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The reliability of TIRADS classification in predicting thyroid malignancy based on ultrasound findings in Mosul city
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Introduction and Aim: Ultrasound of the thyroid gland is a routine procedure. Nodules are the most common disorders seen and analyzed by ultrasound. The study purpose was to show how accurate ultrasonography was at identifying benign from malignant nodules using (Thyroid Imaging Reporting and Data System TIRADS) categories. High-frequency ultrasonography scanning of the neck and thyroid glands offers useful information and anatomical images.
Materials and Methods: This study involved 495 patients who were subjected to a thyroid ultrasound imaging from December 2019 to December 2020. The ultrasound and evaluation was performed by a professional Radiologist by means of a transducer with linear-array (between 5 - 12 MHz) (DC-30, Shenzhen Mindray Bio-Medical Electronics Co., Ltd). Nodules detected were evaluated for composition, echogenicity, boundary, shape and echogenic foci. Each attribute was recorded using the standardized scoring system provided by the ACR Thyroid Imaging Reporting and Data System (ACR TI-RADS). The scores obtained, were used in classifying the nodules as TI-RADS 1, 2, 3, 4a, 4b, and 5 to define risk levels of malignant nodule.
Results: TIRADS approach was used to assess the thyroid ultrasound data obtained and the nodules categorized created on ultrasound features such as irregular edges, shape, tall rather wide, hypo echogenic, calcified, and vascular. The TIRAD 3 category was the most common accounting for about 251 cases (52.73 percent of the calculated diagnostic results, which included specificity (50%), sensitivity (96.59%), positive (97.21%) and negative (55.17%) predictive values. The study revealed 26 (4.25%) of the nodules to be cancerous.
Conclusion: Since the TIRADS system of categorization is a good technique for predicting malignancies in thyroid nodules, we employ ultrasound as the first diagnostic tool for efficiently finding and classifying thyroid nodules.
Indian Association of Biomedical Scientists
Title: The reliability of TIRADS classification in predicting thyroid malignancy based on ultrasound findings in Mosul city
Description:
Introduction and Aim: Ultrasound of the thyroid gland is a routine procedure.
Nodules are the most common disorders seen and analyzed by ultrasound.
The study purpose was to show how accurate ultrasonography was at identifying benign from malignant nodules using (Thyroid Imaging Reporting and Data System TIRADS) categories.
High-frequency ultrasonography scanning of the neck and thyroid glands offers useful information and anatomical images.
Materials and Methods: This study involved 495 patients who were subjected to a thyroid ultrasound imaging from December 2019 to December 2020.
The ultrasound and evaluation was performed by a professional Radiologist by means of a transducer with linear-array (between 5 - 12 MHz) (DC-30, Shenzhen Mindray Bio-Medical Electronics Co.
, Ltd).
Nodules detected were evaluated for composition, echogenicity, boundary, shape and echogenic foci.
Each attribute was recorded using the standardized scoring system provided by the ACR Thyroid Imaging Reporting and Data System (ACR TI-RADS).
The scores obtained, were used in classifying the nodules as TI-RADS 1, 2, 3, 4a, 4b, and 5 to define risk levels of malignant nodule.
Results: TIRADS approach was used to assess the thyroid ultrasound data obtained and the nodules categorized created on ultrasound features such as irregular edges, shape, tall rather wide, hypo echogenic, calcified, and vascular.
The TIRAD 3 category was the most common accounting for about 251 cases (52.
73 percent of the calculated diagnostic results, which included specificity (50%), sensitivity (96.
59%), positive (97.
21%) and negative (55.
17%) predictive values.
The study revealed 26 (4.
25%) of the nodules to be cancerous.
Conclusion: Since the TIRADS system of categorization is a good technique for predicting malignancies in thyroid nodules, we employ ultrasound as the first diagnostic tool for efficiently finding and classifying thyroid nodules.
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