BioMedical Engineering OnLine (May 2019)
A novel vision-based system for quantitative analysis of abdominal aortic aneurysm deformation
Abstract
Abstract Background In clinical diagnostics, combination of different imaging techniques is applied to assess spatial configuration of the abdominal aortic aneurysm (AAA) and deformation of its wall. As deformation of aneurysm wall is crucial parameter in assessing wall rupture, we aimed to develop and validate a Non-Invasive Vision-Based System (NIVBS) for the analysis of 3D elastic artificial abdominal aortic models. 3D-printed elastic AAA models from four patients were applied for the reconstruction of real hemodynamic. During experiments, the inlet boundary conditions included the injection volume and frequency of pulsation averaged from electrocardiography traces. NIVBS system was equipped with nine cameras placed at a constant distance to record wall movement from 360o angle and a dedicated set of artificial lights providing coherent illumination. Additionally, self-prepared algorithms for image acquisition, processing, segmentation, and contour detection were used to analyze wall deformation. Finally, the shape deformation factor was applied to evaluate aorta’s deformation. Experimental results were confronted with medical data from AngioCT and 2D speckle-tracking echocardiography (2DSTE). Results Image square analyses indicated that the optimal distance between the camera’s lens and the investigated object was in the range of 0.30–0.35 m. There was approximately 1.44% difference observed in aneurysm diameters between NIVBS (86.57 ± 5.86 mm) and AngioCT (87.82 ± 6.04 mm) (p = 0.7764). The accuracy of developed algorithm for the reconstruction of the AAA deformation was equal to 98.56%. Bland–Altman analysis showed that the difference between clinical data (2DSTE) and predicted wall deformation (NIVBS) for all patients was 0.00 mm (confidence interval equal to 0.12 mm) for aneurysm size, 0.01 mm (confidence interval equal to 0.13 mm) and 0.00 mm (confidence interval equal to 0.09 mm) for the anterior and posterior side, as well as 0.01 mm (confidence interval equal to 0.18 mm) and 0.01 mm (confidence interval equal to 0.11 mm) for the left and right side. The optimal range of camera’s lens did not affect acquired values. Conclusions The NIVBS with proposed algorithm that reconstructs the pressure from surrounding organs is appropriate to analyze the AAAs in water environment. Moreover, NIVBS allowed detailed quantitative analysis of aneurysm sac wall deformation.
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