Use of Numerical Simulation to Predict Iliac Complications During Placement of an Aortic Stent Graft
| Autor: | Juliette Gindre, Adrien Kaladji, Moundji Kafi, Florent Lalys, Claire Dupont, Antoine Lucas, Anne Daoudal, Pascal Haigron |
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| Přispěvatelé: | Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Therenva SAS, Agence Nationale de la Recherche, Europe FEDER, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Male
Computed Tomography Angiography medicine.medical_treatment 030204 cardiovascular system & hematology Endovascular aneurysm repair 030218 nuclear medicine & medical imaging Aortic aneurysm 0302 clinical medicine Postoperative Complications Risk Factors ComputingMilieux_MISCELLANEOUS Computed tomography angiography Aged 80 and over medicine.diagnostic_test Endovascular Procedures Models Cardiovascular General Medicine Middle Aged Biomechanical Phenomena medicine.anatomical_structure Treatment Outcome Female [SDV.IB]Life Sciences [q-bio]/Bioengineering Radiology Cardiology and Cardiovascular Medicine Artery medicine.medical_specialty Finite Element Analysis Prosthesis Design Aortography Iliac Artery 03 medical and health sciences Blood Vessel Prosthesis Implantation Blood vessel prosthesis medicine.artery medicine Humans Computer Simulation Aged Retrospective Studies Aorta business.industry Numerical Analysis Computer-Assisted Perioperative medicine.disease Blood Vessel Prosthesis Regional Blood Flow Surgery business Abdominal surgery Aortic Aneurysm Abdominal |
| Zdroj: | Annals of Vascular Surgery Annals of Vascular Surgery, 2019, 61, pp.291-298. ⟨10.1016/j.avsg.2019.04.035⟩ Annals of Vascular Surgery, Elsevier Masson, 2019, 61, pp.291-298. ⟨10.1016/j.avsg.2019.04.035⟩ |
| ISSN: | 0890-5096 1615-5947 |
| DOI: | 10.1016/j.avsg.2019.04.035⟩ |
| Popis: | Background During endovascular aneurysm repair (EVAR), complex iliac anatomy is a source of complications such as unintentional coverage of the hypogastric artery. The aim of our study was to evaluate ability to predict coverage of the hypogastric artery using a biomechanical model simulating arterial deformations caused by the delivery system. Methods The biomechanical model of deformation has been validated by many publications. The simulations were performed on 38 patients included retrospectively, for a total of 75 iliac arteries used for the study. On the basis of objective measurements, two groups were formed: one with “complex” iliac anatomy (n = 38 iliac arteries) and the other with “simple” iliac anatomy (n = 37 iliac arteries). The simulation enabled measurement of the lengths of the aorta and the iliac arteries once deformed by the device. Coverage of the hypogastric artery was predicted if the deformed renal/iliac bifurcation length (Lpre) was less than the length of the implanted device (Lstent-measured on the postoperative computed tomography [CT]) and nondeformed Lpre was greater than Lstent. Results Nine (12%) internal iliac arteries were covered unintentionally. Of the coverage attributed to perioperative deformations, 1 case (1.3%) occurred with simple anatomy and 6 (8.0%) with complex anatomy (P = 0.25). All cases of unintentional coverage were predicted by the simulation. The simulation predicted hypogastric coverage in 35 cases (46.7%). There were therefore 26 (34.6%) false positives. The simulation had a sensitivity of 100% and a specificity of 60.6%. On multivariate analysis, the factors significantly predictive of coverage were the iliac tortuosity index (P = 0.02) and the predicted margin between the termination of the graft limb and the origin of the hypogastric artery in nondeformed (P = 0.009) and deformed (P = 0.001) anatomy. Conclusions Numerical simulation is a sensitive tool for predicting the risk of hypogastric coverage during EVAR and allows more precise preoperative sizing. Its specificity is liable to be improved by using a larger cohort. |
| Databáze: | OpenAIRE |
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