Myocardial strain computed at multiple spatial scales from tagged magnetic resonance imaging: Estimating cardiac biomarkers for CRT patients

Matthew Sinclair, Devis Peressutti, Esther Puyol-Antón, Wenjia Bai, Simone Rivolo, Jessica Webb, Simon Claridge, Thomas Jackson, David Nordsletten, Myrianthi Hadjicharalambous, Eric Kerfoot, Christopher A. Rinaldi, Daniel Rueckert, Andrew P. King

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Abnormal cardiac motion can indicate different forms of disease, which can manifest at different spatial scales in the myocardium. Many studies have sought to characterise particular motion abnormalities associated with specific diseases, and to utilise motion information to improve diagnoses. However, the importance of spatial scale in the analysis of cardiac deformation has not been extensively investigated. We build on recent work on the analysis of myocardial strains at different spatial scales using a cardiac motion atlas to find the optimal scales for estimating different cardiac biomarkers. We apply a multi-scale strain analysis to a 43 patient cohort of cardiac resynchronisation therapy (CRT) patients using tagged magnetic resonance imaging data for (1) predicting response to CRT, (2) identifying septal flash, (3) estimating QRS duration, and (4) identifying the presence of ischaemia. A repeated, stratified cross-validation is used to demonstrate the importance of spatial scale in our analysis, revealing different optimal spatial scales for the estimation of different biomarkers.

Original languageEnglish
Pages (from-to)1339-1351
Number of pages13
JournalMedical Image Analysis
Volume43
DOIs
StatePublished - Jan 2018
Externally publishedYes

Keywords

  • Cardiac motion atlas
  • Cardiac resynchronisation therapy
  • Multi-scale strain

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