Quantitative classification and radiomics of [F-18]FDG-PET/CT in indeterminate thyroid nodules

Koster, E.J. de; Noortman, W.A.; Mostert, J.M.; Booij, J.; Brouwer, C.B.; Keizer, B. de; Klerk, J.M.H. de; Oyen, W.J.G.; Velden, F.H.P. van; Geus-Oei, L.F. de; Vriens, D.; EfFECTS Trial Study Grp

doi:doi:10.1007/s00259-022-05712-0

Purpose To evaluate whether quantitative [F-18]FDG-PET/CT assessment, including radiomic analysis of [F-18]FDG-positive thyroid nodules, improved the preoperative differentiation of indeterminate thyroid nodules of non-Hurthle cell and Hurthle cell cytology.Methods Prospectively included patients with a Bethesda III or IV thyroid nodule underwent [F-18]FDG-PET/CT imaging. Receiver operating characteristic (ROC) curve analysis was performed for standardised uptake values (SUV) and SUV-ratios, including assessment of SUV cut-offs at which a malignant/borderline neoplasm was reliably ruled out (>= 95% sensitivity). [F-18]FDG-positive scans were included in radiomic analysis. After segmentation at 50% of SUVpeak, 107 radiomic features were extracted from [F-18]FDG-PET and low-dose CT images. Elastic net regression classifiers were trained in a 20-times repeated random split. Dimensionality reduction was incorporated into the splits. Predictive performance of radiomics was presented as...Show morePurpose To evaluate whether quantitative [F-18]FDG-PET/CT assessment, including radiomic analysis of [F-18]FDG-positive thyroid nodules, improved the preoperative differentiation of indeterminate thyroid nodules of non-Hurthle cell and Hurthle cell cytology.Methods Prospectively included patients with a Bethesda III or IV thyroid nodule underwent [F-18]FDG-PET/CT imaging. Receiver operating characteristic (ROC) curve analysis was performed for standardised uptake values (SUV) and SUV-ratios, including assessment of SUV cut-offs at which a malignant/borderline neoplasm was reliably ruled out (>= 95% sensitivity). [F-18]FDG-positive scans were included in radiomic analysis. After segmentation at 50% of SUVpeak, 107 radiomic features were extracted from [F-18]FDG-PET and low-dose CT images. Elastic net regression classifiers were trained in a 20-times repeated random split. Dimensionality reduction was incorporated into the splits. Predictive performance of radiomics was presented as mean area under the ROC curve (AUC) across the test sets.Results Of 123 included patients, 84 (68%) index nodules were visually [F-18]FDG-positive. The malignant/borderline rate was 27% (33/123). SUV-metrices showed AUCs ranging from 0.705 (95% CI, 0.601-0.810) to 0.729 (0.633-0.824), 0.708 (0.580-0.835) to 0.757 (0.650-0.864), and 0.533 (0.320-0.747) to 0.700 (0.502-0.898) in all (n = 123), non-Hurthle (n= 94), and Hurthle cell (n = 29) nodules, respectively. At SUVmax, SUVpeak, SUVmax-ratio, and SUVpeak-ratio cut-offs of 2.1 g/mL, 1.6 g/mL, 1.2, and 0.9, respectively, sensitivity of [F-18]FDG-PET/CT was 95.8% (95% CI, 78.9-99.9%) in non-Hurthle cell nodules. In Hurthle cell nodules, cut-offs of 5.2 g/mL, 4.7 g/mL, 3.4, and 2.8, respectively, resulted in 100% sensitivity (95% CI, 66.4-100%). Radiomic analysis of 84 (68%) [F-18]FDG-positive nodules showed a mean test set AUC of 0.445 (95% CI, 0.290-0.600) for the PET model.Conclusion Quantitative [F-18]FDG-PET/CT assessment ruled out malignancy in indeterminate thyroid nodules. Distinctive, higher SUV cut-offs should be applied in Hurthle cell nodules to optimize rule-out ability. Radiomic analysis did not contribute to the additional differentiation of [F-18]FDG-positive nodules.Show less

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Quantitative classification and radiomics of [F-18]FDG-PET/CT in indeterminate thyroid nodules