Patient Specific Numerical Simulation of EVAR to Predict Type Ia Endoleak

Introduction

Type 1a endoleak is the leading cause of rupture following endovascular infrarenal abdominal aorto-iliac aneurysm repair (EVAR). Individual Type 1a endoleak risk prediction is difficult, but digital twin technology based on numerical simulation of the stent graft (SG) and aorta may overcome this problem.

Finite element analysis (FEA) is a numerical method to solve complex mechanical problems; it is widely used in industrial conception engineering. Previous reports have demonstrated good accuracy of FEA models in reproducing SG behaviour, particularly at the level of the aortic neck.

This preliminary study aimed to evaluate the performance of a new FEA algorithm for predicting Type 1a Endoleak risk following implantation of Endurant devices (Medtronic, Dublin, Ireland) and to identify a discriminative numerical score.

Methods

Computational simulation was performed in all patients who underwent implantation of a bifurcated Endurant device between January 2012 and September 2017 in two high volume vascular units. Group 1 consisted of patients with an early or late Type 1a Endoleak.

Control cases (Group 2) consisted of patients who did not have a Type 1a Endoleak with a minimum five years of follow up confirmed by computed tomography angiography (CTA).

Exclusion criteria were non-availability of pre- or post-operative CTA, poor CTA quality, post-dissection aneurysm, and the use of additional endovascular techniques at the proximal landing zone (e.g.,endoanchor, chimney).

Proximal aortic neck standard parameters were studied on pre-operative CTA (diameter, length, angulation, thrombus, and conicity) with AW Server 3.2 (GE Healthcare,Chicago, IL, USA).

Previously described proprietary algorithms were used. Numerical SG deployment was performed using finite element solver. Read more of methods here

Observations

This study showed that the ERI score is a good predictor of Type 1a Endoleak . Although ERI was constructed by selecting and weighing DTPs with the purpose of maximum discrimination between Groups 1 and 2, individual DTPs also statistically significantly and consistently differed between groups.

In contrast, there was no significant difference for any of the standard parameters. Integration of SG mechanical parameters in analysis and use of dedicated algorithms may enhance the predictability of Type 1a endoleak compared with previous methods based on assessment of aortic morphology alone.

The numerical parameters extracted from simulations were markers of SG apposition onto the aortic wall. The digital aorta was analysed after virtual SG deployment and the algorithm provided several thousand automatic radius measurements, well beyond those performed in standard sizing.

Ten of 15 patients in Group 1 were treated within instructions for use (IFU), which might indicate that sticking to IFU may not prevent the occurrence of Type 1a endoleak risk. Recent guidelines have emphasised that actual SG apposition should be systematically assessed on post-operative CTA to stratify the risk of proximal sealing complications and to guide follow upimaging.

The ERI could also guide follow up protocols by predicting this risk, but more importantly avoid aneurysm related complications by modifying the therapeutic strategy(e.g., open surgical repair or fenestrated EVAR instead of EVAR).

Conclusion

This was a preliminary study with an algorithm that willbe further evaluated on larger retrospective cohorts in a multicentre trial. It is likely that the ERI will require adjustments to find the best combination of imaging parameters, with the help of artificial intelligence techniques.