ArticleBiomedical engineering online2018
A novel TIRADS of US classification.
Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Trial
- The Importance of the Taller-than-Wide Feature and the Dimensions of Focal Thyroid Lesions in Assessing the Risk of Malignancy.Diagnostics (Basel, Switzerland) · 2026Article
- TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.Journal of ultrasound · 2025Article
- Thyroid nodule and lymph node metastasis assessment from ultrasound images using deep learning.Frontiers in neuroscience · 2025Article
- A Rare Case of Papillary Thyroid Carcinoma in Marine-Lehnhart Syndrome-Indication for Biopsy of Hot Thyroid Nodules?JCEM case reports · 2024Article
- Differentiation of Benign and Malignant Thyroid Nodules with ANFIS by Using Genetic Algorithm and Proposing a Novel CAD-Based Risk Stratification System of Thyroid Nodules.Diagnostics (Basel, Switzerland) · 2023Article
- Concordance between TIRADS and Cytology in Thyroid Nodule.Iranian journal of otorhinolaryngology · 2022Article
- Observation Variation in Ultrasonography Assessment of Thyroid Nodules.Asia Oceania journal of nuclear medicine & biology · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundThyroid imaging reporting and data system (TIRADS) is the assessment of a risk stratification of thyroid nodules, usually using a score. However, there is no consensus as to the version of TIRADS for reporting the results of thyroid ultrasound in clinic. The objective of this study is to develop a practical TIRADS with which to categorize thyroid nodules and stratify their malignant risk.
methodsA TIRADS scoring system was developed to provide more decision levels than standard scoring through the selection of the ultrasound features which include the calcification shape, margins, taller-than-wide, internal echo, blood flow quantization of features, setting of the weight, and calculation of the score. Ultimately, the accuracy of our TIRADS was evaluated by comparing with the results of current vision of TIRADS and thyroid radiologist in 153 patients who had US-guided fine-needle aspiration biopsy.
resultsClassification results showed that the total accuracy reached 97% (100% of malignant and 95% of the benign) in 153 cases (benign:78, malignant:75). The percentages of malignancy is defined in our TIRADS were as follows: TIRADS 2 (0% malignancy), TIRADS 3 (3.6% malignancy), TIRADS 4 (17-75% malignancy), and TIRADS 5 (98% malignancy).
conclusionsWe established a novel TIRADS to predict the malignancy risk of the thyroid nodules based on six categories US features by a scoring system, which included a standardized vocabulary and score and a quantified risk assessment. The results showed that objective quantitative classification of thyroid nodules by our TIRADS can be useful in guiding management decisions.
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