Publications by authors named "Yunling Long"

To investigate the ability of a MRI-based radiomics-clinicopathological model to predict pituitary macroadenoma (PMA) recurrence within 5 years. We recruited 74 recurrent and 94 non-recurrent subjects, following first surgery with 5-year follow-up data. Univariate and multivariate analyses were conducted to identify independent clinicopathological risk factors.

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Intracranial stents are becoming increasingly a useful option in the treatment of intracranial aneurysms (IAs). Image simulation of the releasing stent configuration together with computational fluid dynamics (CFD) simulation prior to intervention will help surgeons optimize intervention scheme. This paper proposed a fast virtual stenting of IAs based on active contour model (ACM) which was able to virtually release stents within any patient-specific shaped vessel and aneurysm models built on real medical image data.

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Background And Purpose: Energy loss (EL) was regarded to be one of the key parameters in predicting the rupture risk of IA. In this paper, we took varied aspect ratio (AR) as a scaling law to create a series of longitudinal models to investigate the longitudinal changes of flow pattern and EL as the AR varies, in order to explore the relationship between the longitudinal characteristic EL parameters with aneurysm rupture risk.

Methods: Seven original intracranial aneurysms (IA) models with similar locations were reconstructed from patient 3D rotational angiography (3DRA) images.

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Background: The intracranial aneurysm (IA) size has been proved to have impacts on the hemodynamics and can be applied for the prediction of IA rupture risk. Although the relationship between aspect ratio and hemodynamic parameters was investigated using real patients and virtual models, few studies focused on longitudinal experiments of IAs based on patient-specific aneurysm models. We attempted to do longitudinal simulation experiments of IAs by developing a series of scaled models.

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