Combining Volumetric and Wall Shear Stress Analysis from CT to Assess Risk of Abdominal Aortic Aneurysm Progression

Abstract

A bdominal aortic aneurysm (AAA) is a serious and common pathologic abnormality that accompanies aging. Among men older than 65 years, the prevalence of AAA reaches 7.7%, increasing from 5.7% in ages 64-69 years to 8.9% in individuals older than 74 years (1). The high overall mortality from ruptured AAAs makes growth and subsequent rupture risk assessment crucial for AAA management.Since the 1970s, many studies (2) have demonstrated that AAA diameter correlates with rupture rate. Accordingly, AAA maximum diameter, effectively measured by using diagnostic US, has been the primary prognostic variable used to determine patient care (3,4). Current guidelines dictate elective repair to be appropriate at a diameter threshold of 50-55 mm or for AAA exhibiting growth greater than 1 cm per year (5,6).However, whereas some AAAs smaller than 55 mm do not grow more than 1 cm per year (7), other AAAs that are too small to trigger intervention grow rapidly. The sole use of maximal diameter measurement may be insufficient to

Hemostatic Biomarkers and Volumetry Help to Identify High-Risk Abdominal Aortic Aneurysms

“…Still, our semi-automatic measurement method, based on the 3mensio workstation, has been previously validated with good intra- and inter-observer variabilities for the volumetric determination of the aortic aneurysm [ 28 ]. Indeed, we report in here a difference in AAA volume of 9.4 ± 7.75 mL at 1 year, similar to the volume defined as significant for AAA progression (10 mL) in non-surgical AAA [ 8 , 29 , 30 ]. Despite offering the participation in the study equally to men and women, we have verified a significant difference according to the estimated proportion of men and women affected by AAA (4 male/1 female) [ 31 ].…”

Geometric and biomechanical modeling aided by machine learning improves the prediction of growth and rupture of small abdominal aortic aneurysms

“…The method is fast, easy to use and computes PWS and PWRI (as well as mean ILT stress) but not shear stresses which requires computationally demanding and time-consuming blood flow simulations. While consideration of blood flow in addition to blood pressure seems to have negligible effects on PWS estimations 64 and thus not deemed crucial for rupture risk estimations, our group and others have previously noted an association between shear stresses and growth 57 , 65 .…”

“…Moreover, some studies have examined the ability of biomechanical estimates to predict the growth rates of AAAs. Examples of approaches used previously are PWS in a model with local wall thickness estimated from CT images by a custom algorithm 34 , lumen volume and the computational fluid dynamics-derived wall shear stress in logistic regression 57 , and a measurement similar to PWRI to predict the combined event of elective repair or rupture 35 . Functional imaging strategies to predict AAA growth have relied on fluorodeoxyglucose ( 18 F-FDG) 23 , 58 and Fluorine-18–sodium fluoride ( 18 F-NaF) 25 positron emission tomography CT and ultrasmall superparamagnetic particles of iron oxide (USPIO) on magnetic resonance imaging 59 .…”

Enlarged Lumen Volume of Proximal Aortic Segment and Acute Type B Aortic Dissection: A Computer Fluid Dynamics Study of Ideal Aortic Models

“…Hemodynamic simulation has been widely used in the study of aortic diseases, [8][9][10][11] and has enabled the quantification of the specific impact of each aortic anatomical risk factor. 12 Polanczyk et al created a mathematical approach for blood hemodynamic description with the use of brightness analysis and proved post-operative remodelling of the aorta after TEVAR for aortic dissection improved hemodynamic patterns.…”