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Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer

Authors :
Wyanne A. Noortman
Nicolas Aide
Dennis Vriens
Lisa S. Arkes
Cornelis H. Slump
Ronald Boellaard
Jelle J. Goeman
Christophe M. Deroose
Jean-Pascal Machiels
Lisa F. Licitra
Renaud Lhommel
Alessandra Alessi
Erwin Woff
Karolien Goffin
Christophe Le Tourneau
Jocelyn Gal
Stéphane Temam
Jean-Pierre Delord
Floris H. P. van Velden
Lioe-Fee de Geus-Oei
Radiology and nuclear medicine
Amsterdam Neuroscience - Brain Imaging
CCA - Imaging and biomarkers
Biomedical Photonic Imaging
TechMed Centre
Robotics and Mechatronics
Source :
Cancers, 15(10):2681. Multidisciplinary Digital Publishing Institute (MDPI), Cancers, 15, Cancers; Volume 15; Issue 10; Pages: 2681, Cancers, 15(10):2681. MDPI, Noortman, W A, Aide, N, Vriens, D, Arkes, L S, Slump, C H, Boellaard, R, Goeman, J J, Deroose, C M, Machiels, J-P, Licitra, L F, Lhommel, R, Alessi, A, Woff, E, Goffin, K, le Tourneau, C, Gal, J, Temam, S, Delord, J-P, van Velden, F H P & de Geus-Oei, L-F 2023, ' Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer ', Cancers, vol. 15, no. 10, 2681 . https://doi.org/10.3390/cancers15102681, Cancers, 15, 10
Publication Year :
2023

Abstract

AIM: To build and externally validate an [18F]FDG PET radiomic model to predict overall survival in patients with head and neck squamous cell carcinoma (HNSCC). METHODS: Two multicentre datasets of patients with operable HNSCC treated with preoperative afatinib who underwent a baseline and evaluation [18F]FDG PET/CT scan were included (EORTC: n = 20, Unicancer: n = 34). Tumours were delineated, and radiomic features were extracted. Each cohort served once as a training and once as an external validation set for the prediction of overall survival. Supervised feature selection was performed using variable hunting with variable importance, selecting the top two features. A Cox proportional hazards regression model using selected radiomic features and clinical characteristics was fitted on the training dataset and validated in the external validation set. Model performances are expressed by the concordance index (C-index). RESULTS: In both models, the radiomic model surpassed the clinical model with validation C-indices of 0.69 and 0.79 vs. 0.60 and 0.67, respectively. The model that combined the radiomic features and clinical variables performed best, with validation C-indices of 0.71 and 0.82. CONCLUSION: Although assessed in two small but independent cohorts, an [18F]FDG-PET radiomic signature based on the evaluation scan seems promising for the prediction of overall survival for HNSSC treated with preoperative afatinib. The robustness and clinical applicability of this radiomic signature should be assessed in a larger cohort. ispartof: CANCERS vol:15 issue:10 ispartof: location:Switzerland status: published

Details

Language :
English
ISSN :
20726694
Database :
OpenAIRE
Journal :
Cancers, 15(10):2681. Multidisciplinary Digital Publishing Institute (MDPI), Cancers, 15, Cancers; Volume 15; Issue 10; Pages: 2681, Cancers, 15(10):2681. MDPI, Noortman, W A, Aide, N, Vriens, D, Arkes, L S, Slump, C H, Boellaard, R, Goeman, J J, Deroose, C M, Machiels, J-P, Licitra, L F, Lhommel, R, Alessi, A, Woff, E, Goffin, K, le Tourneau, C, Gal, J, Temam, S, Delord, J-P, van Velden, F H P & de Geus-Oei, L-F 2023, ' Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer ', Cancers, vol. 15, no. 10, 2681 . https://doi.org/10.3390/cancers15102681, Cancers, 15, 10
Accession number :
edsair.doi.dedup.....cb11ebf7bc15d249d4d3f0994a3b4eba
Full Text :
https://doi.org/10.3390/cancers15102681