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Image resampling and discretization effect on the estimate of myocardial radiomic features from T1 and T2 mapping in hypertrophic cardiomyopathy

Authors :
Daniela Marfisi
Carlo Tessa
Chiara Marzi
Jacopo Del Meglio
Stefania Linsalata
Rita Borgheresi
Alessio Lilli
Riccardo Lazzarini
Luca Salvatori
Claudio Vignali
Andrea Barucci
Mario Mascalchi
Giancarlo Casolo
Stefano Diciotti
Antonio Claudio Traino
Marco Giannelli
Marfisi D.
Tessa C.
Marzi C.
Del Meglio J.
Linsalata S.
Borgheresi R.
Lilli A.
Lazzarini R.
Salvatori L.
Vignali C.
Barucci A.
Mascalchi M.
Casolo G.
Diciotti S.
Traino A.C.
Giannelli M.
Source :
Scientific Reports. 12
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

Radiomics is emerging as a promising and useful tool in cardiac magnetic resonance (CMR) imaging applications. Accordingly, the purpose of this study was to investigate, for the first time, the effect of image resampling/discretization and filtering on radiomic features estimation from quantitative CMR T1 and T2 mapping. Specifically, T1 and T2 maps of 26 patients with hypertrophic cardiomyopathy (HCM) were used to estimate 98 radiomic features for 7 different resampling voxel sizes (at fixed bin width), 9 different bin widths (at fixed resampling voxel size), and 7 different spatial filters (at fixed resampling voxel size/bin width). While we found a remarkable dependence of myocardial radiomic features from T1 and T2 mapping on image filters, many radiomic features showed a limited sensitivity to resampling voxel size/bin width, in terms of intraclass correlation coefficient (> 0.75) and coefficient of variation (

Details

ISSN :
20452322
Volume :
12
Database :
OpenAIRE
Journal :
Scientific Reports
Accession number :
edsair.doi.dedup.....d7b577bb907024a91403346b1b0843fc
Full Text :
https://doi.org/10.1038/s41598-022-13937-0