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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
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Prediction of thyroid nodule malignancy using thyroid imaging reporting and data system (TIRADS) and nodule size
Azin Shayganfar1, Peyman Hashemi1, Mahsa Masjedi Esfahani1
1Department of Radiology, Isfahan University of Medical Sciences, Isfahan, Iran.
Clinical Imaging
|January 14, 2020
Summary
Thyroid Imaging Reporting and Data System (TIRADS) scores of 4 and 5, combined with nodule size under 12 mm, strongly indicate malignancy. These factors are valuable for predicting thyroid nodule cancer risk.
Area of Science:
- Radiology
- Oncology
- Endocrinology
Background:
- Thyroid Imaging Reporting and Data System (TIRADS) aids in assessing thyroid nodule malignancy risk.
- Thyroid nodule size is a critical factor in malignancy determination.
Purpose of the Study:
- To evaluate the predictive value of TIRADS and nodule size for thyroid cancer prognostication.
- To correlate sonographic features with Bethesda classification outcomes.
Main Methods:
- Cross-sectional study involving 239 patients with thyroid nodules.
- Utilized TIRADS classification for ultrasonography and FNA biopsy based on Bethesda categorization.
- Statistical analysis using SPSS to determine cutoff points and predictive values.
Main Results:
- TIRADS ≥4 demonstrated 91.67% sensitivity and 52.8% specificity for detecting malignant nodules.
- An inverse relationship was found between nodule size and malignancy risk.
- A 12 mm cutoff for nodule size was identified for predicting malignancy.
Conclusions:
- Thyroid nodules with TIRADS 4-5 and diameter <12 mm are highly suspicious for malignancy.
- These findings suggest TIRADS and nodule size are sensitive predictors of thyroid cancer.
- Consider fine needle aspiration biopsy for suspicious nodules based on these criteria.
