Optimising approximate entropy for assessing cardiac dyssynchrony with radionuclide ventriculography. (July 2021)

• Record Type: Journal Article
• Authors: Jones, K.A.; Paterson, C.A.; Hamilton, D.J.; Small, A.D.; Martin, W.; Robinson, J.; Goodfield, N.E.R.
• Is Part Of: Biomedical signal processing and control. Volume 68(2021)
• Publication Date: 2021-07
• Subjects: Approximate entropy -- RNVG phase -- Cardiac dyssynchrony; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102703
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract: Left ventricular dyssynchrony can be assessed with phase parameters from radionuclide ventriculography (RNVG), including approximate entropy ( ApEn ). The input values used to calculate ApEn will affect the results significantly, so it is essential to optimise ApEn for the application. However to date, no optimisation for ApEn applied to images has been published. In this paper, generated data were used to simulate patient phase images, allowing the input parameters for ApEn to be tested and optimised in a controlled environment. Clinical images were then used to confirm that the selected parameters were appropriate. The results demonstrate the effect of input parameters for ApEn and the most appropriate use with RNVG phase images. This work demonstrates the importance of optimisation and standardisation when using ApEn as a measure of dyssynchrony.