Development of a Patient-Specific Cerebral Vasculature Fluid-Structure-Interaction Model

Moerman, Kevin M.; Konduri, Praneeta; Fereidoonnezhad, Behrooz; Marquering, Henk A.; Lugt, Aad van der; Luraghi, Giulia; Bridio, Sara; Migliavacca, Francesco; Matas, José Félix Rodríguez; McGarry, Patrick

doi:10.31224/osf.io/qaujs

Cited by 3 publications

(5 citation statements)

References 19 publications

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“…), a semi-automated software, was used to extract centerlines, local radius, and to label arterial segments. For a more detailed description of the vascular segmentation and centerline computation, refer to ( 21 ). The centerlines of the arteries of interest, i.e.…”

Section: Methodsmentioning

confidence: 99%

“…The patient-specific domains were obtained from the computed centerlines with the aid of level-set images ( 21 ). In particular, triangular shell elements with a mean element size of 0.2 mm were used to discretized the vessel walls using the open-source MATLAB toolbox GIBBON ( 23 ).…”

Section: Methodsmentioning

confidence: 99%

“…To study the impact of the geometric features of the intracranial ICA on the virtual thrombectomy procedures, the same thrombus, stent-retriever, and thrombectomy procedure were implemented in the 14 patient-specific vessel geometries. The patient-specific domains were obtained from the computed centerlines with the aid of level-set images (21). In particular, triangular shell elements with a mean element size of 0.2 mm were used to discretized the vessel walls using the open-source MATLAB toolbox GIBBON (23).…”

Section: Virtual Thrombectomy Proceduresmentioning

confidence: 99%

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Impact of the Internal Carotid Artery Morphology on in silico Stent-Retriever Thrombectomy Outcome

Bridio

Luraghi

Matas

et al. 2021

Front. Med. Technol.

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The aim of this work is to propose a methodology for identifying relationships between morphological features of the cerebral vasculature and the outcome of in silico simulations of thrombectomy, the mechanical treatment for acute ischemic stroke. Fourteen patient-specific cerebral vasculature segmentations were collected and used for geometric characterization of the intracranial arteries mostly affected by large vessel occlusions, i.e., internal carotid artery (ICA), middle cerebral artery (MCA) and anterior cerebral artery (ACA). First, a set of global parameters was created, including the geometrical information commonly provided in the clinical context, namely the total length, the average diameter and the tortuosity (length over head-tail distance) of the intracranial ICA. Then, a more exhaustive geometrical analysis was performed to collect a set of local parameters. A total of 27 parameters was measured from each patient-specific vascular configuration. Fourteen virtual thrombectomy simulations were performed with a blood clot with the same length and composition placed in the middle of the MCA. The model of TREVO ProVue stent-retriever was used for all the simulations. Results from simulations produced five unsuccessful outcomes, i.e., the clot was not removed from the vessels. The geometric parameters of the successful and unsuccessful simulations were compared to find relations between the vascular geometry and the outcome. None of the global parameters alone or combined proved able to discriminate between positive and negative outcome, while a combination of local parameters allowed to correctly identify the successful from the unsuccessful simulations. Although these results are limited by the number of patients considered, this study indicates a promising methodology to relate patient-specific geometry to virtual thrombectomy outcome, which might eventually guide decision making in the treatment of acute ischemic stroke.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Virtual Thrombectomy Proceduresmentioning

confidence: 99%

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Impact of the Internal Carotid Artery Morphology on in silico Stent-Retriever Thrombectomy Outcome

Bridio

Luraghi

Matas

et al. 2021

Front. Med. Technol.

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“…2c). This level-set image intensity is based on the ratio between the distance to the nearest centerline point and the radius at this point (Moerman et al, 2021). Hence a single iso-surface for the unit-intensity (where the ratio is 1) appropriately defines the vessel geometry (Fig.…”

Section: Vessel Surface Mesh Creationmentioning

confidence: 99%

The first virtual patient-specific thrombectomy procedure

Luraghi

Bridio

Matas

et al. 2021

Journal of Biomechanics

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“…Incomplete removal of the thrombus is assumed to result from a poor match between the highly variable mechanical properties of the thrombus and the design of the stent retriever. In the paper by Moerman and colleagues (Moerman et al, 2021), a costumized and automated platform for the generation of high-resolution patientspecific models of cerebral arteries directly from clinical images was developed. It is the first step in the preprocessing phase to have a patient-specific virtual representation of the EVT procedure.…”

mentioning

confidence: 99%