Nikhil Sindhwani1,2, Andrew Feola1,2, Frederik De Keyzer3, Filip Claus3, Geertje Callewaert1,2, Iva Urbankova1,2, Sebastien Ourselin4, Jan D'hooge5, Jan Deprest6,7,8. 1. Department of Development and Regeneration, Cluster Organ Systems, Faculty of Medicine, KU, Leuven, Leuven, Belgium. 2. Interdepartmental Center for Surgical Technologies, Faculty of Medicine, KU Leuven, Leuven, Belgium. 3. Department of Radiology, University Hospitals Leuven, Leuven, Belgium. 4. Centre for Medical Image Computing (CMIC), University College London, London, UK. 5. Laboratory on Cardiovascular Imaging and Dynamics, Department of Cardiovascular Sciences, Faculty of Medicine, KU Leuven, Leuven, Belgium. 6. Department of Development and Regeneration, Cluster Organ Systems, Faculty of Medicine, KU, Leuven, Leuven, Belgium. Jan.Deprest@uzleuven.be. 7. Pelvic Floor Unit, University Hospitals Leuven, Leuven, Belgium. Jan.Deprest@uzleuven.be. 8. Department of Obstetrics and Gynaecology, University Hospitals, KU Leuven, Leuven, 3000, Belgium. Jan.Deprest@uzleuven.be.
Abstract
OBJECTIVE: Our primary objective was to develop relevant algorithms for quantification of mesh position and 3D shape in magnetic resonance (MR) images. METHODS: In this proof-of-principle study, one patient with severe anterior vaginal wall prolapse was implanted with an MR-visible mesh. High-resolution MR images of the pelvis were acquired 6 weeks and 8 months postsurgery. 3D models were created using semiautomatic segmentation techniques. Conformational changes were recorded quantitatively using part-comparison analysis. An ellipticity measure is proposed to record longitudinal conformational changes in the mesh arms. The surface that is the effective reinforcement provided by the mesh is calculated using a novel methodology. The area of this surface is the effective support area (ESA). RESULTS: MR-visible mesh was clearly outlined in the images, which allowed us to longitudinally quantify mesh configuration between 6 weeks and 8 months after implantation. No significant changes were found in mesh position, effective support area, conformation of the mesh's main body, and arm length during the period of observation. Ellipticity profiles show longitudinal conformational changes in posterior arms. CONCLUSIONS: This paper proposes novel methodologies for a systematic 3D assessment of the position and morphology of MR-visible meshes. A novel semiautomatic tool was developed to calculate the effective area of support provided by the mesh, a potentially clinically important parameter.
OBJECTIVE: Our primary objective was to develop relevant algorithms for quantification of mesh position and 3D shape in magnetic resonance (MR) images. METHODS: In this proof-of-principle study, one patient with severe anterior vaginal wall prolapse was implanted with an MR-visible mesh. High-resolution MR images of the pelvis were acquired 6 weeks and 8 months postsurgery. 3D models were created using semiautomatic segmentation techniques. Conformational changes were recorded quantitatively using part-comparison analysis. An ellipticity measure is proposed to record longitudinal conformational changes in the mesh arms. The surface that is the effective reinforcement provided by the mesh is calculated using a novel methodology. The area of this surface is the effective support area (ESA). RESULTS: MR-visible mesh was clearly outlined in the images, which allowed us to longitudinally quantify mesh configuration between 6 weeks and 8 months after implantation. No significant changes were found in mesh position, effective support area, conformation of the mesh's main body, and arm length during the period of observation. Ellipticity profiles show longitudinal conformational changes in posterior arms. CONCLUSIONS: This paper proposes novel methodologies for a systematic 3D assessment of the position and morphology of MR-visible meshes. A novel semiautomatic tool was developed to calculate the effective area of support provided by the mesh, a potentially clinically important parameter.
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