RESUMO
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.
Assuntos
Colágeno/metabolismo , Tendão do Calcâneo/metabolismo , Algoritmos , Animais , Matriz Extracelular/metabolismo , Processamento de Imagem Assistida por Computador/métodos , Microscopia/métodos , Microscopia de Polarização/métodos , Imagem Óptica/métodos , SuínosRESUMO
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.
Assuntos
Aneurisma da Aorta Abdominal/epidemiologia , Aneurisma da Aorta Abdominal/fisiopatologia , Ruptura Aórtica/epidemiologia , Ruptura Aórtica/fisiopatologia , Medição de Risco/métodos , Idoso , Idoso de 80 Anos ou mais , Aneurisma da Aorta Abdominal/diagnóstico , Ruptura Aórtica/diagnóstico , Doenças Assintomáticas , Fenômenos Biomecânicos , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Estudos Retrospectivos , Sensibilidade e EspecificidadeRESUMO
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 0.13â¯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.
Assuntos
Metabolismo dos Lipídeos , Modelos Biológicos , Placa Aterosclerótica/metabolismo , Placa Aterosclerótica/patologia , Ombro , Análise de Elementos Finitos , Estresse MecânicoRESUMO
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.
Assuntos
Aorta Abdominal/fisiopatologia , Aneurisma da Aorta Abdominal/fisiopatologia , Simulação por Computador , Modelos Cardiovasculares , Idoso , Idoso de 80 Anos ou mais , Aneurisma da Aorta Abdominal/cirurgia , Fenômenos Biomecânicos , Feminino , Análise de Elementos Finitos , Hemodinâmica , Humanos , Masculino , Estresse MecânicoRESUMO
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.
Assuntos
Aneurisma Roto/diagnóstico por imagem , Aneurisma Roto/epidemiologia , Aorta Abdominal/diagnóstico por imagem , Aneurisma da Aorta Abdominal/diagnóstico por imagem , Aneurisma da Aorta Abdominal/epidemiologia , Angiografia por Tomografia Computadorizada/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Aneurisma Roto/fisiopatologia , Aneurisma da Aorta Abdominal/fisiopatologia , Angiografia por Tomografia Computadorizada/estatística & dados numéricos , Simulação por Computador , República Tcheca/epidemiologia , Humanos , Modelos Cardiovasculares , Prevalência , Reprodutibilidade dos Testes , Medição de Risco/métodos , Sensibilidade e Especificidade , Estatística como AssuntoRESUMO
Mechanical properties of the arterial wall depend largely on orientation and density of collagen fiber bundles. Several methods have been developed for observation of collagen orientation and density; the most frequently applied collagen-specific manual approach is based on polarized light (PL). However, it is very time consuming and the results are operator dependent. We have proposed a new automated method for evaluation of collagen fiber direction from two-dimensional polarized light microscopy images (2D PLM). The algorithm has been verified against artificial images and validated against manual measurements. Finally the collagen content has been estimated. The proposed algorithm was capable of estimating orientation of some 35 k points in 15 min when applied to aortic tissue and over 500 k points in 35 min for Achilles tendon. The average angular disagreement between each operator and the algorithm was -9.3±8.6° and -3.8±8.6° in the case of aortic tissue and -1.6±6.4° and 2.6±7.8° for Achilles tendon. Estimated mean collagen content was 30.3±5.8% and 94.3±2.7% for aortic media and Achilles tendon, respectively. The proposed automated approach is operator independent and several orders faster than manual measurements and therefore has the potential to replace manual measurements of collagen orientation via PLM.