A prospective cohort study to assess the role of FDG-PET in differentiating benign and malignant follicular neoplasms


BACKGROUND Follicular and Hürthle cell neoplasms are diagnostic challenges. This prospective study was designed to evaluate the efficacy of [18F]-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT) in predicting the risk of malignancy in follicular/Hürthle cell neoplasms. MATERIALS AND METHODS Fifty thyroid nodules showing follicular/Hürthle cell neoplasm on prior ultrasonography guided fine needle aspiration cytology (FNAC) were recruited into this study. A FDG-PET/CT scan, performed for neck and superior mediastinum, was reported by a single observer, blinded to the surgical and pathology findings. Receiver operating characteristic (ROC) curve analysis of maximum standardized uptake value (SUVmax) and the area under the curve (AUROC) were used to assess discrimination between benign from malignant nodules. Youden index was used to identify the optimal cut-off SUVmax for diagnosing malignancy. Sensitivity, specificity, predictive values and overall accuracy were used as measures of performance. RESULTS Our study group comprises of 31 benign and 19 malignant thyroid nodules. After excluding all Hürthle cell adenomas, the AUROC for discriminating benign and malignant non-Hürthle cell neoplasms was 0.79 (95% CI, 0.64-0.94; p = 0.001); with SUVmax of 3.25 as the best cut-off for the purpose. PET/CT had sensitivity of 79% (95% CI, 54-93%), specificity of 83% (95% CI, 60-94%), positive predictive value (PPV) of 79% (95% CI, 54-93%), and negative predictive value (NPV) of 83% (95% CI, 60-94%). The overall accuracy was 81%. CONCLUSIONS FDG-PET/CT can help in differentiating benign and malignant non-Hürthle cell neoplasms. SUVmax of 3.25 was found to be the best for identifying malignant non-Hürthle cell follicular neoplasms.

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@inproceedings{Pathak2016APC, title={A prospective cohort study to assess the role of FDG-PET in differentiating benign and malignant follicular neoplasms}, author={Kumar Alok Pathak and Andrew L. Goertzen and Richard W. Nason and Thomas C Klonisch and William D Leslie}, booktitle={Annals of medicine and surgery}, year={2016} }