| Title |
[18F]FDG PET/CT features for the molecular characterization of primary breast tumors
|
|---|---|
| Published in |
European Journal of Nuclear Medicine and Molecular Imaging, July 2017
|
| DOI | 10.1007/s00259-017-3770-9 |
| Pubmed ID | |
| Authors |
Lidija Antunovic, Francesca Gallivanone, Martina Sollini, Andrea Sagona, Alessandra Invento, Giulia Manfrinato, Margarita Kirienko, Corrado Tinterri, Arturo Chiti, Isabella Castiglioni |
| Abstract |
The aim of this study was to evaluate the role of imaging features derived from [(18)F]FDG-PET/CT to provide in vivo characterization of breast cancer (BC). 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. 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. Our results suggest a complementary role of standard PET imaging parameters and advanced imaging features for the in vivo biological characterization of BC lesions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 62 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 16% |
| Student > Doctoral Student | 9 | 15% |
| Student > Postgraduate | 8 | 13% |
| Other | 5 | 8% |
| Student > Ph. D. Student | 5 | 8% |
| Other | 12 | 19% |
| Unknown | 13 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 33 | 53% |
| Computer Science | 5 | 8% |
| Physics and Astronomy | 2 | 3% |
| Immunology and Microbiology | 1 | 2% |
| Nursing and Health Professions | 1 | 2% |
| Other | 3 | 5% |
| Unknown | 17 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2018.
All research outputs
#21,153,429
of 23,806,312 outputs
Outputs from European Journal of Nuclear Medicine and Molecular Imaging
#2,610
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Outputs of similar age
#273,946
of 313,465 outputs
Outputs of similar age from European Journal of Nuclear Medicine and Molecular Imaging
#30
of 44 outputs
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