Thickness of the left atrial wall surrounding the left atrial appendage orifice

Słodowska, Katarzyna; Hołda, Jakub; Dudkiewicz, Damian; Malinowska, Karolina; Bolechała, Filip; Kopacz, Paweł; Koziej, Mateusz

doi:10.1111/jce.15157

Cited by 11 publications

(6 citation statements)

References 38 publications

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“…The inner shell corresponded to the initial segmentation. The outer shell had an offset of 2 mm to the inner shell, comparable to the reported thickness of the LAA [21,22]. The cast model was 3D printed using PLA filament.…”

Section: Silicone Models Of the Left Atrial Appendagementioning

confidence: 79%

MRI-based training model for left atrial appendage closure

et al. 2023

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Purpose Percutaneous closure of the left atrial appendage (LAA) reduces the risk of embolic stroke in patients with atrial fibrillation. Thereby, the optimal transseptal puncture (TSP) site differs due to the highly variable anatomical shape of the LAA, which is rarely considered in existing training models. Based on non-contrast-enhanced magnetic resonance imaging (MRI) volumes, we propose a training model for LAA closure with interchangeable and patient-specific LAA enabling LAA-specific identification of the TSP site best suited. Methods Based on patient-specific MRI data, silicone models of the LAAs were produced using a 3D-printed cast model. In addition, an MRI-derived 3D-printed base model was set up, including the right and left atrium with predefined passages in the septum, mimicking multiple TSP sites. The various silicone models and a tube mimicking venous access were connected to the base model. Empirical use of the model allowed the demonstration of its usability. Results Patient-specific silicone models of the LAA could be generated from all LAA patient MRI datasets. The influence of various combinations regarding TSP sites and LAA shapes could be demonstrated as well as the technical functionality of the occluder system. Via the attached tube mimicking the venous access, the correct handling of the deployment catheter even in case of not optimal puncture site could be practiced. Conclusion The proposed contrast-agent and radiation-free MRI-based training model for percutaneous LAA closure enables the pre-interventional assessment of the influence of the TSP site on the access of patient-specific LAA shapes. A straightforward replication of this work is measured by using clinically available imaging protocols and a widespread 3D printer technique to build the model.

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Section: Silicone Models Of the Left Atrial Appendagementioning

confidence: 79%

MRI-based training model for left atrial appendage closure

et al. 2023

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“…Although the LAA anatomy appears thoroughly known (Dudkiewicz et al, 2021; Roberts et al, 2019; Slodowska et al, 2022; Słodowska, Hołda, et al, 2021; Słodowska, Szczepanek, et al, 2021), the LAA neck has not been well defined or explored. The growing clinical importance of the LAA as a common source of thrombus formation and the introduction of various LAA exclusion techniques into daily clinical practice forced us to provide a detailed morphological description of the most proximal part of the LAA—the neck region (Naksuk et al, 2016; Słodowska, Szczepanek, et al, 2021; Whiteman et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Definition and anatomical description of the left atrial appendage neck

Batko,

Jakiel,

Krawczyk–Ożóg

et al. 2023

Clinical Anatomy

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The left atrial appendage (LAA) is well known as a source of cardiac thrombus formation. Despite its clinical importance, the LAA neck is still anatomically poorly defined. Therefore, this study aimed to define the LAA neck and determine its morphometric characteristics. We performed three‐dimensional reconstructions of the heart chambers based on contrast‐enhanced electrocardiography–gated computed tomography scans of 200 patients (47% females, 66.5 ± 13.6 years old). The LAA neck was defined as a truncated cone‐shaped canal bounded proximally by the LAA orifice and distally by the lobe origin and was present in 98.0% of cases. The central axis of the LAA neck was 14.7 ± 2.3 mm. The mean area of the LAA neck walls was 856.6 ± 316.7 mm2. The LAA neck can be divided into aortic, arterial (the smallest), venous (the largest), and free surfaces. All areas have a trapezoidal shape with a broader proximal base. There were no statistically significant differences in the morphometric characteristics of the LAA neck between LAA types. Statistically significant differences between the sexes in the main morphometric parameters of the LAA neck were found in the central axis length and the LAA neck wall area. The LAA neck can be evaluated from computed tomography scans and their three‐dimensional reconstructions. The current study provides a complex morphometric analysis of the LAA neck. The precise definition and morphometric details of the LAA neck presented in this study may influence the effectiveness and safety of LAA exclusion procedures.

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“…We reported the 3D AWT of 20 patients with AF with an error of <10% when compared with the manual WT measurements. However, the relatively high error observed between the left PV and LAA junction was a reasonable difference considering the morphology of the most complex LAA in the LA geometry [28] and the variability of the AWT in the anterior and posterior regions of the left PV [29,30]. Another potential cause for the high error percentage could be the presence of a poor segmentation between the left PV and LAA due to the practical limitations of cross-sectional imaging [31] and the subjectivity of manual segmentation.…”

Section: B Atrial Wall Thickness Measurementsmentioning

confidence: 97%

Three-Dimensional Atrial Wall Thickness Measurement Algorithm From a Segmented Atrial Wall Using a Partial Differential Equation

et al. 2022

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Despite advancements in high-precision segmentation technology for computed tomographic angiography (CTA)-based cardiac wall segmentation, the accurate detection of the endocardial (Endo) and epicardial (Epi) boundaries remains a prerequisite for automated measurements of the cardiac wall thickness (WT). We proposed a novel algorithm for automated three-dimensional (3D) atrial WT (AWT) measurements, including an automatic Endo-Epi boundary detection. We detected the boundaries that were topologically indistinguishable due to an open geometry at the anatomical boundaries using the combined Convex hull and Poisson solver methods. The Laplace equation for the WT measurement was solved by a partial differential equation combining the two detected boundaries of the myocardial wall. We verified the robustness of our algorithm in mask images of the atrial wall that were separated from the CTA images of 20 patients and a phantom model. The accuracy of the automatically detected Endo-Epi boundaries was acceptable as compared to that manually extracted from the phantom model (Dice coefficient=0.979). The 3D AWTs calculated by the novel automated method from the CTA images obtained from 20 patients with atrial fibrillation had <10% error as compared to the conventional manual AWT measurement method for comparing the regional WT in all locations except the left antral area. The proposed algorithm's AWT detection time was 27.15±6.99 s per patient, which was 1/40 that of the conventional method. Consequently, our results showed that the proposed automatic 3D AWT measurement algorithm had the potential to significantly improve the efficiency of calculating the AWT while maintaining the existing level of accuracy.INDEX TERMS Atrial fibrillation, atrial wall thickness, computed tomography, partial differential equation.

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Thickness of the left atrial wall surrounding the left atrial appendage orifice

Abstract: Introduction: The aim of this study was to investigate the thickness of the left atrial wall surrounding the left atrial appendage (LAA) orifice.

Cited by 11 publications

References 38 publications

MRI-based training model for left atrial appendage closure

MRI-based training model for left atrial appendage closure

Definition and anatomical description of the left atrial appendage neck

Three-Dimensional Atrial Wall Thickness Measurement Algorithm From a Segmented Atrial Wall Using a Partial Differential Equation

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