MATLAB Toolbox For Analysis Research Articles

Four-dimensional Ultrasound for Characterization of In Vivo Murine Aortic Valve Dynamics

Objective: Aortic valve (AoV) disease affects up to 5% of Americans over 65 years age. While AoV disease is frequently diagnosed using 3D transesophageal echocardiography, these same methods are not available for small animals, hindering the ability to track disease progression. A recently developed small animal imaging technique, four-dimensional ultrasound (4DUS), has opened the possibility of direct AoV visualization in mice. Methods: Data Acquisition: 4DUS imaging (Vevo 3100; FUJIFILM VisualSonics) was performed on the AoVs of 16 C57BL/6J mice, consisting of ten wild-type (n=5 each, male and female, 3 months old), and three osteogenesis imperfecta mice with three littermate controls (12 months old). Data Analysis: AoV data was loaded into a custom MATLAB toolbox for analysis. Data was oriented orthogonal to the aortic annulus, stabilized against intra-thoracic motion, and boundary-tracked using discrete points along both the AoV wall and the leaflet free edge. Results: This method allows for volumetric visualization of the valve across the cardiac cycle, shown here in open (Figure 1B) and closed (1C) states. Analysis-derived surfaces composing the three AoV leaflets are extracted and provide 3D visualizations of leaflet dynamics, as shown in the open (Figure 1D) and closed (1E) states with calculated displacement from end-diastole overlaid. Peak average displacements of each leaflet in the mouse displayed here were RCC: 0.38mm (yellow star), LCC: 0.35mm, and NCC: 0.31mm. Conclusions: We demonstrate the ability to reliably capture gated, volumetric in vivo data of the murine AoV, which were previously only reported through 1D and 2D measures. The technique detailed here allows for robust assessment of leaflet dynamics in 3D, thus providing a foundation for longitudinal characterization of murine models of aortic valve disease.

Update (1.1) to ANDURIL — A MATLAB toolbox for ANalysis and Decisions with UnceRtaInty: Learning from expert judgments: ANDURYL

This is an update to PII: S2352711018300608In this paper, we discuss ANDURYL, which is a Python-based open source successor of the MATLAB toolbox ANDURIL. The output of ANDURYL is in good agreement with the results obtained from ANDURIL and EXCALIBUR. Additional features available in ANDURYL, and not available in its predecessors, are discussed.