Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging: Estimating Cardiac Biomarkers for CRT Patients

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

doi:10.1016/j.media.2017.10.004

Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging: Estimating Cardiac Biomarkers for CRT Patients

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

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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 language	English
Pages (from-to)	1339-1351
Journal	Medical Image Analysis
Volume	43
Early online date	31 Oct 2017
DOIs	https://doi.org/10.1016/j.media.2017.10.004
Publication status	Published - Jan 2018

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Myocardial Strain Computed at_SINCLAIR_Publishedonline31Ocotber2017_GOLD VoR (CC BY)Final published version, 4.64 MBLicence: CC BY

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Sinclair, M., Peressutti, D., Puyol-Anton, E., Bai, W., Rivolo, S., Webb, J., Claridge, S., Jackson, T., Nordsletten, D., Hadjicharalambous, M., Kerfoot, E., Rinaldi, C. A., Rueckert, D., & King, A. P. (2018). Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging: Estimating Cardiac Biomarkers for CRT Patients. Medical Image Analysis, 43, 1339-1351. https://doi.org/10.1016/j.media.2017.10.004

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title = "Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging: Estimating Cardiac Biomarkers for CRT Patients",

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. ",

author = "Matthew Sinclair and Devis Peressutti and Esther Puyol-Anton and Wenjia Bai and Simone Rivolo and Jessica Webb and Simon Claridge and Tom Jackson and David Nordsletten and Myrianthi Hadjicharalambous and Eric Kerfoot and Rinaldi, {Christopher A.} and Daniel Rueckert and King, {Andrew P.}",

year = "2018",

month = jan,

doi = "10.1016/j.media.2017.10.004",

language = "English",

volume = "43",

pages = "1339--1351",

journal = "Medical Image Analysis",

issn = "1361-8415",

publisher = "Elsevier",

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Sinclair, M , Peressutti, D , Puyol-Anton, E, Bai, W, Rivolo, S , Webb, J , Claridge, S, Jackson, T, Nordsletten, D , Hadjicharalambous, M , Kerfoot, E , Rinaldi, CA, Rueckert, D & King, AP 2018, 'Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging: Estimating Cardiac Biomarkers for CRT Patients', Medical Image Analysis, vol. 43, pp. 1339-1351. https://doi.org/10.1016/j.media.2017.10.004

TY - JOUR

T1 - Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging

T2 - Estimating Cardiac Biomarkers for CRT Patients

AU - Sinclair, Matthew

AU - Peressutti, Devis

AU - Puyol-Anton, Esther

AU - Bai, Wenjia

AU - Rivolo, Simone

AU - Webb, Jessica

AU - Claridge, Simon

AU - Jackson, Tom

AU - Nordsletten, David

AU - Hadjicharalambous, Myrianthi

AU - Kerfoot, Eric

AU - Rinaldi, Christopher A.

AU - Rueckert, Daniel

AU - King, Andrew P.

PY - 2018/1

Y1 - 2018/1

N2 - 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.

AB - 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.

U2 - 10.1016/j.media.2017.10.004

DO - 10.1016/j.media.2017.10.004

M3 - Article

SN - 1361-8415

VL - 43

SP - 1339

EP - 1351

JO - Medical Image Analysis

JF - Medical Image Analysis

ER -

Myocardial Strain Computed at Multiple Spatial Scales from Tagged Magnetic Resonance Imaging: Estimating Cardiac Biomarkers for CRT Patients

Abstract

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