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EJNMMI Research
Published in: EJNMMI Research 1/2018

Open Access 01-12-2018 | Original research

Radiomics of the primary tumour as a tool to improve 18F-FDG-PET sensitivity in detecting nodal metastases in endometrial cancer

Authors: Elisabetta De Bernardi, Alessandro Buda, Luca Guerra, Debora Vicini, Federica Elisei, Claudio Landoni, Robert Fruscio, Cristina Messa, Cinzia Crivellaro

Published in: EJNMMI Research | Issue 1/2018

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Abstract

Background

A radiomic approach was applied in 18F-FDG PET endometrial cancer, to investigate if imaging features computed on the primary tumour could improve sensitivity in nodal metastases detection. One hundred fifteen women with histologically proven endometrial cancer who underwent preoperative 18F-FDG PET/CT were retrospectively considered. SUV, MTV, TLG, geometrical shape, histograms and texture features were computed inside tumour contours. On a first group of 86 patients (DB1), univariate association with LN metastases was computed by Mann-Whitney test and a neural network multivariate model was developed. Univariate and multivariate models were assessed with leave one out on 20 training sessions and on a second group of 29 patients (DB2). A unified framework combining LN metastases visual detection results and radiomic analysis was also assessed.

Results

Sensitivity and specificity of LN visual detection were 50% and 99% on DB1 and 33% and 95% on DB2, respectively. A unique heterogeneity feature computed on the primary tumour (the zone percentage of the grey level size zone matrix, GLSZM ZP) was able to predict LN metastases better than any other feature or multivariate model (sensitivity and specificity of 75% and 81% on DB1 and of 89% and 80% on DB2). Tumours with LN metastases are in fact generally characterized by a lower GLSZM ZP value, i.e. by the co-presence of high-uptake and low-uptake areas. The combination of visual detection and GLSZM ZP values in a unified framework obtained sensitivity and specificity of 94% and 67% on DB1 and of 89% and 75% on DB2, respectively.

Conclusions

The computation of imaging features on the primary tumour increases nodal staging detection sensitivity in 18F-FDG PET and can be considered for a better patient stratification for treatment selection. Results need a confirmation on larger cohort studies.
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Metadata
Title
Radiomics of the primary tumour as a tool to improve 18F-FDG-PET sensitivity in detecting nodal metastases in endometrial cancer
Authors
Elisabetta De Bernardi
Alessandro Buda
Luca Guerra
Debora Vicini
Federica Elisei
Claudio Landoni
Robert Fruscio
Cristina Messa
Cinzia Crivellaro
Publication date
01-12-2018
Publisher
Springer Berlin Heidelberg
Published in
EJNMMI Research / Issue 1/2018
Electronic ISSN: 2191-219X
DOI
https://doi.org/10.1186/s13550-018-0441-1

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