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Rupture of atherosclerotic plaque is a major cause of mortality. Plaque stress analysis, based on patient-specific multisequence in vivo MRI, can provide critical information for the understanding of plaque rupture and could eventually lead to plaque rupture prediction. However, the direct link between stress and plaque rupture is not fully understood. In the present study, the plaque from a patient who recently experienced a transient ischaemic attack (TIA) was studied using a fluid-structure interaction method to quantify stress distribution in the plaque region based on in vivo MR images. The results showed that wall shear stress is generally low in the artery with a slight increase at the plaque throat owing to minor luminal narrowing. The oscillatory shear index is much higher in the proximal part of the plaque. Both local wall stress concentrations and the relative stress variation distribution during a cardiac cycle indicate that the actual plaque rupture site is collocated with the highest rupture risk region in the studied patient.

Background & Objectives The aim of this study was to apply three simple risk - scoring systems to prospectively collected data on all elective open Abdominal Aortic Aneurysm (AAA) operations in the Cambridge Academic Vascular Unit over a 6 - year period (January 1998 to January 2004), to compare their predictive values and to evaluate their validity with respect to prediction of mortality and post-operative complications. Methods 204 patients underwent elective open infra-renal AAA repair. Data were prospectively collected and risk assessment scores were calculated for mortality and morbidity according to the Glasgow Aneurysm Score (GAS), VBHOM (Vascular Biochemistry and Haematology Outcome Models) and Estimation of Physiologic Ability and Surgical Stress (E-PASS). Results The mortality rate was 6.3% (13/204) and 59% (121/204) experienced a post-operative complication (30-day outcome). For GAS, VBHOM and E-PASS the receiver operating characteristics (ROC) curve analysis for prediction of in-hospital mortality showed area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.76 to 0.92; p < 0.0001), 0.82 (95% CI, 0.68 to 0.95; p = 0.0001) and 0.92 (95% CI, 0.87 to 0.97; p < 0.0001) respectively. There were also significant correlations between post-operative complications and length of hospital stay and each of the three scores, but the correlation was substantially higher in the case of E-PASS. Conclusions All three scoring systems accurately predicted the risk of mortality and morbidity in patients undergoing elective open AAA repair. Among these, E-PASS seemed to be the most accurate predictor in this patient population.

Background The Estimation of Physiologic Ability and Surgical Stress (E-PASS) score was designed on the premise that the balance between the patient’s physiologic reserve capacity and the surgical stress inflicted at operation was important in the occurrence of postoperative complications. The aim of this study was to assess its value in predicting mortality and morbidity after open elective abdominal aortic aneurysm (AAA) repair. Methods E-PASS data items were collected prospectively in a group of 204 patients undergoing elective open AAA repair over a 6-year period. The operative morbidity and mortality rates were compared with the preoperative risk score (PRS), surgical stress score (SSS) and comprehensive risk score (CRS) of E-PASS. The group comprised 180 (88%) males and the median age was 73 (range 44 to 86) years. Results There were 13 (6%) deaths and 121 (59%) experienced a postoperative complication. As the PRS, SSS and CRS increased, the incidence of postoperative morbidity and mortality significantly increased (P < .0001). Overall mean CRS was .52 (±.27). Mean CRS in the groups of patients who survived and died were .49 (±.24) and .98 (±26), respectively. PRS, SSS, and CRS all had extremely good predictive power for both mortality and morbidity as demonstrated by high areas under the receiver operator curve (range .799 to .953). CRS also showed a strong statistically significant association with the severity of postoperative complication (P < .0001) and length of hospital stay (P < .0001). Conclusions The E-PASS model appears to be a promising method of predicting death and the development of postoperative complications in patients undergoing elective open AAA surgery. It requires further validation in arterial surgery at different geographical locations.