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Prediction of abdominal aortic aneurysm shrinkage after endovascular repair

Prediction of abdominal aortic aneurysm shrinkage after endovascular repair

PROJECT ACRONYM
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FUNDED BY
Stichting Lijf en Leven

PHD CANDIDATE
R.E. van Rijswijk, MSc

SUPERVISORS
Prof. M.M.P.J. Reijnen
Dr. E. Groot Jebbink
Dr. J.M. Wolterink

COLLABORATION
Applied Analysis group, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS)
Rijnstate Ziekenhuis Arnhem

CLINICAL BACKGROUND
An abdominal aortic aneurysm is a localized, pathologic dilation of the large body artery in the abdomen. Such an aneurysm usually does not give rise to any symptoms and therefore often goes unnoticed. Prevalence of AAA in the Western world varies between 1 and 3% for men and 0.7% for women over the age of 60. When the aneurysm ruptures, the risk of death is high, as much as 80%. Each year, more than more than 400 Dutch patients die as a result of this condition. Early diagnosis and treatment are therefore of vital importance.

Annually 2,600 preventive aneurysm operations are performed in the Netherlands, of which approximately 2,000 are endovascular using a stent-graft (EVAR). The goal is to reduce the continuous cyclic load of blood pressure on the aneurysm wall, so that the risk of rupture is dramatically decreases.

After EVAR, the stent-graft and the aneurysm are closely monitored by ultrasound and CT examinations. A stable or shrinking aneurysm sac was previously judged to be a successful outcome. However, recently it has been shown that only patients with a shrinking aneurysm 1 year after treatment have a significantly higher 10 year survival, compared to patients with a stable or growing aneurysm. Also, patients with a shrinking aneurysm have a significantly lower chance of re-intervention, long-term complications, and rupture.

If we could reliably predict remodeling of the aneurysm sac before the surgery, choices could be made that could increase the chances of patient survival. For example, a small chance of aneurysm shrinkage could influence the choice between endovascular and open repair. Also, based on the prediction model, EVAR treatment can be optimized for patients with an initial worse prognosis. For example, patients could be selected who would benefit from preoperative embolization of side branches of the aneurysm. This is a treatment with proven positive impact on aneurysm remodeling, but it is too complex and costly to perform in all patients. Thus, this prediction model may ultimately lead to an overall higher survival rate after EVAR.

Also, reliable prediction of aneurysm remodeling would impact the follow-up protocol after EVAR. In patients predicted to have a shrinking aneurysm, the follow-up frequency of could be significantly reduced. Given that 40-50% of all patients have a shrinking aneurysm, a prediction model might have a major impact on the costs of EVAR, as well as the burden on the treated patient.

OBJECTIVE
The aim of this study is to develop a validated prediction model that can reliably predict, prior to endovascular treatment of an abdominal aortic aneurysm, in which patients the aneurysm will or will not shrink.  This prediction model will be based on classical physiological and anatomical parameters combined with innovative imaging parameters, derived from preoperative CT and 3D ultrasound measurements. The prediction model will lead to better patient selection and a more patient-specific treatment strategy and follow-up with the ultimate goal of improved survival and less reinterventions.

PUBLICATIONS
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