Oncotarget

Research Papers:

Influence of age on radiomic features in 18F-FDG PET in normal breast tissue and in breast cancer tumors

Sarah Boughdad _, Christophe Nioche, Fanny Orlhac, Laurine Jehl, Laurence Champion, Irène Buvat

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Oncotarget. 2018; 9:30855-30868. https://doi.org/10.18632/oncotarget.25762

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Abstract

Sarah Boughdad1, Christophe Nioche1, Fanny Orlhac1, Laurine Jehl2, Laurence Champion2 and Irène Buvat1

1IMIV, CEA, Inserm, CNRS, Université Paris-Sud, Université Paris-Saclay, CEA-SHFJ, Orsay, France

2Nuclear Medicine Department, Institut Curie, Site St-Cloud, France

Correspondence to:

Sarah Boughdad, email: Sarah.boughdad@gmail.com

Keywords: breast tissue; breast cancer; 18F-FDG PET/CT; radiomic features; influence of age

Received: March 27, 2018     Accepted: June 22, 2018     Published: July 20, 2018

ABSTRACT

Background: To help interpret measurements in breast tissue and breast tumors from 18F-FDG PET scans, we studied the influence of age in measurements of PET parameters in normal breast tissue and in a breast cancer (BC) population.

Results: 522 women were included: 331 pts without history of BC (B-VOI) and 191 patients with BC (T-VOI). In B-VOI, there were significant differences between all age groups for Standardized Uptake Values (SUVs) and for 12 textural indices (TI) whereas histogram-based indices (HBI) did not vary between age groups. SUV values decreased over time whereas Homogeneity increased. We had a total of 210 T-VOI and no significant differences were found according to the histological type between 190 ductal carcinoma and 18 lobular carcinoma. Conversely, according to BC subtype most differences in PET parameters between age groups were found in Triple-Negative tumors (52) for 9 TI. On post-hoc Hochberg, most differences were found between the <45 year old (PRE) group and POST groups in NBT and in Triple-Negative tumors.

Conclusion: We found significant SUVs and TI differences as a function of age in normal breast tissue and in BC radiomic phenotype with Triple-Negative tumors being the most affected. Our findings suggest that age should be taken into account as a co-covariable in radiomic models.

Methods: Patients were classified in 3 age groups: <45 yo (PRE), ≥45 and <55 yo (PERI) and ≥55 and <85 yo (POST) and we compared PET parameters using Anova test with post-hoc Bonferroni/Hochberg analyses: SUV (max, mean and peak), HBI and TI in both breasts and in breast tumor regions.


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