Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging

Abstract Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition singl...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Simon Bernatz, Yauheniya Zhdanovich, Jörg Ackermann, Ina Koch, Peter J. Wild, Daniel Pinto dos Santos, Thomas J. Vogl, Benjamin Kaltenbach, Nicolas Rosbach
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a1c61c5e004a4415ba264b6bd8f82694
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:a1c61c5e004a4415ba264b6bd8f82694
record_format	dspace
spelling	oai:doaj.org-article:a1c61c5e004a4415ba264b6bd8f826942021-12-02T16:15:06ZImpact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging10.1038/s41598-021-93756-x2045-2322https://doaj.org/article/a1c61c5e004a4415ba264b6bd8f826942021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93756-xhttps://doaj.org/toc/2045-2322Abstract Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition single-shot turbo spin-echo (HASTE), T2w turbo spin-echo (TSE), T2w fluid-attenuated inversion recovery (FLAIR), T2 map and T1-weighted (T1w) TSE. Images were resampled to isotropic voxels. Fruits were segmented. The workflow was repeated by a second reader and the first reader after a pause of one month. We applied PyRadiomics to extract 107 radiomic features per fruit and sequence from seven feature classes. We calculated concordance correlation coefficients (CCC) and dynamic range (DR) to obtain measurements of feature robustness. Intraclass correlation coefficient (ICC) was calculated to assess intra- and inter-observer reproducibility. We calculated Gini scores to test the pairwise discriminative power specific for the features and MRI sequences. We depict Bland Altmann plots of features with top discriminative power (Mann–Whitney U test). Shape features were the most robust feature class. T2 map was the most robust imaging technique (robust features (rf), n = 84). HASTE sequence led to the least amount of rf (n = 20). Intra-observer ICC was excellent (≥ 0.75) for nearly all features (max–min; 99.1–97.2%). Deterioration of ICC values was seen in the inter-observer analyses (max–min; 88.7–81.1%). Complete robustness across all sequences was found for 8 features. Shape features and T2 map yielded the highest pairwise discriminative performance. Radiomics validity depends on the MRI sequence and feature class. T2 map seems to be the most promising imaging technique with the highest feature robustness, high intra-/inter-observer reproducibility and most promising discriminative power.Simon BernatzYauheniya ZhdanovichJörg AckermannIna KochPeter J. WildDaniel Pinto dos SantosThomas J. VoglBenjamin KaltenbachNicolas RosbachNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Simon Bernatz Yauheniya Zhdanovich Jörg Ackermann Ina Koch Peter J. Wild Daniel Pinto dos Santos Thomas J. Vogl Benjamin Kaltenbach Nicolas Rosbach Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
description	Abstract Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition single-shot turbo spin-echo (HASTE), T2w turbo spin-echo (TSE), T2w fluid-attenuated inversion recovery (FLAIR), T2 map and T1-weighted (T1w) TSE. Images were resampled to isotropic voxels. Fruits were segmented. The workflow was repeated by a second reader and the first reader after a pause of one month. We applied PyRadiomics to extract 107 radiomic features per fruit and sequence from seven feature classes. We calculated concordance correlation coefficients (CCC) and dynamic range (DR) to obtain measurements of feature robustness. Intraclass correlation coefficient (ICC) was calculated to assess intra- and inter-observer reproducibility. We calculated Gini scores to test the pairwise discriminative power specific for the features and MRI sequences. We depict Bland Altmann plots of features with top discriminative power (Mann–Whitney U test). Shape features were the most robust feature class. T2 map was the most robust imaging technique (robust features (rf), n = 84). HASTE sequence led to the least amount of rf (n = 20). Intra-observer ICC was excellent (≥ 0.75) for nearly all features (max–min; 99.1–97.2%). Deterioration of ICC values was seen in the inter-observer analyses (max–min; 88.7–81.1%). Complete robustness across all sequences was found for 8 features. Shape features and T2 map yielded the highest pairwise discriminative performance. Radiomics validity depends on the MRI sequence and feature class. T2 map seems to be the most promising imaging technique with the highest feature robustness, high intra-/inter-observer reproducibility and most promising discriminative power.
format	article
author	Simon Bernatz Yauheniya Zhdanovich Jörg Ackermann Ina Koch Peter J. Wild Daniel Pinto dos Santos Thomas J. Vogl Benjamin Kaltenbach Nicolas Rosbach
author_facet	Simon Bernatz Yauheniya Zhdanovich Jörg Ackermann Ina Koch Peter J. Wild Daniel Pinto dos Santos Thomas J. Vogl Benjamin Kaltenbach Nicolas Rosbach
author_sort	Simon Bernatz
title	Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
title_short	Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
title_full	Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
title_fullStr	Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
title_full_unstemmed	Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
title_sort	impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a1c61c5e004a4415ba264b6bd8f82694
work_keys_str_mv	AT simonbernatz impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT yauheniyazhdanovich impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT jorgackermann impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT inakoch impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT peterjwild impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT danielpintodossantos impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT thomasjvogl impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT benjaminkaltenbach impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging AT nicolasrosbach impactofrescanningandrepositioningonradiomicfeaturesemployingamultiobjectphantominmagneticresonanceimaging
_version_	1718384308193853440

Impact of rescanning and repositioning on radiomic features employing a multi-object phantom in magnetic resonance imaging

Ejemplares similares