Background: Progression of aortic valve calcifications (AVC) leads to aortic valve stenosis (AS). Importantly, the AVC degree has a great impact on AS progression, treatment selection and outcomes. Methods of AVC assessment do not provide accurate quantitative evaluation and analysis of calcium distribution and deposition in a repetitive manner.
Objective: We aim to prepare a reliable tool for detailed AVC pattern analysis with quantitative parameters.
Methods: We analyzed computed tomography (CT) scans of fifty patients with severe AS using a dedicated software based on MATLAB version R2017a (MathWorks, Natick, MA, USA) and ImageJ version 1.51 (NIH, USA) with the BoneJ plugin version 1.4.2 with a self-developed algorithm.
Results: We listed unique parameters describing AVC and prepared 3D AVC models with color pointed calcium layer thickness in the stenotic aortic valve. These parameters were derived from CT-images in a semi-automated and repeatable manner. They were divided into morphometric, topological and textural parameters and may yield crucial information about the anatomy of the stenotic aortic valve.
Conclusion: In our study, we were able to obtain and define quantitative parameters for calcium assessment of the degenerated aortic valves. Whether the defined parameters are able to predict potential long-term outcomes after treatment, requires further investigation.
[http://dx.doi.org/10.5114/aic.2018.74359] [PMID: 29743908]
[http://dx.doi.org/10.1186/s13244-019-0764-0] [PMID: 31468205]
[http://dx.doi.org/10.1093/eurheartj/ehz127] [PMID: 30977787]
[http://dx.doi.org/10.23736/S0026-4725.18.04793-X] [PMID: 30226030]