| Title: |
Thyroid Nodule Characterization: Which Thyroid Imaging Reporting and Data System (TIRADS) Is More Accurate? A Comparison Between Radiologists with Different Experiences and Artificial Intelligence Software |
| Authors: |
E. David; L. Aliotta; F. Frezza; M. Riccio; A. Cannavale; P. Pacini; C. Di Bella; V. Dolcetti; E. Seri; L. Giuliani; M. Di Segni; G. Lo Conte; G. Bonito; A. Guerrisi; F. Mangini; F. M. Drudi; C. De Vito; V. Cantisani |
| Contributors: |
David, E.; Aliotta, L.; Frezza, F.; Riccio, M.; Cannavale, A.; Pacini, P.; Di Bella, C.; Dolcetti, V.; Seri, E.; Giuliani, L.; Di Segni, M.; Lo Conte, G.; Bonito, G.; Guerrisi, A.; Mangini, F.; Drudi, F. M.; De Vito, C.; Cantisani, V. |
| Publication Year: |
2025 |
| Collection: |
Sapienza Università di Roma: CINECA IRIS |
| Subject Terms: |
thyroid cancer characterization; CAD system; TIRADS |
| Description: |
Purpose: This study aimed to compare: the performance of K-TIRADS, EU-TIRADS and ACR TIRADS when used by observers with different levels of experience compared with the gold standard of cytology, and to evaluate the diagnostic performance of CAD (computer-aided design) compared with TI-RADS systems. Methods and Materials: In total, 323 thyroid nodules were evaluated in patients who were candidates for needle aspiration. Three observers with different levels of experience evaluated the diagnostic accuracy of three risk stratification systems (ACR TI-RADS, EU-TIRADS and K-TIRADS) and CAD software (S-Detect, made by Samsung) in characterizing the nodules. The results were compared with cytology examination. All nodules were characterized in terms of shape, margins, composition, calcifications, size, echogenicity and microcalcifications, and by stratifying individual nodules by using the three TIRADS systems; then S-detect software was applied and the data were compared with each other and with the gold standard. Results: Through cytology, 308 benign and 33 malignant nodules were identified. ACR-TIRADS showed a sensitivity of 100%, a specificity of 86%, a positive predictive value of 43% and a negative predictive value of 100%. EU-TIRADS showed a sensitivity of 100%, a specificity of 79%, a positive predictive value of 33% and a negative predictive value of 100%. K-TIRADS showed a sensitivity of 100%, a specificity of 89%, a positive predictive value of 50% and a negative predictive value of 100%. S-Detect combined with EU-TIRADS showed a high agreement (>95%) with the gold standard. Conclusions: K-TIRADS’s positive predictive power was slightly better than the other TIRADS, suggesting greater accuracy in correctly diagnosing positive cases. S-DETECT combined with EU-TIRADS has similar results to S-Detect with ACR- and K-TIRADS in terms of sensitivity, specificity and negative predictive power. However, it has a slightly better positive predictive power, suggesting greater accuracy in correctly diagnosing ... |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
volume:15; issue:16; firstpage:1; lastpage:13; numberofpages:13; journal:DIAGNOSTICS; https://hdl.handle.net/11573/1744439 |
| DOI: |
10.3390/diagnostics15162108 |
| Availability: |
https://hdl.handle.net/11573/1744439; https://doi.org/10.3390/diagnostics15162108 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.F09381B4 |
| Database: |
BASE |