Modeling and visualization techniques for virtual stenting of aneurysms and stenoses

Egger, Jan; Großkopf, Stefan; Nimsky, Christopher; Kapur, Tina; Freisleben, Bernd

doi:10.1016/j.compmedimag.2011.12.002

Cited by 16 publications

(7 citation statements)

References 21 publications

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“…Furthermore, the target contour of the stent expanding has been deemed as the main factor affecting the efficiency and accuracy of stent expansion. Existing virtual stenting methods either used the initial aneurysm vessel model 3 , or adopted the pre-processed vessel model, in which the aneurysm sac was removed and the gap was repaired according to experience 20 . In contrast, in our methods, the aneurysmal sac was shrunk to restore the normal parent vessel with our aneurysm scaling algorithm 19 .…”

Section: Discussionmentioning

confidence: 99%

“…The stent contour was constructed according to real stent parameters 21 22 . The number of nodes in the stent contour depends on the artery’s size and stent design 3 . The coordinates of nodes in the stent contour were computed in Matlab 2010 (The Mathworks, Natick, MA, USA), maintaining relative position among these nodes.…”

Section: Methodsmentioning

confidence: 99%

“…However, certain deployed states of stents may increase the risk of aneurysm rupture. Besides, the stent cannot be changed or removed once inserted 3 . Stent implantation is generally performed based on clinical experience without theoretical evaluation for the surgery outcome.…”

mentioning

confidence: 99%

“…Egger et al . 3 developed the modeling and visualization techniques for virtual stenting of aneurysms and stenoses, in which the virtual stent was expanded by using an active contour model 11 in 3D space. Janiga et al .…”

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confidence: 99%

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Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm

Zhong

Long

et al. 2016

Sci Rep

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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. In this method, an initial stent mesh was generated along the centerline of the parent artery without the need for registration between the stent contour and the vessel. Additionally, the diameter of the initial stent volumetric mesh was set to the maximum inscribed sphere diameter of the parent artery to improve the stenting accuracy and save computational cost. At last, a novel criterion for terminating virtual stent expanding that was based on the collision detection of the axis aligned bounding boxes was applied, making the stent expansion free of edge effect. The experiment results of the virtual stenting and the corresponding CFD simulations exhibited the efficacy and accuracy of the ACM based method, which are valuable to intervention scheme selection and therapy plan confirmation.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm

Zhong

Long

et al. 2016

Sci Rep

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“…Egger et al ( , 2012) also extracted aortic diameter measurements for minimally invasive stent planning andLi et al (2018) extracted aortic diameters in aortic dissections, like true and false lumen, and the length of the proximal landing zone for treatment planning.…”

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confidence: 99%

AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo

Yuan¹,

Pepe²,

Li³

et al. 2021

Preprint

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The aortic vessel tree is composed of the aorta and its branching arteries, and plays a key role in supplying the whole body with blood. Aortic diseases, like aneurysms or dissections, can lead to an aortic rupture, whose treatment with open surgery is highly risky. Therefore, patients commonly undergo drug treatment under constant monitoring, which requires regular inspections of the vessels through imaging. The standard imaging modality for diagnosis and monitoring is computed tomography (CT), which can provide a detailed picture of the aorta and its branching vessels if combined with a contrast agent, resulting in a CT angiography (CTA). Optimally, the whole aortic vessel tree geometry from consecutive CTAs, are overlaid and compared. This allows to not only detect changes in the aorta, but also more peripheral vessel tree changes, caused by the primary pathology or newly developed. When performed manually, this reconstruction requires slice by slice contouring, which could easily take a whole day for a single aortic vessel tree and, hence, is not feasible in clinical practice. Automatic or semi-automatic vessel tree segmentation algorithms, on the other hand, can complete this task in a fraction of the manual execution time and run in parallel to the clinical routine of the clinicians. In this paper, we systematically review computing techniques for the automatic and semi-automatic segmentation of the aortic vessel tree. The review concludes with an in-depth discussion on how close these state-of-the-art approaches are to an application in clinical practice and how active this research field is, taking into account the number of publications, datasets and challenges.

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Computerized Navigation Support for Endovascular Procedures

Fallavollita

Demirci

2017

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting

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Modeling and visualization techniques for virtual stenting of aneurysms and stenoses

Cited by 16 publications

References 21 publications

Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm

Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm

AI-based Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo

Computerized Navigation Support for Endovascular Procedures

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