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Indexed/Abstracted in: EMBASE, PubMed/MEDLINE, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 1,118
Online ISSN 1827-1634
Saiegh L. 1, Shechner C. 1, Dickstein G. 1, Sheikh-Ahmad M. 1, Reut M. 1, Odeh M. 2, Toubi A. 3, Bejar J. 4
1 Endocrinology Department Bnai‑Zion Medical Center, Haifa, Israel;
2 Department of Internal Medicine A Bnai‑Zion Medical Center, Haifa, Israel;
3 Ultrasound unit, Radiology Department Bnai-Zion Medical Center, Haifa, Israel;
4 Pathology Department Bnai‑Zion Medical Center, Haifa, Israel
Aim: The aim of this paper was to examine the diagnostic value of several cytological and ultrasonographic features in predicting malignancy in thyroid follicular neoplasms.
Methods: The sample of the study consisted of 145 patients, who have had the diagnosis of follicular neoplasm on US guided fine-needle aspiration (FNA), and had undergone thyroidectomy. The cytological slides and the ultrasonographic images were reviewed, and several ultrasonographic and cytological features were evaluated and correlated with final histology.
Results: Histological diagnosis of malignancy was obtained in 14.5% of the patients, papillary carcinoma being the most frequent (66% of malignancies). The cytological and ultrasonographic features that have been associated with malignancy were: micro-fragments (P<0.00001), overlapping (P<0.005), hypercellularity (P<0.009), micronucleoli (P<0.013), atypical features (P<0.027), nodule size larger than 2 cm (P<0.029) and micro-calcifications (P<0.0002). Using the features that were statistically independent ones, which included two cytological features: micro-fragments and micronuclei, and one ultrasonographic feature: micro-calcifications, a statistical model for predicting malignancy was constructed. According to this model, it was found that the risk for malignancy is 2.65% in the absence of the three parameters, and amounts to 93.93% in the presence of all three of them.
Conclusion: In a thyroid follicular neoplasm, the cytological and ultrasonographic features that were associated with malignancy were: micro-fragments, overlapping, hypercellularity, micronucleoli, atypical features, nodule size larger than 2 cm and micro-calcifications. In an attempt to predict malignancy, we proposed a simple statistical model using only three features derived from cytological and ultrasonographic tests.