Correlation between ultrasound calcification patterns, and clinicopathological factors and recurrence risk in papillary thyroid carcinoma

Introduction

Thyroid cancer represents the most common malignancy of the endocrine system (1,2). Recent global and national cancer statistics indicate a steady and concerning increase in both incidence and mortality rates associated with this disease. In 2022, approximately 821,200 new cases of thyroid cancer and 47,000 related deaths were reported worldwide. Thyroid cancer accounted for 4.1% of all newly diagnosed cancers (up from 3.0% in previous years) and 0.5% of all cancer-related death (up from 0.4%) (1).

The burden of disease is particularly notable in China, where 466,100 new thyroid cancer cases were documented in 2022, making it the third most frequently diagnosed malignancy in the country (3). Among the different histological subtypes, papillary thyroid carcinoma (PTC) remains the most prevalent, representing 80–90% of all thyroid cancer cases. While PTC generally has a favorable prognosis when diagnosed at an early stage, a subset of patients presents with locally advanced disease, aggressive behavior, and distant metastases, which significantly contribute to thyroid cancer-specific mortality (4). These clinical dichotomies highlight the urgent need for improved early diagnostic strategies and precise risk stratification tools to optimize therapeutic decisions and enhance patient outcomes.

The development of cell diagnostics, the new generation sequencing technology and the microRNA technology platform have enhanced the diagnostic capabilities of molecular detection for thyroid nodules (5-7). High-resolution ultrasonography (US) remains the cornerstone for the evaluation of thyroid nodules identified through palpation or routine screening. Among the various sonographic features, calcification patterns are gaining recognition for their diagnostic and prognostic relevance. Microcalcifications, in particular, are widely acknowledged as a classic ultrasonographic marker of PTC malignancy.

In addition, emerging evidence indicates that heterogeneous calcification morphologies and distribution patterns may correlate with more aggressive tumor behaviors, including larger tumor size, regional lymph node metastasis, and an increased risk of recurrence (8,9). However, current classification systems for thyroid calcification remain inconsistent, and there is a scarcity of studies that systematically explore the relationship between specific calcification subtypes and detailed clinicopathological features. Most prior research has focused primarily on isolated calcification types with limited attention to mixed or complex patterns, leaving the clinical significance of combined calcification morphologies and their spatial distribution poorly defined (10,11).

This knowledge gap has hindered the integration of calcification features into standardized preoperative risk assessment models for PTC.

To address these limitations, the present study aimed to investigate the association between different ultrasound calcification patterns—including absence of calcification, microcalcification, and mixed calcification and clinicopathological parameters, with a particular focus on recurrence risk in PTC. By establishing a standardized and reproducible calcification classification framework, and by analyzing a large retrospective patient cohort, we hypothesized that distinct calcification profiles could serve as independent predictors of tumor aggressiveness and prognosis, with potential implications for preoperative surgical planning and postoperative surveillance strategies. We present this article in accordance with the STROBE reporting checklist (available at https://gs.amegroups.com/article/view/10.21037/gs-2025-324/rc).

Methods

Patient population

A retrospective analysis was conducted on the clinicopathological data of patients with thyroid cancer who were first diagnosed at the Tianjin Medical University Cancer Institute and Hospital between January 2020 and December 2021. The inclusion criteria were as follows: (I) having undergone an ultrasonic examination at our hospital; (II) with complete imaging data; and (III) patients who were postoperatively confirmed to have a PTC pathological type. Exclusion criteria included: (I) patients who underwent secondary or multiple surgeries; (II) with incomplete clinical and pathological data; (III) with benign or other histopathological nodule types; (IV) with history of head and neck radiotherapy; (V) those after radiofrequency ablation.

The baseline clinicopathological and hematological data of the patients were collected. Factors related to the primary tumor included tumor size, multifocality, capsular invasion, Hashimoto’s thyroiditis, and the pathological subtype. Lymph node features included the number of metastases, metastasis ratio, maximum diameter of lymph node metastases, and presence of the extra-nodal extension of lymph node metastasis. The recurrence risk assessment was based on the 2015 American Thyroid Association (ATA) recurrence risk stratification criteria for thyroid cancer (12). This study was approved by the Ethics Committee of the Tianjin Medical University Cancer Institute and Hospital (No. bc2022100). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Patient consent was waived due to the retrospective nature.

Instruments and methods

All patients underwent ultrasound examinations at Tianjin Medical University Cancer Institute and Hospital using Philips iu22 and Philips HD11 color Doppler ultrasound diagnostic instruments (Philips Ultrasound, Fishers, USA). The scanning range included the thyroid area and neck lymph nodes in regions I–VII. The recorded information for the primary lesion included the location, size, number, echo, boundary, relationship with the capsule, aspect ratio, calcification, blood flow, and Thyroid Imaging Reporting and Data System (TI-RADS) classification. For lymph nodes, the recorded information included the region, size, shape, boundary, ratio of the long to short axis, internal echo, cystic changes, calcification, and other relevant features. Patients with cN0/cN1a stage underwent thyroid lobectomy or total thyroidectomy, as well as unilateral/bilateral central lymph node dissection. Patients whose preoperative puncture pathology confirmed the presence of lymph node metastasis on the side of the neck underwent total thyroidectomy as well as lateral cervical lymph node dissection.

Ultrasonographic calcification patterns

Based on the calcification morphology, the patients were classified into the following three groups: the no calcification group, the microcalcification group, and the mixed calcification group (Figure 1). Microcalcification was defined as strong echogenic foci ≤2 mm in size without posterior acoustic shadowing; macrocalcification was defined as strong echogenic structures >2 mm in size, usually accompanied by acoustic shadowing; while mixed calcification was defined as the coexistence of microcalcification and macrocalcification. When multiple nodules were present in the ultrasound images, the most suspicious positive nodule was analyzed.

Figure 1 Transverse ultrasound image of thyroid nodules. (A) No calcification; (B) microcalcification; (C) mixed calcification.

Statistical analysis

The statistical analysis was performed using SPSS 26.0. For the continuous variables, a one-way analysis of variance was used for the univariate analysis if the data followed a normal distribution, while the rank-sum test was used if the data did not follow a normal distribution. For the categorical variables, the Chi-squared test was used for the univariate analysis. For the binary variables, binary logistic regression was used for the multivariate analysis, and for the multicategory variables, unordered multicategory logistic regression was used for the multivariate analysis. Results were presented as odds ratios (ORs) with 95% confidence intervals (CIs), and statistical significance was defined as P<0.05.

Results

Basic data characteristics

A total of 1,182 patients with PTC who met the inclusion criteria were enrolled in the study (Figure 2). The clinicopathological data, pre-treatment blood test indicators, and pre-treatment ultrasonographic images of the patients were collected.

Figure 2 Flowchart of the inclusion and exclusion criteria for patients with papillary thyroid carcinoma in this study.

As detailed in Table 1, of the enrolled patients, 336 were male and 846 were female; the average age of the patients was 43.6 years (ranging from 18 to 74 years); and 984 patients (83.2%) were aged under 55 years. Additionally, the average tumor diameter was 1.10 cm; 721 patients (61.0%) had thyroid microcarcinomas; 469 (39.7%) had multifocal carcinomas; 518 (43.8%) had classical PTCs; 40 (3.4%) had extrathyroidal extension (involving fat or striated muscle); 265 (22.4%) had Hashimoto’s thyroiditis; 632 (53.5%) had central lymph node metastasis; 274 (23.2%) had lateral neck lymph node metastasis; 299 (25.3%) had extra-nodal extension of lymph node metastasis; 271 (22.9%) had more than 5 lymph nodes with metastasis; and according to the 2015 ATA risk stratification criteria for recurrence, 256 patients were at a high risk of recurrence.

The relationship between the calcification morphology of the primary lesion in thyroid cancer and clinicopathological factors

As Table 2 shows, microcalcification was the most common type of calcification. Of the patients, 748 (63.3%) had microcalcifications, 295 (25.0%) had no calcifications, and 139 (11.8%) had mixed calcifications. A correlation analysis was conducted between the calcification morphology and clinicopathological factors. Statistically significant differences were found among the groups in terms of gender, age, tumor size, multifocality, and extrathyroidal extension. Microcalcification was more common in patients aged less than 55 years, while mixed calcification was more common in the older patients. The proportion of capsular invasion was highest in the microcalcification group. The patients with mixed calcification had larger tumor diameters and a higher number of lesions. The patients with microcalcification had a higher risk of recurrence than those with no calcification or mixed calcification, and the difference was statistically significant.

We also conducted a correlation analysis of the calcification morphology of the primary tumor and the characteristics of lymph node metastasis. Statistically significant differences were found in the characteristics of lymph node metastasis among the subgroups with different calcification patterns, including in terms of central lymph node metastasis (χ²=54.514, P<0.001), lateral lymph node metastasis (χ²=68.310, P<0.001), extracapsular spread of lymph nodes (χ²=32.749, P<0.001), the number of lymph node metastases (χ²=50.246, P<0.001), soft-tissue involvement (χ²=15.554, P<0.001), the maximum diameter of metastatic lymph nodes (χ²=59.498, P<0.001), and lymph node calcification (χ²=73.860, P<0.001). The patients with microcalcification had a higher number of lymph node metastases, larger metastatic lymph node diameters, and a higher proportion had lymph node extracapsular spread.

As set out in Table 3, the correlation between calcification morphology and hematological indicators was analyzed using the rank-sum test. The expression level of thyroglobulin was significantly higher in the mixed calcification group (19.90 µg/L) than in the microcalcification group (15.80 µg/L), which in turn had a higher expression level of thyroglobulin than in the non-calcification group (12.10 µg/L), and the difference was statistically significant (Z=18.522, P<0.001). The parathyroid hormone level was highest in the non-calcification group (4.30 pmol/L), followed by the mixed calcification group (4.15 pmol/L), and lowest in the microcalcification group (3.93 pmol/L), and the difference was statistically significant (Z=9.081, P=0.01). However, no statistically significant differences were observed among the groups in terms of the expression levels of thyroid-stimulating hormone, thyroglobulin antibodies, thyroid peroxidase antibodies, calcitonin, blood lipids, blood glucose, and other indicators.

As detailed in Table 4, multinomial logistic regression analysis demonstrated significant gender-based differences in calcification patterns. Males had higher odds of microcalcifications (OR =1.457) and mixed calcifications (OR =2.174) compared to females. Tumors exhibiting microcalcifications showed 2.00-fold increased risk of exceeding 1 cm diameter, while mixed calcifications conferred a 3.10-fold risk elevation of the tumor diameter exceeding 1 cm. Microcalcifications were associated with increased central (OR =1.613) and lateral cervical (OR =4.082) lymph node metastasis risks. Mixed calcifications showed no significant association with central lymph node metastasis but increased lateral cervical metastasis risk (OR =2.841).

As set out in Table 5, all three types of calcifications were observed in the classic subtype, follicular subtype, and tall-cell subtype, of which, microcalcification was the most prevalent. However, only microcalcification was observed in the Warthin-like subtype, solid subtype, and clear-cell subtype. The diffuse sclerosing subtype exhibited both microcalcification and mixed calcification.

Discussion

The pathogenesis of calcifications in thyroid nodules is a complex process involving multiple biological mechanisms, including tissue necrosis, hemorrhage, chronic inflammation, and fibrosis. In the context of PTC, microcalcifications are frequently associated histologically with psammoma bodies—concentric laminated calcific deposits formed as a result of tumor cell degeneration via apoptotic or necrotic processes (13). These microcalcifications linked to psammoma bodies represent a highly specific, though not highly sensitive, marker of malignancy (14). They are often associated with increased tumor aggressiveness, higher rates of cervical lymph node metastasis, and elevated risk of recurrence (15). Their detection through thyroid US therefore constitutes an important diagnostic feature. Conversely, macrocalcifications and mixed calcification patterns may reflect a different tumor biology. Macrocalcifications typically arise from chronic dystrophic processes affecting larger, slower-growing nodules, whether benign or malignant. Emerging evidence suggests that heterogeneous or mixed calcification patterns may correlate with larger tumor volumes and more extensive local tissue invasion, although their predictive value for malignancy remains less well defined (9,16,17). Moreover, calcification patterns may also mirror characteristics of the tumor microenvironment, such as neoangiogenesis, fibrotic remodeling, and immune cell infiltration—factors increasingly recognized as critical determinants of tumor progression and treatment response (18). Given these considerations, a more detailed and standardized characterization of calcification morphologies could substantially improve preoperative risk stratification and help guide clinical decision-making in thyroid cancer management.

Previous research has demonstrated that the biological nature of thyroid nodules can give rise to distinct calcification morphologies, prompting numerous investigators to systematically examine the association between calcification patterns and specific nodule characteristics. Calcifications within thyroid nodules are typically classified based on size into two main categories: microcalcifications and macrocalcifications. According to the 2017 American College of Radiology (ACR) TI-RADS guidelines, microcalcifications are defined as punctate hyperechoic foci measuring ≤1 mm in maximum diameter (19). However, it is important to note that the threshold criteria for differentiating microcalcifications from macrocalcifications remain inconsistent across the literature, with cut-off values ranging from 1 to 2 mm depending on the specific study (20-22). This lack of uniformity in classification standards contributes to variability in study results and underlines the need for more standardized definitions to enable better comparison across clinical investigations.

In this study, hyperechoic foci ≤2 mm in diameter were classified as microcalcifications, while those >2 mm in diameter were classified as macrocalcifications, and coexisting forms of both were defined as mixed calcifications. Microcalcifications are recognized as a specific marker of PTC. In this study, the proportion of PTC patients with microcalcifications was 63.0%, while the proportion of PTC patients with mixed calcifications was 11.8%. Ha et al. (23) reported that among 354 PTC cases, 45.8% exhibited no calcifications, 11.9% displayed both macrocalcifications and microcalcifications, and 30.5% showed microcalcifications alone. Notably, their study defined microcalcifications as ≤1 mm in diameter, which differs from the criteria employed in this study.

This study found that the prevalence of calcifications was higher in male patients than in female patients, and the odds of male patients developing microcalcifications and mixed calcifications increased 1.5-fold and 2.2-fold, respectively. In patients aged <55 years, ​64.8% had microcalcifications, while 9.1%​had mixed calcifications. Conversely, in patients aged ≥55 years, the proportion of microcalcifications decreased to 55.5%, while the proportion of mixed calcifications increased to 24.7%.

This age-related shift in calcification patterns aligns with the findings reported by Ha et al. (23), who observed that patients with mixed calcifications were generally older, whereas those with no calcifications or only microcalcifications tended to be younger. Similarly, Sugitani et al. (24), in their active surveillance study on low-risk PTC, demonstrated that the extent and type of calcification were closely associated with both tumor size progression and patient age. These findings collectively underscore the potential role of calcification patterns as dynamic biomarkers, reflecting both tumor biology and host factors with possible implications for risk stratification and personalized management strategies in thyroid cancer.

Previous studies have reported that calcifications are associated with the invasive behavior of PTC (25,26). Our study demonstrated that microcalcifications were significantly correlated with aggressive tumor biology, particularly lymph node metastasis. Specifically, microcalcifications increased the risk of central lymph node metastasis by 1.6-fold and the risk of lateral cervical lymph node metastasis by 4.1-fold. In contrast, mixed calcifications showed a stronger association with increased tumor size. Microcalcifications were linked to a 2.0-fold higher risk of tumors larger than 1 cm, whereas mixed calcifications correlated with a 3.1-fold increased risk of larger tumors. These results indicate that calcification heterogeneity may reflect distinct underlying biological behaviors.

Furthermore, hematological correlations provided additional mechanistic insights. The stepwise increase in thyroglobulin levels from non-calcified to microcalcification and mixed calcification groups may indicate progressive tumor burden or altered thyroid follicular cell function. Conversely, the observed paradoxical decrease in parathyroid hormone levels across these groups suggests possible involvement of the parathyroid gland related to calcification processes or alterations in calcium metabolism.

Previous studies have suggested that the vast majority of cases with diffuse calcifications belong to the classic subtype of PTC. However, rare subtypes, such as the diffuse sclerosing variant and the hypercellular subtype, have also been reported to exhibit this feature (27,28). In our study, histological subtype analysis revealed intriguing patterns in the distribution of calcifications. While microcalcifications were commonly observed across all major PTC subtypes—including classic, follicular, and tall cell variants—their exclusive presence in rare histological variants (such as Warthin-like, solid, and clear cell subtypes) suggests that distinct, subtype-specific mechanisms may underlie calcification in these more aggressive forms. Furthermore, the diffuse sclerosing variant was characterized by a combination of microcalcifications and mixed calcification patterns, likely reflecting its dense fibroinflammatory stroma interspersed with scattered tumor foci, a hallmark feature of this aggressive histological entity.

The 2015 ATA risk stratification system for PTC is primarily based on postoperative pathological features and does not currently incorporate calcification patterns as prognostic factors (12). However, emerging evidence suggests their potential relevance. For example, Shen et al. (29) reported a significant association between calcification presence and intermediate-to-high recurrence risk in PTC, though their study did not perform a detailed analysis of calcification subtypes. In our study, we demonstrated that patients with microcalcifications exhibited a significantly higher recurrence risk compared to those with no calcification or mixed calcifications (χ²=69.009, P<0.001). These findings suggest that calcification morphology, particularly the presence of microcalcifications, may serve as an independent marker of poor prognosis. Clinicians may therefore consider integrating calcification-based risk assessment into preoperative evaluation and postoperative management strategies.

There are several limitations in this study. First, its retrospective design inherently limits the ability to establish causal relationships. Second, the analysis was conducted within a single-center cohort, which may introduce selection bias and limit the generalizability of the findings. Third, this study did not incorporate the original image data and pathological controls, which might affect the accuracy of the interpretation of the calcification features. Nevertheless, the large sample size, combined with a comprehensive multidimensional analysis of both clinical and hematological parameters, provides robust evidence supporting the prognostic value of calcification morphology in PTC.

Looking ahead, future prospective, multicenter studies incorporating molecular profiling, radiomics, and potentially artificial intelligence-based ultrasound feature analysis are warranted to validate and refine these findings. Such studies could help clarify the biological mechanisms driving the observed associations between calcification subtypes and tumor behavior.

In conclusion, our study establishes calcification morphology as an important determinant of tumor aggressiveness, lymph node metastasis risk, and even preoperative hematological profiles in PTC. These findings emphasize the need to incorporate calcification characteristics into risk stratification algorithms, with potential therapeutic and surveillance implications for patients with distinct calcification patterns. Ultimately, the integration of calcification features may help pave the way toward more personalized and biologically-informed management strategies in thyroid cancer care.

Conclusions

Our study highlights the clinical significance of ultrasound-detected calcification patterns in PTC. Specifically, microcalcifications were identified as strong predictors of tumor aggressiveness, lymph node metastasis, and increased recurrence risk, while mixed calcifications were more strongly associated with tumor size progression. Additionally, the observed correlations with hematological markers, such as thyroglobulin and parathyroid hormone levels, provide novel insights into the biological behavior of PTC with varying calcification morphologies.

These findings suggest that calcification patterns—currently overlooked in most risk stratification systems—could serve as valuable, non-invasive preoperative biomarkers for guiding both surgical planning (e.g., extent of lymph node dissection) and postoperative surveillance strategies.

Given the retrospective and single-center nature of our study, further prospective, multicenter trials integrating molecular and radiomics analyses are warranted to validate these results and explore the underlying pathophysiological mechanisms. Ultimately, integrating calcification morphology into future risk stratification algorithms could contribute to a more personalized and biologically-driven approach to the management of thyroid cancer patients.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-324/rc

Data Sharing Statement: Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-324/dss

Peer Review File: Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-324/prf

Funding: This research was funded by the Tianjin Health Science and Technology Project (No. TJWJ2023QN048), and the Discipline Research Special Project of Tianjin Medical University (No. 2024XKNFM18).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-2025-324/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was approved by the Ethics Committee of the Tianjin Medical University Cancer Institute and Hospital (No. bc2022100). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Patient consent was waived due to the retrospective nature.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
2. Kitahara CM, Schneider AB. Epidemiology of Thyroid Cancer. Cancer Epidemiol Biomarkers Prev 2022;31:1284-97. [Crossref] [PubMed]
3. Han B, Zheng R, Zeng H, et al. Cancer incidence and mortality in China, 2022. J Natl Cancer Cent 2024;4:47-53. [Crossref] [PubMed]
4. Patel J, Klopper J, Cottrill EE. Molecular diagnostics in the evaluation of thyroid nodules: Current use and prospective opportunities. Front Endocrinol (Lausanne) 2023;14:1101410. [Crossref] [PubMed]
5. Dell'Aquila M, Granitto A, Martini M, et al. PD-L1 and thyroid cytology: A possible diagnostic and prognostic marker. Cancer Cytopathol 2020;128:177-89. [Crossref] [PubMed]
6. Fiorentino V. The Role of Cytology in the Diagnosis of Subcentimeter Thyroid Lesions. Diagnostics (Basel) 2021;11:1043. [Crossref] [PubMed]
7. Lim H, Devesa SS, Sosa JA, et al. Trends in Thyroid Cancer Incidence and Mortality in the United States, 1974-2013. JAMA 2017;317:1338-48. [Crossref] [PubMed]
8. Qian ZJ, Jin MC, Meister KD, et al. Pediatric Thyroid Cancer Incidence and Mortality Trends in the United States, 1973-2013. JAMA Otolaryngol Head Neck Surg 2019;145:617-23. [Crossref] [PubMed]
9. Şah Ünal FT, Gökçay Canpolat A, Elhan AH, et al. Cancer rates and characteristics of thyroid nodules with macrocalcification. Endocrine 2024;84:1021-9. [Crossref] [PubMed]
10. Ye M, Wu S, Zhou Q, et al. Association between macrocalcification and papillary thyroid carcinoma and corresponding valuable diagnostic tool: retrospective study. World J Surg Oncol 2023;21:149. [Crossref] [PubMed]
11. Shin HS, Na DG, Paik W, et al. Malignancy Risk Stratification of Thyroid Nodules with Macrocalcification and Rim Calcification Based on Ultrasound Patterns. Korean J Radiol 2021;22:663-71. [Crossref] [PubMed]
12. Haugen BR, Alexander EK, Bible KC, et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 2016;26:1-133. [Crossref] [PubMed]
13. Triggiani V, Guastamacchia E, Licchelli B, et al. Microcalcifications and psammoma bodies in thyroid tumors. Thyroid 2008;18:1017-8. [Crossref] [PubMed]
14. O'Connor E, Mullins M, O'Connor D, et al. The relationship between ultrasound microcalcifications and psammoma bodies in thyroid tumours: a single-institution retrospective study. Clin Radiol 2022;77:e48-54. [Crossref] [PubMed]
15. Bai Y, Zhou G, Nakamura M, et al. Survival impact of psammoma body, stromal calcification, and bone formation in papillary thyroid carcinoma. Mod Pathol 2009;22:887-94. [Crossref] [PubMed]
16. Park YJ, Kim JA, Son EJ, et al. Thyroid nodules with macrocalcification: sonographic findings predictive of malignancy. Yonsei Med J 2014;55:339-44. [Crossref] [PubMed]
17. Gwon HY, Na DG, Noh BJ, et al. Thyroid Nodules with Isolated Macrocalcifications: Malignancy Risk of Isolated Macrocalcifications and Postoperative Risk Stratification of Malignant Tumors Manifesting as Isolated Macrocalcifications. Korean J Radiol 2020;21:605-13. [Crossref] [PubMed]
18. Niu DF, Kondo T, Nakazawa T, et al. Transcription factor Runx2 is a regulator of epithelial-mesenchymal transition and invasion in thyroid carcinomas. Lab Invest 2012;92:1181-90. [Crossref] [PubMed]
19. 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;14:587-95. [Crossref] [PubMed]
20. Moon WJ, Jung SL, Lee JH, et al. Benign and malignant thyroid nodules: US differentiation--multicenter retrospective study. Radiology 2008;247:762-70. [Crossref] [PubMed]
21. Yuan WH, Chiou HJ, Chou YH, et al. Gray-scale and color Doppler ultrasonographic manifestations of papillary thyroid carcinoma: analysis of 51 cases. Clin Imaging 2006;30:394-401. [Crossref] [PubMed]
22. Jeh SK, Jung SL, Kim BS, et al. Evaluating the degree of conformity of papillary carcinoma and follicular carcinoma to the reported ultrasonographic findings of malignant thyroid tumor. Korean J Radiol 2007;8:192-7. [Crossref] [PubMed]
23. Ha J, Lee J, Jo K, et al. Calcification Patterns in Papillary Thyroid Carcinoma are Associated with Changes in Thyroid Hormones and Coronary Artery Calcification. J Clin Med 2018;7:183. [Crossref] [PubMed]
24. Sugitani I, Nagaoka R, Saitou M, et al. Long-term outcomes of active surveillance for low-risk papillary thyroid carcinoma: Progression patterns and tumor calcification. World J Surg 2025;49:159-69. [Crossref] [PubMed]
25. Li C, Zhou L, Dionigi G, et al. The Association Between Tumor Tissue Calcification, Obesity, and Thyroid Cancer Invasiveness In A Cohort Study. Endocr Pract 2020;26:830-9. [Crossref] [PubMed]
26. Jia W, Cai Y, Wang S, et al. Predictive value of an ultrasound-based radiomics model for central lymph node metastasis of papillary thyroid carcinoma. Int J Med Sci 2024;21:1701-9. [Crossref] [PubMed]
27. Ioakim S, Constantinides V, Toumba M, et al. Microcalcifications without a thyroid nodule as the sole sign of papillary thyroid carcinoma. Endocrinol Diabetes Metab Case Rep 2021;2021:21-0072. [Crossref] [PubMed]
28. Kwak JY, Kim EK, Son EJ, et al. Papillary thyroid carcinoma manifested solely as microcalcifications on sonography. AJR Am J Roentgenol 2007;189:227-31. [Crossref] [PubMed]
29. Shen K, Xiao S, Wu X, et al. Preoperative prognostic risk stratification model for papillary thyroid carcinoma based on clinical and ultrasound characteristics. Front Endocrinol (Lausanne) 2022;13:1025739. [Crossref] [PubMed]