Prediction model construction of cervical central lymph node metastasis in papillary thyroid carcinoma combined with Hashimoto’s thyroiditis utilizing conventional ultrasound and elastography
Highlight box
Key findings
• The nomogram model, based on primary lesion ultrasound features and shear wave elastography (SWE) quantitative parameters in patients with papillary thyroid carcinoma (PTC) combined with Hashimoto’s thyroiditis (HT), can assist clinicians in predicting the likelihood of central lymph node metastasis in PTC patients preoperatively.
What is known and what is new?
• Some studies suggest a significant correlation between the ultrasound characteristics of primary PTC lesions and central lymph node metastasis. Others have found a notable association between primary lesion SWE quantitative parameters and central lymph node metastasis. However, few studies have investigated the relationship between these two factors and central lymph node metastasis in PTC patients with concurrent HT.
• This study aims to explore the relationship between primary lesion ultrasound features, SWE quantitative parameters, and central lymph node metastasis in PTC patients with HT. Based on this relationship, a predictive model is constructed to guide decisions on central lymph node dissection, helping to avoid overtreatment.
What is the implication, and what should change now?
• In cases of PTC combined with HT, when preoperative ultrasound shows enlarged, rounded central lymph nodes, the ultrasound features of the primary.
Introduction
Thyroid carcinoma represents a prevalent malignancy within the endocrine system, exhibiting an upward trajectory in incidence rates in recent times. Papillary thyroid carcinoma (PTC), constituting 80–90% of thyroid carcinoma cases, stands as the predominant histopathological subtype (1). Notably, patients with PTC commonly manifest lymph node metastasis, predominantly observed as central lymph node metastasis (CLNM) (2). Hashimoto’s thyroiditis (HT), or chronic lymphocytic thyroiditis, typifies an autoimmune disease characterized by extensive infiltration of lymphocytes into the thyroid gland often culminating in inflammatory enlargement and central lymph node involvement. However, when PTC is combined with HT, preoperative ultrasound often struggles to distinguish whether central lymph node enlargement is due to metastatic spread from PTC or an inflammatory response caused by HT. In most cases, the lymph nodes appear as rounded enlargements (3,4). However, CLNM is closely associated with the risk of recurrence following PTC surgery (5,6).
A significant association has been identified between ultrasound imaging features of the primary PTC lesion and CLNM (7-9), while other evidence has suggested a strong correlation between primary lesion SWE quantitative parameters and CLNM (10). However, few studies have explored the relationship between these factors and CLNM in cases where PTC is combined with HT. Hence, in our study, we aimed to explore the interplay between ultrasound characteristics of primary foci, quantitative parameters derived from shear wave elastography (SWE), and CLNM in patients presenting with concurrent PTC and HT. By interpreting these relationships, we aim to develop a predictive model that can furnish clinical evidence for the implementation of central lymph node dissection thereby mitigating the risk of over-treatment. Ultimately, our objective is to furnish a more precise and tailored therapeutic approach for PTC patients concurrently afflicted with HT, thereby enhancing treatment efficacy and augmenting the quality of life for these patients. We present this article in accordance with the TRIPOD reporting checklist (available at https://gs.amegroups.com/article/view/10.21037/gs-24-271/rc).
Methods
Patients
We conducted a retrospective analysis of the ultrasound data from patients diagnosed with PTC combined with HT who underwent surgical treatment with routine cervical central lymph node dissection at Xi’an People’s Hospital (Xi’an Fourth Hospital) between January 2019 and October 2023. A total of 181 patients, comprising 215 nodes, were enrolled in this study. The age of the patients ranged from 5 to 70 years, with a mean age of 46.50±9.57 years. All enrolled PTC patients were randomly divided into training and test groups at a 7:3 ratio. Then, patients in each group were further categorized into two groups based on pathology results: the CLNM group (comprising 104 nodes) and non-CLNM group (comprising 111 nodes) with pathology serving as the gold standard. A flowchart of enrollment and grouping is shown in Figure 1.
Inclusion criteria were: (I) patients who underwent preoperative ultrasound and SWE examination post-admission with complete image data available; (II) patients who underwent thyroid nodule surgery with routine intraoperative cervical central lymph node dissection (11).
Exclusion criteria were: (I) patients with concurrent malignant tumors in the head and neck region; (II) patients with incomplete or inadequate ultrasound image data making it unsuitable for study requirements; (III) patients with medical history of head and neck radiotherapy.
Instruments and methods
Instruments
The ultrasound data utilized in this study were obtained using the Aixplorer ultrasound machine manufactured by SuperSonic Imagine (Aix-en-Provence, France). The imaging was conducted with a linear array probe model SLl5-4, featuring a frequency range of 4–15 MHz.
Study methods
Patients were arranged in a supine position with neck elevated to fully expose the thyroid region. A routine ultrasound scan was performed to assess thyroid nodules including observations regarding the quantity, location, depth, size, orientation (both vertical and horizontal). Additionally, characteristics such as structure (solid, cystic solid, and cystic) echogenicity (hyper-echoic, iso-echoic, hypo-echoic, extremely hypo-echoic), calcification (no calcification, coarse calcification, peripheral calcification), margins (well-defined, indistinct, irregular), and capsule (invasive, non-invasive) of the nodules were meticulously evaluated during the examination.
Following the conventional ultrasound examination, the SWE mode was activated, and the region of interest (ROI) was meticulously selected to encompass the entire nodule along with surrounding normal thyroid tissue. Throughout the examination, patients were instructed to hold their breath while the probe was gently placed without exerting any pressure. Once the image was stabilized and properly framed, a 2-mm-diameter Q-BOX was positioned at the firmest region within the nodules. Quantitative SWE parameters including the Young’s modulus maximum (Emax), the mean (Emean), and the minimum (Emin) were then acquired. To ensure data accuracy, three measurements were obtained and subsequently averaged.
Image acquisition and evaluation were conducted collaboratively by two senior sonographers. In case of disagreement, a third senior sonographer was consulted to facilitate discussion and ultimately achieve a consensus regarding the assessment.
Statistical analysis
SPSS version 26.0 and R software version 4.1.3 were utilized for statistical analysis. All enrolled PTC patients were randomly divided into training and test groups at a 7:3 ratio. The study began with univariate analysis of primary foci features and quantitative SWE parameters of the training group. Quantitative data were expressed as and comparison between groups was conducted using independent samples t-test. Categorical data were expressed as n (%), and comparison between groups was performed using Chi-squared test or Fisher’s exact test. Following this, logistic regression analysis was utilized to conduct multifactorial analysis on statistically significant indicators identified in univariate analysis aiming to determine independent risk factors of CLNM. Subsequently, a nomogram model was constructed based on the results of logistic regression analysis and validated using the test group (12-14). The diagnostic efficacy of the model was assessed by generating receiver operating characteristic (ROC) curves, while calibration curves were plotted to assess the model’s prediction compliance. A statistical significance level of P<0.05 was applied throughout the statistical analyses.
Ethical statement
This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). It was approved by the Ethics Committee of Xi’an People’s Hospital (Xi’an Fourth Hospital) (No. KJLL-Z-K-2024008). Since this study was retrospective and did not involve direct contact with study participants, the ethics committee waived the requirement for informed consent.
Results
Univariate analysis of CLNM in PTC patients when accompanied by HT
Univariate analysis of the training group revealed significant associations between CLNM and several factors including nodule size, multiplicity, location, capsule invasion, and Emax (all P<0.05). Specifically, larger nodule diameter, multiple nodules located in the isthmus, capsule invasion, and higher Emax were observed to be associated with an increased tendency for CLNM (as summarized n Table 1).
Table 1
| Variables | Non-CLNM (n=111) | CLNM (n=104) | Statistical value | P |
|---|---|---|---|---|
| Nodule size (cm) | 0.82±0.58 | 1.35±0.74 | −5.872 | <0.001 |
| Multiple | 4.665 | 0.03 | ||
| No | 59 (53.2) | 40 (38.5) | ||
| Yes | 52 (46.8) | 64 (61.5) | ||
| Location | 20.336 | <0.001 | ||
| Isthmus | 2 (1.8) | 13 (12.5) | ||
| Upper pole | 21 (18.9) | 36 (34.6) | ||
| Middle pole | 36 (32.4) | 18 (17.3) | ||
| Lower pole | 52 (46.8) | 37 (35.6) | ||
| Depth | 1.921 | 0.69 | ||
| Shallow | 41 (36.9) | 40 (38.5) | ||
| Middle | 11 (9.9) | 7 (6.7) | ||
| Deep | 39 (35.1) | 32 (30.8) | ||
| Shallow-deep | 20 (18.0) | 25 (24.0) | ||
| Orientation | 0.014 | 0.90 | ||
| Horizontal | 45 (40.5) | 43 (41.3) | ||
| Vertical | 66 (59.5) | 61 (58.7) | ||
| Structure | 0.144 | 0.71 | ||
| Solid | 108 (97.3) | 102 (98.1) | ||
| Predominantly solid | 3 (2.7) | 2 (1.9) | ||
| Echogenicity | 1.392 | 0.50 | ||
| Iso-echoic | 1 (0.9) | 3 (2.9) | ||
| Hypo-echoic | 70 (63.1) | 61 (58.7) | ||
| Extreme hypo-echoic | 40 (36.0) | 40 (38.5) | ||
| Calcification | 1.434 | 0.49 | ||
| No | 38 (34.2) | 29 (27.9) | ||
| Gross calcification | 7 (6.3) | 5 (4.8) | ||
| Microcalcification | 66 (59.5) | 70 (67.3) | ||
| Edge | 3.336 | 0.07 | ||
| Smooth | 13 (11.7) | 5 (4.8) | ||
| Blurred or irregular | 98 (88.3) | 99 (95.2) | ||
| Capsule invasion | 32.931 | <0.001 | ||
| No | 65 (58.6) | 21 (20.2) | ||
| Yes | 46 (41.4) | 83 (79.8) | ||
| Emax (kPa) | 51.96±21.51 | 65.69±25.84 | −4.219 | <0.001 |
| Emean (kPa) | 40.64±16.11 | 41.28±16.55 | −0.287 | 0.77 |
| Emin (kPa) | 25.86±11.35 | 25.45±11.38 | 0.266 | 0.79 |
Data are presented as mean ± standard deviation or n (%). CLNM, central lymph node metastasis; PTC, papillary thyroid carcinoma; HT, Hashimoto thyroiditis.
Multifactorial analysis of CLNM in PTC patients when accompanied by HT
Multifactorial analysis of the training group demonstrated that nodule size, multiplicity, location, capsule invasion, and Emax emerged as independent risk factors for CLNM (all with P<0.05) (as indicated in Table 2).
Table 2
| Indicator | β | SE | Wald | P | Exp(B) | 95% CI |
|---|---|---|---|---|---|---|
| Size (cm) | 1.044 | 0.336 | 9.656 | 0.002 | 2.84 | 1.470–5.485 |
| Emax (kPa) | 0.021 | 0.009 | 5.915 | 0.02 | 1.022 | 1.004–1.040 |
| Multiple occurrence | 0.966 | 0.348 | 7.680 | 0.006 | 2.627 | 1.327–5.201 |
| Location | 0.336 | 0.140 | 5.715 | 0.02 | 1.399 | 1.062–1.842 |
| Capsule invasion | 1.673 | 0.355 | 22.145 | 0.001 | 5.327 | 2.654–10.691 |
CLNM, central lymph node metastasis; PTC, papillary thyroid carcinoma; HT, Hashimoto thyroiditis; SE, standard error; CI, confidence interval.
Nomogram model construction of CLNM in PTC patients when accompanied by HT
The nomogram model for predicting CLNM in PTC patients combined with HT was constructed based on the results of multifactorial analysis. In this model, the presence of CLNM was defined as the dependent variable, while the six independent risk factors identified were defined as independent variables. Each predictive indicator was assigned a score within the model, and cumulative total score corresponded to the predicted risk value (Figure 2).
The accuracy of the model in predicting CLNM was assessed using ROC analysis. The area under the ROC curve (AUC) for the training set was 0.837 (95% confidence interval: 0.773−0.901). For the test set, the AUC was 0.882 (95% confidence interval: 0.803−0.960) (Figure 3).
Additionally, calibration curves of the training and test groups were generated to evaluate the alignment between the actual observations and the probabilistic prediction made by the nomogram model. The calibration curve was close to the diagonal line, which signifies good fitting, affirming the consistency of the model in predicting CLNM (Figure 4).
Discussion
PTC generally carries a favorable prognosis, but it is often accompanied with CLNM (15). International experts typically do not recommend prophylactic central lymph node dissection for low-risk PTC patients who clinically or radiologically show negative lymph nodes. Domestic experts also tend to adopt a conservative approach in such cases (15-17). Nonetheless, research has indicated recurrence rates of PTC ranging from 8% to 25% postoperatively, with CLNM being a primary contributing factor (5,18). Ultrasound serves as the primary imaging modality for preoperative diagnosis of CLNM in PTC patients. Accurate evaluation of central lymph nodes preoperatively is crucial to prevent recurrence resulting from misdiagnosis via ultrasound. Central lymph nodes are situated around the trachea and suprasternal fossa. However, due to gas interference and patients’ individual conditions, direct ultrasound diagnosis rates of CLNM are low, particularly in PTC patients with concurrent HT. In this subgroup, the presence of numerous inflammation-stimulated reactive hyperplasia lymph nodes in the central region significantly hampers ultrasound diagnosis sensitivity.
Studies have indicated a preoperative misdiagnosis rate of CLNM in patients with PTC via ultrasound ranging from 30% to 70% (19,20), which is consistent with our findings, showing that only 64 cases of thyroid metastasis were diagnosed preoperatively through ultrasound. Despite the low direct detection rate of CLNM by ultrasound, its depiction of primary foci of PTC is typically clear and reliable. However, the relationship between PTC combined with HT and CLNM has not been explored enough. Therefore, in this study we aimed to investigate this relationship focusing on routine ultrasound features of primary foci, quantitative parameters of SWE and their association with CLNM in patients with PTC with concurrent HT. Our results indicated that larger nodule size, multiple nodules, isthmus location, capsule invasion, and larger Emax were all identified as independent risk factors for CLNM. Based on these findings we constructed a prediction model that demonstrated high accuracy in predicting CLNM.
It is commonly observed that many thyroid nodules are multifocal, with prevalence rates ranging from approximately 18% to 87% (21). Several studies have confirmed that multifocal PTC is indeed associated with CLNM, which aligns with the findings of this study (22-24). From a biological perspective, tumor cells in multifocal PTC tend to be more invasive, spreading faster, and are more prone to developing CLNM. Additionally, considering tumor burden, having multiple nodules results in a higher overall tumor burden and consequently increases the risk of metastasis, despite the maximum diameter of individual nodes in multifocal PTC often being smaller than those in solitary PTC (25).
Several studies have highlighted thyroid capsule invasion as a significant risk factor for CLNM in PTC, consistent with the findings of this study (26-28). Another research has suggested that diagnosing CLNM may involve considering capsule invasion up to 25% of the total capsule of the tumor-capsule interface (21). The thyroid capsule comprises both a true capsule consisting of the outer thyroid membrane and a false capsule composed of cervical visceral fascia. The false capsule is present only on the medial side of lateral lobes and posterior side of the isthmus. Consequently, most of the thyroid gland is covered solely by the outer thyroid membrane which is composed of thin fibrous tissue and is prone to being breached by tumor tissues. This makes it more likely for tumor tissues to invade central lymph nodes via the lymphatic vessels (29).
According to reports, CLNM is positively correlated with node size, where the larger the nodule the higher the CLNM probability (30,31). Certain studies have also reported that nodules larger than 1 cm in diameter were a risk factor for CLNM, which is consistent with this study (32). This could be attributed to the secretion of vascular endothelial growth factor by malignant nodules, which stimulates neo-vascularization, accelerating nodule growth and facilitating further infiltration (33).
Several studies have indicated that isthmus nodules are more susceptible to extra-glandular invasion and CLNM when compared to lobar nodules, which corroborates with the results of our study (34). Additionally, some researchers have suggested that bilateral central lymph node dissection should be considered a standard procedure for isthmus tumors (35). The recommendation may be attributed to the proximity of isthmus nodules to the thyroid capsule, making them more likely to cause damage to it during tumor growth.
In this study, a larger nodal Emax was associated with a higher likelihood of CLNM which aligns with the findings of Wang et al. (36). This relationship may be attributed to the degree of nodal fibrosis, which is known to promote tumor aggressiveness. Elastography, by assessing tissue stiffness, can indirectly indicate the extent of tissue fibrosis and may also suggest the presence of lymph node metastasis (30,32,37).
Conclusions
The decision to perform cervical central lymph nodes dissection in PTC patients who also have HT, hinges on the development of CLNM. Therefore, it is of great clinical significance to establish an individual-specific prediction model for CLNM in patients with PTC who also have HT. In this study, through multifactorial regression analysis, we constructed a nomogram model integrating five independent risk factors including node size, multiplicity, location, capsule invasion, and Emax to visualize the risk of CLNM in different patients. The model demonstrated a favorable predictive value for CLNM with an AUC of 0.846, as evaluated by ROC analysis.
However, there are several limitations in this study. Firstly, being a retrospective single-center study, the sample size was limited, necessitating future expansion for validation in multicenter prospective studies. Additionally, this study considered multiple PTC nodules within the same patient as separate samples, potentially failing to account for the influence of other cancer foci on the model. Further analysis and exploration of this aspect will be crucial in future prospective studies.
Acknowledgments
Funding: None.
Footnote
Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://gs.amegroups.com/article/view/10.21037/gs-24-271/rc
Data Sharing Statement: Available at https://gs.amegroups.com/article/view/10.21037/gs-24-271/dss
Peer Review File: Available at https://gs.amegroups.com/article/view/10.21037/gs-24-271/prf
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-24-271/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 conducted in accordance with the Declaration of Helsinki (as revised in 2013). It was approved by the Ethics Committee of Xi’an People’s Hospital (Xi’an Fourth Hospital) (No. KJLL-Z-K-2024008). Since this study was retrospective and did not involve direct contact with study participants, the ethics committee waived the requirement for informed consent.
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/.
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