MATLAB-Based Algorithm and Software for Analysis of Wavy Collagen Fibers.

Knowledge of soft tissue fiber structure is necessary for accurate characterization and modeling of their mechanical response. Fiber configuration and structure informs both our understanding of healthy tissue physiology and of pathological processes resulting from diseased states. This study develops an automatic algorithm to simultaneously estimate fiber global orientation, abundance, and waviness in an investigated image. To our best knowledge, this is the first validated algorithm which can reliably separate fiber waviness from its global orientation for considerably wavy fibers. This is much needed feature for biological tissue characterization. The algorithm is based on incremental movement of local regions of interest (ROI) and analyzes two-dimensional images. Pixels belonging to the fiber are identified in the ROI, and ROI movement is determined according to local orientation of fiber within the ROI. The algorithm is validated with artificial images and ten images of porcine trachea containing wavy fibers. In each image, 80-120 fibers were tracked manually to serve as verification. The coefficient of determination R2 between curve lengths and histograms documenting the fiber waviness and global orientation were used as metrics for analysis. Verification-confirmed results were independent of image rotation and degree of fiber waviness, with curve length accuracy demonstrated to be below 1% of fiber curved length. Validation-confirmed median and interquartile range of R2, respectively, were 0.90 and 0.05 for curved length, 0.92 and 0.07 for waviness, and 0.96 and 0.04 for global orientation histograms. Software constructed from the proposed algorithm was able to track one fiber in about 1.1 s using a typical office computer. The proposed algorithm can reliably and accurately estimate fiber waviness, curve length, and global orientation simultaneously, moving beyond the limitations of prior methods.

Effect of aortic bifurcation geometry on pressure and peak wall stress in abdominal aorta: Fluid-structure interaction study.

BACKGROUND AND OBJECTIVE: Geometry of aorto-iliac bifurcation may affect pressure and wall stress in aorta and thus potentially serve as a predictor of abdominal aortic aneurysm (AAA), similarly to hypertension. METHODS: Effect of aorto-iliac bifurcation geometry was investigated via parametric analysis based on two-way weakly coupled fluid-structure interaction simulations. The arterial wall was modelled as isotropic hyperelastic monolayer, and non-Newtonian behaviour was introduced for the fluid. Realistic boundary conditions of the pulsatile blood flow were used on the basis of experiments in literature and their time shift was tailored to the pulse wave velocity in the model to obtain physiological wave shapes. Eighteen idealized and one patient-specific geometries of human aortic tree with common iliac and renal arteries were considered with different angles between abdominal aorta (AA) and both iliac arteries and different area ratios (AR) of iliac and aortic luminal cross sections. RESULTS: Peak wall stress (PWS) and systolic blood pressure (SBP) were insensitive to the aorto-iliac angles but sensitive to the AR: when AR decreased by 50%, the PWS and SBP increased by up to 18.4% and 18.8%, respectively. CONCLUSIONS: Lower AR (as a result of the iliac stenosis or aging), rather than the aorto-iliac angles increases the BP in the AA and may be thus a risk factor for the AAA development.

Methodology for estimation of undeformed thickness of arterial tissues.

Soft tissue sample thickness measurement is one of the major sources of differences between mechanical responses published by different groups. New method for the estimation of unloaded sample thickness of soft tissues is proposed in this study. Ten 30 × 30 mm and ten 20 × 20 mm samples of porcine anterior thoracic aortas were loaded by gradually increased radial force. Their deformed thickness was then recorded in order to generate a pressure-thickness response. Next, the limit pressure to which the response can be considered linear was estimated. Line was fitted to the linear part of the curve and extrapolated towards zero pressure to estimate unloaded thickness (7 kPa fit). For comparison, data near zero pressure were fitted separately and extrapolated towards zero (Near Zero fit). The limit pressure for the linearity of the response was around 7 kPa. The Unloaded thickness for 30 × 30 mm samples was 2.68 ± 0.31 mm and 2.68 ± 0.3 mm for Near Zero fit and 7 kPa fit, respectively. The Unloaded thickness for 20 × 20 mm samples was 2.60 ± 0.35 mm and 2.59 ± 0.35 mm for Near Zero fit and 7 kPa fit, respectively. The median of thickness difference between smaller and larger samples was not found statistically different. Proposed method can estimate unloaded undeformed sample thickness quickly and reliably.

Low cycle fatigue properties of porcine aorta - Pilot study.

INTRODUCTION: Biomechanical rupture risk assessment of aortic tissues is commonly based on computed stress to measured uniaxial static strength comparison. Loading of the arterial wall, however, is cyclic; thus, the static strength may not be a proper limit value. This study investigates the low cycle fatigue of porcine aortic samples tested in a circumferential direction. METHODS: 7 porcine descending aorta (both thoracic and abdominal) were harvested and 56 dogbone-shaped samples were prepared. Static strength was measured, the limit of engineering stress was chosen and then force controlled cyclic loading was performed up to 100,000 cycles. Efforts were made to obtain a sufficient number of points across the entire range of 0-100,000 cycles. Data were fitted by both linear and logarithmic law and extrapolated towards 1 cycle for validation against static strength/ultimate tension. Data dispersion was evaluated via normalised root mean square error. RESULTS: Out of 56 samples from 7pigs, 28 samples from 4 pigs were successfully tested. There was a strong negative correlation between applied stress/tension and number of cycles to failure. The fitting of both linear and logarithmic values resulted in a similar accuracy (R2=0.72 and 0.71 for stress and R2=0.62 and 0.7 for tension, respectively), while predicting static failure properties was more accurate by logarithmic law. NRMSE was lower for absolute values (20-21%) than for relative values (27-30%). CONCLUSIONS: Absolute values of cyclic strength and tension are less dispersed than relative ones. Logarithmic fits are more robust in predicting static strength from cyclic data, while linear fits serve as a lower limit estimation.

A quarter of a century biomechanical rupture risk assessment of abdominal aortic aneurysms. Achievements, clinical relevance, and ongoing developments.

Abdominal aortic aneurysm (AAA) disease, the local enlargement of the infrarenal aorta, is a serious condition that causes many deaths, especially in men exceeding 65 years of age. Over the past quarter of a century, computational biomechanical models have been developed towards the assessment of AAA risk of rupture, technology that is now on the verge of being integrated within the clinical decision-making process. The modeling of AAA requires a holistic understanding of the clinical problem, in order to set appropriate modeling assumptions and to draw sound conclusions from the simulation results. In this article we summarize and critically discuss the proposed modeling approaches and report the outcome of clinical validation studies for a number of biomechanics-based rupture risk indices. Whilst most of the aspects concerning computational mechanics have already been settled, it is the exploration of the failure properties of the AAA wall and the acquisition of robust input data for simulations that has the greatest potential for the further improvement of this technology.

Effect of Water-Induced and Physical Aging on Mechanical Properties of 3D Printed Elastomeric Polyurethane.

In this study, the effect of moisture on the elastic and failure properties of elastomeric polyurethane (EPU 40) 3D printed via Vat Photopolymerization was investigated. EPU 40 samples were printed, and uniaxial tensile tests were performed on Dry-fresh, Dry-aged (eight months aged), and after various times of being immersed in water (0−8 months). Elastic response, initial stiffness, failure strength, and failure elongation were analyzed. Besides, gravimetric analysis was performed to determine the increase in weight and thickness after water immersion. The elastic response was fitted by the Arruda-Boyce constitutive model. Results show that initial stiffness decreased after immersion (mean 6.8 MPa dry vs. 6.3 MPa immersed p-value 0.002). Contrary, the initial stiffness increased due to physical aging under a dry state from a mean 6.3 MPa to 6.9 MPa (p = 0.006). The same effect was observed for stiffness parameter G of the constitutive model, while the limit stretch parameter λL was not affected by either aging. The 95% confidence intervals for strength and failure stretch were 5.27−9.48 MPa and 2.18−2.86, respectively, and were not affected either by immersion time or by physical aging. The median diffusion coefficient was 3.8·10−12 m^2/s. The immersion time has a significant effect only on stiffness, while oxidative aging has an inverse effect on the mechanical properties compared to water immersion. The transition process is completed within 24 h after immersion.

On stress in abdominal aortic aneurysm: Linear versus non-linear analysis and aneurysm rupture risk.

We present comprehensive biomechanical analyses of abdominal aortic aneurysms (AAA) for 43 patients. We compare stress magnitudes and stress distributions within arterial walls of abdominal aortic aneurysms (AAA) obtained using two simulation and modelling methods: (a) Fully automated and computationally very efficient linear method embedded in the software platform Biomechanics based Prediction of Aneurysm Rupture Risk (BioPARR), freely available from https://bioparr.mech.uwa.edu.au/; (b) More complex and much more computationally demanding Non-Linear Iterative Stress Analysis (Non-LISA) that uses a non-linear inverse iterative approach and strongly non-linear material model. Both methods predicted localised high stress zones with over 90% of AAA model volume fraction subjected to stress below 20% of the 99th percentile maximum principal stress. However, for the non-linear iterative method, the peak maximum principal stress (and 99th percentile maximum principal stress) was higher and the stress magnitude in the low stress area lower than for the automated linear method embedded in BioPARR. Differences between the stress distributions obtained using the two methods tended to be particularly pronounced in the areas where the AAA curvature was large. Performance of the selected characteristic features of the stress fields (we used 99th percentile maximum principal stress) obtained using BioPARR and Non-LISA in distinguishing between the AAAs that would rupture and remain intact was for practical purposes the same for both methods.

Biomechanical Rupture Risk Assessment in Management of Patients with Abdominal Aortic Aneurysm in COVID-19 Pandemic.

Background: The acute phase of the COVID-19 pandemic requires a redefinition of healthcare system to increase the number of available intensive care units for COVID-19 patients. This leads to the postponement of elective surgeries including the treatment of abdominal aortic aneurysm (AAA). The probabilistic rupture risk index (PRRI) recently showed its advantage over the diameter criterion in AAA rupture risk assessment. Its major improvement is in increased specificity and yet has the same sensitivity as the maximal diameter criterion. The objective of this study was to test the clinical applicability of the PRRI method in a quasi-prospective patient cohort study. Methods: Nineteen patients (fourteen males, five females) with intact AAA who were postponed due to COVID-19 pandemic were included in this study. The PRRI was calculated at the baseline via finite element method models. If a case was diagnosed as high risk (PRRI > 3%), the patient was offered priority in AAA intervention. Cases were followed until 10 September 2021 and a number of false positive and false negative cases were recorded. Results: Each case was assessed within 3 days. Priority in intervention was offered to two patients with high PRRI. There were four false positive cases and no false negative cases classified by PRRI. In three cases, the follow-up was very short to reach any conclusion. Conclusions: Integrating PRRI into clinical workflow is possible. Longitudinal validation of PRRI did not fail and may significantly decrease the false positive rate in AAA treatment.

Full-Range Optical Imaging of Planar Collagen Fiber Orientation Using Polarized Light Microscopy.

A novel method for semiautomated assessment of directions of collagen fibers in soft tissues using histological image analysis is presented. It is based on multiple rotated images obtained via polarized light microscopy without any additional components, i.e., with just two polarizers being either perpendicular or nonperpendicular (rotated). This arrangement breaks the limitation of 90° periodicity of polarized light intensity and evaluates the in-plane fiber orientation over the whole 180° range accurately and quickly. After having verified the method, we used histological specimens of porcine Achilles tendon and aorta to validate the proposed algorithm and to lower the number of rotated images needed for evaluation. Our algorithm is capable to analyze 5·105 pixels in one micrograph in a few seconds and is thus a powerful and cheap tool promising a broad application in detection of collagen fiber distribution in soft tissues.

Biomechanical properties of ascending aortic aneurysms: Quantification of inter- and intra-patient variability.

This study investigates the biomechanical properties of ascending aortic aneurysms focusing on the inter-patient differences vs. the heterogeneity within a patient's aneurysm. Each specimen was tested on a biaxial testing device and the resulting stress-strain response was fitted to a four-parameter Fung constitutive model. We postulate that the inter-patient variability (differences between patients) blurs possible intra-patient variability (regional heterogeneity) and, thus, that both effects must be considered to shed light on the role of heterogeneity in aneurysm progression. We propose, demonstrate, and discuss two techniques to assess differences by, first, comparing conventional biomechanical properties and, second, the overall constitutive response. Results show that both inter- and intra-patient variability contribute to errors when using population averaged models to fit individual tissue behaviour. When inter-patient variability was accounted for and its effects excluded, intra-patient heterogeneity could be assessed, showing a wide degree of heterogeneity at the individual patient level. Furthermore, the right lateral region (from the patient's perspective) appeared different (stiffer) than the other regions. We posit that this heterogeneity could be a consequence of maladaptive remodelling due to altered loading conditions that hastens microstructural changes naturally occurring with age. Further validation of these results should be sought from a larger cohort study.

Methodology for Estimation of Annual Risk of Rupture for Abdominal Aortic Aneurysm.

BACKGROUND AND OBJECTIVE: Estimating patient specific annual risk of rupture of abdominal aortic aneurysm (AAA) is currently based only on population. More accurate knowledge based on patient specific data would allow surgical treatment of only those AAAs with significant risk of rupture. This would be beneficial for both patients and health care system. METHODS: A methodology for estimating annual risk of rupture (EARR) of abdominal aortic aneurysms (AAA) that utilizes Bayesian statistics, mechanics and patient-specific blood pressure monitoring data is proposed. EARR estimation takes into consideration, peak wall stress in AAA computed by patient-specific finite element modeling, the probability distributions of wall thickness, wall strength, systolic blood pressure and the period of time that the patient is known to have already survived with the intact AAA. Initial testing of proposed approach was performed on fifteen patients with intact AAA (mean maximal diameter 51mm±8mm). They were equipped with a pressure holter and their blood pressure was recorded over 24 hours. Then, we calculated EARR values for four possible scenarios - without considering any days of survival prior identification of AAA at computed tomography scans (EARR_0), considering past survival of 30 (EARR_30), 90 (EARR_90) and 180 days (EARR_180). Finally, effect of patient-specific blood pressure variability was analyzed. RESULTS: Consideration of past survival does indeed significantly improve predictions of future risk: EARR_30 (1.04%± 0.87%), EARR_90 (0.67%± 0.56%) and EARR_180 (0.47%± 0.39%) which are unrealistically high otherwise (EARR_0 5.02%± 5.24%). Finally, EARR values were observed to vary by an order as a consequence of blood pressure variability and by factor of two as a consequence of neglected growth. CONCLUSIONS: Methodology for computing annual risk of rupture of AAA was developed for the first time. Sensitivity analyses showed respecting patient specific blood pressure is important factor and should be included in the AAA rupture risk assessment. Obtained EARR values were generally low and in good agreement with confirmed survival time of investigated patients so proposed method should be further clinically validated.

Sources of inconsistency in mean mechanical response of abdominal aortic aneurysm tissue.

INTRODUCTION: There is a striking difference in the reported mean response of abdominal aortic aneurysm tissue in academic literature depending on the type of tests (uniaxial vs biaxial) performed. In this paper, the hypothesis variability caused by differences in experimental protocols is explored using porcine aortic tissue as a substitute for aneurysmal tissue. METHODS: Nine samples of porcine aorta were created and both uniaxial and biaxial tests were performed. Three effects were investigated. (i) Effect of sample (non) preconditioning, (ii) effect of objective function used (normalised vs non-normalised), and (iii) effect of chosen procedure used for mean response calculation: constant averaging (CA) vs fit to averaged response (FAR) vs fit to all data (FAD). Both the overall shape of mean curve and mean initial stiffness were compared. RESULTS: (i) Non-preconditioning led to a much stiffer response, and initial stiffness was about three times higher for a non-preconditioned response based on uniaxial data compared to a preconditioned biaxial response. (ii) CA led to a much stiffer response compared to FAR and FAD procedures which gave similar results. (iii) Normalised objective function produced a mean response with six times lower initial stiffness and more pronounced nonlinearity compared to non-normalised objective function. DISCUSSION: It is possible to reproduce a mechanically inconsistent response purely by using the chosen experimental protocol. Non-preconditioned data from failure tests should be used for FE simulation of the elastic response of aneurysms. CA should not be used to obtain a mean response.

Failure properties of abdominal aortic aneurysm tissue are orientation dependent.

INTRODUCTION: Biomechanical rupture risk assessment of abdominal aortic aneurysm (AAA) requires information about failure properties of aneurysmal tissue. There are large differences between reported values. Among others, studies vary in using either axially or circumferentially oriented samples. This study investigates the effect of sample orientation on failure properties. METHODS: Aneurysmal tissues from 45 patients (11 females) were harvested during open AAA repair, cut into uniaxial samples (90) and tested mechanically within 3 h. If possible, the samples were cut in both axial (49 samples) and circumferential (41 samples) directions. Wall thickness, First Piola-Kirchhoff strength Pult and ultimate tension Tult were recorded. Influence of sample orientation and other clinical parameters were investigated using non parametric tests. RESULTS: Medians of Pult (values 1100 kPa for circumferential vs. 715 kPa for axial direction, p < 10-4) and Tult (17.4 N/cm in circumferential vs. 11.2 N/cm in axial direction, p < 10-4) were significantly higher in circumferential direction. For paired data, the median of difference was 411 kPa (p < 10-3) in Pult and 7.4 N/cm (p < 10-4) in Tult in favor of circumferential direction. CONCLUSIONS: In this first study of anisotropy in AAA wall failure properties using paired comparisons, the strength in circumferential orientation was found to be higher than in axial orientation.

Effect of testing conditions on the mechanical response of aortic tissues from planar biaxial experiments: Loading protocol and specimen side.

This study concerns procedural aspects of planar biaxial experiments on aortic tissues that have not been exhaustively addressed in the literature. The following questions are explored. First, is there a difference in the apparent mechanical properties if the experiments are conducted in a force-controlled regime or a displacement-controlled regime. Second, does it matter whether the deformations of the surface are tracked from one side of the tissue or the other (luminal vs. abluminal surface). The study provides answers to these questions with the help of a series of experiments on porcine aortic tissue, constitutive modelling and statistical analysis. It was found that the loading protocol does not substantially affect the constitutive response, while the surface orientation does.

Biomechanical indices are more sensitive than diameter in predicting rupture of asymptomatic abdominal aortic aneurysms.

OBJECTIVE: Several studies of biomechanical rupture risk assessment (BRRA) showed its advantage over the diameter criterion in rupture risk assessment of abdominal aortic aneurysm (AAA). However, BRRA studies have not investigated the predictability of biomechanical risk indices at different time points ahead of rupture, nor have they been performed blinded for biomechanical analysts. The objective of this study was to test the predictability of the BRRA method against diameter-based risk indices in a quasi-prospective patient cohort study. METHODS: In total, 12 women and 31 men with intact AAAs at baseline have been selected retrospectively at two medical centers. Within 56 months, 19 cases ruptured, whereas 24 cases remained intact within 2 to 56 months. This outcome was kept confidential until all biomechanical activities in this study were finished. The biomechanical AAA rupture risk was calculated at baseline using high-fidelity and low-fidelity finite element method models. The capability of biomechanics-based and diameter-based risk indices to predict the known outcomes at 1 month, 3 months, 6 months, 9 months, and 12 months after baseline was validated. Besides common cohort statistics, the area under the curve (AUC) of receiver operating characteristic curves has been used to grade the different rupture risk indices. RESULTS: Up to 9 months ahead of rupture, the receiver operating characteristic analysis of biomechanics-based risk indices showed a higher AUC than diameter-based indices. Six months ahead of rupture, the largest difference was observed with an AUC of 0.878 for the high-fidelity biomechanical risk index, 0.859 for the low-fidelity biomechanical risk index, 0.789 for the diameter, and 0.821 for the sex-adjusted diameter. In predictions beyond 9 months, none of the risk indices proved to be superior. CONCLUSIONS: High-fidelity biomechanical modeling improves the predictability of AAA rupture. Asymptomatic AAA patients with high biomechanical AAA rupture risk indices have an increased risk of rupture. Integrating biomechanics-based diagnostic indices may significantly decrease the false-positive rate in AAA treatment. CLINICAL RELEVANCE: Rupture of abdominal aortic aneurysm (AAA) is the tenth leading cause of death in men older than 60 years; however, the currently used maximal diameter criterion has a high false-positive rate. In this study, we have compared this criterion with biomechanical rupture risk assessment on the unique data set of 43 asymptomatic AAAs, of which 19 ruptured later. Moreover, the AAA outcome was blinded to the operator for the first time. Our data demonstrated that the biomechanical rupture risk assessment is superior to maximal diameter in predicting AAA rupture up to 9 months ahead and significantly decreases the false-positive rate.

Moderate thickness of lipid core in shoulder region of atherosclerotic plaque determines vulnerable plaque A parametric study.

Peak stress in the fibrous cap of atherosclerotic plaque is largely determined by the cap thickness which cannot be accurately estimated in vivo. This parametric study investigates idealized atherosclerotic plaque geometries. Finite element modeling is applied to search for larger morphological features associated with high cap stresses. By varying seven geometrical and two loading parameters, 100 3D model geometries of atherosclerotic plaques in common iliac artery were generated. In each model peak cap stress was calculated, and statistical comparison of the geometries generating the highest and lowest peak cap stresses was performed. The analysis showed that, compared to geometries generating the lowest stresses, those with high peak cap stress had a significantly lower cap thickness, higher stenosis ratio, lower relative lipid core volume, and cap shoulder radius larger than lipid core radius. High cap stress was observed for cap thicknesses up to 0.13 mm. It can be concluded that vulnerable plaques contain thin fibrous cap, large stenosis ratio and only moderate small-radius lipid core which reaches the shoulder region of the fibrous cap.

A simple method of incorporating the effect of the Uniform Stress Hypothesis in arterial wall stress computations.

PURPOSE: Residual stress has a great influence on the mechanical behaviour of arterial wall. Numerous research groups used the Uniform Stress Hypothesis to allow the inclusion of the effects of residual stress when computing stress distributions in the arterial wall. Nevertheless, the available methods used for this purpose are very computationally expensive, due to their iterative nature. In this paper we present a new method for including the effects of residual stress on the computed stress distribution in the arterial wall. METHODS: The new method, by using the Uniform Stress Hypothesis, enables computing the effect of residual stress by averaging stresses across the thickness of the arterial wall. RESULTS: Being a post-processing method for the computed stress distributions, the proposed method is computationally inexpensive, and thus, better suited for clinical applications than the previously used ones. CONCLUSIONS: The resulting stress distributions and values obtained using the proposed method based on the Uniform Stress Hypothesis are very close to the ones returned by an existing iterative method.

Predictive capabilities of various constitutive models for arterial tissue.

INTRODUCTION: Aim of this study is to validate some constitutive models by assessing their capabilities in describing and predicting uniaxial and biaxial behavior of porcine aortic tissue. METHODS: 14 samples from porcine aortas were used to perform 2 uniaxial and 5 biaxial tensile tests. Transversal strains were furthermore stored for uniaxial data. The experimental data were fitted by four constitutive models: Holzapfel-Gasser-Ogden model (HGO), model based on generalized structure tensor (GST), Four-Fiber-Family model (FFF) and Microfiber model. Fitting was performed to uniaxial and biaxial data sets separately and descriptive capabilities of the models were compared. Their predictive capabilities were assessed in two ways. Firstly each model was fitted to biaxial data and its accuracy (in term of R2 and NRMSE) in prediction of both uniaxial responses was evaluated. Then this procedure was performed conversely: each model was fitted to both uniaxial tests and its accuracy in prediction of 5 biaxial responses was observed. RESULTS: Descriptive capabilities of all models were excellent. In predicting uniaxial response from biaxial data, microfiber model was the most accurate while the other models showed also reasonable accuracy. Microfiber and FFF models were capable to reasonably predict biaxial responses from uniaxial data while HGO and GST models failed completely in this task. CONCLUSIONS: HGO and GST models are not capable to predict biaxial arterial wall behavior while FFF model is the most robust of the investigated constitutive models. Knowledge of transversal strains in uniaxial tests improves robustness of constitutive models.

Applicability of simplified computational models in prediction of peak wall stress in abdominal aortic aneurysms.

In the paper impact of different material models on the calculated peak wall stress (PWS) and peak wall rupture risk (PWRR) in abdominal aortic aneurysms (AAAs) is assessed. Computational finite element models of 70 patient-specific AAAs were created using two different material models - a realistic one based on mean population results of uniaxial tests of AAA wall considered as reference, and a 100 times stiffer artificial model. The calculated results of PWS and PWRR were tested to evaluate statistical significance of differences caused by the non-realistic material model. It was shown that for majority of AAAs the differences are insignificant but for some 10% of them their relative differences exceed 20% which may lead to incorrect decisions on their surgical treatment. This percentage of failures favours application of realistic material models in clinical practise although they are much more time-consuming.

Correlation between transversal and orthogonal maximal diameters of abdominal aortic aneurysms and alternative rupture risk predictors.

PURPOSE: There is no standard for measuring maximal diameter (Dmax) of abdominal aortic aneurysm (AAA) from computer tomography (CT) images although differences between Dmax evaluated from transversal (axialDmax) or orthogonal (orthoDmax) planes can be large especially for angulated AAAs. Therefore we investigated their correlations with alternative rupture risk indicators as peak wall stress (PWS) and peak wall rupture risk (PWRR) to decide which Dmax is more relevant in AAA rupture risk assessment. MATERIAL AND METHODS: The Dmax values were measured by a trained radiologist from 70 collected CT scans, and the corresponding PWS and PWRR were evaluated using Finite Element Analysis (FEA). The cohort was ordered according to the difference between axialDmax and orthoDmax (Da-o) quantifying the aneurysm angulation, and Spearman's correlation coefficients between PWS/PWRR - orthoDmax/axialDmax were calculated. RESULTS: The calculated correlations PWS/PWRR vs. orthoDmax were substantially higher for angulated AAAs (with Da-o≥3mm). Under this limit, the correlations were almost the same for both Dmax values. Analysis of AAAs divided into two groups of angulated (n=38) and straight (n=32) cases revealed that both groups are similar in all parameters (orthoDmax, PWS, PWRR) with the exception of axialDmax (p=0.024). CONCLUSIONS: It was confirmed that orthoDmax is better correlated with the alternative rupture risk predictors PWS and PWRR for angulated AAAs (DA-O≥3mm) while there is no difference between orthoDmax and axialDmax for straight AAAs (DA-O<3mm). As angulated AAAs represent a significant portion of cases it can be recommended to use orthoDmax as the only Dmax parameter for AAA rupture risk assessment.