P-016 Lagrangian trajectory simulations with synchrotron microtomography improves hemodynamic analysis of intracranial aneurysms treated with flow diverting stents
Notice bibliographique
Résumé
Background Successful treatment of cerebral aneurysms with flow diverting stents (FDS) depends upon altering biomechanical forces to precipitate stable thrombus formation. Computational fluid dynamics (CFD) simulations can model such forces for treatment outcome prediction, and particle tracking methods can simulate the behavior of components of blood such as platelets. Previous work using a porous medium (PM) to simulate the stent surface demonstrated changes in particle tracking metrics following treatment.(1) However, the fidelity of the PM representation of the stent (and its effect on intraaneurysmal blood flow) has not been established, and previous studies of PM methods for aneurysm coils suggest the potential for inaccuracies.(2) Thus, the goal of this study is to perform CFD and particle tracking in simulations of patient-specific aneurysms before and after FDS treatment, and evaluate the accuracy of the PM method compared to actual FDS geometry. Method Data were collected from patients with unruptured intracranial aneurysms treated with FDS. Three-dimensional reconstructions of patient blood vessels were created from rotational angiography and segmented for CFD simulations. A porous layer with face permeability, pressure-jump coefficient, and thickness corresponding to the geometry of the FDS was applied across the aneurysm neck in each patient. To provide a ground truth, each patients’ segmented arterial anatomy was used to 3D-print optically-clear silicone phantoms. Each phantom was treated with an FDS that was deployed by an experienced neurosurgeon and replicated the patient’s in vivo treatment. Phantoms were then imaged by microtomography to obtain high resolution volumetric reconstructions of the implanted FDS. Simulations were run for both the PM and microtomography FDS conditions in each patient, with patient-specific boundary conditions derived from endovascular measurements of blood flow and velocity obtained before and after treatment. Massless particles injected into these simulations were individually tracked to calculate particle tracking metrics, such as residence time and shear stress history. The hemodynamic results were compared between the PM and microtomographic simulations. Results Nine subjects have undergone microtomography, with a goal of 25 subjects total for the study. We anticipate that the PM method will exaggerate the effects of treatment on residence time and shear stress history in comparison to the ground truth microtomography simulations. The inaccuracy of the PM method will be quantified, and corrective factors derived for application in future CFD studies. Conclusions Appreciating how endovascular therapies alter fluid biomechanics is critical to understanding what hemodynamic changes are needed to achieve treatment success. Improving the accuracy of the computational representation of endovascular treatment devices will increase the confidence and clinical utility of these methods. 1. Marsh LMM, Barbour MC, Chivukula VK, Chassagne F, Kelly CM, Levy SH, et al. Platelet Dynamics and Hemodynamics of Cerebral Aneurysms Treated with Flow-Diverting Stents. Ann Biomed Eng. 2019;September. 2. Chivukula VK, Marsh L, Chasagne F, Barbour M, Kelly C, Levy S, et al. Lagrangian Trajectory Simulation of Platelets and Synchrotron Microtomography Augment Hemodynamic Analysis of Intracranial Aneurysms Treated with Embolic Coils. J Biomech Eng. 2021;July. Disclosures D. Bass: None. L. Marsh: None. V. Chivukula: None. M. Barbour: None. P. Fillingham: None. L. Kim: None. A. Aliseda: None. M. Levitt: 1; C; Medtronic: Investigator-initiated unrestricted educational grant, Stryker: Investigator-initiated unrestricted educational grant. 2; C; Medtronic, Stereotaxis. 4; C; Fluid Biomed. 5; C; Metis Innovative, Aeaean Advisors. 6; C; JNIS and Frontiers in Surgery Editorial Boards.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».