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18 F-FDG PET/CT imaging of pediatric peripheral neuroblastic tumor: a combined model to predict the International Neuroblastoma Pathology Classification.

Authors :
Qian LD
Feng LJ
Zhang SX
Liu J
Ren JL
Liu L
Zhang H
Yang J
Source :
Quantitative imaging in medicine and surgery [Quant Imaging Med Surg] 2023 Jan 01; Vol. 13 (1), pp. 94-107. Date of Electronic Publication: 2022 Oct 10.
Publication Year :
2023

Abstract

Background: The aim of this study was to evaluate the effect of a model combining a 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( <superscript>18</superscript> F-FDG PET/CT)-based radiomics signature with clinical factors in the preoperative prediction of the International Neuroblastoma Pathology Classification (INPC) type of pediatric peripheral neuroblastic tumor (pNT).<br />Methods: A total of 106 consecutive pediatric pNT patients confirmed by pathology were retrospectively analyzed. Significant features determined by multivariate logistic regression were retained to establish a clinical model (C-model), which included clinical parameters and PET/CT radiographic features. A radiomics model (R-model) was constructed on the basis of PET and CT images. A semiautomatic method was used for segmenting regions of interest. A total of 1,016 radiomics features were extracted. Univariate analysis and the least absolute shrinkage selection operator were then used to select significant features. The C-model was combined with the R-model to establish a combination model (RC-model). The predictive performance was validated by receiver operating characteristic (ROC) curve analysis, calibration curves, and decision curve analysis (DCA) in both the training cohort and validation cohort.<br />Results: The radiomics signature was constructed using 5 selected radiomics features. The RC-model, which was based on the 5 radiomics features and 3 clinical factors, showed better predictive performance compared with the C-model alone [area under the curve in the validation cohort: 0.908 vs. 0.803; accuracy: 0.903 vs. 0.710; sensitivity: 0.895 vs. 0.789; specificity: 0.917 vs. 0.583; net reclassification improvement (NRI) 0.439, 95% confidence interval (CI): 0.1047-0.773; P=0.01]. The calibration curve showed that the RC-model had goodness of fit, and DCA confirmed its clinical utility.<br />Conclusions: In this preliminary single-center retrospective study, an R-model based on <superscript>18</superscript> F-FDG PET/CT was shown to be promising in predicting INPC type in pediatric pNT, allowing for the noninvasive prediction of INPC and assisting in therapeutic strategies.<br />Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-343/coif). The authors report that this work was supported by the National Natural Science Foundation of China: Imaging genomics of neuroblastoma based on 18F-FDG PET/CT and 123I-MIBG SPECT/CT (No. 81971642). JLR is in partnership with GE Healthcare China. LL is in partnership with Sinounion Medical Technology (Beijing) Co., Ltd., Beijing. The authors have no other conflicts of interest to declare.<br /> (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Details

Language :
English
ISSN :
2223-4292
Volume :
13
Issue :
1
Database :
MEDLINE
Journal :
Quantitative imaging in medicine and surgery
Publication Type :
Academic Journal
Accession number :
36620179
Full Text :
https://doi.org/10.21037/qims-22-343