Morphologic evaluation of ruptured and symptomatic abdominal aortic aneurysm by three-dimensional modeling.
OBJECTIVE
To identify geometric indices of abdominal aortic aneurysms (AAAs) on computed tomography that are associated with higher risk of rupture.


METHODS
This retrospective case-control, institutional review board-approved study involved 63 cases with ruptured or symptomatic AAA and 94 controls with asymptomatic AAA. Three-dimensional models were generated from computed tomography segmentation and used for the calculation of 27 geometric indices. On the basis of the results of univariate analysis and multivariable sequential logistic regression analyses with a forward stepwise model selection based on likelihood ratios, a traditional model based on gender and maximal diameter (Dmax) was compared with a model that also incorporated geometric indices while adjusting for gender and Dmax. Receiver operating characteristic (ROC) curves were calculated for these two models to evaluate their classification accuracy.


RESULTS
Univariate analysis revealed that gender (P = .024), Dmax (P = .001), and 14 other geometric indices were associated with AAA rupture at P < .05. In the multivariable analysis, adjusting for gender and Dmax, the AAA with a higher bulge location (P = .020) and lower mean averaged area (P = .005) were associated with AAA rupture. With these two geometric indices, the area under the ROC curve showed an improvement from 0.67 (95% confidence interval, 0.58-0.77) to 0.75 (95% confidence interval, 0.67-0.83; P < .001). Our predictive model showed comparable sensitivity (64% vs 60%) and specificity (79% vs 77%) with current treatment criteria based on gender and diameter at the point optimizing the Youden index (sensitivity + specificity - 1) on the ROC curve.


CONCLUSIONS
Two geometric indices derived from AAA three-dimensional modeling were independently associated with AAA rupture. The addition of these indices in a predictive model based on current treatment criteria modestly improved the accuracy to detect aneurysm rupture.
Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.
An
A
Tang
Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, Québec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.
Claude
C
Kauffmann
Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada.
Sophie
S
Tremblay-Paquet
Division of Vascular Surgery, Department of Surgery, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.
Stéphane
S
Elkouri
Division of Vascular Surgery, Surgery Department, Royal Victoria Hospital, McGill University Health Center (MUHC), Montréal, Québec, Canada.
Oren
O
Steinmetz
Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada.
Florence
F
Morin-Roy
Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada.
Laurie
L
Cloutier-Gill
Department of Radiology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, Québec, Canada; Centre de recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada. Electronic address: gilles.soulez.chum@ssss.gouv.qc.ca.
Gilles
G
Soulez
D000368:Aged; D000369:Aged, 80 and over; D001012:Aorta, Abdominal / Q000000981:diagnostic imaging*; D017544:Aortic Aneurysm, Abdominal / Q000150:complications / Q000000981:diagnostic imaging*; D001019:Aortic Rupture / Q000000981:diagnostic imaging* / Q000209:etiology; D001027:Aortography / Q000379:methods*; D016009:Chi-Square Distribution; D003661:Decision Support Techniques; D018450:Disease Progression; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D061330:Multidetector Computed Tomography; D015999:Multivariate Analysis; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted; D012189:Retrospective Studies; D012307:Risk Factors