346 chapter 5 borderline nodules were defined as index nodules that were histopathologically diagnosed as thyroid carcinoma or borderline tumours, the latter including non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), follicular tumour of uncertain malignant potential (FT-UMP), and paraganglioma. Throughout the manuscript, malignant and borderline lesions are grouped, as diagnostic surgery is considered the right course of treatment for all these lesions according to current insights. Incidentally detected (micro)carcinomas or borderline tumours located outside the index nodule were not considered for the reference standard. Blinded central revision of all cyto- and histopathology was performed by a dedicated thyroid pathologist. In case of discordance with the local histopathologist, a third pathologist was consulted and consensus was reached. Outcomes The primary outcome of the study was the diagnostic accuracy of quantitative [18F]FDG-PET/CT assessment and radiomics in non-Hürthle cell (defined as AUS/FLUS and FN/SFN cytology) and Hürthle cell (defined as HCN/SHCN cytology) nodules. True-positive and false-negative were respectively defined as test-positive and test-negative histopathologically malignant/borderline nodules. Falsepositive and true-negative were respectively defined as test-positive and test-negative benign nodules. Statistical and radiomic analysis Categorical data were expressed as absolute and relative (%) frequencies, and compared using Pearson’s chi squared or Fisher’s exact tests, where appropriate. Continuous data were assessed for log-normality, expressed using mean ± standard deviation or median (interquartile range), and compared using independent samples T-tests or Mann-Whitney U tests when (log-)normally or non-normally distributed, respectively. Receiver operator characteristic (ROC) curve analysis was performed for the SUVmax, SUVpeak, SUVmax-ratio and SUVpeak-ratio, using the area under the curve (AUC) to describe the overall diagnostic accuracy. Next, for each of the SUV-metrices the cut-off value was determined at which an optimal test sensitivity was found, defined as a sensitivity ≥95%. This is in accordance with the current ATA recommendations that a useful rule-out test is characterised by a negative predictive value (NPV) similar to a Bethesda II cytological diagnosis (i.e., 96%) [17]. At these SUV cut-offs, we assessed the benign call rate, representing the rate of potentially avoidable diagnostic surgeries. Sensitivity, specificity, negative and positive predictive value (PPV), benign call rate, and 95% confidence intervals (CI) were calculated using the traditional formulas and β-distribution (Clopper-Pearson interval), respectively. Subgroup analysis was performed for [18F] FDG-positive non-Hürthle cell nodules. Data collection was performed using Castor EDC (Castor EDC, Amsterdam, the Netherlands). Statistical analysis was performed in SPSS Statistics (version 26; IBM Corp, Armonk, NY, USA).
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