Automatic Segmentation and Mechanical Characterisation of the Intraluminal Thrombus and Arterial Wall of Abdominal Aortic Aneurysms Using Time Resolved 3D Ultrasound Images.
Autor: | Margaretha Nievergeld AH; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Vascular Surgery, Catharina Hospital Eindhoven, Eindhoven, The Netherlands. Electronic address: a.h.m.nievergeld@tue.nl., Maas EJ; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Vascular Surgery, Catharina Hospital Eindhoven, Eindhoven, The Netherlands., de Ruijter J; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., Cornelia Fonken JH; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Vascular Surgery, Catharina Hospital Eindhoven, Eindhoven, The Netherlands., Henricus Maria van Sambeek MR; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Department of Vascular Surgery, Catharina Hospital Eindhoven, Eindhoven, The Netherlands., Paulus Lopata RG; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. |
---|---|
Jazyk: | angličtina |
Zdroj: | European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery [Eur J Vasc Endovasc Surg] 2023 Sep; Vol. 66 (3), pp. 418-427. Date of Electronic Publication: 2023 Mar 22. |
DOI: | 10.1016/j.ejvs.2023.03.033 |
Abstrakt: | Objective: This study proposed a method for semi-automatic segmentation of abdominal aortic aneurysms (AAAs) and their intraluminal thrombus (ILT), based on time resolved 3D ultrasound (US), and validated results with computed tomography (CT). Mechanical properties of both wall and ILT were determined, and possible correlations with ILT size and blood pressure were investigated. Methods: A semi-automatic segmentation algorithm was developed combining a star-Kalman approach with a 3D snake algorithm. The segmented geometries of both lumen and inner vessel wall were validated with both manual US based segmentations and CT based segmentations. Finally, the lumen and vessel wall distensibility and ILT compressibility were estimated and correlated with ILT size and blood pressure. Results: For the vessel wall and lumen, the median Similarity Index (SI) was 92% (IQR 90, 94%) and 83% (IQR 75, 87%), respectively. The distensibility of the vessel wall could be determined in 37 of 40 cases and had a median value of 0.28 10 -5 Pa -1 (IQR 0.18, 0.51 ×10 -5 ). The median systolic to diastolic volume change of the ILT was determined successfully in 21 of 40 patients, and was -0.57% (IQR -1.1, 1.2%). The vessel and lumen distensibility showed a strong correlation with the systolic pressure (p < .010), rather than with the diastolic pressure. Lumen distensibility was strongly correlated with ILT thickness (p = .023). The performance of the semi-automatic segmentation algorithm was shown to be as good as the manual segmentations and highly dependent on the visibility of the ILT (limited contrast in seven patients and clutter in nine patients). Conclusion: This study has shown promising results for mechanical characterisation of the vessel, and ILT, including a correlation between distensibility, ILT size, and blood pressure. For future work, the inclusion rate needs to be increased by improving the image contrast with novel US techniques. (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.) |
Databáze: | MEDLINE |
Externí odkaz: |