[<sup>18</sup>F]FDG-PET/CT radiomics for the identification of genetic clusters in pheochromocytomas and paragangliomas.

Noortman, Wyanne A; Vriens, Dennis; de Geus-Oei, Lioe-Fee; Slump, Cornelis H; Aarntzen, Erik H; van Berkel, Anouk; Timmers, Henri J L M; van Velden, Floris H P · Eur Radiol · 2022

retrospective_cohort · Level III

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Abstract

Based on germline and somatic mutation profiles, pheochromocytomas and paragangliomas (PPGLs) can be classified into different clusters. We investigated the use of [<sup>18</sup>F]FDG-PET/CT radiomics, SUV<sub>max</sub> and biochemical profile for the identification of the genetic clusters of PPGLs. In this single-centre cohort, 40 PPGLs (13 cluster 1, 18 cluster 2, 9 sporadic) were delineated using a 41% adaptive threshold of SUV<sub>peak</sub> ([<sup>18</sup>F]FDG-PET) and manually (low-dose CT; ldCT). Using PyRadiomics, 211 radiomic features were extracted. Stratified 5-fold cross-validation for the identification of the genetic cluster was performed using multinomial logistic regression with dimensionality reduction incorporated per fold. Classification performances of biochemistry, SUV<sub>max</sub> and PET(/CT) radiomic models were compared and presented as mean (multiclass) test AUCs over the five folds. Results were validated using a sham experiment, randomly shuffling the outcome labels. The model with biochemistry only could identify the genetic cluster (multiclass AUC 0.60). The three-factor PET model had the best classification performance (multiclass AUC 0.88). A simplified model with only SUV<sub>max</sub> performed almost similarly. Addition of ldCT features and biochemistry decreased the classification performances. All sham AUCs were approximately 0.50. PET radiomics achieves a better identification of PPGLs compared to biochemistry, SUV<sub>max</sub>, ldCT radiomics and combined approaches, especially for the differentiation of sporadic PPGLs. Nevertheless, a model with SUV<sub>max</sub> alone might be preferred clinically, weighing model performances against laborious radiomic analysis. The limited added value of radiomics to the overall classification performance for PPGL should be validated in a larger external cohort. • Radiomics derived from [<sup>18</sup>F]FDG-PET/CT has the potential to improve the identification of the genetic clusters of pheochromocytomas and paragangliomas. • A simplified model with SUV<sub>max</sub> only might be preferred clinically, weighing model performances against the laborious radiomic analysis. • Cluster 1 and 2 PPGLs generally present distinctive characteristics that can be captured using [<sup>18</sup>F]FDG-PET imaging. Sporadic PPGLs appear more heterogeneous, frequently resembling cluster 2 PPGLs and occasionally resembling cluster 1 PPGLs.

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