Comparison of diagnostic accuracy and utility of artificial intelligence-optimized ACR TI-RADS and original ACR TI-RADS: a multi-center validation study based on 2061 thyroid nodules.

Ying LiuXiaoxian LiCuiju YanLongzhong LiuYing LiaoHongyan ZengWeijun HuangQian LiNansheng TaoJian-Hua Zhou

Published in: European radiology (2022)

• AI TI-RADS assigned lower TI-RADS risk levels than ACR TI-RADS, showing similar sensitivity but higher specificity. • Half of the benign nodules can be downgraded of which 42.3% of biopsy nodules avoided unnecessary fine-needle aspiration (FNA). • AI TI-RADS had a better overall inter-rater agreement.

Keyphrases

artificial intelligence
fine needle aspiration
ultrasound guided
machine learning
big data
deep learning