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

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...

Full description

Saved in:
Bibliographic Details
Published inScientific reports Vol. 12; no. 1; pp. 10186 - 14
Main Authors Marfisi, Daniela, Tessa, Carlo, Marzi, Chiara, Del Meglio, Jacopo, Linsalata, Stefania, Borgheresi, Rita, Lilli, Alessio, Lazzarini, Riccardo, Salvatori, Luca, Vignali, Claudio, Barucci, Andrea, Mascalchi, Mario, Casolo, Giancarlo, Diciotti, Stefano, Traino, Antonio Claudio, Giannelli, Marco
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 17.06.2022
Nature Publishing Group
Nature Portfolio
Subjects
Online AccessGet full text
ISSN2045-2322
2045-2322
DOI10.1038/s41598-022-13937-0

Cover

More Information
Summary: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 (< 30%). The estimate of most textural radiomic features showed a linear significant (p < 0.05) correlation with resampling voxel size/bin width. Overall, radiomic features from T2 maps have proven to be less sensitive to image preprocessing than those from T1 maps, especially when varying bin width. Our results might corroborate the potential of radiomics from T1/T2 mapping in HCM and hopefully in other myocardial diseases.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-022-13937-0