The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases.

Background The posterior wall of the proximal internal carotid artery (ICA) is the predilection site for the development of stenosis. To optimally prevent stroke, identification of new risk factors for plaque progression is of high interest. Therefore, we studied the impact of carotid geometry and wall shear stress on cardiovascular magnetic resonance (CMR)-depicted wall thickness in the ICA of patients with high cardiovascular disease risk. Methods One hundred twenty-one consecutive patients ≥50 years with hypertension, ≥1 additional cardiovascular risk factor and ICA plaque ≥1.5 mm thickness and < 50% stenosis were prospectively included. High-resolution 3D-multi-contrast (time of flight, T1, T2, proton density) and 4D flow CMR were performed for the assessment of morphological (bifurcation angle, ICA/common carotid artery (CCA) diameter ratio, tortuosity, and wall thickness) and hemodynamic parameters (absolute/systolic wall shear stress (WSS), oscillatory shear index (OSI)) in 242 carotid bifurcations. Results We found lower absolute/systolic WSS, higher OSI and increased wall thickness in the posterior compared to the anterior wall of the ICA bulb (p < 0.001), whereas this correlation disappeared in ≥10% stenosis. Higher carotid tortuosity (regression coefficient = 0.764; p < 0.001) and lower ICA/CCA diameter ratio (regression coefficient = − 0.302; p < 0.001) were independent predictors of increased wall thickness even after adjustment for cardiovascular risk factors. This association was not found for bifurcation angle, WSS or OSI in multivariate regression analysis. Conclusions High carotid tortuosity and low ICA diameter were independent predictors for wall thickness of the ICA bulb in this cross-sectional study, whereas this association was not present for WSS or OSI. Thus, consideration of geometric parameters of the carotid bifurcation could be helpful to identify patients at increased risk of carotid plaque generation. However, this association and the potential benefit of WSS measurement need to be further explored in a longitudinal study.

The proposed phase unwrapping method for real-time flow MRI allows for measurements with reduced velocity encoding and increased VNR.

Our approach enables an expert user to easily segment the open mitral valve in CT data, even when image noise or low contrast limits the visibility of the valve.

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Introduction: Carotid geometry and wall shear stress (WSS) have been proposed as independent risk factors for the progression of carotid atherosclerosis, but this has not yet been demonstrated in larger longitudinal studies. Therefore, we investigated the impact of these biomarkers on carotid wall thickness in patients with high cardiovascular risk.Methods: Ninety-seven consecutive patients with hypertension, at least one additional cardiovascular risk factor and internal carotid artery (ICA) plaques (wall thickness ≥ 1.5 mm and degree of stenosis ≤ 50%) were prospectively included. They underwent high-resolution 3D multi-contrast and 4D flow MRI at 3 Tesla both at baseline and follow-up. Geometry (ICA/common carotid artery (CCA)-diameter ratio, bifurcation angle, tortuosity and wall thickness) and hemodynamics [WSS, oscillatory shear index (OSI)] of both carotid bifurcations were measured at baseline. Their predictive value for changes of wall thickness 12 months later was calculated using linear regression analysis for the entire study cohort (group 1, 97 patients) and after excluding patients with ICA stenosis ≥10% to rule out relevant inward remodeling (group 2, 61 patients).Results: In group 1, only tortuosity at baseline was independently associated with carotid wall thickness at follow-up (regression coefficient = −0.52, p &lt; 0.001). However, after excluding patients with ICA stenosis ≥10% in group 2, both ICA/CCA-ratio (0.49, p &lt; 0.001), bifurcation angle (0.04, p = 0.001), tortuosity (−0.30, p = 0.040), and WSS (−0.03, p = 0.010) at baseline were independently associated with changes of carotid wall thickness at follow-up.Conclusions: A large ICA bulb and bifurcation angle and low WSS seem to be independent risk factors for the progression of carotid atherosclerosis in the absence of ICA stenosis. By contrast, a high carotid tortuosity seems to be protective both in patients without and with ICA stenosis. These biomarkers may be helpful for the identification of patients who are at particular risk of wall thickness progression and who may benefit from intensified monitoring and treatment.

We present a novel approach to simulate deformation in aortic valve replacement scenarios with applications in operation planning and batch domain creation for large computational fluid dynamics studies of the aortic arch.

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