Lidija Antunovic1, Francesca Gallivanone2, Martina Sollini3, Andrea Sagona4, Alessandra Invento5, Giulia Manfrinato6, Margarita Kirienko3, Corrado Tinterri4, Arturo Chiti7,8, Isabella Castiglioni2. 1. Nuclear Medicine Department, Humanitas Research Hospital, Via A. Manzoni 56, 20089, Rozzano, Milan, Italy. 2. Laboratory of Innovation and Integration in Molecular Medicine, Institute of Molecular Bioimaging and Physiology, National Research Council, Via F. Cervi 93, 20090, Segrate, Milan, Italy. 3. Department of Biomedical Sciences, Humanitas University, Via A. Manzoni 113, 20089, Rozzano, Milan, Italy. 4. Breast Unit, Humanitas Research Hospital, Via A. Manzoni 56, 20089, Rozzano, Milan, Italy. 5. Breast Unit, Integrated University Hospital, Piazzale A. Stefani 1, Borgo Trento, 37126, Verona, Italy. 6. Residency Program in Nuclear Medicine, University of Milan, Via A. di Rudini 8, 20100, Milan, Italy. 7. Nuclear Medicine Department, Humanitas Research Hospital, Via A. Manzoni 56, 20089, Rozzano, Milan, Italy. arturo.chiti@hunimed.eu. 8. Department of Biomedical Sciences, Humanitas University, Via A. Manzoni 113, 20089, Rozzano, Milan, Italy. arturo.chiti@hunimed.eu.
Abstract
PURPOSE: The aim of this study was to evaluate the role of imaging features derived from [18F]FDG-PET/CT to provide in vivo characterization of breast cancer (BC). METHODS: Images from 43 patients with a first diagnosis of BC were reviewed. Images were acquired before any treatment. Histological data were derived from pretreatment biopsy or surgical histological specimen; these included tumor type, grade, ER and PgR receptor status, lymphovascular invasion, Ki67 index, HER2 status, and molecular subtype. Standard parameters (SUVmean, TLG, MTV) and advanced imaging features (histogram-based and shape and size features) were evaluated. Univariate analysis, hierarchical clustering analysis, and exact Fisher's test were used for statistical analysis of data. Imaging-derived metrics were reduced evaluating the mutual correlation within group of features as well as the mutual correlation between groups of features to form a signature. RESULTS: A significant correlation was found between some advanced imaging features and the histological type. Different molecular subtypes were characterized by different values of two histogram-based features (median and energy). A significant association was observed between the imaging signature and luminal A and luminal B HER2 negative molecular subtype and also when considering luminal A, luminal B HER2-negative and HER2-positive groups. Similar results were found between the signature and all five molecular subtypes and also when considering the histological types of BC. CONCLUSIONS: Our results suggest a complementary role of standard PET imaging parameters and advanced imaging features for the in vivo biological characterization of BC lesions.
PURPOSE: The aim of this study was to evaluate the role of imaging features derived from [18F]FDG-PET/CT to provide in vivo characterization of breast cancer (BC). METHODS: Images from 43 patients with a first diagnosis of BC were reviewed. Images were acquired before any treatment. Histological data were derived from pretreatment biopsy or surgical histological specimen; these included tumor type, grade, ER and PgR receptor status, lymphovascular invasion, Ki67 index, HER2 status, and molecular subtype. Standard parameters (SUVmean, TLG, MTV) and advanced imaging features (histogram-based and shape and size features) were evaluated. Univariate analysis, hierarchical clustering analysis, and exact Fisher's test were used for statistical analysis of data. Imaging-derived metrics were reduced evaluating the mutual correlation within group of features as well as the mutual correlation between groups of features to form a signature. RESULTS: A significant correlation was found between some advanced imaging features and the histological type. Different molecular subtypes were characterized by different values of two histogram-based features (median and energy). A significant association was observed between the imaging signature and luminal A and luminal B HER2 negative molecular subtype and also when considering luminal A, luminal B HER2-negative and HER2-positive groups. Similar results were found between the signature and all five molecular subtypes and also when considering the histological types of BC. CONCLUSIONS: Our results suggest a complementary role of standard PET imaging parameters and advanced imaging features for the in vivo biological characterization of BC lesions.
Entities:
Keywords:
Breast cancer; Radiomics; [18F]FDG-pet/Ct
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