Missed Malignancies in Unbiopsied Thyroid Nodules: Diagnostic Performance of Combined TI-RADS and Bethesda Systems

Missed Malignancies in Unbiopsied Thyroid Nodules: Diagnostic Performance of Combined TI-RADS and Bethesda Systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Missed Malignancies in Unbiopsied Thyroid Nodules: Diagnostic Performance of Combined TI-RADS and Bethesda Systems Sherihan AboElyazed, Fadi Hani Wahba Mikhail, Aya Essam Ahmed, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8934299/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Purpose Thyroid nodules are a widespread pathology. While only a small percentage of cases prove to be malignant, careful preoperative evaluation is essential to identify patients who need intervention. We aimed to evaluate the diagnostic performance of preoperative ultrasound and fine-needle aspiration cytology in predicting thyroid malignancy. Methods This cross-sectional study included 100 adult patients with 145 suspicious thyroid nodules who were scheduled for hemithyroidectomy or total thyroidectomy. Postoperative histopathology was considered the reference standard. Ultrasound findings and FNAC results were compared with the final histopathology. Results Final histopathology revealed 63.5% benign and 36.5% malignant nodules, with 58% PTC being the most common malignancy; 27% of the unbiopsied nodules were found to be malignant. Malignant nodules had significantly higher TI-RADS and Bethesda scores (p-value < 0.001, 95% CI 5–5; p-value < 0.001, 95% CI 4–5, respectively), while nodule size and number showed no significant association. ROC analysis demonstrated good diagnostic performance for the Bethesda scores (0.819 AUC, 95% CI: 0.731–0.908, p 2) and the TI-RADS score (0.763 AUC, 95% CI: 0.668–0.858, p 4). Univariate analysis showed hypoechogenicity, taller-than-wide shape, irregular or lobulated margins, and microcalcifications were strong predictors of malignancy (p < 0.001). Conclusion This study confirms that the combination of TI-RADS and Bethesda systems in preoperative thyroid nodule evaluation enhances diagnostic confidence and optimizes clinical decision-making. Ultrasound features, like taller-than-wide shape, irregular margin, hypoechogenicity, and microcalcifications, are significant indicators of thyroid malignancy, particularly PTC. Nondominant nodules in MNG may harbor neoplasms, necessitating multiple FNACs in specific cases. Thyroid Nodule TI-RADS FNAC BETHESDA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction There is an increased prevalence of thyroid nodules, reflecting the widespread use of high-resolution imaging. Epidemiological data demonstrate 2–6% of nodules detected clinically by palpation, 19–35% by ultrasound, and up to 50–60% in autopsy series [ 1 , 2 ]. Most nodules are benign, but 5–15% are malignant [ 3 , 4 ]. Thyroid neoplasms are classified according to tumor behavior, differentiation, and histologic variants into benign lesions, low-risk neoplasms, and malignant thyroid neoplasms, according to the last WHO classification [ 5 ]. Thyroid ultrasound is a non-invasive, widely available imaging technique considered the first-line imaging modality for thyroid nodules [ 6 ]. The American College of Radiology developed the TI-RADS scoring system, which assigns scores to composition, echogenicity, shape, margin, and echogenic foci, ultimately stratifying nodules from TR1 (benign) to TR5 (high suspicion). This system's goal is to make interpretations less subjective [ 6 , 7 ]. Fine needle aspiration cytology (FNAC) remains an essential component of preoperative assessment. The Bethesda System for Reporting Thyroid Cytopathology arranges FNAC results into six categories, each associated with a specific malignancy risk [ 8 , 9 ]. The definitive postoperative histopathology is the gold standard for diagnosing thyroid malignancy [ 10 ]. Many studies have examined ultrasound-based risk systems, including TI-RADS, in relation to histopathological outcomes, consistently indicating a strong correlation between elevated TI-RADS categories and malignancy [ 7 , 10 ]. However, differences across populations and institutions indicate that further validation is needed to optimize cutoff values and confirm predictive accuracy. Methods This cross-sectional analytical study was conducted at the Endocrinology Clinic and the Endocrine Surgical Department of Ain Shams University Hospital over one year (from August 2024 to July 2025), after the study protocol had been approved by the local Research Ethics Committee of the Faculty of Medicine, Ain Shams University (FMASU R187/2024). Before enrolling, all participants signed a written consent. Patient identification was kept strictly confidential. Eligibility Criteria The study included adult patients with suspicious thyroid nodules diagnosed by neck ultrasonography and indicated for FNAC or large nodular goiter causing pressure symptoms, and then planned for surgical excision (hemi- or total thyroidectomy). Histopathological examination of the excised specimens was considered the gold standard. Patient Assessment All patients received a structured clinical evaluation, including detailed history taking and clinical examination. Laboratory investigations included thyroid function tests (FT3, FT4, and TSH) performed by the ECLIA method. U/S Assessment High-resolution ultrasonography of the thyroid gland was conducted by the radiologist, who has 10 years of experience in thyroid U/S, to evaluate thyroid nodules according to the ACR TI-RADS score [ 6 ]. The radiologist utilized an 8- to 17-MHz linear probe to examine thyroid nodule characteristics. FNAC was taken from nodules indicated for it, using a 10 mL syringe and a 23-gauge needle with ultrasound guidance. Samples were smeared on a glass slide and fixed with 95% ethanol. Histopathological Assessment For FNAC, alcohol-fixed slides were stained by hematoxylin and eosin (H&E), examined, and reported according to the Bethesda system for reporting thyroid pathology [ 11 ]. Finally, patients underwent surgical excision (hemi- or total thyroidectomy). For excisional specimens, the tissue was first properly fixed in 10% neutral-buffered formalin for 24 hours, then processed through graded alcohols for dehydration, cleared in xylene, and embedded in paraffin blocks. Sections are cut to a thickness of about 4–5 µm, then deparaffinized in xylene, and rehydrated through decreasing alcohol concentrations to water. Finally, sections were stained by H&E and evaluated according to the 2022 WHO classification of endocrine [ 5 ]. Operative Details The patient was placed on the operating table in a supine position with a reverse Trendelenburg tilt and the neck extended. After skin preparation and administration of general anesthesia, a transverse incision was made 2–3 cm above the sternal notch, and the skin, subcutaneous tissue, and platysma were incised to expose the cervical fascia. The investing fascia was opened in the midline, and the strap muscles were elevated to show and move the thyroid gland. Dissection started at the superior pole, where the superior thyroid vessels were safely separated from the recurrent laryngeal nerve (RLN). After identifying and exposing the RLN, the vessels to the lower pole were ligated. The thyroid lobe was carefully dissected from the trachea. After complete removal, meticulous hemostasis was performed. A Hemovac drain was placed, the strap muscles were re-approximated, and the platysma and skin were closed in layers. Then the wound was cleaned, and a sterile dressing was placed. Data Analysis We gathered, revised, categorized, and entered data into the Statistical Package for Social Science (SPSS 27) software. Descriptive statistics were calculated using standard deviation (± SD) and range for age, TSH, FT3, and FT4 levels, and median and interquartile range (IQR) for nodule size, TI-RADS, and Bethesda scores. And we used frequency and percentage of non-numeric data. Analytical statistics, including the Student’s T test, were used to determine the statistical differences in age means and thyroid profiles; the Mann-Whitney test (U) was employed to assess the statistical differences in nodule size, TI-RADS, and Bethesda scores between the two studied groups. We used the chi-square (Fisher’s exact test when needed) to assess the association between each ultrasound feature and malignant pathology. Univariate analysis with odds ratios (OR) and 95% confidence intervals (CI) was calculated to estimate the association between each ultrasound feature and malignancy risk. The ROC curve was used to figure out the diagnostic performance of the TI-RADS and Bethesda systems for malignancy prediction. The P-value represents the level of significance (P > 0.05: Non-significant (NS), P < 0.05: Significant (S), and P < 0.001: Highly significant). Results One hundred euthyroid patients with suspicious thyroid nodules who were indicated for thyroidectomy were included in this study. Among these patients, 89 (89%) were female, 53 (60%) were diagnosed with benign pathology, and 36 (40%) with malignant pathology. The remaining 11 (11%) patients were male, of whom 5 (45%) had benign pathology, and 6 (55%) had malignant pathology. Descriptive analysis of the studied population is presented in Table 1. 100 nodules were biopsied preoperatively according to ultrasound criteria for FNAC, and 45 nodules were not indicated for biopsy. 145 nodules were analyzed in relation to preoperative assessment (ultrasound with or without FNAC) and postoperative histopathology. 92 (63.45%) nodules were benign, and 53 (36.55%) nodules were malignant in the postoperative histopathology (Figs. 1, 2). One patient had mixed multifocal pathologies: papillary carcinoma at the left lobe and NIFTP at the isthmus, and another patient had papillary carcinoma at the right lobe and invasive EFVPTC at the isthmus. We compared U/S and FNAC findings of benign and malignant nodules. Results indicated that the overall TI-RADS and BETHESDA scores were significantly higher in the malignant group ( p -value < 0.001, 95% CI 5-5; p-value < 0.001, 95% CI 4-5, respectively). However, there were no significant differences in nodule size, location on U/S, or number of nodules in the gland (Table 2). We divided the studied nodules based on preoperative FNAC into biopsied and unbiopsied nodules and compared these groups with respect to U/S criteria and final pathology results. Results revealed significant differences, as biopsied nodules were larger in size, had a higher incidence of echogenic foci, and some exhibited irregular margins or extrathyroidal extension (p-value < 0.05) as well as higher overall TI-RADS scores (p-value < 0.05, 95% CI 4-5). It was observed that 12 (27%) of the unbiopsied nodules were found to be malignant in the final histopathological evaluation (Table 3). We analyzed the percentage distribution of postoperative histopathological outcomes across the TI-RADS scores of all studied nodules (n = 145) (Fig. 3). TI-RADS 2 were predominantly benign (83.3%), and only 16.7% were malignant nodules. TI-RADS 3 showed predominant benign pathology (80.3%) and 19.7% malignant pathology, with 6.6% PTC. TI-RADS 4 demonstrated a similar pattern to TR3, with a modest increase in the incidence of malignant pathology (27.1%); however, benign pathology remained predominant (72.9%). TI-RADS 5 showed the highest malignant potential (90%), with 76.7% PTC, alongside small percentages of other entities. However, 10% of the nodules were benign. Additionally, the percentage distribution of histopathological outcomes was analyzed across the preoperative Bethesda categories of all biopsied nodules (n = 100) (Fig. 4). Bethesda I (Nondiagnostic) was largely benign (80.0%), showing a predominance of FND. And 20% were malignant nodules, with 6.7% PTC. Bethesda II (Benign) was predominantly benign (82.6%). 17.4% were diagnosed as malignant nodules, with 4.3% PTC. Bethesda III (AUS/FLUS) showed greater heterogeneity, including 46.2% diagnosed as benign pathology and 53.8% of malignant nature, with 15.4% PTC. Bethesda IV (FN/SFN) exhibited a higher proportion of malignancy (72.7%), with PTC (36.4%). And only 27.3% of nodules were benign. Bethesda V–VI (Suspicious for Malignancy and Malignant) were exclusively malignant, showing 100% PTC. Receiver Operating Characteristic (ROC) analysis was performed to assess the diagnostic performance of both the TI-RADS and Bethesda systems in differentiating benign from malignant thyroid nodules. A TI-RADS score of more than 4 demonstrated an AUC of 0.763 (95% CI: 0.668–0.858, p < 0.001) , with 50.94% sensitivity , 96.74% specificity , 90% PPV, and 77.4% NPV.The Bethesda score of more than 2 yielded an AUC of 0.819 (95% CI: 0.731–0.908, p < 0.001) , with 73.17% sensitivity and 84.75% specificity , with 76.9% PPV and 82% NPV, showing superior discriminative power compared to TI-RADS (Fig. 5). Additionally, ROC analysis was conducted to assess the diagnostic accuracy of the TI-RADS and Bethesda systems for PTC. Using a cut-off value > 4, TI-RADS demonstrated an AUC of 0.871 (95% CI: 0.788–0.955, p 3 , yielding an AUC of 0.91 (95% CI: 0.822–0.999, p < 0.001) , 79.17% sensitivity , 94.92% specificity , 86.4% PPV, and 91.8% NPV (Fig. 6). We used univariate analysis to evaluate the diagnostic performance of key U/S features in relation to postoperative histopathological diagnoses with a specific focus on PTC separately (Tables 4 and 5). Nodule Composition (Solid vs. Cystic/Spongiform/Mixed) Solid composition was observed more frequently in all malignant nodules (87%) and in PTC (87.1%) than in benign ones (73.9%). However, this difference did not reach statistical significance ( p = 0.13, OR = 2.38, 95% CI = 0.76–7.51; p = 0.06, OR = 2.31, 95% CI = 0.923–5.828, respectively), with 26% specificity and sensitivity of 86.8% and 87.1%, respectively, with diagnostic accuracy of 48.3% and 41.5%, respectively. Nodule Echogenicity (Hypoechoic / Very Hypoechoic vs. Others) Hypoechoic or very hypoechoic nodules were significantly more prevalent in malignant nodules (58.5%) and in PTC (71%) compared to benign cases (26.1%) ( p < 0.001, OR = 3.99, 95% CI 1.95–8.18; p < 0.001, OR = 6.93, 95% CI = 2.80–17.11, respectively). It demonstrated 73.9% specificity and sensitivity of 58.5% and 71%, respectively, with diagnostic accuracy of 68% and 73%, respectively. Nodule Shape (Taller-than-wide vs. Wider-than-tall) The “taller-than-wide” configuration was found in 37.7% of malignant nodules and 54.8% in PTC versus only 5.4% of benign ones ( p < 0.001, OR = 10.55, 95% CI 3.66–30.4; p < 0.001, OR = 21.13, 95% CI = 6.72–66.45, respectively). It exhibited 94.6% specificity with diagnostic accuracy of 74% and 84.6%, respectively, making it one of the strongest predictors of malignancy despite low sensitivity (37.7% and 54.8%, respectively). Nodule Margin (Lobulated / Irregular / Extra-thyroidal vs Smooth / Ill-defined) Irregular or lobulated margins and evidence of extrathyroidal extension were significantly associated with malignant nodules (32.1%), being higher in PTC (51.6%), and only 4.4% of benign nodules ( p < 0.001, OR = 10.39, 95% CI 3.27–33.01; p < 0.001, OR = 23.5, 95% CI 6.89–79.87, respectively). It demonstrated 95.7% specificity and sensitivity of 32% and 51.6%, respectively, with diagnostic accuracy of 72.4% and 84.5%, respectively. Echogenic foci (Microcalcifications vs Others) Microcalcifications were observed in 35.9% of malignant and 45.2% of PTC versus 10.9% of benign nodules ( p < 0.001; OR = 4.58, 95% CI 1.93–10.87; p < 0.001, OR = 6.75, 95% CI = 2.57–17.73, respectively). It exhibited 89.1% specificity and sensitivity of 35.9% and 45.2%, respectively, with diagnostic accuracy of 69.66% and 78%, respectively. Table 1: Descriptive Analysis All Patients (n=100) Benign Group* (n = 58) Malignant Group* (n = 42) Test of significance* value p-value Gender Male 11 (11%) 5 (8.62%) 6 (14.29%) X 2 = 0.799 0.372 Female 89 (89%) 53 (91.38%) 36 (85.71%) Age (years) Mean ± SD (95% CI) 41.7 ± 12.66 (39.19 - 44.21) 41.1 ± 12.54 (37.81 - 44.4) 42.52 ± 12.93 (38.5 - 46.55) t= -0.552 0.582 TSH (uIU/ml) Mean ± SD (95% CI) 1.29 ± 0.84 (1.12 - 1.45) 1.15 ± 0.78 (0.95 - 1.36) 1.47 ± 0.9 (1.2 - 1.75) t= -1.922 0.058 Free T3 (pg/ml) Mean ± SD (95% CI) 2.97 ± 0.53 (2.87 - 3.08) 3.01 ± 0.54 (2.87 - 3.15) 2.92 ± 0.53 (2.76 - 3.09) t= 0.833 0.407 Free T4 (ng/dl) Mean ± SD (95% CI) 1.24 ± 0.34 (1.17 - 1.31) 1.14 ± 0.27 (1.07 - 1.21) 1.37 ± 0.37 (1.25 - 1.49) t= -3.548 0.001 # *Comparison between benign and malignant patients using the Chi-Square test (X²) and Student t-test (t). # Highly significant Table 2: Comparative analysis of postoperative final pathology concerning preoperative U/S characteristics, TI-RADS, and Bethesda scores of all studied nodules Postoperative final pathology Test of significance + Benign Malignant N (%) 95% CI for % N (%) 95% CI for % value p-value Location of nodules on U/S Right 43 (46.74%) (36.8% - 56.9%) 30 (56.6%) (43.2% - 69.3%) X 2 = 1.328 0.515 Left 42 (45.65%) (35.7% - 55.8%) 20 (37.74%) (25.6% - 51.2%) Isthmus 7 (7.61%) (3.5% - 14.4%) 3 (5.66%) (1.6% - 14.3%) Number of nodules in each gland Single 12 (20.69%) (11.8% - 32.4%) 11 (26.19%) (14.8% - 40.8%) X 2 = 0.417 0.812 2 Nodules 9 (15.52%) (8% - 26.4%) 6 (14.29%) (6.2% - 27.1%) MNG 37 (63.79%) (51% - 75.3%) 25 (59.52%) (44.5% - 73.3%) Nodule size $ Median (IQR) (95% CI) 2.8 (1.65 - 3.85) (2.5 - 3.1) 2.5 (1.4 - 3.6) (2 - 3.2) z= -0.795 0.427 TIRADS Median (IQR) (95% CI) 3 (3 - 4) (3 - 4) 5 (4 - 5) (5 - 5) z= -5.651 <0.001 # BETHESDA Median (IQR) (95% CI) 2 (2 - 2) (2 - 3) 4 (2 - 5) (4 - 5) z= -5.723 <0.001 # +Fisher’s Exact test (FE), Chi-Square test (X2), Mann-Whitney test (z). # Highly significant. * Each subscript letter denotes a subset of group categories whose column proportions do not differ significantly from each other at the .05 level. $Largest dimension (cm). Table 3. Comparative analysis of preoperative U/S features of biopsied and unbiopsied nodules by FNAB Preoperative FNAB Test of significance + Not biopsied Biopsied N (%) 95% CI for % N (%) 95% CI for % value p-value Composition Cystic/Spongiform 1 (2.22%) (0.2% - 9.9%) 0 (0%) (0% - 0%) FE 0.333 Mixed 8 (17.78%) (8.8% - 30.8%) 22 (22%) (14.8% - 30.8%) Solid 36 (80%) (66.7% - 89.6%) 78 (78%) (69.2% - 85.2%) Echogenicity Anechoic 0 (0%) (0% - 0%) 2 (2%) (0.4% - 6.3%) FE 0.349 Hyper- or isoechoic 30 (66.67%) (52.2% - 79.1%) 58 (58%) (48.2% - 67.3%) Hypoechoic 14 (31.11%) (19.1% - 45.5%) 30 (30%) (21.7% - 39.5%) Very hypoechoic 1 (2.22%) (0.2% - 9.9%) 10 (10%) (5.3% - 17%) Shape Wider than tall 40 (88.89%) (77.3% - 95.6%) 80 (80%) (71.4% - 86.9%) X 2 = 1.719 0.19 Taller than wide 5 (11.11%) (4.4% - 22.7%) 20 (20%) (13.1% - 28.6%) Margin Smooth / ill-defined 44 (97.78%) a (90.1% - 99.8%) 80 (80%) b (71.4% - 86.9%) FE 0.009 # Lobulated or irregular 0 (0%) a (0% - 0%) 12 (12%) b (6.7% - 19.4%) Extra thyroidal extension 1 (2.22%) a (0.2% - 9.9%) 8 (8%) a (3.9% - 14.5%) Echogenic foci None or large comet-tail artifacts 36 (80%) a (66.7% - 89.6%) 54 (54%) b (44.2% - 63.5%) FE 0.007 # Macrocalcifications 1 (2.22%) a (0.2% - 9.9%) 19 (19%) b (12.3% - 27.5%) Rim of calcifications 1 (2.22%) a (0.2% - 9.9%) 5 (5%) a (1.9% - 10.6%) Microcalcifications 7 (15.56%) a (7.2% - 28.1%) 22 (22%) a (14.8% - 30.8%) Nodule size $ Median (IQR) 95% CI for median 1.6 (1.2 - 2.9) (1.5 - 2.7) 3 (2.1 - 4.2) (2.9 - 3.5) z= -4.266 <0.001 ## TIRADS Median (IQR) 95% CI for median 3 (3 - 4) (3 - 4) 4 (3 - 4) (4 - 5) z= -2.373 0.018 # Final pathological findings Benign 33 (73.3%) (59.3% - 84.5%) 59 (59%) (49.2% - 68.3%) X 2 = 2.749 0.097 Malignant 12 (26.7%) (15.5% - 40.7%) 41 (41%) (31.7% - 50.8%) + Fisher’s Exact test of significance (FE), Chi-Square test of significance (X 2 ), Mann-Whitney test of significance (z). # Significant, ## Highly significant. * Each subscript letter denotes a subset of group categories whose column proportions do not differ significantly from each other at the .05 level. $ Largest dimension (cm). Table 4. Diagnostic Performance and Statistical Association of Ultrasound Features with Malignant Thyroid Nodules Post operative final pathology Sensitivity 95% CI Specificity 95% CI PPV 95% CI NPV 95% CI Accuracy 95% CI X 2 p-value OR (95% CI) Malignant Benign N (%) 95% CI N (%) 95% CI Composition Solid vs. Cystic/Spongiform/Mixed 46 (86.79%) (75.8% - 93.9%) 68 (73.91%) (64.3% - 82%) 86.79 (74.66 – 94.52) 26.09 (17.48 – 36.92) 40.35 (31.27 – 49.95) 77.42 (58.9 – 90.41) 48.28 (39.91 – 56.72) 3.319 0.068 2.319 (0.923 – 5.828) 7 (13.21%) (6.1% - 24.2%) 24 (26.09%) (18% - 35.7%) Echogenicity Hypoechoic / Very hypoechoic vs. Anechoic / Hyper- or isoechoic 31 (58.49%) (45.1% - 71%) 24 (26.09%) (18% - 35.7%) 58.49 (44.13 – 71.86) 73.91 (63.71 – 82.52) 56.36 (46.11 – 66.1) 75.56 (68.71 – 81.31) 68.28 (60.04 – 75.75) 14.997 <0.001 # 3.992 (1.948 – 8.183) 22 (41.51%) (29% - 54.9%) 68 (73.91%) (64.3% - 82%) Shape Taller than wide vs. Wider than tall 20 (37.74%) (25.6% - 51.2%) 5 (5.43%) (2.1% - 11.5%) 37.74 (24.79 – 52.11) 94.57 (87.77 – 98.21) 80 (61.45 – 90.94) 72.5 (68.01 – 76.58) 73.79 (65.85 – 80.74) 24.589 <0.001 # 10.545 (3.658 – 30.4) 33 (62.26%) (48.8% - 74.4%) 87 (94.57%) (88.5% - 98%) Margin Lobulated or irregular/ Extra thyroidal extension vs. Smooth / ill-defined 17 (32.08%) (20.7% - 45.3%) 4 (4.35%) (1.5% - 10%) 32.08 (19.92 – 46.32) 95.65 (89.24 – 98.8) 80.95 (60.14 – 92.29) 70.97 (66.9 – 74.72) 72.41 (64.38 – 79.5) 20.875 <0.001 # 10.389 (3.269 – 33.013) 36 (67.92%) (54.7% - 79.3%) 88 (95.65%) (90% - 98.5%) Echogenic foci Microcalcifications vs. None or large comet-tail artifacts / Macrocalcifications / Rim of calcifications 19 (35.85%) (24% - 49.2%) 10 (10.87%) (5.7% - 18.4%) 35.85 (23.14 – 50.2) 89.13 (80.92 – 94.66) 65.52 (48.87 – 79.07) 70.69 (66.08 – 74.91) 69.66 (61.48 – 77.01) 13.114 <0.001 # 4.582 (1.932 – 10.87) 34 (64.15%) (50.8% - 76%) 82 (89.13%) (81.6% - 94%) Chi-Square test (X²); PPV = Positive Predictive Value; NPV = Negative Predictive Value; CI = Confidence Interval; # Highly significant Table 5. Diagnostic Performance of Ultrasound Features in Predicting Papillary Thyroid Carcinoma Post operative final pathology Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) Accuracy (95% CI) X 2 p-value OR (95% CI) PTC Benign N (%) 95% CI N (%) 95% CI Composition Solid vs. Cystic/Spongiform/Mixed 27 (87.1%) (72.2% - 95.5%) 68 (73.91%) (64.3% - 82%) 87.1 (70.17 – 96.37) 26.09 (17.48 – 36.29) 28.42 (24.87 – 32.26) 85.71 (69.31 – 94.1) 41.46 (32.65 – 50.69) 2.292 0.13 2.382 (0.755 – 7.513) 4 (12.9%) (4.5% - 27.8%) 24 (26.09%) (18% - 35.7%) Echogenicity Hypoechoic / Very hypoechoic vs. Anechoic / Hyper- or isoechoic 22 (70.97%) (53.7% - 84.6%) 24 (26.09%) (18% - 35.7%) 70.97 (51.96 – 85.78) 73.91 (63.71 – 82.52) 47.83 (37.8 – 58.03) 88.31 (81.13 – 92.99) 73.17 (64.43 – 80.76) 19.949 <0.001 # 6.926 (2.803 – 17.11) 9 (29.03%) (15.4% - 46.3%) 68 (73.91%) (64.3% - 82%) Shape Taller than wide vs. Wider than tall 17 (54.84%) (37.5% - 71.3%) 5 (5.43%) (2.1% - 11.5%) 54.84 (36.03 – 72.68) 94.57 (87.77 – 98.21) 77.27 (57.77 – 89.42) 86.14 (80.78 – 90.18) 84.55 (76.93 – 90.44) 38.533 <0.001 # 21.129 (6.718 – 66.447) 14 (45.16%) (28.7% - 62.5%) 87 (94.57%) (88.5% - 98%) Margin Lobulated or irregular/ Extra thyroidal extension vs. Smooth / ill-defined 16 (51.61%) (34.5% - 68.4%) 4 (4.35%) (1.5% - 10%) 51.61 (33.06 – 69.85) 95.65 (89.24 – 98.8) 80 (59.12 – 91.71) 85.44 (80.27 – 89.43) 84.55 (76.93 – 90.44) 30.042 <0.001 # 23.467 (6.895 – 79.871) 15 (48.39%) (31.6% - 65.5%) 88 (95.65%) (90% - 98.5%) Echogenic foci Microcalcifications vs. None or large comet-tail artifacts / Macrocalcifications / Rim of calcifications 14 (45.16%) (28.7% - 62.5%) 10 (10.87%) (5.7% - 18.4%) 45.16 (27.32 – 63.97) 89.13 (80.92 – 94.66) 58.33 (40.96 – 73.86) 82.83 (77.66 – 87.0) 78.05 (69.69 – 85.01) 17.361 <0.001 # 6.753 (2.573 – 17.726) 17 (54.84%) (37.5% - 71.3%) 82 (89.13%) (81.6% - 94%) Chi-Square test (X²); PPV = Positive Predictive Value; NPV = Negative Predictive Value; CI = Confidence Interval; PTC= papillary thyroid carcinoma; # Highly significant Discussion The high prevalence of thyroid nodules with relatively low malignant potential necessitates accurate preoperative evaluation to guide management to avoid both unnecessary thyroidectomy and missed malignancies. Thyroid nodules are more prevalent in middle-aged females, which might be due to increased incidence of autoimmune thyroid disease; fortunately, most of them are of benign pathology. However, the risk of malignancy is higher in male patients. Other risk factors, like family history and exposure to irradiation, should be considered [ 12 , 13 ]. However, in our study, thyroid malignancy was found in 42% of the studied participants. Ultrasound evaluation and FNAC of thyroid nodules are the widely used available tools for preoperative assessment. Suspicion for malignancy is categorized according to the TI-RADS and the Bethesda systems [ 6 ]. In this study, we analyzed each ultrasound characteristic for malignancy risk, as well as the overall TI-RADS and Bethesda scores of each nodule, in relation to the final pathology outcomes following surgical excision. Nodule shape remains one of the most reliable indicators of malignant potential, as malignant thyroid nodules typically grow perpendicular to the thyroid capsule, indicating vertical growth that breaches normal tissue planes, resulting in a taller-than-wide appearance. Despite limited sensitivity, the high specificity of this feature, with more than a tenfold increased malignancy risk, supports its significance as a major indicator of malignancy. This finding aligns with the TI-RADS and ATA guidelines, which recognize vertical orientation as a hallmark of malignant infiltration [ 6 , 14 , 15 ]. Margin irregularity and lobulation or extrathyroidal extension indicate capsular or adjacent soft-tissue invasion; these hallmarks of malignant infiltration with more than tenfold increased malignancy risk and high specificity reinforce their diagnostic importance, particularly in PTC, which commonly exhibits an infiltrative growth pattern [ 6 , 4 , 16 ]. Microcalcifications, representing psammoma bodies histologically, were another strong predictor with a nearly fivefold increased risk of malignancy, which is a characteristic of PTC. This finding aligns with previous studies demonstrating that microcalcifications are among the most characteristic but less sensitive signs of PTC [ 6 , 15 , 17 ]. Hypoechogenicity, though less specific, was a useful complementary sign with about a fivefold increased risk of malignancy. Its moderate sensitivity and specificity support its inclusion as a secondary suspicious criterion. These findings are consistent with prior studies reporting that malignant nodules tend to be more hypoechoic than the surrounding thyroid parenchyma due to increased cellular density and reduced colloid content [ 6 , 4 , 18 ]. In contrast, solid composition alone was not significantly predictive, as many benign nodules also present with a solid pattern, limiting its diagnostic utility. This underscores the importance of combining multiple ultrasound features rather than relying on a single finding to improve diagnostic accuracy. These results align with previous studies showing that although most malignant nodules are solid, most of the solid nodules are benign [ 18 , 19 , 20 ]. Therefore, nodule composition should be interpreted cautiously and in combination with other suspicious findings rather than as an isolated malignancy indicator. The indication for FNAC of a thyroid nodule depends on the TI-RADS score and the nodule size [ 6 , 4 , 21 ]. We observed in our study that in patients with multinodular goiter (MNG), 26% of unbiopsied nodules had a malignant disease in postoperative pathology, so we recommend that in MNG, all suspicious nodules should be biopsied, irrespective of nodule size, if the nodule size is suitable for FNAC (~ 1 cm in the largest dimension). This comes in line with a study by Paksoy et al., who stated that in MNG, nondominant nodules should be biopsied regardless of the nodule size if the ultrasonographic criteria are suspicious [ 22 ]. Additionally, Wong et al. mentioned that in MNG, if more than one nodule had criteria for FNAC, it should be biopsied [ 23 ]. In this study, both the TI-RADS and Bethesda systems demonstrated statistically significant diagnostic performance for predicting thyroid malignancy. Lower scores were largely associated with benign pathology, whereas higher categories correlated strongly with malignant pathology, particularly PTC. TI-RADS showed an AUC of 0.763 (95% CI: 0.668–0.858) with optimal diagnostic performance at a cut-off value > TR4. Similarly, in a comparative study using TI-RADS cutoffs, TR4/TR5 demonstrated an AUC of 0.77 (95% CI 0.74–0.81) [ 24 ]. The TI-RADS system, although highly specific, demonstrated lower sensitivity, suggesting its value in predicting malignancy when higher-risk sonographic features are present but less sensitivity for detecting all malignant cases. The Bethesda system showed slightly superior performance compared to TI-RADS, reflecting its greater diagnostic precision when cytological evaluation is available. The Bethesda system exhibited higher accuracy with an AUC of 0.819 (95% CI: 0.73–0.91), at a cut-off of Bethesda 3. In line with this, an observational study by Tan et al. found that Bethesda 3 showed an AUC of 0.91 (95% CI: 0.87–0.96) [ 25 ]. Our findings emphasize the complementary strength of both systems: TI-RADS serves as an effective noninvasive screening tool for identifying nodules that require cytological assessment, whereas Bethesda provides a suggestive histological diagnosis. The combination of both systems in preoperative thyroid nodule evaluation enhances diagnostic confidence and optimizes clinical decision-making regarding surgical excision or follow-up. However, the presence of low-risk neoplasms like NIFTP, WDT-UMP, and various types of malignant pathologies, other than PTC, in varying percentages across all categories points out the diagnostic overlap in follicular-patterned lesions. This indicates that physicians require new, accessible, and widely used assessment tools for evaluating thyroid nodules to optimize clinical decision-making. Limitations and Future Directions The relatively modest sensitivity of many features suggests that some malignant nodules will evade detection by ultrasound alone. The cohort size may affect the confidence intervals and generalizability. Low-risk neoplasms and follicular-patterned malignant nodules are challenging to evaluate preoperatively, which has led to a research area focused on improving the preoperative assessment of thyroid nodules. Conclusion This study confirms that the combination of the TI-RADS and Bethesda systems in preoperative thyroid nodule evaluation enhances diagnostic confidence and optimizes clinical decision-making. Ultrasound features, like taller-than-wide shape, irregular margin, hypoechogenicity, and microcalcifications, are significant indicators of thyroid malignancy, particularly PTC. Nondominant nodules in MNG may harbor neoplasms, necessitating multiple FNACs in specific cases. Abbreviations FNAC Fine Needle Aspiration Cytology FND Thyroid Follicular Nodular Disease NIFTP Non-Invasive Follicular Thyroid Neoplasm With Papillary-Like Nuclear Features WD-UMP Well-Differentiated Tumor Of Uncertain Malignant Potential FTC Follicular Thyroid Carcinoma IEFV-PTC Invasive Encapsulated Follicular Variant Papillary Thyroid Carcinoma PTC Papillary Thyroid Carcinoma MTC Medullary Thyroid Carcinoma TI-RADS Thyroid Imaging Reporting and Data System U/S Ultrasonography MNG Multinodular Goiter ROC Receiver Operating Characteristic PPV Positive Predictive Value NPV Negative Predictive Value Declarations Ethical approval and informed consent The local Research Ethics Committee of the Faculty of Medicine, Ain Shams University, Federal Wide Assurance No. FWA 000017585, had approved the protocol of this study on the 8th of August 2024, ID FMASU R187/2024, before the start of work. Informed consent was obtained from all patients who participated in the study to use their workup data for the research. Consent for Publication Patients provided consent for the use of their ultrasound and pathology images for illustration in the manuscript. Data Availability Patients’ laboratory, images, and pathology data are available upon reasonable request Funding This work didn’t receive any financial funding from any organization. Competing of Interests No conflicts of interest in this study. Clinical trial number: not applicable. Author Contribution SA and AMMAS formulated the study conception and design. Data collection, entry, and statistical analysis were done by SA, SSA, and AMMAS. Thyroid ultrasound and FNA were performed by the radiologist AEA; she has more than 7 years of experience in this field. Histopathological assessment performed by EAMA; she has more than 5 years of experience. Surgical excision of the thyroid gland was performed by the surgeon FHWM; he has more than 5 years of experience in thyroid surgery. All authors contributed to manuscript writing and revision. All authors approved the final manuscript. Acknowledgements The authors offer great thanks to all staff members who helped in this study and to all patients who agreed to participate in our study. References Hegedüs L. Clinical practice. The thyroid nodule. N Engl J Med. 2004;351(17):1764–71. Guth S, Theune U, Aberle J, Galach A, Bamberger CM. Very high prevalence of thyroid nodules detected by high frequency (13 MHz) ultrasound examination. Eur J Clin Invest. 2009;39(8):699–706. Dean DS, Gharib H. Epidemiology of thyroid nodules. Best Pract Res Clin Endocrinol Metab. 2008;22(6):901–11. Haugen BR, Alexander EK, Bible KC, et al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer. Thyroid. 2016;26(1):1–133. Juhlin CC, Mete O, Baloch ZW. The 2022 WHO classification of thyroid tumors: novel concepts in nomenclature and grading. Endocr Relat Cancer. 2023;30(2):e220293. Tessler FN, Middleton WD, Grant EG, et al. ACR thyroid imaging, reporting and data system (TI-RADS): white paper of the ACR TI-RADS committee. J Am Coll Radiol. 2017;14(5):587–95. Grani G, Lamartina L, Ascoli V, et al. Reducing the number of unnecessary thyroid biopsies while improving diagnostic accuracy: toward the Right TIRADS. J Clin Endocrinol Metab. 2019;104(1):95–102. Cibas ES, Ali SZ. The 2017 Bethesda System for Reporting Thyroid Cytopathology. Thyroid. 2017;27(11):1341–6. Bongiovanni M, Spitale A, Faquin WC, Mazzucchelli L, Baloch ZW. The Bethesda System for Reporting Thyroid Cytopathology: a meta-analysis. Acta Cytol. 2012;56(4):333–9. Trimboli P, Ngu R, Royer B, Giovanella L, et al. A multicenter validation study for the EU-TIRADS using histological diagnosis as a gold standard. Clin Endocrinol (Oxf). 2019;91(3):340–7. Ali SZ, VanderLaan PA. The Bethesda system for reporting thyroid cytopathology: definitions, criteria, and explanatory notes. 3rd ed. Cham: Springer; 2023. Elbalka SS, Metwally IH, Shetiwy M, et al. Prevalence and predictors of thyroid cancer among thyroid nodules: a retrospective cohort study of 1,000 patients. Ann R Coll Surg Engl. 2021;103(9):683–9. Silva de Morais N, Stuart J, Guan H, et al. The impact of Hashimoto thyroiditis on thyroid nodule cytology and risk of thyroid cancer. J Endocr Soc. 2019;3(4):791–800. Yoon JH, Lee HS, Kim EK, Moon HJ, Kwak JY. Malignancy risk stratification of thyroid nodules: comparison between the thyroid imaging reporting and data system and the 2015 American Thyroid Association management guidelines. Radiology. 2016;278(3):917–24. Papapostolou KD, Evangelopoulou CC, Ioannidis IA, et al. Taller-than-wide thyroid nodules with microcalcifications are at high risk of malignancy. Vivo. 2020;34(4):2101–5. Kwak JY, Han KH, Yoon JH, et al. Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk. Radiology. 2011;260(3):892–9. Kim JY, Lee CH, Kim SY, et al. Radiologic and pathologic findings of papillary thyroid microcarcinoma. Korean J Radiol. 2009;10(2):194–201. Lee JY, Na DG, Yoon SJ, et al. Ultrasound malignancy risk stratification of thyroid nodules based on the degree of hypoechogenicity and echotexture. Eur Radiol. 2020;30(3):1653–63. Al Argan RJ, Alkhafaji DM, Almajid FM, et al. The role of ultrasound as a predictor of malignancy in indeterminate thyroid nodules—a multicenter study. Med (Kaunas). 2025;61(6):1082. Molina-Vega M, Rodríguez-Pérez CA, Álvarez-Mancha AI, et al. Clinical and ultrasound thyroid nodule characteristics and their association with cytological and histopathological outcomes. J Clin Med. 2019;8(12):2172. Russ G, Bonnema SJ, Erdogan MF, Durante C, et al. European Thyroid Association guidelines for ultrasound malignancy risk stratification of thyroid nodules in adults: the EU-TIRADS. Eur Thyroid J. 2017;6(5):225–37. Paksoy N, Yazal K, Çorak S. Malignancy rate in nondominant nodules in patients with multinodular goiter. Cytojournal. 2011;8:19. Wong R, Farrell SG, Grossmann M. Thyroid nodules: diagnosis and management. Med J Aust. 2018;209(2):92–8. Torshizian A, Hashemi F, Khoshhal N, et al. Diagnostic performance of ACR TI-RADS and ATA guidelines in the prediction of thyroid malignancy. Diagnostics (Basel). 2023;13(18):2972. Tan H, Li Z, Li N, et al. Thyroid imaging reporting and data system combined with Bethesda classification in qualitative thyroid nodule diagnosis. Med (Baltim). 2019;98(50):e18320. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8934299","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611996115,"identity":"17383830-9479-4db4-850a-6c2c65e85fcf","order_by":0,"name":"Sherihan AboElyazed","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Sherihan","middleName":"","lastName":"AboElyazed","suffix":""},{"id":611996116,"identity":"278683a0-47d9-40ff-aad2-0446affe5342","order_by":1,"name":"Fadi Hani Wahba Mikhail","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Fadi","middleName":"Hani Wahba","lastName":"Mikhail","suffix":""},{"id":611996118,"identity":"9f7edb64-00f0-4b60-9d93-12c600b9b557","order_by":2,"name":"Aya Essam Ahmed","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Aya","middleName":"Essam","lastName":"Ahmed","suffix":""},{"id":611996119,"identity":"f15e889e-7de4-42d2-93c4-78f4eeb92f9f","order_by":3,"name":"Sherief Samy Aboelala","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Sherief","middleName":"Samy","lastName":"Aboelala","suffix":""},{"id":611996120,"identity":"19bf7d8d-1956-45eb-8c0c-bec913280e43","order_by":4,"name":"Esraa Adel Mahmoud Atia","email":"","orcid":"","institution":"Ain Shams University","correspondingAuthor":false,"prefix":"","firstName":"Esraa","middleName":"Adel Mahmoud","lastName":"Atia","suffix":""},{"id":611996121,"identity":"c87e8b2f-2c32-406f-8549-ffd32da7ae90","order_by":5,"name":"Amr Mahmoud Mohamed Abd El Hady Saleh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYNCCAoYEfiAlAeUaEKHFgCFBsoFkLQYHiNXCP+3s4w8/DGzyjK8dPniDoaYusYG9eZsEQ0UtTi0St9PNJHsM0orNbqclWzAcO5zYwHOsTILhzHHc1txOY2PgMTicuO12jpkEA9uBxAYJIIOx7RhOHfK305g//jH4n7h5dv43CYZ/QIfJvwFq+Ydbi8HtNAZpHoMDiRukc9iAhjMDbeEBammowanFEOgwaRmD5MQZt9OMLRL7Dhu38aQVWyQcO4BTixzIYW8q7BL7Zyc/vPHhW51sP/vhjTc+1NTh9j4KSABiNgjjMJFakACxtoyCUTAKRsEIAABCYVPtZwlfSgAAAABJRU5ErkJggg==","orcid":"","institution":"Ain Shams University","correspondingAuthor":true,"prefix":"","firstName":"Amr","middleName":"Mahmoud Mohamed Abd El Hady","lastName":"Saleh","suffix":""}],"badges":[],"createdAt":"2026-02-21 15:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8934299/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8934299/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105536796,"identity":"3f44ee47-c9fe-471d-8473-c92c31637726","added_by":"auto","created_at":"2026-03-27 07:21:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":79266,"visible":true,"origin":"","legend":"\u003cp\u003ePostoperative pathological findings of the studied nodules: 92 nodules had benign pathology, divided as follows: 76 nodules were FND, and 16 nodules had FND with lymphocytic thyroiditis. 53 nodules were malignant, divided as follows: 31 nodules were PTC, 4 nodules were invasive EFVPTC, 1 nodule was invasive FVPTC, 3 nodules were MTC, 10 nodules were NIFTP, and 4 nodules were WDT-UMP. FND: follicular nodular disease; invasive FVPTC: invasive follicular variant of papillary thyroid cancer; invasive EFVPTC: invasive encapsulated follicular variant of papillary thyroid cancer; NIFTP: non-invasive follicular thyroid neoplasm with papillary-like nuclear features; WDT-UMP: well-differentiated thyroid tumor of uncertain malignant potential.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/861879b0a0d57e870f3ddd1b.png"},{"id":105536794,"identity":"93c00038-d6df-4555-9bda-0f243ed23eae","added_by":"auto","created_at":"2026-03-27 07:21:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":560377,"visible":true,"origin":"","legend":"\u003cp\u003e(1a) ultrasound image of a right thyroid lobe nodule measuring 2.7 × 5.0 × 5.2 cm, wider than tall, solid, isoechoic to mildly hyperechoic, with smooth margins, and no calcifications; (1b) FNAC from the nodule, showing bland-looking follicular cells in a bloody background showing colloid and hemosiderin-laden macrophages, diagnosed as follicular nodular disease, Bethesda category II (H\u0026amp;E x400); (1c) thyroidectomy specimen of the same nodule reveals follicular nodular disease (multinodular goiter) (H\u0026amp;E x40). \u003cstrong\u003eCase 2\u003c/strong\u003e: (2a) U/S image demonstrates a well-defined, predominantly solid nodule occupying most of the right lobe, measuring 4.8X5.6X3.4 cm, wider than tall, with a heterogeneous echogenicity with no obvious calcifications; (2b) FNAC from the nodule, showing groups of follicular cells exhibiting mild nuclear atypia, diagnosed as atypia of undetermined significance, Bethesda category III (H\u0026amp;E x400); (2c) Thyroidectomy specimen reveals a well-differentiated tumor of uncertain malignant potential, showing a single focus questionable for angioinvasion and equivocal nuclear features in the form of nuclear clearing and occasional grooving (H\u0026amp;E x100, inset picture x400). \u003cstrong\u003eCase 3\u003c/strong\u003e: (3a) A left thyroid nodule is identified measuring \u003cstrong\u003e1.9 × 1.9 × 3.0 cm\u003c/strong\u003e, wider than tall\u003cstrong\u003e, solid\u003c/strong\u003ewith \u003cstrong\u003emarked hypoechogenicity,\u003c/strong\u003e with \u003cstrong\u003eirregular margins\u003c/strong\u003e and \u003cstrong\u003emultiple punctate echogenic foci\u003c/strong\u003e consistent with microcalcifications. (3b) FNAC from the nodule, showing many groups of follicular cells with focal oncocytic cytoplasmic changes arranged in sheets, micro- and macro-follicular patterns. The cells exhibit nuclear enlargement, powdery chromatin, and frequent inclusions, diagnosed as malignant smears, Bethesda category VI (H\u0026amp;E x100, inset picture x400); (3c) the thyroidectomy specimen reveals multifocal papillary thyroid carcinoma, mixed classic and follicular subtypes (H\u0026amp;E x100).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/7b9208ad1edf8d8b714a01af.png"},{"id":105567374,"identity":"43a9d24f-9bd6-4e33-80a5-7f1b3407cdf4","added_by":"auto","created_at":"2026-03-27 12:59:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":75382,"visible":true,"origin":"","legend":"\u003cp\u003eThe stacked column chart shows the percentage distribution of postoperative histopathological outcomes of thyroid nodules stratified by preoperative TIRADS scores (2–5). Benign lesions such as FND and FND with lymphocytic thyroiditis are mainly seen in lower TIRADS categories, while malignant and low-risk malignancies become more frequent with higher TIRADS scores. FND: follicular nodular disease; invasive FVPTC: invasive follicular variant of papillary thyroid cancer; invasive EFVPTC: invasive encapsulated follicular variant of papillary thyroid cancer; NIFTP: non-invasive follicular thyroid neoplasm with papillary-like nuclear features; WDT-UMP: well-differentiated thyroid tumor of uncertain malignant potential.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/f4d0b9a4b6aae2201db8c143.png"},{"id":105536797,"identity":"fa39d0c3-7be5-45e0-8aa8-a1c2abe6ce4b","added_by":"auto","created_at":"2026-03-27 07:21:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":71291,"visible":true,"origin":"","legend":"\u003cp\u003eThe stacked column chart illustrates the percentage distribution of histopathological outcomes among thyroid nodules stratified by Bethesda categories (I–VI). Papillary thyroid carcinoma was exhibited across all categories, showing a rising incidence from Bethesda III to VI. Benign entities such as FND and FND with lymphocytic thyroiditis were mainly found in Bethesda I–IV. Low-risk malignancies, including NIFTP and WDT-UMP, were found in Bethesda I–IV. FND: follicular nodular disease; invasive FVPTC: invasivefollicular variant of papillary thyroid cancer; invasive EFVPTC: invasive encapsulated follicular variant of papillary thyroid cancer; NIFTP: non-invasive follicular thyroid neoplasm with papillary-like nuclear features; WDT-UMP: well-differentiated thyroid tumor of uncertain malignant potential.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/095c6b18beff79488a9ebf0a.png"},{"id":105536798,"identity":"4f6bd4b0-b4c2-4de9-b8cf-746f2d089d52","added_by":"auto","created_at":"2026-03-27 07:21:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":94491,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis demonstrating the diagnostic performance of the TI-RADS and Bethesda systems in differentiating benign from malignant thyroid nodules. Both systems demonstrated statistically significant diagnostic accuracy (p \u0026lt; 0.001). TIRADS showed an AUC of 0.763 (95% CI: 0.668–0.858) with optimal accuracy at a cut-off value of \u0026gt; 4, yielding 50.94% sensitivity and 96.74% specificity. The Bethesda system exhibited higher accuracy with an AUC of 0.819 (95% CI: 0.731–0.908) at a cut-off value \u0026gt; 2, achieving a 73.17% sensitivity and 84.75% specificity.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/dfd3072f0dce3850b7c600b6.png"},{"id":105536799,"identity":"686ade35-b796-4169-b378-2891e3e0f1a0","added_by":"auto","created_at":"2026-03-27 07:21:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":90096,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis demonstrating the diagnostic performance of the TI-RADS and Bethesda systems in differentiating benign from PTC. Both systems exhibited a highly significant accuracy (p \u0026lt; 0.001). TIRADS achieved an AUC of \u003cstrong\u003e0.871 (95% CI: 0.788–0.955)\u003c/strong\u003e at a cut-off value of \u003cstrong\u003e\u0026gt; 4\u003c/strong\u003e, showing \u003cstrong\u003e74.19% sensitivity\u003c/strong\u003e and \u003cstrong\u003e96.74% specificity\u003c/strong\u003e. The Bethesda system showed slightly higher accuracy with an AUC of \u003cstrong\u003e0.91 (95% CI: 0.822–0.999)\u003c/strong\u003e at a cut-off value of \u003cstrong\u003e\u0026gt; 3\u003c/strong\u003e, yielding \u003cstrong\u003e79.17% sensitivity\u003c/strong\u003e and \u003cstrong\u003e94.92% specificity\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/c7a71af9d26b4ed05fda42cf.png"},{"id":105728169,"identity":"5d04b238-ad0e-44c7-817a-5df1bc756873","added_by":"auto","created_at":"2026-03-30 11:10:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2606537,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8934299/v1/61567e16-0d3b-4b79-abeb-1d7c6706b461.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Missed Malignancies in Unbiopsied Thyroid Nodules: Diagnostic Performance of Combined TI-RADS and Bethesda Systems","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThere is an increased prevalence of thyroid nodules, reflecting the widespread use of high-resolution imaging. Epidemiological data demonstrate 2\u0026ndash;6% of nodules detected clinically by palpation, 19\u0026ndash;35% by ultrasound, and up to 50\u0026ndash;60% in autopsy series [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Most nodules are benign, but 5\u0026ndash;15% are malignant [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Thyroid neoplasms are classified according to tumor behavior, differentiation, and histologic variants into benign lesions, low-risk neoplasms, and malignant thyroid neoplasms, according to the last WHO classification [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThyroid ultrasound is a non-invasive, widely available imaging technique considered the first-line imaging modality for thyroid nodules [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The American College of Radiology developed the TI-RADS scoring system, which assigns scores to composition, echogenicity, shape, margin, and echogenic foci, ultimately stratifying nodules from TR1 (benign) to TR5 (high suspicion). This system's goal is to make interpretations less subjective [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Fine needle aspiration cytology (FNAC) remains an essential component of preoperative assessment. The Bethesda System for Reporting Thyroid Cytopathology arranges FNAC results into six categories, each associated with a specific malignancy risk [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe definitive postoperative histopathology is the gold standard for diagnosing thyroid malignancy [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Many studies have examined ultrasound-based risk systems, including TI-RADS, in relation to histopathological outcomes, consistently indicating a strong correlation between elevated TI-RADS categories and malignancy [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, differences across populations and institutions indicate that further validation is needed to optimize cutoff values and confirm predictive accuracy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e This cross-sectional analytical study was conducted at the Endocrinology Clinic and the Endocrine Surgical Department of Ain Shams University Hospital over one year (from August 2024 to July 2025), after the study protocol had been approved by the local Research Ethics Committee of the Faculty of Medicine, Ain Shams University (FMASU R187/2024). Before enrolling, all participants signed a written consent. Patient identification was kept strictly confidential.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEligibility Criteria\u003c/h2\u003e \u003cp\u003eThe study included adult patients with suspicious thyroid nodules diagnosed by neck ultrasonography and indicated for FNAC or large nodular goiter causing pressure symptoms, and then planned for surgical excision (hemi- or total thyroidectomy). Histopathological examination of the excised specimens was considered the gold standard.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient Assessment\u003c/h3\u003e\n\u003cp\u003eAll patients received a structured clinical evaluation, including detailed history taking and clinical examination. Laboratory investigations included thyroid function tests (FT3, FT4, and TSH) performed by the ECLIA method.\u003c/p\u003e\n\u003ch3\u003eU/S Assessment\u003c/h3\u003e\n\u003cp\u003eHigh-resolution ultrasonography of the thyroid gland was conducted by the radiologist, who has 10 years of experience in thyroid U/S, to evaluate thyroid nodules according to the ACR TI-RADS score [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The radiologist utilized an 8- to 17-MHz linear probe to examine thyroid nodule characteristics. FNAC was taken from nodules indicated for it, using a 10 mL syringe and a 23-gauge needle with ultrasound guidance. Samples were smeared on a glass slide and fixed with 95% ethanol.\u003c/p\u003e\n\u003ch3\u003eHistopathological Assessment\u003c/h3\u003e\n\u003cp\u003eFor FNAC, alcohol-fixed slides were stained by hematoxylin and eosin (H\u0026amp;E), examined, and reported according to the Bethesda system for reporting thyroid pathology [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Finally, patients underwent surgical excision (hemi- or total thyroidectomy).\u003c/p\u003e \u003cp\u003eFor excisional specimens, the tissue was first properly fixed in 10% neutral-buffered formalin for 24 hours, then processed through graded alcohols for dehydration, cleared in xylene, and embedded in paraffin blocks. Sections are cut to a thickness of about 4\u0026ndash;5 \u0026micro;m, then deparaffinized in xylene, and rehydrated through decreasing alcohol concentrations to water. Finally, sections were stained by H\u0026amp;E and evaluated according to the 2022 WHO classification of endocrine [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOperative Details\u003c/h3\u003e\n\u003cp\u003eThe patient was placed on the operating table in a supine position with a reverse Trendelenburg tilt and the neck extended. After skin preparation and administration of general anesthesia, a transverse incision was made 2\u0026ndash;3 cm above the sternal notch, and the skin, subcutaneous tissue, and platysma were incised to expose the cervical fascia. The investing fascia was opened in the midline, and the strap muscles were elevated to show and move the thyroid gland. Dissection started at the superior pole, where the superior thyroid vessels were safely separated from the recurrent laryngeal nerve (RLN). After identifying and exposing the RLN, the vessels to the lower pole were ligated. The thyroid lobe was carefully dissected from the trachea. After complete removal, meticulous hemostasis was performed. A Hemovac drain was placed, the strap muscles were re-approximated, and the platysma and skin were closed in layers. Then the wound was cleaned, and a sterile dressing was placed.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eWe gathered, revised, categorized, and entered data into the Statistical Package for Social Science \u003cb\u003e(SPSS 27)\u003c/b\u003e software. Descriptive statistics were calculated using standard deviation (\u0026plusmn;\u0026thinsp;SD) and range for age, TSH, FT3, and FT4 levels, and median and interquartile range (IQR) for nodule size, TI-RADS, and Bethesda scores. And we used frequency and percentage of non-numeric data. Analytical statistics, including the Student\u0026rsquo;s T test, were used to determine the statistical differences in age means and thyroid profiles; the Mann-Whitney test (U) was employed to assess the statistical differences in nodule size, TI-RADS, and Bethesda scores between the two studied groups. We used the chi-square (Fisher\u0026rsquo;s exact test when needed) to assess the association between each ultrasound feature and malignant pathology. Univariate analysis with odds ratios (OR) and 95% confidence intervals (CI) was calculated to estimate the association between each ultrasound feature and malignancy risk. The ROC curve was used to figure out the diagnostic performance of the TI-RADS and Bethesda systems for malignancy prediction. The P-value represents the level of significance (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05: Non-significant (NS), P\u0026thinsp;\u0026lt;\u0026thinsp;0.05: Significant (S), and P\u0026thinsp;\u0026lt;\u0026thinsp;0.001: Highly significant).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOne hundred euthyroid patients with suspicious thyroid nodules who were indicated for thyroidectomy were included in this study. Among these patients, 89 (89%) were female, 53 (60%) were diagnosed with benign pathology, and 36 (40%) with malignant pathology. The remaining 11 (11%) patients were male, of whom 5 (45%) had benign pathology, and 6 (55%) had malignant pathology. Descriptive analysis of the studied population is presented in Table 1.\u003c/p\u003e\n\u003cp\u003e100 nodules were biopsied preoperatively according to ultrasound criteria for FNAC, and 45 nodules were not indicated for biopsy. 145 nodules were analyzed in relation to preoperative assessment (ultrasound with or without FNAC) and postoperative histopathology.\u0026nbsp;92 (63.45%)\u0026nbsp;nodules were benign, and\u0026nbsp;53 (36.55%) nodules were malignant in the postoperative histopathology (Figs.\u0026nbsp;1, 2). One patient had mixed multifocal pathologies: papillary carcinoma at the left lobe and NIFTP at the isthmus, and another patient had papillary carcinoma at the right lobe and invasive EFVPTC at the isthmus.\u003c/p\u003e\n\u003cp\u003eWe compared U/S and FNAC findings of benign and malignant nodules. Results indicated that the overall TI-RADS and BETHESDA scores were significantly higher in the malignant group (\u003cem\u003ep\u003c/em\u003e-value \u0026lt; 0.001, 95% CI 5-5; \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.001, 95% CI 4-5, respectively). However, there were no significant differences in nodule size, location on U/S, or number of nodules in the gland (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe divided the studied nodules based on preoperative FNAC into biopsied and unbiopsied nodules and compared these groups with respect to U/S criteria and final pathology results. Results revealed significant differences, as biopsied nodules were larger in size, had a higher incidence of echogenic foci, and some exhibited irregular margins or extrathyroidal extension (p-value \u0026lt; 0.05) as well as higher overall TI-RADS scores (p-value \u0026lt; 0.05, 95% CI 4-5). It was observed that 12 (27%) of the unbiopsied nodules were found to be malignant in the final histopathological evaluation (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe analyzed the percentage distribution of postoperative histopathological outcomes across the TI-RADS scores of all studied nodules (n = 145) (Fig. 3). \u003cstrong\u003e\u003cem\u003eTI-RADS 2\u003c/em\u003e\u003c/strong\u003e were predominantly benign (83.3%), and only 16.7% were malignant nodules. \u003cstrong\u003e\u003cem\u003eTI-RADS 3\u003c/em\u003e\u003c/strong\u003e showed predominant benign pathology (80.3%) and 19.7% malignant pathology, with 6.6% PTC. \u003cstrong\u003e\u003cem\u003eTI-RADS 4\u003c/em\u003e\u003c/strong\u003e demonstrated a similar pattern to TR3, with a modest increase in the incidence of malignant pathology (27.1%); however, benign pathology remained predominant (72.9%). \u003cstrong\u003e\u003cem\u003eTI-RADS 5\u003c/em\u003e\u003c/strong\u003e showed the highest malignant potential (90%), with 76.7% PTC, alongside small percentages of other entities. However, 10% of the nodules were benign.\u003c/p\u003e\n\u003cp\u003eAdditionally, the percentage distribution of histopathological outcomes was analyzed across the preoperative Bethesda categories of all biopsied nodules (n = 100) (Fig. 4). \u003cstrong\u003e\u003cem\u003eBethesda I (Nondiagnostic)\u003c/em\u003e\u003c/strong\u003ewas largely benign (80.0%), showing a predominance of FND. And 20% were malignant nodules, with 6.7% PTC. \u003cstrong\u003e\u003cem\u003eBethesda II (Benign)\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;was predominantly benign (82.6%).\u0026nbsp;\u003c/strong\u003e17.4% were diagnosed as malignant nodules, with 4.3% PTC. \u003cstrong\u003e\u003cem\u003eBethesda III (AUS/FLUS)\u003c/em\u003e\u003c/strong\u003e showed greater heterogeneity, including 46.2% diagnosed as benign pathology and 53.8% of malignant nature, with 15.4% PTC. \u003cstrong\u003e\u003cem\u003eBethesda IV (FN/SFN)\u003c/em\u003e\u003c/strong\u003e exhibited a higher proportion of malignancy (72.7%), with PTC (36.4%). And only 27.3% of nodules were benign. \u003cstrong\u003e\u003cem\u003eBethesda V\u0026ndash;VI (Suspicious for Malignancy and Malignant)\u003c/em\u003e\u003c/strong\u003e were exclusively malignant, showing 100% PTC.\u003c/p\u003e\n\u003cp\u003eReceiver Operating Characteristic (ROC) analysis was performed to assess the diagnostic performance of both the TI-RADS and Bethesda systems in differentiating benign from malignant thyroid nodules. A TI-RADS score of more than 4 demonstrated an AUC of \u003cstrong\u003e0.763 (95% CI: 0.668\u0026ndash;0.858, p \u0026lt; 0.001)\u003c/strong\u003e, with \u003cstrong\u003e50.94% sensitivity\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e96.74% specificity\u003c/strong\u003e, 90% PPV, and \u003cstrong\u003e77.4%\u003c/strong\u003e NPV.The\u003cstrong\u003eBethesda score of more than 2\u003c/strong\u003e yielded an \u003cstrong\u003eAUC of 0.819 (95% CI: 0.731\u0026ndash;0.908, p \u0026lt; 0.001)\u003c/strong\u003e, with \u003cstrong\u003e73.17% sensitivity\u003c/strong\u003e and \u003cstrong\u003e84.75% specificity\u003c/strong\u003e, with \u003cstrong\u003e76.9%\u003c/strong\u003e \u003cstrong\u003ePPV\u0026nbsp;\u003c/strong\u003eand 82% NPV, showing superior discriminative power compared to TI-RADS (Fig. 5).\u003c/p\u003e\n\u003cp\u003eAdditionally, ROC analysis was conducted to assess the diagnostic accuracy of the TI-RADS and Bethesda systems for PTC. Using a \u003cstrong\u003ecut-off value \u0026gt; 4, TI-RADS\u003c/strong\u003e demonstrated an \u003cstrong\u003eAUC of 0.871 (95% CI: 0.788\u0026ndash;0.955, p \u0026lt; 0.001)\u003c/strong\u003e, with 74.19%\u003cstrong\u003e\u0026nbsp;sensitivity\u003c/strong\u003e, \u003cstrong\u003e96.74% specificity,\u0026nbsp;\u003c/strong\u003e88.5% PPV,and \u003cstrong\u003e91.8%\u003c/strong\u003e \u003cstrong\u003eNPV\u003c/strong\u003e. \u003cstrong\u003eBethesda\u003c/strong\u003eexhibited a good diagnostic accuracy at a cut-off\u003cstrong\u003e\u0026nbsp;\u0026gt; 3\u003c/strong\u003e, yielding an \u003cstrong\u003eAUC of 0.91 (95% CI: 0.822\u0026ndash;0.999, p \u0026lt; 0.001)\u003c/strong\u003e, \u003cstrong\u003e79.17% sensitivity\u003c/strong\u003e, \u003cstrong\u003e94.92% specificity\u003c/strong\u003e, \u003cstrong\u003e86.4% PPV,\u0026nbsp;\u003c/strong\u003eand 91.8% NPV (Fig. 6).\u003c/p\u003e\n\u003cp\u003eWe used univariate analysis to evaluate the diagnostic performance of key U/S features in relation to postoperative histopathological diagnoses with a specific focus on PTC separately (Tables 4 and 5).\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eNodule Composition (Solid vs. Cystic/Spongiform/Mixed)\u003c/em\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eSolid composition was observed more frequently in all malignant nodules (87%) and in PTC (87.1%) than in benign ones (73.9%). However, this difference did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.13, OR = 2.38, 95% CI = 0.76\u0026ndash;7.51; \u003cem\u003ep\u003c/em\u003e = 0.06, OR = 2.31, 95% CI = 0.923\u0026ndash;5.828, respectively), with 26% specificity and sensitivity of 86.8% and 87.1%, respectively, with diagnostic accuracy of 48.3% and 41.5%, respectively.\u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eNodule Echogenicity (Hypoechoic / Very Hypoechoic vs. Others)\u003c/em\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eHypoechoic or very hypoechoic nodules were significantly more prevalent in malignant nodules (58.5%) and in PTC (71%) compared to benign cases (26.1%) (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001, OR = 3.99, 95% CI 1.95\u0026ndash;8.18; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, OR = 6.93, 95% CI = 2.80\u0026ndash;17.11, respectively). It demonstrated 73.9% specificity and sensitivity of 58.5% and 71%, respectively, with diagnostic accuracy of 68% and 73%, respectively.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eNodule Shape (Taller-than-wide vs. Wider-than-tall)\u003c/em\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe \u0026ldquo;taller-than-wide\u0026rdquo; configuration was found in 37.7% of malignant nodules and 54.8% in PTC versus only 5.4% of benign ones (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, OR = 10.55, 95% CI 3.66\u0026ndash;30.4; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, OR = 21.13, 95% CI = 6.72\u0026ndash;66.45, respectively). It exhibited 94.6% specificity with diagnostic accuracy of 74% and 84.6%, respectively, making it one of the strongest predictors of malignancy despite low sensitivity (37.7% and 54.8%, respectively).\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eNodule Margin (Lobulated / Irregular / Extra-thyroidal vs Smooth / Ill-defined)\u003c/em\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eIrregular or lobulated margins and evidence of extrathyroidal extension were significantly associated with malignant nodules (32.1%), being higher in PTC (51.6%), and only 4.4% of benign nodules (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, OR = 10.39, 95% CI 3.27\u0026ndash;33.01; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, OR = 23.5, 95% CI 6.89\u0026ndash;79.87, respectively). It demonstrated 95.7% specificity and sensitivity of 32% and 51.6%, respectively, with diagnostic accuracy of 72.4% and 84.5%, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEchogenic foci (Microcalcifications vs Others)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMicrocalcifications were observed in 35.9% of malignant and 45.2% of PTC versus 10.9% of benign nodules (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001; OR = 4.58, 95% CI 1.93\u0026ndash;10.87; p \u0026lt; 0.001, OR = 6.75, 95% CI = 2.57\u0026ndash;17.73, respectively). It exhibited 89.1% specificity and sensitivity of 35.9% and 45.2%, respectively, with diagnostic accuracy of 69.66% and 78%, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Descriptive Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll Patients\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBenign Group*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant Group*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 42)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest of significance*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e11 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e5 (8.62%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6 (14.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e89 (89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e53 (91.38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e36 (85.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e41.7 \u0026plusmn; 12.66\u003c/p\u003e\n \u003cp\u003e(39.19 - 44.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e41.1 \u0026plusmn; 12.54\u003c/p\u003e\n \u003cp\u003e(37.81 - 44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e42.52 \u0026plusmn; 12.93\u003c/p\u003e\n \u003cp\u003e(38.5 - 46.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et=\u003c/strong\u003e -0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTSH\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e(uIU/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1.29 \u0026plusmn; 0.84\u003c/p\u003e\n \u003cp\u003e(1.12 - 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e1.15 \u0026plusmn; 0.78\u003c/p\u003e\n \u003cp\u003e(0.95 - 1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.47 \u0026plusmn; 0.9\u003c/p\u003e\n \u003cp\u003e(1.2 - 1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et=\u003c/strong\u003e -1.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFree T3\u0026nbsp;\u003c/strong\u003e(pg/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e2.97 \u0026plusmn; 0.53\u003c/p\u003e\n \u003cp\u003e(2.87 - 3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e3.01 \u0026plusmn; 0.54\u003c/p\u003e\n \u003cp\u003e(2.87 - 3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.92 \u0026plusmn; 0.53\u003c/p\u003e\n \u003cp\u003e(2.76 - 3.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et=\u003c/strong\u003e 0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFree T4\u0026nbsp;\u003c/strong\u003e(ng/dl)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1.24 \u0026plusmn; 0.34\u003c/p\u003e\n \u003cp\u003e(1.17 - 1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e1.14 \u0026plusmn; 0.27\u003c/p\u003e\n \u003cp\u003e(1.07 - 1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.37 \u0026plusmn; 0.37\u003c/p\u003e\n \u003cp\u003e(1.25 - 1.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et=\u003c/strong\u003e -3.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Comparison between benign and malignant patients using the Chi-Square test (X\u0026sup2;) and Student t-test (t). \u003csup\u003e#\u003c/sup\u003eHighly significant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Comparative analysis of postoperative final pathology concerning preoperative U/S characteristics, TI-RADS, and Bethesda scores of all studied nodules\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"635\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" rowspan=\"3\" style=\"width: 220px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 262px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostoperative final pathology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" rowspan=\"2\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest of significance\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003eMalignant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 130px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003cp\u003e95% CI for %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 132px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003cp\u003e95% CI for %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 89px;\"\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 65px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation of nodules on U/S\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e43 (46.74%)\u003c/p\u003e\n \u003cp\u003e(36.8% - 56.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e30 (56.6%)\u003c/p\u003e\n \u003cp\u003e(43.2% - 69.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e1.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e42 (45.65%)\u003c/p\u003e\n \u003cp\u003e(35.7% - 55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e20 (37.74%)\u003c/p\u003e\n \u003cp\u003e(25.6% - 51.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eIsthmus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e7 (7.61%)\u003c/p\u003e\n \u003cp\u003e(3.5% - 14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e3 (5.66%)\u003c/p\u003e\n \u003cp\u003e(1.6% - 14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of nodules in each gland\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e12 (20.69%)\u003c/p\u003e\n \u003cp\u003e(11.8% - 32.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11 (26.19%)\u003c/p\u003e\n \u003cp\u003e(14.8% - 40.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.812\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e2 Nodules\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e9 (15.52%)\u003c/p\u003e\n \u003cp\u003e(8% - 26.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e6 (14.29%)\u003c/p\u003e\n \u003cp\u003e(6.2% - 27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMNG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e37 (63.79%)\u003c/p\u003e\n \u003cp\u003e(51% - 75.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e25 (59.52%)\u003c/p\u003e\n \u003cp\u003e(44.5% - 73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNodule size\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e$\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2.8 (1.65 - 3.85)\u003c/p\u003e\n \u003cp\u003e(2.5 - 3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2.5 (1.4 - 3.6)\u003c/p\u003e\n \u003cp\u003e(2 - 3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ez=\u003c/strong\u003e -0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.427\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTIRADS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e3 (3 - 4)\u003c/p\u003e\n \u003cp\u003e(3 - 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5 (4 - 5)\u003c/p\u003e\n \u003cp\u003e(5 - 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ez=\u003c/strong\u003e -5.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBETHESDA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\n \u003cp\u003e2 (2 - 2)\u003c/p\u003e\n \u003cp\u003e(2 - 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e4 (2 - 5)\u003c/p\u003e\n \u003cp\u003e(4 - 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ez=\u003c/strong\u003e -5.723\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e+Fisher\u0026rsquo;s Exact test (FE), Chi-Square test (X2), Mann-Whitney test (z). # Highly significant.\u003c/p\u003e\n\u003cp\u003e* Each subscript letter denotes a subset of group categories whose column proportions do not differ significantly from each other at the .05 level.\u003c/p\u003e\n\u003cp\u003e$Largest dimension (cm).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Comparative analysis of preoperative U/S features of biopsied and unbiopsied nodules by FNAB\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"637\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" rowspan=\"3\" style=\"width: 244px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 230px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative FNAB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" rowspan=\"2\" style=\"width: 163px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest of significance\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eNot biopsied\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eBiopsied\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eN (%)\u003cbr\u003e\u0026nbsp;95% CI for %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eN (%)\u003cbr\u003e\u0026nbsp;95% CI for %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 90px;\"\u003e\n \u003cp\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 73px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComposition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eCystic/Spongiform\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (2.22%)\u003c/p\u003e\n \u003cp\u003e(0.2% - 9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e(0% - 0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 90px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eMixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e8 (17.78%)\u003c/p\u003e\n \u003cp\u003e(8.8% - 30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e22 (22%)\u003c/p\u003e\n \u003cp\u003e(14.8% - 30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eSolid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e36 (80%)\u003c/p\u003e\n \u003cp\u003e(66.7% - 89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e78 (78%)\u003c/p\u003e\n \u003cp\u003e(69.2% - 85.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eAnechoic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e(0% - 0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2 (2%)\u003c/p\u003e\n \u003cp\u003e(0.4% - 6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 90px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eHyper- or isoechoic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e30 (66.67%)\u003c/p\u003e\n \u003cp\u003e(52.2% - 79.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e58 (58%)\u003c/p\u003e\n \u003cp\u003e(48.2% - 67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eHypoechoic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e14 (31.11%)\u003c/p\u003e\n \u003cp\u003e(19.1% - 45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e30 (30%)\u003c/p\u003e\n \u003cp\u003e(21.7% - 39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eVery hypoechoic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (2.22%)\u003c/p\u003e\n \u003cp\u003e(0.2% - 9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e10 (10%)\u003c/p\u003e\n \u003cp\u003e(5.3% - 17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShape\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eWider than tall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e40 (88.89%)\u003c/p\u003e\n \u003cp\u003e(77.3% - 95.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e80 (80%)\u003c/p\u003e\n \u003cp\u003e(71.4% - 86.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e1.719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eTaller than wide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (11.11%)\u003c/p\u003e\n \u003cp\u003e(4.4% - 22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e20 (20%)\u003c/p\u003e\n \u003cp\u003e(13.1% - 28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eSmooth / ill-defined\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e44 (97.78%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(90.1% - 99.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e80 (80%) \u003cstrong\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(71.4% - 86.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 90px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.009\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eLobulated or irregular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0 (0%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0% - 0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e12 (12%)\u003cstrong\u003e\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(6.7% - 19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eExtra thyroidal extension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (2.22%)\u003cstrong\u003e\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.2% - 9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e8 (8%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(3.9% - 14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenic foci\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eNone or large comet-tail artifacts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e36 (80%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(66.7% - 89.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e54 (54%) \u003cstrong\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(44.2% - 63.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 90px;\"\u003e\n \u003cp\u003eFE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"4\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.007\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eMacrocalcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (2.22%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.2% - 9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e19 (19%)\u003cstrong\u003e\u003csup\u003e\u0026nbsp;b\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(12.3% - 27.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eRim of calcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1 (2.22%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(0.2% - 9.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e5 (5%) \u003cstrong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(1.9% - 10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eMicrocalcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e7 (15.56%)\u003cstrong\u003e\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(7.2% - 28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 123px;\"\u003e\n \u003cp\u003e22 (22%)\u003cstrong\u003e\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(14.8% - 30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNodule size\u003csup\u003e$\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003cp\u003e95% CI for median\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.6 (1.2 - 2.9)\u003c/p\u003e\n \u003cp\u003e(1.5 - 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3 (2.1 - 4.2)\u003c/p\u003e\n \u003cp\u003e(2.9 - 3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ez=\u003c/strong\u003e -4.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTIRADS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003cp\u003e95% CI for median\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e3 (3 - 4)\u003c/p\u003e\n \u003cp\u003e(3 - 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e4 (3 - 4)\u003c/p\u003e\n \u003cp\u003e(4 - 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ez=\u003c/strong\u003e -2.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.018\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinal pathological findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e33 (73.3%)\u003c/p\u003e\n \u003cp\u003e(59.3% - 84.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e59 (59%)\u003c/p\u003e\n \u003cp\u003e(49.2% - 68.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e=\u0026nbsp;\u003c/strong\u003e2.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eMalignant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e12 (26.7%)\u003c/p\u003e\n \u003cp\u003e(15.5% - 40.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e41 (41%)\u003c/p\u003e\n \u003cp\u003e(31.7% - 50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e+\u003c/sup\u003eFisher\u0026rsquo;s Exact test of significance (FE), Chi-Square test of significance (X\u003csup\u003e2\u003c/sup\u003e), Mann-Whitney test of significance (z).\u003csup\u003e\u0026nbsp;#\u0026nbsp;\u003c/sup\u003eSignificant, \u003csup\u003e##\u003c/sup\u003e Highly significant.\u003c/p\u003e\n\u003cp\u003e*\u0026nbsp;Each subscript letter denotes a subset of group categories whose column proportions do not differ significantly from each other at the .05 level.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e$\u003c/sup\u003eLargest dimension (cm).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e \u003cstrong\u003eDiagnostic Performance and Statistical Association of Ultrasound Features with Malignant Thyroid Nodules\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"1011\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 244px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost operative final pathology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" rowspan=\"3\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccuracy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eMalignant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eN (%)\u003cbr\u003e\u0026nbsp;95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eN (%)\u003cbr\u003e\u0026nbsp;95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComposition\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSolid vs.\u003c/p\u003e\n \u003cp\u003eCystic/Spongiform/Mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e46 (86.79%)\u003c/p\u003e\n \u003cp\u003e(75.8% - 93.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e68 (73.91%)\u003c/p\u003e\n \u003cp\u003e(64.3% - 82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e86.79\u003c/p\u003e\n \u003cp\u003e(74.66 \u0026ndash; 94.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e26.09\u003c/p\u003e\n \u003cp\u003e(17.48 \u0026ndash; 36.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e40.35\u003c/p\u003e\n \u003cp\u003e(31.27 \u0026ndash; 49.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e77.42\u003c/p\u003e\n \u003cp\u003e(58.9 \u0026ndash; 90.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e48.28\u003c/p\u003e\n \u003cp\u003e(39.91 \u0026ndash; 56.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e2.319\u003c/p\u003e\n \u003cp\u003e(0.923 \u0026ndash; 5.828)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e7 (13.21%)\u003c/p\u003e\n \u003cp\u003e(6.1% - 24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e24 (26.09%)\u003c/p\u003e\n \u003cp\u003e(18% - 35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eHypoechoic / Very hypoechoic vs.\u003c/p\u003e\n \u003cp\u003eAnechoic / Hyper- or isoechoic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e31 (58.49%)\u003c/p\u003e\n \u003cp\u003e(45.1% - 71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e24 (26.09%)\u003c/p\u003e\n \u003cp\u003e(18% - 35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e58.49\u003c/p\u003e\n \u003cp\u003e(44.13 \u0026ndash; 71.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e73.91\u003c/p\u003e\n \u003cp\u003e(63.71 \u0026ndash; 82.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e56.36\u003c/p\u003e\n \u003cp\u003e(46.11 \u0026ndash; 66.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e75.56\u003c/p\u003e\n \u003cp\u003e(68.71 \u0026ndash; 81.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e68.28\u003c/p\u003e\n \u003cp\u003e(60.04 \u0026ndash; 75.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e14.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e3.992\u003c/p\u003e\n \u003cp\u003e(1.948 \u0026ndash; 8.183)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e22 (41.51%)\u003c/p\u003e\n \u003cp\u003e(29% - 54.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e68 (73.91%)\u003c/p\u003e\n \u003cp\u003e(64.3% - 82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShape\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTaller than wide vs.\u003c/p\u003e\n \u003cp\u003eWider than tall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e20 (37.74%)\u003c/p\u003e\n \u003cp\u003e(25.6% - 51.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 (5.43%)\u003c/p\u003e\n \u003cp\u003e(2.1% - 11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e37.74\u003c/p\u003e\n \u003cp\u003e(24.79 \u0026ndash; 52.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e94.57\u003c/p\u003e\n \u003cp\u003e(87.77 \u0026ndash; 98.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003cp\u003e(61.45 \u0026ndash; 90.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e72.5\u003c/p\u003e\n \u003cp\u003e(68.01 \u0026ndash; 76.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e73.79\u003c/p\u003e\n \u003cp\u003e(65.85 \u0026ndash; 80.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e24.589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e10.545\u003c/p\u003e\n \u003cp\u003e(3.658 \u0026ndash; 30.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e33 (62.26%)\u003c/p\u003e\n \u003cp\u003e(48.8% - 74.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e87 (94.57%)\u003c/p\u003e\n \u003cp\u003e(88.5% - 98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLobulated or irregular/ Extra thyroidal extension vs.\u003c/p\u003e\n \u003cp\u003eSmooth / ill-defined\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e17 (32.08%)\u003c/p\u003e\n \u003cp\u003e(20.7% - 45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e4 (4.35%)\u003c/p\u003e\n \u003cp\u003e(1.5% - 10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e32.08\u003c/p\u003e\n \u003cp\u003e(19.92 \u0026ndash; 46.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e95.65\u003c/p\u003e\n \u003cp\u003e(89.24 \u0026ndash; 98.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e80.95\u003c/p\u003e\n \u003cp\u003e(60.14 \u0026ndash; 92.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e70.97\u003c/p\u003e\n \u003cp\u003e(66.9 \u0026ndash; 74.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e72.41\u003c/p\u003e\n \u003cp\u003e(64.38 \u0026ndash; 79.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e20.875\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e10.389\u003c/p\u003e\n \u003cp\u003e(3.269 \u0026ndash; 33.013)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e36 (67.92%)\u003c/p\u003e\n \u003cp\u003e(54.7% - 79.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e88 (95.65%)\u003c/p\u003e\n \u003cp\u003e(90% - 98.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 244px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenic foci\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMicrocalcifications vs.\u003c/p\u003e\n \u003cp\u003eNone or large comet-tail artifacts / Macrocalcifications / Rim of calcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e19 (35.85%)\u003c/p\u003e\n \u003cp\u003e(24% - 49.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e10 (10.87%)\u003c/p\u003e\n \u003cp\u003e(5.7% - 18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e35.85\u003c/p\u003e\n \u003cp\u003e(23.14 \u0026ndash; 50.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 74px;\"\u003e\n \u003cp\u003e89.13\u003c/p\u003e\n \u003cp\u003e(80.92 \u0026ndash; 94.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 62px;\"\u003e\n \u003cp\u003e65.52\u003c/p\u003e\n \u003cp\u003e(48.87 \u0026ndash; 79.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e70.69\u003c/p\u003e\n \u003cp\u003e(66.08 \u0026ndash; 74.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003e69.66\u003c/p\u003e\n \u003cp\u003e(61.48 \u0026ndash; 77.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e13.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e4.582\u003c/p\u003e\n \u003cp\u003e(1.932 \u0026ndash; 10.87)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 108px;\"\u003e\n \u003cp\u003e34 (64.15%)\u003c/p\u003e\n \u003cp\u003e(50.8% - 76%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" style=\"width: 98px;\"\u003e\n \u003cp\u003e82 (89.13%)\u003c/p\u003e\n \u003cp\u003e(81.6% - 94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eChi-Square test (X\u0026sup2;); PPV = Positive Predictive Value; NPV = Negative Predictive Value; CI = Confidence Interval; \u003csup\u003e\u0026nbsp;#\u0026nbsp;\u003c/sup\u003eHighly significant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Diagnostic Performance of Ultrasound Features in Predicting Papillary Thyroid Carcinoma\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"992\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 242px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 213px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost operative final pathology\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"3\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccuracy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eX\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003ePTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eN (%)\u003cbr\u003e\u0026nbsp;95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\n \u003cp\u003eN (%)\u003cbr\u003e\u0026nbsp;95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComposition\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eSolid vs.\u003c/p\u003e\n \u003cp\u003eCystic/Spongiform/Mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e27 (87.1%)\u003c/p\u003e\n \u003cp\u003e(72.2% - 95.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e68 (73.91%)\u003c/p\u003e\n \u003cp\u003e(64.3% - 82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e87.1\u003c/p\u003e\n \u003cp\u003e(70.17 \u0026ndash; 96.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e26.09\u003c/p\u003e\n \u003cp\u003e(17.48 \u0026ndash; 36.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 71px;\"\u003e\n \u003cp\u003e28.42\u003c/p\u003e\n \u003cp\u003e(24.87 \u0026ndash; 32.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e85.71\u003c/p\u003e\n \u003cp\u003e(69.31 \u0026ndash; 94.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e41.46\u003c/p\u003e\n \u003cp\u003e(32.65 \u0026ndash; 50.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e2.292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.382\u003c/p\u003e\n \u003cp\u003e(0.755 \u0026ndash; 7.513)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e4 (12.9%)\u003c/p\u003e\n \u003cp\u003e(4.5% - 27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e24 (26.09%)\u003c/p\u003e\n \u003cp\u003e(18% - 35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eHypoechoic / Very hypoechoic vs.\u003c/p\u003e\n \u003cp\u003eAnechoic / Hyper- or isoechoic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e22 (70.97%)\u003c/p\u003e\n \u003cp\u003e(53.7% - 84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e24 (26.09%)\u003c/p\u003e\n \u003cp\u003e(18% - 35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e70.97\u003c/p\u003e\n \u003cp\u003e(51.96 \u0026ndash; 85.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e73.91\u003c/p\u003e\n \u003cp\u003e(63.71 \u0026ndash; 82.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 71px;\"\u003e\n \u003cp\u003e47.83\u003c/p\u003e\n \u003cp\u003e(37.8 \u0026ndash; 58.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e88.31\u003c/p\u003e\n \u003cp\u003e(81.13 \u0026ndash; 92.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e73.17\u003c/p\u003e\n \u003cp\u003e(64.43 \u0026ndash; 80.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e19.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e6.926\u003c/p\u003e\n \u003cp\u003e(2.803 \u0026ndash; 17.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e9 (29.03%)\u003c/p\u003e\n \u003cp\u003e(15.4% - 46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e68 (73.91%)\u003c/p\u003e\n \u003cp\u003e(64.3% - 82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eShape\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTaller than wide vs.\u003c/p\u003e\n \u003cp\u003eWider than tall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e17 (54.84%)\u003c/p\u003e\n \u003cp\u003e(37.5% - 71.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e5 (5.43%)\u003c/p\u003e\n \u003cp\u003e(2.1% - 11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e54.84\u003c/p\u003e\n \u003cp\u003e(36.03 \u0026ndash; 72.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e94.57\u003c/p\u003e\n \u003cp\u003e(87.77 \u0026ndash; 98.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 71px;\"\u003e\n \u003cp\u003e77.27\u003c/p\u003e\n \u003cp\u003e(57.77 \u0026ndash; 89.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e86.14\u003c/p\u003e\n \u003cp\u003e(80.78 \u0026ndash; 90.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e84.55\u003c/p\u003e\n \u003cp\u003e(76.93 \u0026ndash; 90.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e38.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e21.129\u003c/p\u003e\n \u003cp\u003e(6.718 \u0026ndash; 66.447)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e14 (45.16%)\u003c/p\u003e\n \u003cp\u003e(28.7% - 62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e87 (94.57%)\u003c/p\u003e\n \u003cp\u003e(88.5% - 98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMargin\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLobulated or irregular/ Extra thyroidal extension vs.\u003c/p\u003e\n \u003cp\u003eSmooth / ill-defined\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e16 (51.61%)\u003c/p\u003e\n \u003cp\u003e(34.5% - 68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e4 (4.35%)\u003c/p\u003e\n \u003cp\u003e(1.5% - 10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e51.61\u003c/p\u003e\n \u003cp\u003e(33.06 \u0026ndash; 69.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e95.65\u003c/p\u003e\n \u003cp\u003e(89.24 \u0026ndash; 98.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 71px;\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003cp\u003e(59.12 \u0026ndash; 91.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e85.44\u003c/p\u003e\n \u003cp\u003e(80.27 \u0026ndash; 89.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e84.55\u003c/p\u003e\n \u003cp\u003e(76.93 \u0026ndash; 90.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e30.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e23.467\u003c/p\u003e\n \u003cp\u003e(6.895 \u0026ndash; 79.871)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e15 (48.39%)\u003c/p\u003e\n \u003cp\u003e(31.6% - 65.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e88 (95.65%)\u003c/p\u003e\n \u003cp\u003e(90% - 98.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEchogenic foci\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMicrocalcifications vs.\u003c/p\u003e\n \u003cp\u003eNone or large comet-tail artifacts / Macrocalcifications / Rim of calcifications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e14 (45.16%)\u003c/p\u003e\n \u003cp\u003e(28.7% - 62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e10 (10.87%)\u003c/p\u003e\n \u003cp\u003e(5.7% - 18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e45.16\u003c/p\u003e\n \u003cp\u003e(27.32 \u0026ndash; 63.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 75px;\"\u003e\n \u003cp\u003e89.13\u003c/p\u003e\n \u003cp\u003e(80.92 \u0026ndash; 94.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 71px;\"\u003e\n \u003cp\u003e58.33\u003c/p\u003e\n \u003cp\u003e(40.96 \u0026ndash; 73.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e82.83\u003c/p\u003e\n \u003cp\u003e(77.66 \u0026ndash; 87.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 68px;\"\u003e\n \u003cp\u003e78.05\u003c/p\u003e\n \u003cp\u003e(69.69 \u0026ndash; 85.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e17.361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003e6.753\u003c/p\u003e\n \u003cp\u003e(2.573 \u0026ndash; 17.726)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 114px;\"\u003e\n \u003cp\u003e17 (54.84%)\u003c/p\u003e\n \u003cp\u003e(37.5% - 71.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 99px;\"\u003e\n \u003cp\u003e82 (89.13%)\u003c/p\u003e\n \u003cp\u003e(81.6% - 94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eChi-Square test (X\u0026sup2;); PPV = Positive Predictive Value; NPV = Negative Predictive Value; CI = Confidence Interval; PTC= papillary thyroid carcinoma; \u003csup\u003e\u0026nbsp;#\u0026nbsp;\u003c/sup\u003eHighly significant\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe high prevalence of thyroid nodules with relatively low malignant potential necessitates accurate preoperative evaluation to guide management to avoid both unnecessary thyroidectomy and missed malignancies. Thyroid nodules are more prevalent in middle-aged females, which might be due to increased incidence of autoimmune thyroid disease; fortunately, most of them are of benign pathology. However, the risk of malignancy is higher in male patients. Other risk factors, like family history and exposure to irradiation, should be considered [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, in our study, thyroid malignancy was found in 42% of the studied participants.\u003c/p\u003e \u003cp\u003eUltrasound evaluation and FNAC of thyroid nodules are the widely used available tools for preoperative assessment. Suspicion for malignancy is categorized according to the TI-RADS and the Bethesda systems [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In this study, we analyzed each ultrasound characteristic for malignancy risk, as well as the overall TI-RADS and Bethesda scores of each nodule, in relation to the final pathology outcomes following surgical excision.\u003c/p\u003e \u003cp\u003eNodule shape remains one of the most reliable indicators of malignant potential, as malignant thyroid nodules typically grow perpendicular to the thyroid capsule, indicating vertical growth that breaches normal tissue planes, resulting in a taller-than-wide appearance. Despite limited sensitivity, the high specificity of this feature, with more than a tenfold increased malignancy risk, supports its significance as a major indicator of malignancy. This finding aligns with the TI-RADS and ATA guidelines, which recognize vertical orientation as a hallmark of malignant infiltration [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMargin irregularity and lobulation or extrathyroidal extension indicate capsular or adjacent soft-tissue invasion; these hallmarks of malignant infiltration with more than tenfold increased malignancy risk and high specificity reinforce their diagnostic importance, particularly in PTC, which commonly exhibits an infiltrative growth pattern [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicrocalcifications, representing psammoma bodies histologically, were another strong predictor with a nearly fivefold increased risk of malignancy, which is a characteristic of PTC. This finding aligns with previous studies demonstrating that microcalcifications are among the most characteristic but less sensitive signs of PTC [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHypoechogenicity, though less specific, was a useful complementary sign with about a fivefold increased risk of malignancy. Its moderate sensitivity and specificity support its inclusion as a secondary suspicious criterion. These findings are consistent with prior studies reporting that malignant nodules tend to be more hypoechoic than the surrounding thyroid parenchyma due to increased cellular density and reduced colloid content [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast, solid composition alone was not significantly predictive, as many benign nodules also present with a solid pattern, limiting its diagnostic utility. This underscores the importance of combining multiple ultrasound features rather than relying on a single finding to improve diagnostic accuracy. These results align with previous studies showing that although most malignant nodules are solid, most of the solid nodules are benign [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, nodule composition should be interpreted cautiously and in combination with other suspicious findings rather than as an isolated malignancy indicator.\u003c/p\u003e \u003cp\u003eThe indication for FNAC of a thyroid nodule depends on the TI-RADS score and the nodule size [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. We observed in our study that in patients with multinodular goiter (MNG), 26% of unbiopsied nodules had a malignant disease in postoperative pathology, so we recommend that in MNG, all suspicious nodules should be biopsied, irrespective of nodule size, if the nodule size is suitable for FNAC (~\u0026thinsp;1 cm in the largest dimension). This comes in line with a study by Paksoy et al., who stated that in MNG, nondominant nodules should be biopsied regardless of the nodule size if the ultrasonographic criteria are suspicious [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, Wong et al. mentioned that in MNG, if more than one nodule had criteria for FNAC, it should be biopsied [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, both the TI-RADS and Bethesda systems demonstrated statistically significant diagnostic performance for predicting thyroid malignancy. Lower scores were largely associated with benign pathology, whereas higher categories correlated strongly with malignant pathology, particularly PTC. TI-RADS showed an AUC of 0.763 (95% CI: 0.668\u0026ndash;0.858) with optimal diagnostic performance at a cut-off value\u0026thinsp;\u0026gt;\u0026thinsp;TR4. Similarly, in a comparative study using TI-RADS cutoffs, TR4/TR5 demonstrated an AUC of 0.77 (95% CI 0.74\u0026ndash;0.81) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe TI-RADS system, although highly specific, demonstrated lower sensitivity, suggesting its value in predicting malignancy when higher-risk sonographic features are present but less sensitivity for detecting all malignant cases.\u003c/p\u003e \u003cp\u003eThe Bethesda system showed slightly superior performance compared to TI-RADS, reflecting its greater diagnostic precision when cytological evaluation is available. The Bethesda system exhibited higher accuracy with an AUC of 0.819 (95% CI: 0.73\u0026ndash;0.91), at a cut-off of Bethesda 3. In line with this, an observational study by Tan et al. found that Bethesda 3 showed an AUC of 0.91 (95% CI: 0.87\u0026ndash;0.96) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur findings emphasize the complementary strength of both systems: TI-RADS serves as an effective noninvasive screening tool for identifying nodules that require cytological assessment, whereas Bethesda provides a suggestive histological diagnosis. The combination of both systems in preoperative thyroid nodule evaluation enhances diagnostic confidence and optimizes clinical decision-making regarding surgical excision or follow-up. However, the presence of low-risk neoplasms like NIFTP, WDT-UMP, and various types of malignant pathologies, other than PTC, in varying percentages across all categories points out the diagnostic overlap in follicular-patterned lesions. This indicates that physicians require new, accessible, and widely used assessment tools for evaluating thyroid nodules to optimize clinical decision-making.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Future Directions\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe relatively modest sensitivity of many features suggests that some malignant nodules will evade detection by ultrasound alone.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe cohort size may affect the confidence intervals and generalizability.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLow-risk neoplasms and follicular-patterned malignant nodules are challenging to evaluate preoperatively, which has led to a research area focused on improving the preoperative assessment of thyroid nodules.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study confirms that the combination of the TI-RADS and Bethesda systems in preoperative thyroid nodule evaluation enhances diagnostic confidence and optimizes clinical decision-making. Ultrasound features, like taller-than-wide shape, irregular margin, hypoechogenicity, and microcalcifications, are significant indicators of thyroid malignancy, particularly PTC. Nondominant nodules in MNG may harbor neoplasms, necessitating multiple FNACs in specific cases.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eFNAC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Fine Needle Aspiration Cytology\u003c/p\u003e\n\u003cp\u003eFND \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Thyroid Follicular Nodular Disease \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNIFTP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Non-Invasive Follicular Thyroid Neoplasm With Papillary-Like Nuclear Features\u003c/p\u003e\n\u003cp\u003eWD-UMP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Well-Differentiated Tumor Of Uncertain Malignant Potential\u003c/p\u003e\n\u003cp\u003eFTC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Follicular Thyroid Carcinoma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIEFV-PTC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Invasive Encapsulated Follicular Variant Papillary Thyroid Carcinoma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePTC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Papillary Thyroid Carcinoma\u003c/p\u003e\n\u003cp\u003eMTC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Medullary Thyroid Carcinoma\u003c/p\u003e\n\u003cp\u003eTI-RADS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Thyroid Imaging Reporting and Data System\u003c/p\u003e\n\u003cp\u003eU/S \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ultrasonography\u003c/p\u003e\n\u003cp\u003eMNG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Multinodular Goiter\u003c/p\u003e\n\u003cp\u003eROC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Receiver Operating Characteristic\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u0026nbsp; \u003cstrong\u003ePositive Predictive Value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Negative Predictive Value\u003c/strong\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe local Research Ethics Committee of the Faculty of Medicine, Ain Shams University, Federal Wide Assurance No. FWA 000017585, had approved the protocol of this study on the 8th of August 2024, ID FMASU R187/2024, before the start of work. Informed consent was obtained from all patients who participated in the study to use their workup data for the research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients provided consent for the use of their ultrasound and pathology images for illustration in the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients’ laboratory, images, and pathology data are available upon reasonable request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work didn’t receive any financial funding from any organization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting of Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo conflicts of interest in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSA and AMMAS formulated the study conception and design. Data collection, entry, and statistical analysis were done by SA, SSA, and AMMAS. Thyroid ultrasound and FNA were performed by the radiologist AEA; she has more than 7 years of experience in this field. Histopathological assessment performed by EAMA; she has more than 5 years of experience. Surgical excision of the thyroid gland was performed by the surgeon FHWM; he has more than 5 years of experience in thyroid surgery. All authors contributed to manuscript writing and revision. All authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors offer great thanks to all staff members who helped in this study and to all patients who agreed to participate in our study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHeged\u0026uuml;s L. Clinical practice. The thyroid nodule. N Engl J Med. 2004;351(17):1764\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuth S, Theune U, Aberle J, Galach A, Bamberger CM. Very high prevalence of thyroid nodules detected by high frequency (13 MHz) ultrasound examination. Eur J Clin Invest. 2009;39(8):699\u0026ndash;706.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDean DS, Gharib H. Epidemiology of thyroid nodules. Best Pract Res Clin Endocrinol Metab. 2008;22(6):901\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaugen BR, Alexander EK, Bible KC, et al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer. Thyroid. 2016;26(1):1\u0026ndash;133.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJuhlin CC, Mete O, Baloch ZW. The 2022 WHO classification of thyroid tumors: novel concepts in nomenclature and grading. 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Acta Cytol. 2012;56(4):333\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTrimboli P, Ngu R, Royer B, Giovanella L, et al. A multicenter validation study for the EU-TIRADS using histological diagnosis as a gold standard. Clin Endocrinol (Oxf). 2019;91(3):340\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAli SZ, VanderLaan PA. The Bethesda system for reporting thyroid cytopathology: definitions, criteria, and explanatory notes. 3rd ed. Cham: Springer; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElbalka SS, Metwally IH, Shetiwy M, et al. Prevalence and predictors of thyroid cancer among thyroid nodules: a retrospective cohort study of 1,000 patients. Ann R Coll Surg Engl. 2021;103(9):683\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilva de Morais N, Stuart J, Guan H, et al. The impact of Hashimoto thyroiditis on thyroid nodule cytology and risk of thyroid cancer. 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Radiologic and pathologic findings of papillary thyroid microcarcinoma. Korean J Radiol. 2009;10(2):194\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JY, Na DG, Yoon SJ, et al. Ultrasound malignancy risk stratification of thyroid nodules based on the degree of hypoechogenicity and echotexture. Eur Radiol. 2020;30(3):1653\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Argan RJ, Alkhafaji DM, Almajid FM, et al. The role of ultrasound as a predictor of malignancy in indeterminate thyroid nodules\u0026mdash;a multicenter study. Med (Kaunas). 2025;61(6):1082.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMolina-Vega M, Rodr\u0026iacute;guez-P\u0026eacute;rez CA, \u0026Aacute;lvarez-Mancha AI, et al. Clinical and ultrasound thyroid nodule characteristics and their association with cytological and histopathological outcomes. J Clin Med. 2019;8(12):2172.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuss G, Bonnema SJ, Erdogan MF, Durante C, et al. European Thyroid Association guidelines for ultrasound malignancy risk stratification of thyroid nodules in adults: the EU-TIRADS. Eur Thyroid J. 2017;6(5):225\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaksoy N, Yazal K, \u0026Ccedil;orak S. Malignancy rate in nondominant nodules in patients with multinodular goiter. Cytojournal. 2011;8:19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong R, Farrell SG, Grossmann M. Thyroid nodules: diagnosis and management. Med J Aust. 2018;209(2):92\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorshizian A, Hashemi F, Khoshhal N, et al. Diagnostic performance of ACR TI-RADS and ATA guidelines in the prediction of thyroid malignancy. Diagnostics (Basel). 2023;13(18):2972.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan H, Li Z, Li N, et al. Thyroid imaging reporting and data system combined with Bethesda classification in qualitative thyroid nodule diagnosis. Med (Baltim). 2019;98(50):e18320.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Thyroid Nodule, TI-RADS, FNAC, BETHESDA","lastPublishedDoi":"10.21203/rs.3.rs-8934299/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8934299/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThyroid nodules are a widespread pathology. While only a small percentage of cases prove to be malignant, careful preoperative evaluation is essential to identify patients who need intervention. We aimed to evaluate the diagnostic performance of preoperative ultrasound and fine-needle aspiration cytology in predicting thyroid malignancy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study included 100 adult patients with 145 suspicious thyroid nodules who were scheduled for hemithyroidectomy or total thyroidectomy. Postoperative histopathology was considered the reference standard. Ultrasound findings and FNAC results were compared with the final histopathology.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFinal histopathology revealed 63.5% benign and 36.5% malignant nodules, with 58% PTC being the most common malignancy; 27% of the unbiopsied nodules were found to be malignant. Malignant nodules had significantly higher TI-RADS and Bethesda scores (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI 5\u0026ndash;5; p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI 4\u0026ndash;5, respectively), while nodule size and number showed no significant association. ROC analysis demonstrated good diagnostic performance for the Bethesda scores (0.819 AUC, 95% CI: 0.731\u0026ndash;0.908, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 at score\u0026thinsp;\u0026gt;\u0026thinsp;2) and the TI-RADS score (0.763 AUC, 95% CI: 0.668\u0026ndash;0.858, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 at score\u0026thinsp;\u0026gt;\u0026thinsp;4). Univariate analysis showed hypoechogenicity, taller-than-wide shape, irregular or lobulated margins, and microcalcifications were strong predictors of malignancy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study confirms that the combination of TI-RADS and Bethesda systems in preoperative thyroid nodule evaluation enhances diagnostic confidence and optimizes clinical decision-making. Ultrasound features, like taller-than-wide shape, irregular margin, hypoechogenicity, and microcalcifications, are significant indicators of thyroid malignancy, particularly PTC. Nondominant nodules in MNG may harbor neoplasms, necessitating multiple FNACs in specific cases.\u003c/p\u003e","manuscriptTitle":"Missed Malignancies in Unbiopsied Thyroid Nodules: Diagnostic Performance of Combined TI-RADS and Bethesda Systems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-27 07:21:15","doi":"10.21203/rs.3.rs-8934299/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-14T11:50:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T00:53:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T07:10:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"38091655379685444725452918650063499585","date":"2026-04-06T09:03:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45932843025517611546517293267534609720","date":"2026-04-01T09:26:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210391943638862900158881276711146614899","date":"2026-04-01T00:23:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T17:57:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210892149420991120435474085701872587764","date":"2026-03-26T17:37:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332293905450775186735870685483227111008","date":"2026-03-25T11:56:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-24T14:20:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-27T10:24:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-25T05:59:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-25T05:58:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Endocrine Disorders","date":"2026-02-21T14:54:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-endocrine-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bend","sideBox":"Learn more about [BMC Endocrine Disorders](http://bmcendocrdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bend/default.aspx","title":"BMC Endocrine Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"83c1778a-51a6-45c5-ba80-a88afbdc8f5e","owner":[],"postedDate":"March 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-27T07:21:15+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-27 07:21:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8934299","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8934299","identity":"rs-8934299","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}