A Statistical Shape Model of Infrarenal Aortic Necks in Patients With and Without Late Type Ia Endoleak After Endovascular Aneurysm Repair.

abdominal aortic aneurysm endoleak endovascular aneurysm repair endovascular procedures principal component

Journal

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists
ISSN: 1545-1550
Titre abrégé: J Endovasc Ther
Pays: United States
ID NLM: 100896915

Informations de publication

Date de publication:
16 Jan 2023
Historique:
entrez: 16 1 2023
pubmed: 17 1 2023
medline: 17 1 2023
Statut: aheadofprint

Résumé

Hostile aortic neck characteristics, including short length, severe suprarenal and infrarenal angulation, conicity, and large diameter, have been associated with increased risk for type Ia endoleak (T1aEL) after endovascular aneurysm repair (EVAR). This study investigates the mid-term discriminative ability of a statistical shape model (SSM) of the infrarenal aortic neck morphology compared with or in combination with conventional measurements in patients who developed T1aEL post-EVAR. The dataset composed of EVAR patients who developed a T1aEL during follow-up and a control group without T1aEL. Principal component (PC) analysis was performed using a parametrization to create an SSM. Three logistic regression models were created. To discriminate between patients with and without T1aEL, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC) were calculated. In total, 126 patients (84% male) were included. Median follow-up time in T1aEl group and control group was 52 (31, 78.5) and 51 (40, 62.5) months, respectively. Median follow-up time was not statistically different between the groups (p=0.72). A statistically significant difference between the median PC scores of the T1aEL and control groups was found for the first, eighth, and ninth PC. Sensitivity, specificity, and AUC values for the SSM-based versus the conventional measurements-based logistic regression models were 79%, 70%, and 0.82 versus 74%, 73%, and 0.85, respectively. The model of the SSM and conventional measurements combined resulted in sensitivity, specificity, and AUC of 81%, 81%, and 0.92. An SSM of the infrarenal aortic neck determines its 3-dimensional geometry. The SSM is a potential valuable tool for risk stratification and T1aEL prediction in EVAR. The SSM complements the conventional measurements of the individual preoperative infrarenal aortic neck geometry by increasing the predictive value for late type Ia endoleak after standard EVAR. A statistical shape model (SSM) determines the 3-dimensional geometry of the infrarenal aortic neck. The SSM complements the conventional measurements of the individual pre-operative infrarenal aortic neck geometry by increasing the predictive value for late type Ia endoleaks post-EVAR. The SSM is a potential valuable tool for risk stratification and late T1aEL prediction in EVAR and it is a first step toward implementation of a treatment planning support tool in daily clinical practice.

Identifiants

pubmed: 36647185
doi: 10.1177/15266028221149913
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

15266028221149913

Auteurs

Willemina A van Veldhuizen (WA)

Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, Groningen, The Netherlands.

Richte C L Schuurmann (RCL)

Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, Groningen, The Netherlands.
Multi-Modality Medical Imaging (M3I) Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands.

Roy Zuidema (R)

Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, Groningen, The Netherlands.

Anna C M Geraedts (ACM)

Department of Surgery, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.

Frank F A IJpma (FFA)

Department of Surgery, Division of Trauma Surgery, University Medical Center Groningen, Groningen, The Netherlands.

Rogier H J Kropman (RHJ)

Department of Vascular Surgery, St. Antonius Hospital, Nieuwegein, The Netherlands.

George A Antoniou (GA)

Department of Vascular and Endovascular Surgery, Manchester University NHS Foundation Trust, Manchester, UK.
Division of Cardiovascular Sciences, School of Medical Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.

Marc R H M van Sambeek (MRHM)

Department of Vascular Surgery, Catharina Hospital, Eindhoven, The Netherlands.

Ron Balm (R)

Department of Surgery, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.

Jelmer M Wolterink (JM)

Department of Applied Mathematics, Technical Medical Centre, University of Twente, Enschede, The Netherlands.

Jean-Paul P M de Vries (JPM)

Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, Groningen, The Netherlands.

Classifications MeSH