Background/aim: To investigate the reliability of fine-needle aspiration biopsy (FNAB) in thyroid nodules and benign/malignant discrimination, particularly in large nodules.
Materials And Methods: A retrospective analysis of 1466 nodules in 402 patients with thyroid nodules who underwent thyroid surgery was made. The pathologic results of the thyroid nodules from preoperative FNAB and postoperative surgical pathology results were compared.
Results: FNAB was found to be in accordance with the postoperative pathologic results. A concordance between the FNAB and postoperative pathologic results, particularly in nodules less than 3 cm in size, was detected. However, a similar finding was not detected in nodules larger than 3 cm in size. The rates, calculated without taking into consideration the nodule dimensions, were found to be: sensitivity, 47.65%; specificity, 93.98%; false-negative, 52.35%; and false-positive 6.02%
Conclusion: In our experience, the false-negative rate of FNAB in nodules larger than 3 cm was high. Therefore, we have concluded that in the event of malignant FNAB, this rate is significant; however, in the event of benign FNAB, it should not be trusted too much.
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http://dx.doi.org/10.3906/sag-1312-56 | DOI Listing |
BMJ Open
January 2025
Department of Internal Medicine, Federal University of Rio Grande do Norte, Natal, Brazil.
Introduction: Until now, the thyroid cancer case number has increased, and it is not entirely possible to attribute this continuous growth to more meticulous thyroid nodule selection and more accurate diagnostic techniques. While there is currently no conclusive evidence linking dietary factors to thyroid cancer, certain dietary patterns seem to have an impact on the development of the disease. There are interesting connections among diet, environment, metabolism and thyroid carcinogenesis; a deeper comprehension of the underlying mechanisms should help the identification of modifiable risk factors for thyroid cancer.
View Article and Find Full Text PDFLangenbecks Arch Surg
January 2025
Department of General Surgery, Sanatorio Otamendi & Miroli (Otamendi & Miroli Hospital), University of Buenos Aires, Buenos Aires, Argentina.
Thyroid cancer is a common malignancy that requires comprehensive clinical evaluation prior to adequate surgical management. Over the last three decades thyroid surgery has tripled and is considered one of the most commonly performed procedures in general surgery. These procedures are associated with potential postoperative complications with significant deterioration in the patient's quality of life.
View Article and Find Full Text PDFJ Pediatr Endocrinol Metab
January 2025
Department of Otolaryngology, Pendik Training and Research Hospital, Marmara University, Istanbul, Türkiye.
Objectives: Surgery interventions for thyroid disorders are rare in pediatric population. This study aims to present our institution's 10-year experience regarding the surgical treatment and outcomes of thyroid pathologies in children and review the literature.
Methods: All pediatric patients who underwent thyroid surgery at our institution from April 2013 to October 2023 were retrospectively reviewed.
Phys Med Biol
January 2025
Beijing institute of control and electronic technology, 51 Beilijia, Muxidi, Xicheng District, Beijing 100038, Beijing, 100038, CHINA.
Objective Ultrasound is the predominant modality in medical practice for evaluating thyroid nodules. Currently, diagnosis is typically based on textural information. This study aims to develop an automated texture classification approach to aid physicians in interpreting ultrasound images of thyroid nodules.
View Article and Find Full Text PDFInt J Comput Assist Radiol Surg
January 2025
Department of Radiology, University of Chicago, Chicago, IL, USA.
Purpose: Thyroid nodules are common, and ultrasound-based risk stratification using ACR's TIRADS classification is a key step in predicting nodule pathology. Determining thyroid nodule contours is necessary for the calculation of TIRADS scores and can also be used in the development of machine learning nodule diagnosis systems. This paper presents the development, validation, and multi-institutional independent testing of a machine learning system for the automatic segmentation of thyroid nodules on ultrasound.
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