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Abstract
This study evaluates the relevance of 18F-DOPA PET static and dynamic radiomics for differentiation of high-grade glioma (HGG) progression from treatment-related changes (TRC) by comparing diagnostic performances to the current PET imaging standard of care. Eighty-five patients with histologically confirmed HGG and investigated by dynamic 18F-FDOPA PET in two institutions were retrospectively selected. ElasticNet logistic regression, Random Forest and XGBoost machine models were trained with different sets of features—radiomics extracted from static tumor-to-background-ratio (TBR) parametric images, radiomics extracted from time-to-peak (TTP) parametric images, as well as combination of both—in order to discriminate glioma progression from TRC at 6 months from the PET scan. Diagnostic performances of the models were compared to a logistic regression model with TBRmean ± clinical features used as reference. Training was performed on data from the first center, while external validation was performed on data from the second center. Best radiomics models showed only slightly better performances than the reference model (respective AUCs of 0.834 vs. 0.792, p < 0.001). Our current results show similar findings at the multicentric level using different machine learning models and report a marginal additional value for TBR static and TTP dynamic radiomics over the classical analysis based on TBR values.
Highlights
Amino-acid PET radiotracers, such as 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18 F-FDOPA), are useful for diagnosis of glioma recurrences [1,2,3], high-grade gliomas (HGG) [4]
Five patients were excluded to avoid mis-training of the models, while three patients had incomplete clinical information and dynamic images and data from two additional patients remained too noisy for voxel-based extraction of TTP, even after denoising
18 F-FDOPA PET acquisitions that could be considered for classification of a progression at 6 months from the PET scan
Summary
Amino-acid PET radiotracers, such as 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18 F-FDOPA), are useful for diagnosis of glioma recurrences [1,2,3], high-grade gliomas (HGG) [4]. Very few studies have investigated whether amino-acid PET-integrating radiomic analyses can differentiate glioma progression from treatment-related changes [8,9,10]. These studies did, show that radiomics could yield high diagnostic performances in this field, though none investigated 18 F-FDOPA at a multi-centric level, directly comparing its performance to the current clinical standard of PET imaging (i.e., as opposed to classical tumor-to-background (TBR) parameters used in routine practice). The integration of dynamic PET imaging added considerable predictive value to conventional static parameters in terms of the initial diagnosis of glioma [6,11]
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