TY - JOUR
T1 - Limits of radiomic-based entropy as a surrogate of tumor heterogeneity
T2 - ROI-area, acquisition protocol and tissue site exert substantial influence
AU - Dercle, Laurent
AU - Ammari, Samy
AU - Bateson, Mathilde
AU - Durand, Paul Blanc
AU - Haspinger, Eva
AU - Massard, Christophe
AU - Jaudet, Cyril
AU - Varga, Andrea
AU - Deutsch, Eric
AU - Soria, Jean Charles
AU - Ferté, Charles
N1 - Publisher Copyright:
© 2017, The Author(s).
PY - 2017/12/1
Y1 - 2017/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85042825101&partnerID=8YFLogxK
U2 - 10.1038/s41598-017-08310-5
DO - 10.1038/s41598-017-08310-5
M3 - Article
C2 - 28801575
AN - SCOPUS:85042825101
SN - 2045-2322
VL - 7
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 7952
ER -