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

Abstract

Purpose: 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.

Materials and methods: 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.

Results: 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.

Conclusion: 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.

Clinical impact: 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.

Keywords: abdominal aortic aneurysm; endoleak; endovascular aneurysm repair; endovascular procedures; principal component.

Figure 1.

Flowchart of patient inclusion. T1aEL, type Ia endoleak; CTA, computed tomography angiography. ^aThree patients from the consecutive control cohort were moved to the T1aEL group due to the presence of a T1aEL in the follow-up.

Figure 2.

Boxplots of the first 9 principal components, of the T1aEL group (red) versus the control group (blue). The first, eighth, and ninth PCs were significantly different between the groups. PCA, principal component analysis; T1aEL, type Ia endoleak.

Figure 3.

(A) Anteroposterior view of the mean shape of the T1aEL group (red) versus the control group (brown). (B) PC 1 describes 54% of the total shape variation, mainly variation in neck length. (C) PC 2 describes 27% of the total shape variation, mainly left and right deflection. (D) PC 3 which describes 9% of the total shape variation, mainly anterior and posterior deflection. T1aEL, type Ia endoleak; PC, principal component.

Figure 4.

ROC curve of the SSM, including the first 9 principal components (blue), the ROC curve of the conventional measurements, including neck length, diameter, supra- and infrarenal angulation, calcification and thrombus categories (green) and the ROC curve of the combination of the SSM and conventional measurements (purple). ROC, receiver operating characteristic; SSM, statistical shape model.