Towards a clinically applicable prediction model for aneurysm shrinkage after EVAR

2074
EVAR
L-R: Rianne van Rijswijk and Michel Reijnen

Michel Reijnen and Rianne van Rijswijk (both Rijnstate Hospital, Arnhem, The Netherlands) write about a new consortium focused on sac regression after endovascular aneurysm repair (EVAR).

Aneurysm shrinkage after EVAR has been identified as an important predictor for treatment success. Patients with a shrinking aneurysm have a lower likelihood of complications and reinterventions and a better survival rate. However, which factors are decisive in this process and how they influence each other is largely unknown.

The RADAR consortium was founded to specifically address this issue in the ART in EVAR study. The project is a collaboration between Rijnstate, Amsterdam UMC, University Medical Centre Groningen, Medisch Spectrum Twente and University of Twente in The Netherlands and the Karolinska Institutet in Sweden.

Besides the standard clinical and anatomical data, the computed tomography angiography (CTA) imaging will be meticulously analysed, investigating factors like intraluminal thrombus volume, distribution and constitution, and wall stress in relation to abdominal aortic aneurysm (AAA) remodelling. In collaboration with the Universitat Pompeu Fabra in Barcelona, Spain, a multi-modal artificial intelligence (AI) model will be developed with the aim of predicting prior to surgery in which patients the aneurysm sac will shrink or not. Or, in other words, the model will identify patients in whom regular EVAR is sufficient AAA treatment to induce sac shrinkage, and, more importantly, identify the patients in whom regular EVAR is insufficient to ensure good outcomes.

The overarching aim is to help clinicians to stratify patients who may benefit from adjunctive treatment modalities like pre-emptive embolisation of side branches, active sac management, or reinforcement of the proximal seal using endoanchors. These techniques have shown to promote AAA shrinkage but are often considered to be either too complex and/or too costly to be performed in all EVAR patients. A reliable prediction model is thus indispensable.

The model could also aid stratification of the follow-up surveillance after EVAR based on the patient’s individual risk, by decreasing the frequency of followup visits in the 40–50% of the patients who will experience sac shrinkage after EVAR.

Overall, the multi-modal AI prediction model aims to decrease the number of reinterventions after EVAR and associated healthcare costs, and potentially improve patient survival.

The ART in EVAR study is considered to be the start of a long-term collaboration in the form of the RADAR consortium. The extensive database that is set up for this study holds the answer to a myriad of other questions, which we aim to unravel. Our next step entails identification of the role of proteomics and peripheral blood mononuclear cells in the remodeling of the aneurysm sac after EVAR. We will investigate the biological response of sac regression versus sac growth, unravelling the reasons behind the longer survival of patients showing sac regression.

Our future aim is to open up and broaden the collaboration with other interested parties and stakeholders, like hospitals, universities, patient groups and industry, both from a device and imaging perspective. Together we aspire to improve clinical care for aneurysm patients and advance our patients’ lives.

Michel Reijnen is a consultant vascular surgeon at Rijnstate Hospital in Arnhem, The Netherlands.

Rianne van Rijswijk is a technical physician and PhD student at Rijnstate.


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