Geometry Quantification of Abdominal Aortic Aneurysms

2010 ◽  
Author(s):  
Judy Shum ◽  
Elena Di Martino ◽  
Satish Muluk ◽  
Ender A. Finol
Keyword(s):  
Wall Thickness ◽  
Three Dimensional ◽  
Roc Curves ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Transverse Diameter ◽  
Rupture Risk ◽  
Abdominal Aortic ◽  
Elective Repair ◽  
Segmented Images

Recent studies have shown that the maximum transverse diameter of an abdominal aortic aneurysm (AAA) and expansion rate are not entirely reliable indicators of rupture potential. We hypothesize that aneurysm morphology and wall thickness can be quantified in a systematic approach leading to accurate differentiation of the geometric characteristics of aneurysm population subsets. A non-invasive, image-based evaluation of AAA shape was implemented on a retrospective study of sixty-six subjects who underwent elective repair and twenty-eight subjects who suffered AAA rupture within 1 month of their last pre-operative follow-up. The contrast-enhanced computed tomography (CT) scans of these patients were used to generate three-dimensional models from the segmented images. Twenty-eight geometry-based indices were calculated to characterize the size and shape of the AAA sac, and regional variations in wall thickness were estimated based on a novel segmentation algorithm. A multivariate analysis of variance using a maximum AAA diameter of 5.5 cm as a factor was performed for all indices as dependent variables, for the electively repaired group. Box and Whisker plots and ROC curves were generated to determine the indices’ potential as predictors of rupture risk. Listed from highest to lowest area under the ROC curve (AUC), the following six indices were found statistically significant (p < 0.05): volume (V, p < 0.0001), surface area (S, p < 0.0001), intraluminal thrombus volume (VILT, p < 0.0001), diameter-to-diameter ratio (DDr, p < 0.0001), diameter-to-height ratio (DHr, p = 0.015), and centroid distance of the maximum diameter (dc, p = 0.008). Given that individual AAAs have complex, tortuous and asymmetric shapes with local changes in surface curvature and wall thickness, the assessment of AAA rupture risk should require the accurate characterization of aneurysmal sac shape.

Three-Dimensional Geometrical Characterization of Abdominal Aortic Aneurysms: Image-Based Wall Thickness Distribution

2009 ◽  
Vol 131 (6) ◽  
Author(s):  
Giampaolo Martufi ◽  
Elena S. Di Martino ◽  
Cristina H. Amon ◽  
Satish C. Muluk ◽  
Ender A. Finol
Keyword(s):  
Wall Thickness ◽  
Three Dimensional ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Patient Specific ◽  
Future Research ◽  
Geometrical Shape ◽  
Rupture Risk ◽  
Abdominal Aortic ◽  
Elective Repair

The clinical assessment of abdominal aortic aneurysm (AAA) rupture risk is based on the quantification of AAA size by measuring its maximum diameter from computed tomography (CT) images and estimating the expansion rate of the aneurysm sac over time. Recent findings have shown that geometrical shape and size, as well as local wall thickness may be related to this risk; thus, reliable noninvasive image-based methods to evaluate AAA geometry have a potential to become valuable clinical tools. Utilizing existing CT data, the three-dimensional geometry of nine unruptured human AAAs was reconstructed and characterized quantitatively. We propose and evaluate a series of 1D size, 2D shape, 3D size, 3D shape, and second-order curvature-based indices to quantify AAA geometry, as well as the geometry of a size-matched idealized fusiform aneurysm and a patient-specific normal abdominal aorta used as controls. The wall thickness estimation algorithm, validated in our previous work, is tested against discrete point measurements taken from a cadaver tissue model, yielding an average relative difference in AAA wall thickness of 7.8%. It is unlikely that any one of the proposed geometrical indices alone would be a reliable index of rupture risk or a threshold for elective repair. Rather, the complete geometry and a positive correlation of a set of indices should be considered to assess the potential for rupture. With this quantitative parameter assessment, future research can be directed toward statistical analyses correlating the numerical values of these parameters with the risk of aneurysm rupture or intervention (surgical or endovascular). While this work does not provide direct insight into the possible clinical use of the geometric parameters, we believe it provides the foundation necessary for future efforts in that direction.

Quantitative Assessment of Abdominal Aortic Aneurysm Geometry and Rupture Potential

2009 ◽  
Author(s):  
Judy Shum ◽  
Giampaolo Martufi ◽  
Elena S. DiMartino ◽  
Ender A. Finol
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Wall Thickness ◽  
Three Dimensional ◽  
Maximum Diameter ◽  
Transverse Diameter ◽  
Geometrical Shape ◽  
Rupture Risk ◽  
Abdominal Aortic ◽  
Elective Repair

Recent biomechanics studies have shown that the maximum transverse diameter of an abdominal aortic aneurysm (AAA) and its expansion rate are not reliable indicators of rupture potential. We hypothesize that geometrical shape and size, as well as wall thickness may be related to rupture risk and can therefore be deciding factors in the clinical management of the disease. A non-invasive, image-based evaluation of AAA size and geometry was implemented on a retrospective study of twenty subjects. The contrast enhanced, computed tomography (CT) scans of 10 patients who suffered AAA rupture within 1 month of the scan were compared to those of 10 patients who received elective repair. The images were segmented and three-dimensional models were generated. Twenty-eight geometry-based indices were calculated to characterize the size and shape of each AAA and regional variations in wall thickness were estimated. A multivariate analysis of variance was performed for all indices comparing the ruptured and non-ruptured data sets to determine which indices are statistically significant. Receiving Operating Characteristic (ROC) curves were generated to determine the indices’ potential as predictors of rupture risk. In addition to maximum diameter, five other geometry-based indices were found to be statistically significant, with the minimum wall thickness being the best discriminator between ruptures and non-ruptured AAAs.

Machine Learning Techniques for the Assessment of AAA Rupture Risk

2011 ◽  
Author(s):  
Judy Shum ◽  
Elena S. Di Martino ◽  
Satish C. Muluk ◽  
Ender A. Finol
Keyword(s):  
Wall Thickness ◽  
Three Dimensional ◽  
Classification Model ◽  
Machine Learning Techniques ◽  
Transverse Diameter ◽  
Data Sets ◽  
Rupture Risk ◽  
Elective Repair ◽  
Three Dimensional Models ◽  
Enhanced Computed Tomography

Recent clinical studies have shown that the maximum transverse diameter of an abdominal aortic aneurysm (AAA) alone, or in combination with its expansion rate are not entirely reliable indicators of rupture potential. We hypothesize that AAA shape, size, and wall thickness may be related to rupture risk and can be deciding factors in the clinical management of the disease. A non-invasive, image-based evaluation of AAA size and geometry was implemented using an in-house code (AAAVASC v1.0, Carnegie Mellon University) on a retrospective study of 88 subjects. The contrast enhanced, computed tomography (CT) scans of 44 patients who suffered AAA rupture within 1 month of the scan were compared to those of 44 patients who received elective repair. The images were segmented and three-dimensional models were generated. Twenty-eight geometry-based indices were calculated to characterize the size and shape of each AAA and estimate regional variations in wall thickness. A multivariate analysis of variance was performed for all indices comparing the ruptured and non-ruptured data sets to determine which indices were statistically significant. A classification model was created using a J48 decision tree algorithm and its performance was assessed using 10-fold cross validation. The model correctly classified eighty-six data sets and had an average prediction accuracy of 74% (κ = 0.69). Such a decision model can be used in a clinical setting to assess the risk of AAA rupture with minimal user intervention.

The similarities and differences among patients with abdominal aortic aneurysms referred to a tertiary hospital and found at necropsy

Vascular ◽  
2014 ◽  
Vol 23 (4) ◽  
pp. 411-418 ◽  
Author(s):  
Erasmo S da Silva ◽  
Vitor C Gornati ◽  
Ivan B Casella ◽  
Ricardo Aun ◽  
Andre EV Estenssoro ◽  
...  
Keyword(s):  
Risk Factors ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Protective Factor ◽  
Abdominal Aortic Aneurysms ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Transverse Diameter ◽  
Abdominal Aortic ◽  
Tertiary Center

Objective To analyze the characteristics of patients with abdominal aortic aneurysms referred to a tertiary center and to compare with individuals with abdominal aortic aneurysm found at necropsy. Methods We have retrospectively analyzed the medical records of 556 patients with abdominal aortic aneurysm and 102 cases abdominal aortic aneurysm found at necropsy. Results At univariated analysis, hypertension, tobacco use and maximum diameter were significant risk factors for symptomatic aneurysm, while diabetes tended to be a protective factor for rupture. By logistic regression analysis, the largest transverse diameter was the only one significantly associated with abdominal aortic aneurysm rupture ( p < .0001, odds ratio 1.7, 95% confidence interval 1.481–1.951). Intact abdominal aortic aneurysm found at necropsy showed similarities with outpatients in relation to abdominal aortic aneurysm diameter and risk factors. Conclusion Intact abdominal aortic aneurysm at necropsy and at outpatients setting showed similarities that confirmed that abdominal aortic aneurysm repair is less offered to women, and they died more frequently with intact abdominal aortic aneurysm from other causes.

scholarly journals High-frequency murine ultrasound provides enhanced metrics of BAPN-induced AAA growth

2019 ◽  
Vol 317 (5) ◽  
pp. H981-H990 ◽  
Author(s):  
Daniel J. Romary ◽  
Alycia G. Berman ◽  
Craig J. Goergen
Keyword(s):  
Surface Area ◽  
Murine Model ◽  
High Frequency ◽  
Wall Stress ◽  
Growth Patterns ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Rupture Risk ◽  
Abdominal Aortic ◽  
Peak Wall Stress

An abdominal aortic aneurysm (AAA), defined as a pathological expansion of the largest artery in the abdomen, is a common vascular disease that frequently leads to death if rupture occurs. Once diagnosed, clinicians typically evaluate the rupture risk based on maximum diameter of the aneurysm, a limited metric that is not accurate for all patients. In this study, we worked to evaluate additional distinguishing factors between growing and stable murine aneurysms toward the aim of eventually improving clinical rupture risk assessment. With the use of a relatively new mouse model that combines surgical application of topical elastase to cause initial aortic expansion and a lysyl oxidase inhibitor, β-aminopropionitrile (BAPN), in the drinking water, we were able to create large AAAs that expanded over 28 days. We further sought to develop and demonstrate applications of advanced imaging approaches, including four-dimensional ultrasound (4DUS), to evaluate alternative geometric and biomechanical parameters between 1) growing AAAs, 2) stable AAAs, and 3) nonaneurysmal control mice. Our study confirmed the reproducibility of this murine model and found reduced circumferential strain values, greater tortuosity, and increased elastin degradation in mice with aneurysms. We also found that expanding murine AAAs had increased peak wall stress and surface area per length compared with stable aneurysms. The results from this work provide clear growth patterns associated with BAPN-elastase murine aneurysms and demonstrate the capabilities of high-frequency ultrasound. These data could help lay the groundwork for improving insight into clinical prediction of AAA expansion. NEW & NOTEWORTHY This work characterizes a relatively new murine model of abdominal aortic aneurysms (AAAs) by quantifying vascular strain, stress, and geometry. Furthermore, Green-Lagrange strain was calculated with a novel mapping approach using four-dimensional ultrasound. We also compared growing and stable AAAs, finding peak wall stress and surface area per length to be most indicative of growth. In all AAAs, strain and elastin health declined, whereas tortuosity increased.

scholarly journals Biomechanical rupture risk assessment of abdominal aortic aneurysms based on a novel probabilistic rupture risk index

2015 ◽  
Vol 12 (113) ◽  
pp. 20150852 ◽  
Author(s):  
Stanislav Polzer ◽  
T. Christian Gasser
Keyword(s):  
Risk Assessment ◽  
Wall Thickness ◽  
Risk Index ◽  
Wall Stress ◽  
Aortic Aneurysms ◽  
Rupture Risk ◽  
Discriminative Power ◽  
Wall Strength ◽  
Abdominal Aortic ◽  
Wide Range

A rupture risk assessment is critical to the clinical treatment of abdominal aortic aneurysm (AAA) patients. The biomechanical AAA rupture risk assessment quantitatively integrates many known AAA rupture risk factors but the variability of risk predictions due to model input uncertainties remains a challenging limitation. This study derives a probabilistic rupture risk index (PRRI). Specifically, the uncertainties in AAA wall thickness and wall strength were considered, and wall stress was predicted with a state-of-the-art deterministic biomechanical model. The discriminative power of PRRI was tested in a diameter-matched cohort of ruptured ( n = 7) and intact ( n = 7) AAAs and compared to alternative risk assessment methods. Computed PRRI at 1.5 mean arterial pressure was significantly ( p = 0.041) higher in ruptured AAAs (20.21(s.d. 14.15%)) than in intact AAAs (3.71(s.d. 5.77)%). PRRI showed a high sensitivity and specificity (discriminative power of 0.837) to discriminate between ruptured and intact AAA cases. The underlying statistical representation of stochastic data of wall thickness, wall strength and peak wall stress had only negligible effects on PRRI computations. Uncertainties in AAA wall stress predictions, the wide range of reported wall strength and the stochastic nature of failure motivate a probabilistic rupture risk assessment. Advanced AAA biomechanical modelling paired with a probabilistic rupture index definition as known from engineering risk assessment seems to be superior to a purely deterministic approach.

Strain Mapping From Four-Dimensional Ultrasound Reveals Complex Remodeling in Dissecting Murine Abdominal Aortic Aneurysms

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Hannah L. Cebull ◽  
Arvin H. Soepriatna ◽  
John J. Boyle ◽  
Sean M. Rothenberger ◽  
Craig J. Goergen
Keyword(s):  
Three Dimensional ◽  
Small Animal ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
High Frequency Ultrasound ◽  
4D Ultrasound ◽  
Abdominal Aortic ◽  
Lagrange Strain ◽  
Aortic Strain

Current in vivo abdominal aortic aneurysm (AAA) imaging approaches tend to focus on maximum diameter but do not measure three-dimensional (3D) vascular deformation or strain. Complex vessel geometries, heterogeneous wall compositions, and surrounding structures can all influence aortic strain. Improved understanding of complex aortic kinematics has the potential to increase our ability to predict aneurysm expansion and eventual rupture. Here, we describe a method that combines four-dimensional (4D) ultrasound and direct deformation estimation to compute in vivo 3D Green-Lagrange strain in murine angiotensin II-induced suprarenal dissecting aortic aneurysms, a commonly used small animal model. We compared heterogeneous patterns of the maximum, first-component 3D Green-Lagrange strain with vessel composition from mice with varying AAA morphologies. Intramural thrombus and focal breakage in the medial elastin significantly reduced aortic strain. Interestingly, a dissection that was not detected with high-frequency ultrasound also experienced reduced strain, suggesting medial elastin breakage that was later confirmed via histology. These results suggest that in vivo measurements of 3D strain can provide improved insight into aneurysm disease progression. While further work is needed with both preclinical animal models and human imaging studies, this initial murine study indicates that vessel strain should be considered when developing an improved metric for predicting aneurysm growth and rupture.

Theoretical Modeling for Monitoring the Growth of Fusiform Abdominal Aortic Aneurysms Using Dielectric Elastomer Capacitive Sensors

2016 ◽  
Vol 08 (07) ◽  
pp. 1640010 ◽  
Author(s):  
C. F. Lü ◽  
Y. K. Du
Keyword(s):  
Early Stage ◽  
Imaging Techniques ◽  
Abdominal Aortic Aneurysms ◽  
Dielectric Elastomer ◽  
Aortic Aneurysms ◽  
Geometrical Parameters ◽  
Rupture Risk ◽  
Abdominal Aortic ◽  
Elective Repair ◽  
Clinical Statistics

To evaluate the rupture risk of abdominal aortic aneurysms, traditional medical imaging techniques, e.g., ultrasonography, CT scanning, or magnetic resonance imaging, form the regular clinic treatments for detecting the growth but can only provide the diameter of the aneurysm. This has been proved to be inadequate since a considerable portion of rupture has been missed by the critical rupture size that is established according to clinical statistics. We proposed to mount a dielectric elastomer capacitive sensor around an early-stage abdominal aneurysm and using the continuously varying capacitance for retrieving both the wall stress and morphology of the aneurysm in a real-time manner. A theoretical mechanics model based on the growth theory is developed to predict the correlation between the capacitance and the stress level as well as the geometrical parameters of the aneurysm. Numerical calculations agree well qualitatively with the clinical statistics of both rupture size and rupture stress of the aneurysm. The results suggest that the rupture risk of an aneurysm in a patient may be assessed more reliably by multiple indicators of stress and morphology during the growth process. A range of capacitance may also be recommended for elective repair based on the proposed theoretical model.

scholarly journals Vascular Deformation Mapping of Abdominal Aortic Aneurysm

Tomography ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 189-201
Author(s):  
Drew J. Braet ◽  
Jonathan Eliason ◽  
Yunus Ahmed ◽  
Pieter A. J. van Bakel ◽  
Jiayang Zhong ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Complex Disease ◽  
Endovascular Aneurysm Repair ◽  
Three Dimensional ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Abdominal Aortic ◽  
Risk Of Rupture ◽  
Imaging Surveillance

Abdominal aortic aneurysm (AAA) is a complex disease that requires regular imaging surveillance to monitor for aneurysm stability. Current imaging surveillance techniques use maximum diameter, often assessed by computed tomography angiography (CTA), to assess risk of rupture and determine candidacy for operative repair. However, maximum diameter measurements can be variable, do not reliably predict rupture risk and future AAA growth, and may be an oversimplification of complex AAA anatomy. Vascular deformation mapping (VDM) is a recently described technique that uses deformable image registration to quantify three-dimensional changes in aortic wall geometry, which has been previously used to quantify three-dimensional (3D) growth in thoracic aortic aneurysms, but the feasibility of the VDM technique for measuring 3D growth in AAA has not yet been studied. Seven patients with infra-renal AAAs were identified and VDM was used to identify three-dimensional maps of AAA growth. In the present study, we demonstrate that VDM is able to successfully identify and quantify 3D growth (and the lack thereof) in AAAs that is not apparent from maximum diameter. Furthermore, VDM can be used to quantify growth of the excluded aneurysm sac after endovascular aneurysm repair (EVAR). VDM may be a useful adjunct for surgical planning and appears to be a sensitive modality for detecting regional growth of AAAs.

Sign in / Sign up

Export Citation Format

Share Document