![]() TNAPP fine-needle aspiration (FNA) retrospective study thyroid carcinoma thyroid nodule web-based algorithm.Ĭopyright © 2023 Triggiani, Lisco, Renzulli, Frasoldati, Guglielmi, Garber and Papini.Īlexander EK, Cibas ES. Additional retrospective and, ultimately, prospective studies are needed to confirm and guide the development of future iterations that incorporate different risk stratification systems and targets for diagnosing malignancy while reducing unnecessary FNA procedures. TNAPP performs well compared to AACE/ACE/AME and ACR-TIRADS algorithms. TNAPP's use of size >20 mm as an independent determinant for considering or recommending FNA reduced its specificity. The rate of malignant nodules missed because of inaccurate characterization at baseline by TNAPP was lower compared to the other two algorithms and, in almost all the cases, the tumors were microcarcinomas. The TNAPP algorithm is a reliable, easy-to-learn tool that can be readily employed to improve the selection of thyroid nodules requiring cytological characterization. A total of 14 nodules that would not have been aspirated were malignant, 13 of which were microcarcinomas (92.8%). The TNAPP reduced the number of missed diagnoses of thyroid nodules with suspicious and highly suspicious cytology (TIR 4 + TIR 5 - Bethesda classes V + VI: TNAPP 18% vs. ![]() TNAPP displayed a slightly better performance than AACE/ACE/AME and ACR TI-RADS algorithms in selectively discriminating unnecessary FNA for nodules with benign cytology (TIR 2 - Bethesda class II: TNAPP 32% vs. TNAPP performed better in terms of sensitivity (>80%) and negative predictive value (68%) with an overall accuracy of 50.5%, which was similar to that found with the AACE/ACE/AME algorithm. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of TNAPP were calculated and compared to the diagnostic performance of the other two algorithms by the American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi (AACE/ACE/AME), which it was derived from the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). Each nodule was evaluated for ultrasonographic risk and suitability for FNA. Neck ultrasound images were collected from a thyroid nodule registry and re-examined to extract data to run TNAPP. One hundred twelve consecutive patients with 188 thyroid nodules who underwent FNA from January to December 2016 and thyroid surgery were retrospectively evaluated. To assess the performance of the Thyroid Nodule App (TNAPP), a web-based, readily modifiable, interactive algorithmic tool, in improving the management of thyroid nodules. ![]() Tailored methods are required to improve the management of thyroid nodules, including algorithms and web-based tools. The detection of thyroid nodules has been increasing over time, resulting in an extensive use of fine-needle aspiration (FNA) and cytology. ![]()
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