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İNCAZ, SEFA

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İNCAZ

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SEFA

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2022 - 20242
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Subject: Klinik Tıp ×

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    PublicationOpen Access
    A single-center multidisciplinary study analyzing thyroid nodule risk stratification by comparing the thyroid imaging reporting and data system (TI-RADS) and American thyroid association (ATA) risk of malignancy for thyroid nodules
    (2022-01-01) ASYA, ORHAN; YUMUŞAKHUYLU, ALİ CEMAL; ENVER, NECATİ; İNCAZ, SEFA; GÜNDOĞMUŞ, CEMAL AYDIN; ERGELEN, RABİA; BAĞCI ÇULÇİ, PELİN; OYSU, ÇAĞATAY; ASYA O., YUMUŞAKHUYLU A. C. , ENVER N., Gündoğdu Y., Abuzaid G., İNCAZ S., GÜNDOĞMUŞ C. A. , ERGELEN R., Bağcı P., OYSU Ç.
    © 2022 Elsevier LtdObjectives: The thyroid imaging reporting and data system (TI-RADS) and 2015 American Thyroid Association (ATA) guidelines are two well-known risk stratification systems for classifying thyroid nodules based on cancer risk. This study aims to evaluate the diagnostic efficacy of these two systems in predicting malignancy in patients undergoing thyroid surgery. Methods: We studied data on 120 individuals who were scheduled to undergo surgery for benign or malignant nodular diseases of the thyroid gland between October 2017 and October 2019. The TI-RADS category and ultrasound pattern based on ATA guidelines were assigned to dominant thyroid nodule categories by two experienced radiologists blinded to patients’ previous thyroid ultrasonography and fine-needle aspiration biopsy results. A pathologist with experience in thyroid diseases blinded to patients’ sonographic and clinical data reviewed the thyroidectomy specimens. Results: A total of 120 patients, 88 women and 32 men, were included in our study. Final histopathological results were as follows: 50% (n=60) papillary thyroid carcinoma, 36.6% (n=44) benign nodular thyroid diseases, 4.1% (n=5) follicular adenoma, 2.5% (n=3) hurtle cell adenoma, 1.7% (n=2) follicular thyroid carcinoma, 1.7% (n=2) medullary thyroid carcinoma, 1.7% (n=2) hurtle cell carcinoma, and 1.7% (n=2) follicular tumor of uncertain malignancy potential. The sensitivity, specificity, positive predictive value, and negative predictive value for TI-RADS were 80%, 56%, 72%, and 67%, respectively, and that for ATA were 80%, 64%, 76%, and 69%, respectively. Conclusion: The TI-RADS and ATA showed similar rates of sensitivity, specificity, NPV, and PPV. Our observed risk of malignancy was higher than expected for the ACR TI-RADS 3–5 categories and the very low, low, and intermediate suspicion risk strata in the ATA guidelines. We found no difference between observed and expected malignancy risk for the ACR TI-RADS 2’s and ATA\"s high suspicion categories.
  • Thumbnail Image
    PublicationOpen Access
    Texture Analysis of Thyroid Nodules Using Computed Tomography: Is it a Viable Method for Objective Assessment of Thyroid Nodules?
    (2024-01-01) İNCAZ, SEFA; YUMUŞAKHUYLU, ALİ CEMAL; İncaz S., Kavak Ö. T., Kersin B., YUMUŞAKHUYLU A. C.
    Objective: Computed aided detection (CAD) systems can be developed to help radiologists in the accurate interpretation of computed tomography (CT) images. The recently popularised texture analysis method allows for qualitative and quantitative evaluation by analysing the grey-level distribution and relationships within an image. We aimed to compare the ratios of texture analysis data in the differentiation of benign-malignant nodules with the proportions of radiologists in the distinction between benign and malignant nodules and to compare the results. Materials and Methods: Retrospectively, the data of 80 patients who underwent thyroidectomy and had contrast-enhanced neck CT preoperatively were analysed. Two radiologists, experienced in head and neck radiology, blinded to the patients’ data evaluated neck CT images. Manual marking was performed and scanned to take tissue sections from the nodule area in transverse contrast-enhanced CT images, and the size of the nodule in the contralateral normal thyroid parenchyma was almost equal. Results: The computed tomography texture analysis (CTTA) model achieved the highest sensitivity of 81.4%, followed by the first radiologist at 51.2% and the second radiologist at 55.8%. Additionally, the CTTA model achieved the highest accuracy at 61.3%, followed by the first radiologist at 41.3% and second radiologist at 47.5%. On average, the CTTA model performed significantly better than the two radiologists, especially with regard to sensitivity. Conclusion: The CTTA model was superior to both radiologists in differentiating between benign and malignant thyroid nodules. Medical experts can benefit from CTTA-based solutions to extend their understanding of thyroid nodules in their routine practise.