Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms

Shum, Judy; DiMartino, E.; Goldhammer, Adam; Goldman, Daniel; Acker, Leah; Patel, Gopal; Ng, Julie H.; Martufi, Giampaolo; Finol, Ender A.

doi:10.1118/1.3284976

Cited by 75 publications

(74 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The mean diameter was 52.36 mm with a standard deviation 1.49 mm, average pixel size of 0.7781 mm, and the mode value of slice spacing 3.0 mm. CT images between the renal arteries and approximately 3 inches distal to the iliac bifurcation were segmented using our in-house MATLAB code VESSEG [15], shown schematically in Fig. 1.…”

Section: Image Segmentationmentioning

confidence: 99%

“…To that end, Martufi et al [14] reported the validation of a set of MATLAB routines for estimating regional vessel wall thickness from CT images by comparing it with postmortem AAA tissue measurements [11], resulting in an average relative difference of 7.8%. A framework for semiautomatic vessel wall detection and quantification of thickness using contrastenhanced CT images was described by Shum et al [15], resulting in low repeatability and reproducibility errors when compared to the manual segmentations performed by trained vascular surgeons. Quantitative assessment of AAA geometry [16] has shown promising results, with wall thickness being one of the morphological indicators significant for rupture risk stratification.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

Raut

Jana

Oliveira

et al. 2013

Journal of Biomechanical Engineering

Self Cite

View full text Add to dashboard Cite

Abdominal aortic aneurysm (AAA) is a vascular condition where the use of a biomechanics-based assessment for patient-specific risk assessment is a promising approach for clinical management of the disease. Among various factors that affect such assessment, AAA wall thickness is expected to be an important factor. However, regionally varying patient-specific wall thickness has not been incorporated as a modeling feature in AAA biomechanics. To the best our knowledge, the present work is the first to incorporate patient-specific variable wall thickness without an underlying empirical assumption on its distribution for AAA wall mechanics estimation. In this work, we present a novel method for incorporating regionally varying wall thickness (the "PSNUT" modeling strategy) in AAA finite element modeling and the application of this method to a diameter-matched cohort of 28 AAA geometries to assess differences in wall mechanics originating from the conventional assumption of a uniform wall thickness. For the latter, we used both a literature-derived population average wall thickness (1.5 mm; the "UT" strategy) as well as the spatial average of our patient-specific variable wall thickness (the "PSUT" strategy). For the three different wall thickness modeling strategies, wall mechanics were assessed by four biomechanical parameters: the spatial maxima of the first principal stress, strain, strain-energy density, and displacement. A statistical analysis was performed to address the hypothesis that the use of any uniform wall thickness model resulted in significantly different biomechanical parameters compared to a patient-specific regionally varying wall thickness model. Statistically significant differences were obtained with the UT modeling strategy compared to the PSNUT strategy for the spatial maxima of the first principal stress (p ¼ 0.002), strain (p ¼ 0.0005), and strain-energy density (p ¼ 7.83 e-5) but not for displacement (p ¼ 0.773). Likewise, significant differences were obtained comparing the PSUT modeling strategy with the PSNUT strategy for the spatial maxima of the first principal stress (p ¼ 9.68 e-7), strain (p ¼ 1.03 e-8), strain-energy density (p ¼ 9.94 e-8), and displacement (p ¼ 0.0059). No significant differences were obtained comparing the UT and PSUT strategies for the spatial maxima of the first principal stress (p ¼ 0.285), strain (p ¼ 0.152), strain-energy density (p ¼ 0.222), and displacement (p ¼ 0.0981). This work strongly recommends the use of patient-specific regionally varying wall thickness derived from the segmentation of abdominal computed tomography (CT) scans if the AAA finite element analysis is focused on estimating peak biomechanical parameters, such as stress, strain, and strain-energy density.

show abstract

Section: Image Segmentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

Raut

Jana

Oliveira

et al. 2013

Journal of Biomechanical Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…The thickness of the AAA wall is nonuniform [49][50][51], influenced by many factors [52], and may [53] or may not [54] change between ruptured and [17], indicating regions at higher risk of rupture, while thin-walled areas could be exposed to high wall stress and be at high risk for rupture. Biomechanical AAA studies report different average population thicknesses (see Table 2, which may be explained by fundamentally different measurement methods and the difficulty specifying the outer border of the adventitia.…”

Section: Aaa Wall Thicknessmentioning

confidence: 99%

Biomechanical Rupture Risk Assessment - A consistent and objective decision-making tool for Abdominal Aortic Aneurysm patients

Gasser¹

2016

aorta

View full text Add to dashboard Cite

Abdominal aortic aneurysm (AAA) rupture is a local event in the aneurysm wall that naturally demands tools to assess the risk for local wall rupture. Consequently, global parameters like the maximum diameter and its expansion over time can only give very rough risk indications; therefore, they frequently fail to predict individual risk for AAA rupture. In contrast, the Biomechanical Rupture Risk Assessment (BRRA) method investigates the wall's risk for local rupture by quantitatively integrating many known AAA rupture risk factors like female sex, large relative expansion, intraluminal thrombus-related wall weakening, and high blood pressure. The BRRA method is almost 20 years old and has progressed considerably in recent years, it can now potentially enrich the diameter indication for AAA repair. The present paper reviews the current state of the BRRA method by summarizing its key underlying concepts (i.e., geometry modeling, biomechanical simulation, and result interpretation). Specifically, the validity of the underlying model assumptions is critically disused in relation to the intended simulation objective (i.e., a clinical AAA rupture risk assessment). Next, reported clinical BRRA validation studies are summarized, and their clinical relevance is reviewed. The BRRA method is a generic, biomecha nics-based approach that provides several interfaces to incorporate information from different research disciplines. As an example, the final section of this review suggests integrating growth aspects to (potentially) further improve BRRA sensitivity and specificity. Despite the fact that no prospective validation studies are reported, a significant and still growing body of validation evidence suggests integrating the BRRA method into the clinical decision-making process (i.e., enriching diameterbased decision-making in AAA patient treatment). Problem DefinitionAbdominal aortic aneurysm (AAA) disease is a serious condition and causes many deaths, especially in males over 65 years. Progressive treatment (i.e., surgical or endovascular AAA repair) cannot be offered to all patients, and according to the best clinical practice, AAA repair is indicated if rupture risk exceeds the interventional risks. While center-specific treatment risks are reasonably predictable, assessing AAA rupture risk for individual patients remains the bottleneck in clinical decision making. However, an accurate rupture risk assessment is critical to reduce aneurysm-related mortality without substantially increasing the rate of AAA repair.According to the current clinical practice, AAA rupture risk is assessed by the aneurysm's largest

show abstract

“…The authors notice, however, that the result obtained need to be checked against image collections coming from different CT scanners and recorded with different layer thicknesses. When analysing other articles regarding aorta segmentation, it can be seen that attempts to segment automatically, described earlier, were abandoned in favour of semi-automatic segmentation with operator input ( [5,6]). An exhaustive presentation of various approaches to the segmentation of the abdominal aorta can be found in [14].…”

Section: When Analysing Work By Researchers From Universitymentioning

confidence: 99%

Semi-Automatic Segmentation of Ct/Mri Images Based on Active Contour Method for 3D Reconstruction of Abdominal Aortic Aneurysms

Drapikowski

Domagała

2014

Image Processing &Amp; Communications

View full text Add to dashboard Cite

show abstract

Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms

Abstract: While further refinement is needed to fully automate the outer wall segmentation algorithm, these preliminary results demonstrate the method's adequate reproducibility and low interobserver variability.

Cited by 75 publications

References 28 publications

The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

The Importance of Patient-Specific Regionally Varying Wall Thickness in Abdominal Aortic Aneurysm Biomechanics

Biomechanical Rupture Risk Assessment - A consistent and objective decision-making tool for Abdominal Aortic Aneurysm patients

Semi-Automatic Segmentation of Ct/Mri Images Based on Active Contour Method for 3D Reconstruction of Abdominal Aortic Aneurysms

Contact Info

Product

Resources

About