| Autor: |
van Veldhuizen WA; Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands., Schuurmann RCL; Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands.; Multimodality Medical Imaging Group, Technical Medical Centre, University of Twente, 7500 AE Enschede, The Netherlands., IJpma FFA; Department of Surgery, Division of Trauma Surgery, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands., Kropman RHJ; Department of Vascular Surgery, St. Antonius Hospital, 3435 CM Nieuwegein, The Netherlands., Antoniou GA; Department of Vascular Surgery and Endovascular Surgery, The Royal Oldham Hospital, Manchester University NHS Foundation Trust, Manchester M13 9WL, UK.; Division of Cardiovascular Sciences, School of Medical Sciences, The University of Manchester, Manchester M13 9PL, UK., Wolterink JM; Department of Applied Mathematics, Technical Medical Centre, University of Twente, 7500 AE Enschede, The Netherlands., de Vries JPM; Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands. |
| Abstrakt: |
Hostile aortic neck characteristics, such as short length and large diameter, have been associated with type Ia endoleaks and reintervention after endovascular aneurysm repair (EVAR). However, such characteristics partially describe the complex aortic neck morphology. A more comprehensive quantitative description of 3D neck shape might lead to new insights into the relationship between aortic neck morphology and EVAR outcomes in individual patients. This study identifies the 3D morphological shape components that describe the infrarenal aortic neck through a statistical shape model (SSM). Pre-EVAR CT scans of 97 patients were used to develop the SSM. Parameterization of the morphology was based on the center lumen line reconstruction, a triangular surface mesh of the aortic lumen, 3D coordinates of the renal arteries, and the distal end of the aortic neck. A principal component analysis of the parametrization of the aortic neck coordinates was used as input for the SSM. The SSM consisted of 96 principal components (PCs) that each described a unique shape feature. The first five PCs represented 95% of the total morphological variation in the dataset. The SSM is an objective model that provides a quantitative description of the neck morphology of an individual patient. |
