Objectives
To construct and validate a combined model based on axial skeleton radiomics of 18F-FDG PET/CT for predicting event-free survival in high-risk pediatric neuroblastoma
patients.
Materials and Methods
Eighty-seven high-risk neuroblastoma patients were retrospectively enrolled in this
study and randomized in a 7:3 ratio to the training and validation cohorts. The radiomics
model was constructed using radiomics features that were extracted from the axial
skeleton. A univariate Cox regression analysis was then performed to screen clinical
risk factors associated with event-free survival for building clinical model. Radiomics
features and clinical risk factors were incorporated to construct the combined model
for predicting the event-free survival in high-risk neuroblastoma patients. The performance
of the models was evaluated by the C-index.
Results
Eighteen radiomics features were selected to build the radiomics model. The radiomics
model achieved better event-free survival prediction than the clinical model in the
training cohort (C-index: 0.846 vs. 0.612) and validation cohort (C-index: 0.754 vs.
0.579). The combined model achieved the best prognostic prediction performance with
a C-index of 0.863 and 0.799 in the training and validation cohorts, respectively.
Conclusion
The combined model integrating radiomics features and clinical risk factors showed
more accurate predictive performance for event-free survival in high-risk pediatric
neuroblastoma patients, which helps to design individualized treatment strategies
and regular follow-ups.
Key words
Abbreviations:
AUC (area under the curve), CI (confidence interval), HVA (homovanillic acid), ICC (intraclass correlation coefficient), INRG (International Neuroblastoma Risk Group), LASSO (least absolute shrinkage and selection operator), ROC (receiver operating characteristic), ROIs (regions of interest), VMA (vanillylmandelic acid)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: February 22, 2023
Accepted:
January 24,
2023
Received in revised form:
January 24,
2023
Received:
December 29,
2022
Publication stage
In Press Corrected ProofIdentification
Copyright
© 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
