Search

ABSTRACTThe morphological assessment of the geometry and the deformation of the mitral annulus has the potential to support the development of minimally invasive solutions for patients suffering from mitral valve regurgitation. Cardiac 4D-CT allows such a morphological assessment, which is, however, often performed manually, by annotating the mitral annulus and other cardiac landmarks. The goal of this study is to automate the annotation of cardiac landmarks in 4D-CT by propagating them from one reference phase to all others. The method proposed is based on non-rigid image registration, and four alternative variations have been tested, based on pairwise and groupwise registration. Their accuracy is evaluated against inter-observer variability on eight 4D-CTs. The results show that the pairwise and groupwise approaches using independent 3D transforms have a comparable performance, with an accuracy comparable with the inter-observer variability; however, the latter approach was computationally more expensive. Instead, the spatio-temporal groupwise approach obtained significantly worse results. The technology has, therefore, the potential to make an efficient analysis of the deforming heart more attainable. Moreover, the manual annotation process confirms that the mitral annulus deforms significantly during the cardiac contraction, supporting the use of 4D imaging for a reliable morphological assessment.

ABSTRACTMitral valve disease is a commonly occurring pathology and its incidence is expected to rise in the coming decades. This has led to an increase in the number and complexity of computational models developed to characterize the mitral valve behaviour, resulting in the need for automated segmentation methods. In this study, we evaluated the suitability of particle systems for segmenting the mitral valve leaflets from 3D TOE images, for both systolic and diastolic phases. With a mean error of 0.77 ± 0.4 mm, our approach results in accurate medial surface representations of the mitral valve. Additionally, we investigated the correlation between particle strength and leaflet thickness. Although a thorough analysis is still required to fully establish this relation, our preliminary results, with a mean RMS error of 0.99 ± 0.27 mm, show that leaflet thickness can be linked to particle strength. We anticipate that particle systems can be of high relevance for the generation of realistic patient-specific computational models, contributing to the development of adequate treatment strategies for mitral valve patients.