Current Medicine Research and Practice (Jan 2024)

Classifying thyroid nodules with the American College of Radiology Thyroid Imaging Reporting and Data System: A simple and cost-effective approach for assessing malignancy risk

  • Pavani Muthoju,
  • Rabiya Baseri Nelofar,
  • Pravalya Chaparala

DOI
https://doi.org/10.4103/cmrp.cmrp_35_23
Journal volume & issue
Vol. 14, no. 1
pp. 3 – 10

Abstract

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Background: Thyroid nodules are common, with up to 68% of adults having them. Ultrasonography is commonly used to examine them, but cannot determine if they are benign or malignant. High-res ultrasonography can detect disease before diagnosis but confirmation requires an invasive procedure, fine-needle aspiration cytology (FNAC), which has risks. Thyroid Imaging Reporting and Data System (TI-RADS) classifies nodules based on ultrasound findings, providing objectivity and guidance. Aim: The aim of this study is to evaluate the ultrasound characteristics of thyroid nodules & categorize them using the ACR-TIRADS category based on suspicious ultrasound findings, assess the malignancy risk and co-relate with the pathological(FNAC) findings. Materials and Methods: A study involving 50 participants was conducted in the department of radiodiagnosis at our institute to assess thyroid nodules using ultrasound. The patients underwent ultrasound examination and FNAC, and the results were analysed using Microsoft Excel 2016. Results: Out of the 50 cases, 88% had single nodules and 72% were classified as TI-RADS 3, 20% as TI-RADS 4 and 8% as TI-RADS 5. The FNAC results revealed benign and malignant nodules. All patients with TI-RADS 3 criteria were benign, 80% of those with TI-RADS 4 criteria were benign and all patients with TI-RADS 5 criteria were malignant. Conclusion: The study concludes that the American College of Radiology (ACR) TI-RADS scoring system is an effective and practical way to categorise thyroid nodules using ultrasound. It provides a level of certainty about the likelihood of malignancy and helps healthcare providers make informed decisions about which nodules require biopsy, monitoring or no further action based on their ultrasound characteristics. This system reduces the need for unnecessary biopsies and surgeries, making it a cost-effective solution.

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