Visualization of myocardial strain pattern uniqueness with respect to activation time and contractility : a computational study

Kirn, Borut (author)

Speckle tracking echography is used to measure myocardial strain patterns in order to assess the state of myocardial tissue. Because electro-mechanical coupling in myocardial tissue is complex and nonlinear, and because of the measurement errors the uniqueness of strain patterns is questionable. In this study, the uniqueness of strain patterns was visualized in order to revel characteristics that may improve their interpretation. A computational model of sarcomere mechanics was used to generate a database of 1681 strain patterns, each simulated with a different set of sarcomere parameters: time of activation (TA) and contractility (Con). TA and Con ranged from -100 ms to 100 ms and 2% to 202% in 41 steps respectively, thus forming a two-dimensional 41 x 41 parameter space. Uniqueness of the strain pattern was assessed by using a cohort of similar strain patterns defined by a measurement error. The cohort members were then visualized in the parameter space. Each cohort formed one connected component (or blob) in the parameter space; however, large differences in the shape, size, and eccentricity of the blobs were found for different regions in the parameter space. The blobs were elongated along the TA direction (±50 ms) when contractility was low, and along the Con direction (±50%) when contractility was high. The uniqueness of the strain patterns can be assessed and visualized in the parameter space. The strain patterns in the studied database are not degenerated because a cohort of similar strain patterns forms only one connected blob in the parameter space. However, the elongation of the blobs means that estimations of TA when contractility is low and of Con when contractility is high have high uncertainty.

• Language: English
• Keywords: myocard, tissue properties, computational modeling, signal uniqueness, visualization, myocardial strain, synthetic data
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: MF - Faculty of Medicine
• Publication status: Published
• Publication version: Version of Record
• Year: 2019
• Number of pages: 7 str.
• Numbering: Vol. 4, iss. 2, art. 79
• PID: 20.500.12556/RUL-132251
• UDC: 616.1
• ISSN on article: 2306-5729
• DOI: 10.3390/data4020079
• COBISS.SI-ID: 34337241
• Publication date in RUL: 19.10.2021

Record is a part of a journal

• Title: Data
• Shortened title: Data
• Publisher: MDPI AG
• ISSN: 2306-5729
• COBISS.SI-ID: 526325273

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 01.06.2019

Secondary language

• Language: Slovenian
• Keywords: miokard, lastnosti tkiva, računalniško modeliranje