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Prognostic Value of [18F]FDG PET Radiomics to Detect Peritoneal and Distant Metastases in Locally Advanced Gastric Cancer—A Side Study of the Prospective Multicentre PLASTIC Study

Authors :
Lieke C. E. Pullen
Wyanne A. Noortman
Lianne Triemstra
Cas de Jongh
Fenna J. Rademaker
Romy Spijkerman
Gijsbert M. Kalisvaart
Emma C. Gertsen
Lioe-Fee de Geus-Oei
Nelleke Tolboom
Wobbe O. de Steur
Maura Dantuma
Riemer H. J. A. Slart
Richard van Hillegersberg
Peter D. Siersema
Jelle P. Ruurda
Floris H. P. van Velden
Erik Vegt
on behalf of the PLASTIC Study Group
Source :
Cancers, Vol 15, Iss 11, p 2874 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Aim: To improve identification of peritoneal and distant metastases in locally advanced gastric cancer using [18F]FDG-PET radiomics. Methods: [18F]FDG-PET scans of 206 patients acquired in 16 different Dutch hospitals in the prospective multicentre PLASTIC-study were analysed. Tumours were delineated and 105 radiomic features were extracted. Three classification models were developed to identify peritoneal and distant metastases (incidence: 21%): a model with clinical variables, a model with radiomic features, and a clinicoradiomic model, combining clinical variables and radiomic features. A least absolute shrinkage and selection operator (LASSO) regression classifier was trained and evaluated in a 100-times repeated random split, stratified for the presence of peritoneal and distant metastases. To exclude features with high mutual correlations, redundancy filtering of the Pearson correlation matrix was performed (r = 0.9). Model performances were expressed by the area under the receiver operating characteristic curve (AUC). In addition, subgroup analyses based on Lauren classification were performed. Results: None of the models could identify metastases with low AUCs of 0.59, 0.51, and 0.56, for the clinical, radiomic, and clinicoradiomic model, respectively. Subgroup analysis of intestinal and mixed-type tumours resulted in low AUCs of 0.67 and 0.60 for the clinical and radiomic models, and a moderate AUC of 0.71 in the clinicoradiomic model. Subgroup analysis of diffuse-type tumours did not improve the classification performance. Conclusion: Overall, [18F]FDG-PET-based radiomics did not contribute to the preoperative identification of peritoneal and distant metastases in patients with locally advanced gastric carcinoma. In intestinal and mixed-type tumours, the classification performance of the clinical model slightly improved with the addition of radiomic features, but this slight improvement does not outweigh the laborious radiomic analysis.

Details

Language :
English
ISSN :
20726694
Volume :
15
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Cancers
Publication Type :
Academic Journal
Accession number :
edsdoj.526a1d843ea4e95b7fb803534ac2d73
Document Type :
article
Full Text :
https://doi.org/10.3390/cancers15112874