An Artificial Neural Network Stratifies the Risks of Reintervention and Mortality after Endovascular Aneurysm Repair; a Retrospective Observational study.

BACKGROUND: Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. METHODS: Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. RESULTS: 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p<0.001). CONCLUSION: This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

Plasma matrix metalloproteinase levels do not predict tissue levels in abdominal aortic aneurysms suitable for elective repair.

The role of matrix metalloproteinases (MMPs) in abdominal aortic aneurysm (AAA) pathogenesis is well described. However, a clear role for the MMPs in disease prediction has not been established. The aim of this study was to determine if circulating levels of MMPs correlated with AAA diameter and with MMP concentrations within the aneurysm wall. Preoperative plasma samples and intraoperative infrarenal AAA sac biopsies were taken in a standard fashion from 31 patients undergoing elective repair.The concentrations of MMP-1, MMP-2, MMP-3, MMP-9, tissue inhibitor of matrix metalloproteinase (TIMP)-1, and TIMP-2 were quantified in plasma and aneurysm wall homogenates using enzyme-linked immunosorbent assay. Comparison used the Spearman correlation. There were no correlations between the paired plasma and aneurysm wall concentrations for any MMP or TIMP. Correlation between MMP-9 levels in the aneurysm wall and aneurysm diameter was negative (r = -.42, p = .019). Other correlations between plasma and tissue levels with aneurysm diameter were nonsignificant.