculated for each patient and compared between ruptured and unruptured aneurysms. Results: Nine radiomics features were selected from the CTA images and used to build the logistic regression model. The radiomics model has shown good performance in the classification of the aneurysm rupture on training and test cohorts [area under the receiver operating characteristic curve: 0.92 [95% confidence interval CI: 0.89-0.95] and 0.86 [95% CI: 0.80-0.93], respectively, p < 0.001]. Rad-score showed statistically significant differences between ruptured and unruptured aneurysms (median, 2.50 vs. -1.60 and 2.35 vs. -1.01 on training and test cohorts, respectively, p < 0.001). Conclusion: The results indicated the potential of aneurysm radiomics features for automatic classification of aneurysm rupture on CTA images.
| S-EPMC7937935 | biostudies-literature
Project description:BackgroundGeometric parameters have been proposed for prediction of cerebral aneurysm rupture risk. Predicting the rupture risk for incidentally detected unruptured aneurysms could help clinicians in their treatment decision. However, assessment of geometric parameters depends on several factors, including the spatial resolution of the imaging modality used and the chosen reconstruction procedure. The aim of this study was to investigate the uncertainty of a variety of previously proposed geometric parameters for rupture risk assessment, caused by variability of reconstruction procedures.Materials26 research groups provided segmentations and surface reconstructions of five cerebral aneurysms as part of the Multiple Aneurysms AnaTomy CHallenge (MATCH) 2018. 40 dimensional and non-dimensional geometric parameters, describing aneurysm size, neck size, and irregularity of aneurysm shape, were computed. The medians as well as the absolute and relative uncertainties of the parameters were calculated. Additionally, linear regression analysis was performed on the absolute uncertainties and the median parameter values.ResultsA large variability of relative uncertainties in the range between 3.9 and 179.8% was found. Linear regression analysis indicates that some parameters capture similar geometric aspects. The lowest uncertainties < 6% were found for the non-dimensional parameters isoperimetric ratio, convexity ratio, and ellipticity index. Uncertainty of 2D and 3D size parameters was significantly higher than uncertainty of 1D parameters. The most extreme uncertainties > 80% were found for some curvature parameters.ConclusionsUncertainty analysis is essential on the road to clinical translation and use of rupture risk prediction models. Uncertainty quantification of geometric rupture risk parameters provided by this study may help support development of future rupture risk prediction models.
| S-EPMC6434802 | biostudies-literature
Project description: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.
| S-EPMC8636593 | biostudies-literature