Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence

Abstract Entropy is a promising quantitative imaging biomarker for characterizing cancer imaging phenotype. Entropy has been associated with tumor gene expression, tumor metabolism, tumor stage, patient prognosis, and treatment response. Our hypothesis states that tumor-specific biomarkers such as e...

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Autores principales:	Laurent Dercle, Samy Ammari, Mathilde Bateson, Paul Blanc Durand, Eva Haspinger, Christophe Massard, Cyril Jaudet, Andrea Varga, Eric Deutsch, Jean-Charles Soria, Charles Ferté
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3550ac8355a84ddf99d4ece2cd80f0d3
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spelling	oai:doaj.org-article:3550ac8355a84ddf99d4ece2cd80f0d32021-12-02T16:08:19ZLimits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence10.1038/s41598-017-08310-52045-2322https://doaj.org/article/3550ac8355a84ddf99d4ece2cd80f0d32017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08310-5https://doaj.org/toc/2045-2322Abstract Entropy is a promising quantitative imaging biomarker for characterizing cancer imaging phenotype. Entropy has been associated with tumor gene expression, tumor metabolism, tumor stage, patient prognosis, and treatment response. Our hypothesis states that tumor-specific biomarkers such as entropy should be correlated between synchronous metastases. Therefore, a significant proportion of the variance of entropy should be attributed to the malignant process. We analyzed 112 patients with matched/paired synchronous metastases (SM#1 and SM#2) prospectively enrolled in the MOSCATO-01 clinical trial. Imaging features were extracted from Regions Of Interest (ROI) delineated on CT-scan using TexRAD software. We showed that synchronous metastasis entropy was correlated across 5 Spatial Scale Filters: Spearman’s Rho ranged between 0.41 and 0.59 (P = 0.0001, Bonferroni correction). Multivariate linear analysis revealed that entropy in SM#1 is significantly associated with (i) primary tumor type; (ii) entropy in SM#2 (same malignant process); (iii) ROI area size; (iv) metastasis site; and (v) entropy in the psoas muscle (reference tissue). Entropy was a logarithmic function of ROI area in normal control tissues (aorta, psoas) and in mathematical models (P < 0.01). We concluded that entropy is a tumor-specific metric only if confounding factors are corrected.Laurent DercleSamy AmmariMathilde BatesonPaul Blanc DurandEva HaspingerChristophe MassardCyril JaudetAndrea VargaEric DeutschJean-Charles SoriaCharles FertéNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Laurent Dercle Samy Ammari Mathilde Bateson Paul Blanc Durand Eva Haspinger Christophe Massard Cyril Jaudet Andrea Varga Eric Deutsch Jean-Charles Soria Charles Ferté Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence
description	Abstract Entropy is a promising quantitative imaging biomarker for characterizing cancer imaging phenotype. Entropy has been associated with tumor gene expression, tumor metabolism, tumor stage, patient prognosis, and treatment response. Our hypothesis states that tumor-specific biomarkers such as entropy should be correlated between synchronous metastases. Therefore, a significant proportion of the variance of entropy should be attributed to the malignant process. We analyzed 112 patients with matched/paired synchronous metastases (SM#1 and SM#2) prospectively enrolled in the MOSCATO-01 clinical trial. Imaging features were extracted from Regions Of Interest (ROI) delineated on CT-scan using TexRAD software. We showed that synchronous metastasis entropy was correlated across 5 Spatial Scale Filters: Spearman’s Rho ranged between 0.41 and 0.59 (P = 0.0001, Bonferroni correction). Multivariate linear analysis revealed that entropy in SM#1 is significantly associated with (i) primary tumor type; (ii) entropy in SM#2 (same malignant process); (iii) ROI area size; (iv) metastasis site; and (v) entropy in the psoas muscle (reference tissue). Entropy was a logarithmic function of ROI area in normal control tissues (aorta, psoas) and in mathematical models (P < 0.01). We concluded that entropy is a tumor-specific metric only if confounding factors are corrected.
format	article
author	Laurent Dercle Samy Ammari Mathilde Bateson Paul Blanc Durand Eva Haspinger Christophe Massard Cyril Jaudet Andrea Varga Eric Deutsch Jean-Charles Soria Charles Ferté
author_facet	Laurent Dercle Samy Ammari Mathilde Bateson Paul Blanc Durand Eva Haspinger Christophe Massard Cyril Jaudet Andrea Varga Eric Deutsch Jean-Charles Soria Charles Ferté
author_sort	Laurent Dercle
title	Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence
title_short	Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence
title_full	Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence
title_fullStr	Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence
title_full_unstemmed	Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence
title_sort	limits of radiomic-based entropy as a surrogate of tumor heterogeneity: roi-area, acquisition protocol and tissue site exert substantial influence
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/3550ac8355a84ddf99d4ece2cd80f0d3
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Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence

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