Risk factor analysis for predicting cervical lymph node metastasis in papillary thyroid carcinoma: a study of 966 patients

External validation of a deep learning-based algorithm for detection of tall cells in papillary thyroid carcinoma: A multicenter study

The tall cell subtype (TC-PTC) is an aggressive subtype of papillary thyroid carcinoma (PTC). The TC-PTC is defined as a PTC comprising at least 30% epithelial cells that are three times as tall as they are wide. In practice, this definition is difficult to adhere to, resulting in high inter-observer variability. In this multicenter study, we validated a previously trained deep learning (DL)-based algorithm for detection of tall cells on 160 externally collected hematoxylin and eosin (HE)-stained PTC whole-slide images. In a test set of 360 manual annotations of regions of interest from 18 separate tissue sections in the external dataset, the DL-based algorithm detected TCs with a sensitivity of 90.6% and a specificity of 88.5%. The DL algorithm detected non-TC areas with a sensitivity of 81.6% and a specificity of 92.9%. In the validation datasets, 20% and 30% TC thresholds correlated with a significantly shorter relapse-free survival. In conclusion, the DL algorithm detected TCs in unseen, external scanned HE tissue slides with high sensitivity and specificity without any retraining.

The value of dual time-point fluorine-18 fluorodeoxyglucose PET/computed tomography imaging in predicting lymph node metastasis in non-small cell lung cancer patients

OBJECTIVE

The purpose of this study was to analyze the correlation between specified dual time-point fluorine-18 fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (CT) imaging parameters and pathological characteristics in non-small cell lung cancer (NSCLC) patients.

METHODS

This study retrospectively analyzed 47 patients with NSCLC. All patients underwent dual time-point 18 F-FDG PET/CT imaging. We obtained the metabolic parameters, standardized uptake value (SUV) maximum, SUV mean , delayed standardized uptake value (DSUV) maximum, DSUV mean , delay index standardized uptake value (DISUV) maximum, and DISUV mean , of the primary tumor. The tumor size was measured by CT. All lymph nodes had a definite pathological diagnosis. We next evaluated the status of the lymph node metastases (LNM) and the correlations between metabolic parameters and clinical characteristics. Receiver operating characteristic curves were drawn for the prediction of LNM.

RESULTS

We found that the DSUV max , DISUV max , DSUV mean , and tumor size were significantly related to LNM ( P  = 0.036, 0.009, and 0.049, respectively). Multivariate analysis revealed that tumor size and DISUV max were independent risk factors for LNM in lung cancer patients. According to the receiver operating characteristic curve analysis, the optimal cutoff values for DISUV max and tumor size were 0.33 and 2.8 cm, respectively. When these two parameters were combined, the area under the curve for predicting LNM in NSCLC was 0.768, and the sensitivity was 95.7% for predicting LNM in lung cancer patients. We further allocated the patients to three groups: the high-risk group (tumor size ≥ 2.8 cm, DISUV max  ≥ 0.33), the moderate-risk group (tumor size ≥ 2.8 cm, DISUV max  < 0.33, or tumor size < 2.8 cm, DISUV max  ≥ 0.33), and the low-risk group (tumor size < 2.8 cm, DISUV max  < 0.33). The rates of LNM were 70, 50, and 0%, respectively.

CONCLUSION

Tumor size and DISUV max are risk factors for predicting LNM, and they are more useful in combination. Compared with standard PET/CT imaging, dual time-point PET/CT imaging has added value in predicting LNM in NSCLC patients.

An Online Model for Central Lymph Node Metastases in Papillary Thyroid Carcinoma With BRAF V600E Mutation

OBJECTIVE

To construct a predictive model to direct the dissection of the central lymph nodes in papillary thyroid cancer (PTC) with BRAF V600E mutation by identifying the risk variables for central lymph node metastases (CLNM).

METHODS

Data from 466 PTC patients with BRAF V600E mutations underwent thyroid surgery was collected and analyzed retrospectively. For these patients, we conducted univariate and multivariate logistic regression analysis to find risk variables for CLNM. To construct a nomogram, the independent predictors were chosen. The calibration, discrimination, and clinical utility of the predictive model were assessed by training and validation data.

RESULTS

CLNM was present in 323/466 PTC patients with BRAF V600E mutations. By using univariate and multivariate logistic regression, we discovered that gender, age, tumor size, multifocality, and pathological subtype were all independent predictors of CLNM in PTC patients with BRAF V600E mutations. A predictive nomogram was created by combining these variables. In both training and validation groups, the nomogram demonstrated great calibration capacities. The training and validation groups' areas under the curve (AUC) were 0.772 (specificity 0.694, sensitivity 0.728, 95% CI: 0.7195-0.8247) and 0.731 (specificity 0.778, sensitivity 0.653, 95% CI: 0.6386-0.8232) respectively. According to the nomogram's decision curve analysis (DCA), the nomogram might be beneficial. As well, an online dynamic calculator was developed to make the application of this nomogram easier in the clinic.

CONCLUSION

An online nomogram model based on the 5 predictors included gender, age, pathological subtype, multifocality, and tumor size was confirmed to predict CLNM and guide the central lymph nodes dissection in PTC patients with BRAF V600E mutations.

Risk stratification for central lymph node metastasis in mono-focal papillary thyroid carcinoma patients with encapsulated tumor as confirmed by preoperative ultrasound: a multi-center analysis

PURPOSES

Mono-focal papillary thyroid carcinoma (PTC) patients with encapsulated tumor have traditionally been considered as low central lymph node metastasis (CLNM) risk subgroup. The aim of the research was to quantitatively predict the probability of CLNM for mono-focal PTC patients with encapsulated tumor as confirmed by preoperative ultrasound based on pre- and post-operative indexes respectively to guide the selection of prophylactic central lymph node dissection (CLND) and follow-up strategies.

METHODS

A total of 1014 mono-focal PTC patients with encapsulated tumor as confirmed by preoperative ultrasound from three medical centers were retrospectively analyzed, with 534 patients served as Training group and 480 patients as Validation group.

RESULTS

Multivariate analyses showed that age < 55 years old, male, clinical maximum tumor diameter (cMTD) > 0.5 cm, pathological maximum tumor diameter (pMTD) > 0.5 cm, and the presence of microscopic thyroid capsular invasion (mTCI) were independent CLNM risk factors. These were used to construct two nomograms that can effectively predict the central neck involvement in mono-focal PTC patients with encapsulated tumor. The first nomogram (pre-model) provides quantitative assessment on the necessity of prophylactic CLND, while the second nomogram (post-model) informs postoperative follow-up strategies.

CONCLUSIONS

Meticulous and comprehensive stratification flow charts that quantitatively evaluate the risk of central lymph node metastasis both pre- and post-operatively were constructed for mono-focal PTC patients with encapsulated tumor as confirmed by preoperative ultrasound, which may benefit both clinical decision-making of prophylactic CLND and postoperative follow-up strategies for the management of neck regions.

Application of color doppler ultrasound and US shear wave elastography with connective tissue growth factor in the risk assessment of papillary thyroid carcinoma

BACKGROUND

This study aims to investigate the role of shear wave elastography (SWE) and connective tissue growth factor (CTGF) in the assessment of papillary thyroid carcinoma (PTC) prognosis.

METHODS

CTGF expression was detected with immunohistochemistry. Clinical and pathological data were collected. Parameters of conventional ultrasound combined with SWE were also collected. The relationship among CTGF expression, ultrasound indicators, the elastic modulus and the clinicopathological parameters were analyzed.

RESULTS

Univariate analysis showed that patients with high risk of PTC were characterized with male, Uygur ethnicity, increased expression of CTGF, convex lesions, calcified, incomplete capsule, intranodular blood flow, rear echo attenuation, cervical lymph node metastasis, lesions larger than 1 cm, psammoma bodies, advanced clinical stage, increased TSH and high value in the shear modulus (P < 0.05). Multivariate analysis demonstrated that the risk factors of high expression of CTGF according to contribution size order were irregular shape, aspect ratio ≥ 1, and increased TSH. The logistic regression model equation was Logit (P) = 1.153 + 1.055 × 1 + 0.926 × 2 + 1.190 × 3 and the Area Under Curve value of the logistic regression was calculated to be 0.850, with a 95% confidence interval of 0.817 to 0.883.

CONCLUSION

SWE and CTGF are of great value in the risk assessment of PTC. The degree of fibrosis of PTC is closely related to the prognosis. The hardness of PTC lesions and the expression level of CTGF are correlated with the main indexes of conventional ultrasound differentiating benign or malignant nodules. Irregular shape, aspect ratio ≥ 1, and increased TSH are independent factors of CTGF.

Evaluation of the risk factors of metastasis to central cervical lymph nodes in patients with papillary thyroid carcinoma

Background

Papillary thyroid cancer, comprising 80% of thyroid malignancies in iodine-sufficient areas, can be effectively treated if detected early before metastasis. Cervical lymph nodes are a common site of metastasis, prompting some surgeons to suggest prophylactic dissection in all patients. To minimize potential side effects, this study aims to identify patients benefiting from this procedure by assessing risk factors for central lymph node metastasis.

Methods and materials

This descriptive-analytical study was conducted on 150 patients with papillary thyroid cancer. The samples included cases in which central lymph node involvement was ruled out clinically and radiologically. After proving papillary cancer in the pathology sample, the variables of age, sex, frequency of central lymph node involvement, tumor size, location of thyroid involvement, multi-centric involvement, multi-focal involvement, presence of microcalcification, capsular invasion, lymphovascular invasion, and pathology were analyzed. The results were presented with descriptive statistics.

Results

The percentage of central lymph node involvement in this study was reported as 9.3%. In the analysis, capsular invasion (P=0.01), lymphovascular invasion (P=0.0001) and involvement of the upper thyroid pole (P=0.001) were identified as risk factors for central lymph node involvement. There was no significant relationship between the variables of age, sex, tumor size, pathology, multi-centricity and multifocality and central lymph node involvement.

Conclusion

Involvement of central lymph nodes in patients with capsular invasion, lymphovascular invasion, and involvement of the upper thyroid bridge is far more common than in other patients, and central lymph node dissection is recommended in patients with several of the above risk factors.

Nomogram for predicting the risk of central lymph node metastasis in papillary thyroid microcarcinoma: a combination of sonographic findings and clinical factors

Background

A considerable controversy over performing thyroidectomy and central lymph node dissection in patients with papillary thyroid microcarcinoma (PTMC) remained. However, accurate prediction of central lymph node metastasis (CLNM) is crucial for surgical extent and proper management. The aim of this study was to develop and validate a practical nomogram for predicting CLNM in patients with PTMC.

Methods

A total of 1,029 patients with PTMC who underwent thyroidectomy and central lymph node dissection at Tangdu Hospital (the Second Affiliated Hospital of Air Force Medical University) and Xijing Hospital (the First Affiliated Hospital of Air Force Medical University) were selected. Seven hundred and nine patients were assigned to the training set and 320 patients to the validation set. Data encompassing demographic characteristics, ultrasonography results, and biochemical indicators were obtained. Stepwise backward selection and multiple logistic regression were used to screen the variables and establish the nomogram. Concordance index (C-index), receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA) were employed to evaluate the nomogram's distinguishability, accuracy, and clinical utility.

Results

Young age, multifocality, bigger tumor, presence of microcalcification, aspect ratio (height divided by width) ≥1, loss of fatty hilum, high free thyroxine (FT4), and lower anti-thyroid peroxidase antibody (TPOAb) were significantly associated with CLNM. The nomogram showed strong predictive capacity, with a C-index and accuracy of 0.784 and 0.713 in the training set and 0.779 and 0.703 in the external validation set, respectively. DCA indicated that the nomogram demonstrated strong clinical applicability.

Conclusions

We established a reliable, cost-effective, reproducible, and noninvasive nomogram for predicting CLNM in patients with PTMC. This tool could be a valuable guidance for deciding on management in PTMC.

Elevated Cancer-Associated Hyaluronan Correlates With Diagnosis and Lymph Node Metastasis of Papillary Thyroid Cancer

The glycosaminoglycan hyaluronan (HA) plays an important role in tumor progression. However, its biological and clinical significance in papillary thyroid cancer (PTC) remains unknown. Immunohistochemistry was performed to examine HA expression in tissues from PTC patients. Two PTC cell lines were treated with HA synthesized inhibitor against HA production to assess its function. Serum HA levels from 107 PTC patients, 30 Hashimoto thyroiditis patients, and 45 normal controls (NC) were measured by chemiluminescence immunoassay. HA levels in fine needle aspiration (FNA) washouts obtained from thyroid nodules and lymph nodes (LNs) were measured by chemiluminescence immunoassay. Area under the curve (AUC) was computed to evaluate HA's clinical value. HA was highly expressed in PTC. Reducing HA production significantly inhibited PTC cell proliferation and invasion. Importantly, serum HA levels in PTC were significantly higher than those in NCs and Hashimoto thyroiditis and allowed distinguishing of thyroid cancers from NCs with high accuracy (AUC = 0.782). Moreover, elevated serum HA levels in PTC correlate with LN metastasis. HA levels in FNA washouts from PTC patients were significantly higher than those in benign controls, with a high AUC value (0.8644) for distinguishing PTC from benign controls. Furthermore, HA levels in FNA washouts from metastatic LN were significantly higher than those in nonmetastatic LN, with a high AUC value (0.8007) for distinguishing metastatic LNs from nonmetastatic LNs. HA levels in serum and FNA washout exhibited a potential significance for PTC diagnosis and an indicator for LN metastasis in patients with PTC.

Risk factors analysis of lateral cervical lymph node metastasis in papillary thyroid carcinoma: a retrospective study of 830 patients

OBJECTIVE

The aim of this study is to investigate the risk factors for lateral cervical lymph node metastasis in papillary thyroid carcinoma (PTC).

METHODS

Clinicopathological data (age, gender, Hashimoto's thyroiditis, preoperative circulating tumor cells (CTCs), multifocal, maximum lesion diameter, invaded capsule, T stage, and lymph node metastasis) of 830 PTC patients diagnosed and treated in Meizhou People's Hospital from June 2021 to April 2023 were collected. The related factors of lateral cervical lymph node metastasis were analyzed.

RESULTS

There were 334 (40.2%), and 103 (12.4%) PTC patients with central lymph node metastasis, and lateral cervical lymph node metastasis, respectively. Compared with patients without lateral cervical lymph node metastasis, PTC patients with lateral cervical lymph node metastasis had a higher proportion of multifocal, maximum lesion diameter > 1 cm, invaded capsule, T3-T4 stage. Regression logistic analysis showed that male (odds ratio (OR): 2.196, 95% confidence interval (CI): 1.279-3.769, p = 0.004), age < 55 years old (OR: 2.057, 95% CI: 1.062-3.988, p = 0.033), multifocal (OR: 2.759, 95% CI: 1.708-4.458, p < 0.001), maximum lesion diameter > 1 cm (OR: 5.408, 95% CI: 3.233-9.046, p < 0.001), T3-T4 stage (OR: 2.396, 95% CI: 1.241-4.626, p = 0.009), and invaded capsule (OR: 2.051, 95% CI: 1.208-3.480, p = 0.008) were associated with lateral cervical lymph node metastasis.

CONCLUSIONS

Male, age < 55 years old, multifocal, maximum lesion diameter > 1 cm, T3-T4 stage, and invaded capsule were independent risk factors for lateral cervical lymph node metastasis in PTC.

Construction and validation of a nomogram for predicting lateral lymph node metastasis in pediatric and adolescent with differentiated thyroid carcinoma

BACKGROUND

Limited research has been conducted to specifically investigate the identification of risk factors and the development of prediction models for lateral lymph node metastasis (LNM) in pediatric and adolescent differentiated thyroid carcinoma (DTC) populations, despite its significant association with unfavorable prognosis.

METHODS

This study entails a retrospective analysis of the clinical characteristics exhibited by pediatric and adolescent patients who have been diagnosed with DTC. The data utilized for this analysis was sourced from the Surveillance, Epidemiology, and End Results (SEER) database, spanning the time frame from 2000 to 2020. Furthermore, the study incorporates patients who were treated at the Departments of Breast and Thyroid Surgery in the Second Clinical Medical College, Affiliated Fifth People's Hospital of Chengdu University of Traditional Chinese Medicine, as well as The General Hospital of Western Theater Command, during the period from 2010 to 2020.

RESULTS

A cohort of 2631 patients from the SEER database, along with an additional 339 patients from our departments who met the specified inclusion criteria, were included in this study. Subsequently, four clinical variables, namely age, tumor size, multifocality, and extrathyroidal invasion, were identified as being significantly associated with lateral LNM in pediatric and adolescent DTC patients. These variables were then utilized to construct a nomogram, which demonstrated effective discrimination with a concordance index (C-index) of 0.731. Furthermore, the performance of this model was validated through both internal and external assessments, yielding C-index values of 0.721 and 0.712, respectively. Afterward, a decision curve analysis was conducted to assess the viability of this nomogram in predicting lymph node metastasis.

CONCLUSION

The current investigation has effectively constructed a nomogram model utilizing visualized multipopulationsal data. Our findings demonstrate a significant association between various clinical characteristics and lateral LNM in pediatric and adolescent DTC patients. These outcomes hold substantial significance for healthcare practitioners, as they can employ this model to inform individualized clinical judgments for the pediatric and adolescent cohorts.

Papillary thyroid carcinoma: ≤ 10 mm does not always mean pN0. A multicentric real-world study

The incidence of papillary thyroid carcinoma (PTC) is increasing and PTC ≤ 10 mm (PTMC) accounts for most new diagnoses. PTMCs are not always low risk, as detection of lymph nodes metastasis (LNM) may occur. The purpose of the study was to analyze the clinical pattern, frequency, and independent risk factors of patients with PTMC and LNM. From January 2022 to June 2023, PTCs managed at CTO Hospital, Rome; Policlinico Vanvitelli, Naples; and Garibaldi Nesima Hospital, Catania were included. PTC management followed the same diagnostic-therapeutic procedures according to the ATA guidelines. Variables such as age, sex, maximum diameter, histologic evidence of LNM (HELNM +), Hashimoto's thyroiditis (HT), multifocality, capsule invasion, and histological subtype were considered. PTCs were divided according to HELNM and size. Two hundred ninety-eight PTCs were included. PTMCs were 136 (45.6%) and LNM occurred in 27.2% of them. In the HELNM + group, analysis of PTMC vs 'MacroPTC' (PTC > 10 mm) did not show any statistical difference. Multivariate regression revealed that young age (OR 0.93; CI 95% 0.90-0.96; p < 0.01) and male sex (male OR 3.44; CI 95% 1.16-10.20; p = 0.03) were the only independent risk factors for HELNM + in PTMC. The risk of LNM in PTMC is not negligible; therefore, a careful evaluation by an expert thyroidologist is mandatory for patients with small thyroid nodule, especially in younger and male patients before excluding surgery. In the future, new tools are needed to detect early PTMC with LNM before surgery.

Machine learning based on SEER database to predict distant metastasis of thyroid cancer

OBJECTIVE

Distant metastasis of thyroid cancer often indicates poor prognosis, and it is important to identify patients who have developed distant metastasis or are at high risk as early as possible. This paper aimed to predict distant metastasis of thyroid cancer through the construction of machine learning models to provide a reference for clinical diagnosis and treatment.

MATERIALS & METHODS

Data on demographic and clinicopathological characteristics of thyroid cancer patients between 2010 and 2015 were extracted from the National Institutes of Health (NIH) Surveillance, Epidemiology, and End Results (SEER) database. Our research used univariate and multivariate logistic models to screen independent risk factors, respectively. Decision Trees (DT), ElasticNet (ENET), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Multilayer Perceptron (MLP), Radial Basis Function Support Vector Machine (RBFSVM) and seven machine learning models were compared and evaluated by the following metrics: the area under receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), sensitivity(also called recall), specificity, precision, accuracy and F1 score. Interpretable machine learning was used to identify possible correlation between variables and distant metastasis.

RESULTS

Independent risk factors for distant metastasis, including age, gender, race, marital status, histological type, capsular invasion, and number of lymph nodes metastases were screened by multifactorial regression analysis. Among the seven machine learning algorithms, RF was the best algorithm, with an AUC of 0.948, sensitivity of 0.919, accuracy of 0.845, and F1 score of 0.886 in the training set, and an AUC of 0.960, sensitivity of 0.929, accuracy of 0.906, and F1 score of 0.908 in the test set.

CONCLUSIONS

The machine learning model constructed in this study helps in the early diagnosis of distant thyroid metastases and helps physicians to make better decisions and medical interventions.

PSAMMOMA BODIES IN LYMPH NODES OF THE NECK: POSSIBLE PRECURSOR OF LOCOREGIONAL METASTASES OF PAPILLARY THYROID CARCINOMA

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common type of well-differentiated thyroid cancer accounting for up to 80% of all thyroid neoplasms. Metastases to the regional lymph nodes (RLN) of the neck are a feature of its biological aggressiveness. The presence of psammoma bodies may be considered a pathomorphological feature of PTC in addition to the papillary structure of tumor and specific nuclear changes. The aim of the study was to evaluate a clinical value of psammoma bodies in the RLN of PTC patients.

MATERIALS AND METHODS

91 patients with PTC who were surgically treated at the Verum Expert Clinic were enrolled in the study. The clinical and pathomorphological data were retrieved from the archival medical records.

RESULTS

According to the results of the clinico-morphological analysis, 51 patients (56%) with PTC had metastases in the RLN of the neck, and 40 (44%) patients had no metastases. Among 51 patients with metastases in the RLN, in 4 patients psammoma bodies in the RLN and tumor tissue were identified. In 3 of these 4 patients, the size of the primary PTC tumor was less than 10 mm, but an aggressive cancer course such as significant number of metastases in the RLN or multifocal growth was found in all these cases.

CONCLUSIONS

The presence of psammoma bodies in RLN and primary PTC tumor could be suggested as a predictor of metastasis to lymph nodes. The detection of point echogenic foci in the lymph nodes by ultrasound at the preoperative stage is a sign of psammoma bodies. This finding can be useful for improving the efficacy in selection of surgical treatment tactics for the optimal neck dissection by planning neck dissection in the presence of such point echogenic foci at the preoperative stage and performing regular check-ups of the patients.

Clinical prediction models for cervical lymph node metastasis of papillary thyroid carcinoma

PURPOSE

Accurate preoperative diagnosis of lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remains an unsolved problem. This study aimed to construct a nomogram and scoring system for predicting LNM based on the clinical characteristics of patients with PTC.

METHODS

1400 patients with PTC who underwent thyroidectomy and lymph node dissection at the First Affiliated Hospital of Sun Yat-sen University were retrospectively enrolled and randomly divided into training and internal testing sets. Furthermore, 692 patients with PTC from three other medical centers were collected as external testing sets. Least absolute shrinkage and selection operator (LASSO) was used to screen the predictors, and a nomogram was constructed. In addition, a scoring system was constructed using 10-fold cross-validation. The performances of the two models were verified among datasets and compared with preoperative ultrasound (US).

RESULTS

Six independent predictors were included in the multivariate logistic model: age, sex, US diagnosis of LNM, tumor diameter, location, and thyroid peroxidase antibody level. The areas under the receiver operating characteristic curve (AUROC) (95% confidence interval) of this nomogram in the training, internal testing, and three external testing sets were 0.816 (0.791-0.840), 0.782 (0.727-0.837), 0.759 (0.699-0.819), 0.749 (0.667-0.831), and 0.777 (0.726-0.828), respectively. The AUROC of the scoring system were 0.810 (0.785-0.835), 0.772 (0.718-0.826), 0.736 (0.675-0.798), 0.717 (0.635-0.799) and 0.756 (0.704-0.808), respectively. The prediction performances were both significantly superior to those of preoperative US (P < 0.001).

CONCLUSION

The nomogram and scoring system performed well in different datasets and significantly improved the preoperative prediction of LNM than US alone.

Ultrasound and clinical factors predicting central lymph node metastases in patients with unilateral multifocal papillary thyroid carcinoma

OBJECTIVE

This retrospective study involving a large dataset of unilateral multifocal papillary thyroid carcinoma (UM-PTC) sought to identify factors that predict central lymph node metastases (CLNM) in patients.

METHODS

We identified a cohort of 158 patients who underwent cervical ultrasonography followed by UM-PTC diagnosis based on postoperative pathology. The relationship between CLNM and UM-PTC clinical ultrasound features was evaluated using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to determine the ability of total tumor diameter (TTD) to predict CLNM.

RESULTS

Among the 158 UM-PTC patients, the incidence of CLNM was 29.7% (47/158). Univariate and multivariate analyses revealed that a number of similarity of sonographic features (NSSF) ≥4 (odds ratio [OR] = 11.335, 95% confidence interval [CI]: 3.95-32.50, p = 0.000), microcalcifications (OR = 3.54, 95% CI: 1.30-9.70, p = 0.014), a TTD of ≥2 cm (OR = 4.48, 95% CI: 1.62-12.34, p = 0.004), number of nodules ≥3 (OR = 13.17, 95% CI: 3.24-53.52, p = 0.000), and Lateral cervical lymph node metastasis (LLNM) (OR = 5.57, 95% CI: 1.59-19.48, p = 0.007) were independently associated with CLNM in UM-PTC. ROC curve analysis revealed that the TTD cut-off of 1.795 cm had a sensitivity of 0.723 and a specificity of 0.676 for predicting CLNM.

CONCLUSIONS

Patients with UM-PTC are at high risk of CLNM. NSSF ≥4, microcalcifications, TTD of ≥2 cm, LLNM, and a number of nodules ≥3 were independently associated with CLNM. Our data show that ultrasound may guide surgical decisions in the treatment of UM-PTC.

Predicting central cervical lymph node metastasis in papillary thyroid carcinoma with Hashimoto's thyroiditis: a practical nomogram based on retrospective study

Background

In papillary thyroid carcinoma (PTC) patients with Hashimoto's thyroiditis (HT), preoperative ultrasonography frequently reveals the presence of enlarged lymph nodes in the central neck region. These nodes pose a diagnostic challenge due to their potential resemblance to metastatic lymph nodes, thereby impacting the surgical decision-making process for clinicians in terms of determining the appropriate surgical extent.

Methods

Logistic regression analysis was conducted to identify independent risk factors associated with central lymph node metastasis (CLNM) in PTC patients with HT. Then a prediction model was developed and visualized using a nomogram. The stability of the model was assessed using ten-fold cross-validation. The performance of the model was further evaluated through the use of ROC curve, calibration curve, and decision curve analysis.

Results

A total of 376 HT PTC patients were included in this study, comprising 162 patients with CLNM and 214 patients without CLNM. The results of the multivariate logistic regression analysis revealed that age, Tg-Ab level, tumor size, punctate echogenic foci, and blood flow grade were identified as independent risk factors associated with the development of CLNM in HT PTC. The area under the curve (AUC) of this model was 0.76 (95% CI [0.71-0.80]). The sensitivity, specificity, accuracy, and positive predictive value of the model were determined to be 88%, 51%, 67%, and 57%, respectively.

Conclusions

The proposed clinic-ultrasound-based nomogram in this study demonstrated a favorable performance in predicting CLNM in HT PTCs. This predictive tool has the potential to assist clinicians in making well-informed decisions regarding the appropriate extent of surgical intervention for patients.

Genetic alterations and allele frequency of BRAF V600E and TERT mutation in papillary thyroid carcinoma with intermediate-to-high recurrence risk: a retrospective study

The predictive value of allele frequency (AF) of BRAF V600E and TERT mutations in papillary thyroid carcinoma (PTC) remains controversial. We aimed to investigate the AF of BRAF V600E and TERT mutations in intermediate-to-high risk PTC and their association between tumor invasiveness, prognosis, and other mutations. Probe hybridization capture and high-throughput sequencing were used to quantitatively test 40 gene loci in 94 intermediate-to-high recurrence risk PTC patients, combined with clinical characteristics and follow-up for retrospective analysis. BRAF V600E mutation AF was linked to a increased risk of thyroid capsule penetration, recurrence, and concurrent mutations. Concurrent mutations could lead to a worse prognosis and increased invasiveness. TERT promoter mutation frequently accompanied other mutations and resulted in a poorer prognosis. However, there was no clear association between the TERT mutation AF and tumor invasiveness or recurrence. The sensitivity and specificity of predicting recurrence in intermediate-to-high risk PTC with BRAF V600E mutation AF > 28.2% were 60 and 80%. Although genetic alterations in PTC can differ among different ethnicities, the AF of BRAF V600E and TERT mutations may be similar. The AF of BRAF V600E has the potential to be a novel indicator in predicting PTC invasiveness and prognosis.

Quantitative parameters of contrast-enhanced ultrasound effectively promote the prediction of cervical lymph node metastasis in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC), the most common endocrine tumor, often spreads to cervical lymph nodes metastasis (CLNM). Preoperative diagnosis of CLNM is important when selecting surgical strategies. Therefore, we aimed to explore the effectiveness of quantitative parameters of contrast-enhanced ultrasound (CEUS) in predicting CLNM in PTC. We retrospectively analyzed 193 patients with PTC undergoing conventional ultrasound (CUS) and CEUS. The CUS features and quantitative parameters of CEUS were evaluated according to PTC size ≤ 10 or > 10 mm, using pathology as the gold standard. For the PTC ≤ 10 mm, microcalcification and multifocality were significantly different between the CLNM (+) and CLNM (-) groups (both P < 0.05). For the PTC > 10 mm, statistical significance was noted between the two groups with respect to the margin, capsule contact, and multifocality (all P < 0.05). For PTC ≤ 10 mm, there was no significant difference between the CLNM (+) and CLNM (-) groups in all quantitative parameters of CEUS (all P > 0.05). However, for PTC > 10 mm, the peak intensity (PI), mean transit time, and slope were significantly associated with CLNM (all P < 0.05). Multivariate analysis showed that PI > 5.8 dB was an independent risk factor for predicting CLNM in patients with PTC > 10 mm (P < 0.05). The area under the curve of PI combined with CUS (0.831) was significantly higher than that of CUS (0.707) or PI (0.703) alone in the receiver operator characteristic curve analysis (P < 0.05). In conclusion, PI has significance in predicting CLNM for PTC > 10 mm; however, it is not helpful for PTC ≤ 10 mm.

Synchronous Papillary Thyroid Cancer and Asymptomatic Cervical Lymph Node Sarcoidosis: A Case Report

Sarcoidosis is a systemic inflammatory disease characterized by the formation of immune granulomas in multiple organs. The cause of this disease is not yet clear. Papillary thyroid cancer (PTC) is the most common malignant endocrine tumor and is often associated with cervical lymph node metastasis. Assessment of risk factors associated with a poor prognosis is crucial in PTC. The coexistence of sarcoidosis and thyroid cancer is rarely reported in the literature. We describe a case of a 54-year-old female diagnosed with PTC and asymptomatic cervical and thoracic hilar lymphadenopathy due to concurrent sarcoidosis. This case will remind clinicians to be aware of the multiple potential causes of lymphadenopathy and realize the importance of the differences in the features of neck lymphadenopathy in patients with suspected head and neck cancer. Overall, careful workup and pretreatment screening enabled us to provide the patient with the most suitable treatment modality and avoid total thyroidectomy.

Prediction of bilateral thyroid carcinoma and lateral cervical lymph node metastasis in PTC patients with suspicious thyroid nodules

PURPOSE

This study aimed to evaluate the factors associated with bilateral papillary thyroid carcinoma (PTC) and lateral cervical lymph node metastasis (LLNM) in patients with suspicious unilateral PTC.

METHODS

This study analyzed patients with suspicious unilateral PTC who were enrolled in a university hospital between 2016 and 2019 in Zhejiang, China. Using logistic regression, the study examined the factors associated with bilateral PTC and LLNM in demographic data, anthropometric measurements, lifestyle factors, medical history, preoperative diagnostic tests, and histopathological factors.

RESULTS

A total of 256 patients, with a mean age of 49 years, were enrolled. Bilateral PTC was associated with multifocality (aOR: 5.069, 95% CI: 2.440-10.529, P < 0.001), and contralateral nodule in the upper (aOR: 9.073, 95% CI: 2.111-38.985, P = 0.003) and middle (aOR: 9.926, 95% CI: 2.683-36.717, P < 0.001). LLNM was positively associated with bilateral PTC (aOR, 4.283, 95% CI: 1.378-13.308, p = 0.012), male (aOR, 3.377, 95% CI: 1.205-9.461, P = 0.021), upper location of carcinoma (aOR, 3.311, 95% CI: 1.091-10.053, p = 0.035), and punctate echogenic foci (aOR, 3.309, 95% CI: 1.165-9.394, P = 0.025). Contralateral maximal nodule in the upper (aOR: 0.098, 95% CI: 0.015-0.628, p = 0.014), middle (aOR: 0.114, 95% CI: 0.033-0.522, p < 0.001), and lower (aOR, 0.028, 95% CI: 0.003-0.276, P = 0.002) location were inversely associated with LLNM.

CONCLUSION

Upper and middle location of contralateral nodule and tumor multifocality predicted the risk bilateral PTC. Bilateral PTC, male, upper tumor location, punctate echogenic foci and contralateral nodule location in the entire lobes were independent predictors for LLNM.

Clinical value of ultrasound parameters PI, TTP, and MTT in assessing cervical lymph node metastasis of papillary thyroid carcinoma

OBJECTIVE

To determine the clinical value of ultrasound in assessing cervical lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC).

METHODS

The medical records of 179 PTC patients treated in Shandong Provincial Qianfoshan Hospital between March 2016 and March 2019 were collected. The patients were assigned to a transfer group (54 cases) and a non-transfer group (125 cases) according to their pathologic results. The ultrasound parameters (peak intensity (PI), time to peak (TTP), and mean transit time (MTT)) of the two groups were compared. Then, multivariate logistic regression was used to analysis the results, and receiver operating characteristic (ROC) curves were plotted to evaluate the value of risk factors in predicting CLNM.

RESULTS

The transfer group showed notably lower PI, TTP and MTT than the non-transfer group (P<0.001), and focus diameter, microcalcification, multiple foci, PI, TTP, and MTT were identified as independent risk factors for LNM in patients (P<0.05). According to the ROC curve, the areas under the curves (AUCs) of microcalcification, multiple foci, and PI were all smaller than 0.7; the AUCs of focus diameter and MTT were smaller than 0.8, and the AUC of TTP was 0.855.

CONCLUSION

PI, TTP, and MTT all decrease in PTC patients with CLNM, and TTP has a strong predictor for CLNM in them, with an AUC of 0.855.

Multi-modal ultrasound multistage classification of PTC cervical lymph node metastasis via DualSwinThyroid

Objective

This study aims to predict cervical lymph node metastasis in papillary thyroid carcinoma (PTC) patients with high accuracy. To achieve this, we introduce a novel deep learning model, DualSwinThyroid, leveraging multi-modal ultrasound imaging data for prediction.

Materials and methods

We assembled a substantial dataset consisting of 3652 multi-modal ultrasound images from 299 PTC patients in this retrospective study. The newly developed DualSwinThyroid model integrates various ultrasound modalities and clinical data. Following its creation, we rigorously assessed the model's performance against a separate testing set, comparing it with established machine learning models and previous deep learning approaches.

Results

Demonstrating remarkable precision, DualSwinThyroid achieved an AUC of 0.924 and an 96.3% accuracy on the test set. The model efficiently processed multi-modal data, pinpointing features indicative of lymph node metastasis in thyroid nodule ultrasound images. It offers a three-tier classification that aligns each level with a specific surgical strategy for PTC treatment.

Conclusion

DualSwinThyroid, a deep learning model designed with multi-modal ultrasound radiomics, effectively estimates the degree of cervical lymph node metastasis in PTC patients. In addition, it also provides early, precise identification and facilitation of interventions for high-risk groups, thereby enhancing the strategic selection of surgical approaches in managing PTC patients.

Killing capacity analysis of tumor-infiltrating cytotoxic lymphocytes and impact on lymph node metastasis in differentiated papillary carcinoma of thyroid with the BRAF V600E mutation

BACKGROUND

Cytotoxic lymphocytes (CLs) express potent toxins, including perforin (P) and granzyme-B (G), which brings about target cell death. The purpose of this study was to evaluate the killing capacity of tumor-infiltrating CLs by means of P and G analysis, and explore the association with lymph node metastasis in papillary carcinoma of thyroid (PTC) without Hashimoto's thyroiditis (HT).

METHODS

Infiltration of lymphocytes in PTC was observed in frozen sections. Both fresh tumor tissues and paracancerous tissues with lymphocyte infiltration were collected and prepared into a single cell suspension. Flow cytometry was used to detect the percentages of CD3+P+, CD3+G+, CD8+P+, and CD8+G+ T lymphocytes (TLs) and CD16-CD56+P+ and CD16-CD56+G+ natural killer (NK) cells. Finally, we investigated differential expression of P and G in NK cells and cytotoxic T lymphocytes (CTLs) in paired tumor tissues (group T, n = 44) and paracancerous tissues (group N, n = 44) from patients with PTC with the BRAF V600E mutation. Furthermore, patients were divided into two groups according to whether cervical central lymph node metastasis (CCLNM) existed: group A (with lymph node metastases, n = 27) and group B (with nonlymph node metastases, n = 17). Patients were also divided into three groups according to the total number of positive CCLNM: group B, group C (with low-level lymph node metastases, less than 5, n = 17) and group D (with high-level lymph node metastases, no less than 5, n = 10).

RESULTS

The percentage of CD3+P+ CTLs was significantly higher in group N than in group T (P < 0.05). The percentage of CD8+G+ CTLs was significantly higher in group T than in group N (P < 0.05). The percentages of CD3+G+, CD16-CD56+P+and CD16-CD56+G+ NK cells showed no significant difference in either group T or group N (P > 0.05). The percentages of CD3+P+ CTLs in group A and group C were significantly higher in the paracancerous tissue than in the tumor tissue (P < 0.05). The percentages of CD8+G+ CTLs in group A and group C were significantly higher in the tumor tissues than in the paracancerous tissues (P < 0.05). The percentage of CD16-CD56+G+ NK cells in group D was significantly higher in the tumor tissues than in the paracancerous tissues (P < 0.05).

CONCLUSIONS

The killing capacity of infiltrating CLs in PTC differed between tumor tissues and paracancerous tissues. In cases with CCLNM, higher expression of CD16-CD56+G+ NK cells in tumor tissues may be associated with a high risk of lymph node metastasis.

A diagnostic model based on DNA methylation haplotype block characteristics for identifying papillary thyroid carcinoma from thyroid adenoma

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer. Methylation of some genes plays a crucial role in the tendency to malignancy as well as poor prognosis of thyroid cancer, suggesting that methylation features can serve as complementary markers for molecular diagnosis. In this study, we aimed to develop and validate a diagnostic model for PTC based on DNA methylation markers. A total of 142 thyroid nodule tissue samples containing 84 cases of PTC and 58 cases of thyroid adenoma (TA) were collected for reduced representation bisulfite sequencing (RRBS) and subsequent analysis. The diagnostic model was constructed by the logistic regression (LR) method followed by 5-cross validation and based on 94 tissue methylation haplotype block (MHB) markers. The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.974 (95% CI, 0.964-0.981) on 108 training samples and 0.917 (95% CI, 0.864-0.973) on 27 independent testing samples. The diagnostic model scores showed significantly high in males (P = 0.0016), age ≤ 45 years (P = 0.026), high body mass index (BMI) (P = 0.040), lymph node metastasis (P = 0.00052) and larger nodules (P = 0.0017) in the PTC group, and the risk score of this diagnostic model showed significantly high in recurrent PTC group (P = 0.0005). These results suggest that the diagnostic model can be expected to be a powerful tool for PTC diagnosis and there are more potential clinical applications of methylation markers to be excavated.

Meta-analysis of the effect and clinical significance of Delphian lymph node metastasis in papillary thyroid cancer

Objective

To investigate the effect and clinical significance of Delphian lymph nodes (DLN) on the factors influencing papillary thyroid cancer (PTC) to provide individualized guidance for the surgical treatment of thyroid cancer.

Methods

Relevant studies from PubMed, Web of Science, the Cochrane Library, Embase, and China National Knowledge Infrastructure databases were searched until February 13, 2023. Stringent selection parameters were used to obtain included data and homogeneous articles. Analyses were performed using Revman 5.4 and SPSS software. A P-value of < 0.05 was considered statistically significant.

Results

Five studies were finally included in this study. The results revealed a higher risk of DLN metastasis (DLNM) in patients with tumor size >1cm, multifocality, and extrathyroidal extension (ETE) of the thyroid. The risk of central lymph node metastasis (CLNM) was 11.25 times higher in DLN-positive patients with PTC than in DLN-negative (OR = 11.25, 95% CI: 8.64-14.64, P < 0.05) patients. The risk of LLNM was 5.57 times higher in DLN-positive patients with PTC than in DLN-negative (OR = 5.57, 95% CI: 4.57-6.78, P < 0.001) patients. The risk of postoperative recurrence in DLN-positive patients with PTC was 3.49 times higher (OR = 3.49, 95% CI: 1.91-6.38, P < 0.001) than in DLN-negative patients with PTC.

Conclusion

Patients with tumor size >1 cm in diameter, multifocality, and ETE have an increased risk for DLN development. DLN-positive patients with central and lateral cervical lymph node metastasis and postoperative recurrence are at higher risk than DLN-negative patients.

Correlation analysis of risk factors for cervical lymphatic metastasis in papillary thyroid carcinoma

OBJECTIVE

This study aims to identify and analyze the risk factors associated with Cervical Lymph Node Metastasis (CNM) in Papillary Thyroid Carcinoma (PTC) patients.

METHODS

We conducted a retrospective study involving the clinicopathological data of 2384 PTC patients admitted to our hospital between January 2016 and December 2020. All relevant data were statistically processed and analyzed.

RESULTS

The related risk factors for Central Lymph Node Metastasis (CLNM) were gender (male), age (≤ 30 years old), tumor lesion size (> 0.855 cm), and multifocal tumor foci. The ROC curve revealed that the critical value for predicting CLNM based on tumor lesion size was 0.855 (sensitivity = 57.9%, specificity = 69%, AUC = 0.269, and P < 0.05). Lateral Lymph Node Metastasis (LLNM) was positively correlated with tumor diameter. Specifically, the LLNM rate increased with the tumor diameter. LLNM occurrence was significantly higher in zones II, III, and IV than in zones I and V. Although the BRAF gene mutation detection assay has certain clinical benefits in diagnosing PTC and LLNM, no statistically significant difference was found in its relationship with central and lateral neck lymph node metastases (P = 0.741).

CONCLUSION

Our findings revealed that CLNM is associated with gender (male), age (≤ 30 years old), tumor lesion size (> 0.855 cm), and multiple tumor lesions in PTC patients. Central Lymph Node Dissection (CLND) is recommended for patients with these risk factors. On the other hand, preoperative ultrasound examination, fine-needle pathological examination, and genetic testing should be used to determine whether Lateral Cervical Lymph Node Dissection (LLND) is needed.

Advancements in theranostic applications: exploring the role of fibroblast activation protein inhibition tracers in enhancing thyroid health assessment

BACKGROUND

The diagnostic accuracy of [18F]-fluorodeoxyglucose ([18F]-FDG) positron emission tomography imaging in accurately identifying thyroid lesions is limited, primarily due to the physiological uptake of normal head and neck tissues and inflammatory uptake in lymph nodes. Since fibroblast activating protein is highly expressed in tumors and largely unexpressed in normal tissues, quinoline-based fibroblast activating protein inhibitors (FAPI) have emerged as promising tools in the diagnosis of cancer and other medical conditions. Several studies have reported on the feasibility and value of FAPI in thyroid cancer.

MAIN BODY

In this narrative review, we summarize the current literature on state-of-the-art FAPI positron emission tomography imaging for thyroid cancer and fibroblast activating protein-targeted radionuclide therapy. We provide an overview of FAPI uptake in normal thyroid tissue, thyroid cancer and its metastases. Additionally, we highlight the difference between FAPI uptake and [18F]-FDG uptake in thyroid lesions. Furthermore, we discuss the therapeutic value of FAPI in iodine-refractory thyroid cancer.

CONCLUSION

The utilization of fibroblast activating protein inhibitors in thyroid cancer holds significant promise, offering clinicians valuable insights for more precise diagnose choices and treatments strategies in the future.

Central Neck Lymph Node Size Measured by Ultrasound Significantly Predicts Central Neck Lymph Node Metastasis of Papillary Thyroid Carcinoma

Objective: The aim of this study was to investigate whether Central lymph node (CLN) size as measured by an ultrasound can significantly predict CLN metastasis of papillary thyroid carcinoma (PTC). Materials and methods: This retrospective chart review of patients diagnosed with PTC who underwent ultrasound and central neck dissection (CND). We excluded patients who received previous thyroid surgery or radiation. We analyzed the correlation between CLN size and characteristics by ultrasound and histopathologic findings among positive CLN patients. Results: Of the 48 patients who underwent preoperative ultrasound and CND, 34 patients had positive CLN identified by ultrasound. The positive predictive value, negative predictive value, sensitivity, specificity, and accuracy of ultrasound in this diagnostic setting was 88.0%, 21.0%, 73.2%, 42.9%, and 68.7%, respectively. The risk of CLN metastasis of PTC was 67.7% and 85.7% for lymph node size 3.1 to 4 mm and 4.1 to 5 mm, respectively. The risk increased to 100% when the lymph node size was >5 mm. Positive preoperative ultrasound of lateral neck lymph node was found to be a significant risk factor for CLN metastasis (P = .003). Conclusion: Ultrasound was found to be an effective preoperative evaluation in patients with PTC to determine the likelihood of CLN metastasis and whether CND is indicated, especially in the ultrasound-positive central lymph node. A high risk of metastasis was found in CLN size >3 mm by ultrasound, and the risk dramatically increased in CLN size >5 mm. We also found positive lateral neck node from preoperative ultrasound to be a significant risk factor for CLN metastasis.

Clinical features and imaging examination assessment of cervical lymph nodes for thyroid carcinoma

BACKGROUNDS

The purpose of this study is to investigate the relationship between clinical characteristics and cervical lymph node metastasis (LNM) in patients with thyroid carcinoma, as well as estimate the preoperative diagnosis values of ultrasound (US) and contrast enhanced computed tomography (CECT) examinations on the neck for detection of cervical LNM in thyroid carcinoma.

METHODS

A retrospective analysis of 3 026 patients with surgically proven thyroid carcinoma was conducted. Patients' clinical characteristics, including gender, age, tumor size, bilateral lesions, multifocality, adenomatous nodules, Hashimoto's thyroiditis (HT), and extrathyroidal extension, were collected to explore their association with cervical LNM in thyroid carcinoma. Preoperative assessments for central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) were conducted through US and CECT. The diagnostic value of US, CECT and US combined with CECT for detection of LNM located in various cervical compartments was estimated based on the pathological results.

RESULTS

The risk of cervical LNM was higher in thyroid cancer patients who were male, age < 55 years old, tumor size > 10 mm, bilateral lesions, and extrathyroidal extension, while multifocality, adenomatous nodules and HT had no significant effect on LNM. US, CECT and US combined with CECT all had a higher sensitivity to LLNM (93.1%, 57.8%, 95.4%) than to CLNM (32.3%, 29.0%, 43.4%). US and CECT had a high specificity to both CLNM and LLNM (94.3-97.8%).

CONCLUSION

Preoperative clinical characteristics and imaging examinations on patients with thyroid carcinoma are crucial to the evaluation of cervical lymph nodes and conducive to individualizing surgical treatments by clinicians. US combined with CECT are superior to single US or CECT alone in detection of CLNM and LLNM.

Exploration and validation of key genes associated with early lymph node metastasis in thyroid carcinoma using weighted gene co-expression network analysis and machine learning

Background

Thyroid carcinoma (THCA), the most common endocrine neoplasm, typically exhibits an indolent behavior. However, in some instances, lymph node metastasis (LNM) may occur in the early stages, with the underlying mechanisms not yet fully understood.

Materials and methods

LNM potential was defined as the tumor's capability to metastasize to lymph nodes at an early stage, even when the tumor volume is small. We performed differential expression analysis using the 'Limma' R package and conducted enrichment analyses using the Metascape tool. Co-expression networks were established using the 'WGCNA' R package, with the soft threshold power determined by the 'pickSoftThreshold' algorithm. For unsupervised clustering, we utilized the 'ConsensusCluster Plus' R package. To determine the topological features and degree centralities of each node (protein) within the Protein-Protein Interaction (PPI) network, we used the CytoNCA plugin integrated with the Cytoscape tool. Immune cell infiltration was assessed using the Immune Cell Abundance Identifier (ImmuCellAI) database. We applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), and Random Forest (RF) algorithms individually, with the 'glmnet,' 'e1071,' and 'randomForest' R packages, respectively. Ridge regression was performed using the 'oncoPredict' algorithm, and all the predictions were based on data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. To ascertain the protein expression levels and subcellular localization of genes, we consulted the Human Protein Atlas (HPA) database. Molecular docking was carried out using the mcule 1-click Docking server online. Experimental validation of gene and protein expression levels was conducted through Real-Time Quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) assays.

Results

Through WGCNA and PPI network analysis, we identified twelve hub genes as the most relevant to LNM potential from these two modules. These 12 hub genes displayed differential expression in THCA and exhibited significant correlations with the downregulation of neutrophil infiltration, as well as the upregulation of dendritic cell and macrophage infiltration, along with activation of the EMT pathway in THCA. We propose a novel molecular classification approach and provide an online web-based nomogram for evaluating the LNM potential of THCA (http://www.empowerstats.net/pmodel/?m=17617_LNM). Machine learning algorithms have identified ERBB3 as the most critical gene associated with LNM potential in THCA. ERBB3 exhibits high expression in patients with THCA who have experienced LNM or have advanced-stage disease. The differential methylation levels partially explain this differential expression of ERBB3. ROC analysis has identified ERBB3 as a diagnostic marker for THCA (AUC=0.89), THCA with high LNM potential (AUC=0.75), and lymph nodes with tumor metastasis (AUC=0.86). We have presented a comprehensive review of endocrine disruptor chemical (EDC) exposures, environmental toxins, and pharmacological agents that may potentially impact LNM potential. Molecular docking revealed a docking score of -10.1 kcal/mol for Lapatinib and ERBB3, indicating a strong binding affinity.

Conclusion

In conclusion, our study, utilizing bioinformatics analysis techniques, identified gene modules and hub genes influencing LNM potential in THCA patients. ERBB3 was identified as a key gene with therapeutic implications. We have also developed a novel molecular classification approach and a user-friendly web-based nomogram tool for assessing LNM potential. These findings pave the way for investigations into the mechanisms underlying differences in LNM potential and provide guidance for personalized clinical treatment plans.

Central lymph nodes in frozen sections can effectively guide extended lymph node resection for papillary thyroid carcinoma

OBJECTIVES

The scope of lateral neck lymph node dissection (LND) in papillary thyroid carcinoma (PTC) remains controversial. Our research aimed to explore the value of central lymph node metastasis (CLNM) in frozen sections for predicting neck lateral lymph node metastasis (NLLNM) and to guide clinical surgeons in performing surgical lymph node dissection.

PATIENTS

A total of 275 patients with PTC with suspected 'Cervical lymph node metastasis (LNM, including CLNM and NLLNM)' underwent unilateral or bilateral thyroidectomy and an intraoperative frozen diagnosis of central lymph nodes (LNs), as well as central and neck lateral LND. Validity indices and consistency of central LNs in frozen sections were calculated. In total, 216 patients then met the inclusion criteria and were enrolled in the follow-up study. The clinical and pathological data of the patients were retrospectively analyzed. The relationship between the number, metastatic diameter, and the ratio of CLNM to NLLNM was investigated.

RESULTS

CLNM in frozen and paraffin-embedded sections was associated with NLLNM. Univariate and multivariate analyses revealed the following risk factors for NLLNM metastasis: maximum diameter, total number, and ratio of metastatic LNs. A significant result was obtained when a cut-off value of 2.050 mm for the maximum metastatic diameter, 5.5 in the total number, and 0.5342 for the CLNM ratio level was used. Interaction term analyses showed that the association between the number of CLNM and NLLNM differed according to maximum diameter.

CONCLUSION

Central LNs in frozen sections accurately predicted NLLNM. In patients with PTC with >5 CLNMs, ≥2 and ≤5 CLNMs and maximum metastatic diameter > 2 mm, neck lateral LND should be considered. Our findings will facilitate the identification of patients who are likely to benefit from extended lateral neck LND.

A model for predicting lymph node metastasis of thyroid carcinoma: a multimodality convolutional neural network study

Background

Early preoperative evaluation of cervical lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) is critical for further surgical treatment. However, insufficient accuracy in predicting LNM status for PTC based on ultrasound images is a problem that needs to be urgently resolved. This study aimed to clarify the role of convolutional neural networks (CNNs) in predicting LNM for PTC based on multimodality ultrasound.

Methods

In this study, the data of 308 patients who were clinically diagnosed with PTC and had confirmed LNM status via postoperative pathology at Beijing Tiantan Hospital, Capital Medical University, from August 2018 to April 2022 were incorporated into CNN algorithm development and evaluation. Of these patients, 80% were randomly included into the training set and 20% into the test set. The ultrasound examination of cervical LNM was performed to assess possible metastasis. Residual network 50 (Resnet50) was employed for feature extraction from the B-mode and contrast-enhanced ultrasound (CEUS) images. For each case, all of features were extracted from B-mode ultrasound images and CEUS images separately, and the ultrasound examination data of cervical LNM information were concatenated together to produce a final multimodality LNM prediction. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of the predictive model. Heatmaps were further developed for visualizing the attention region of the images of the best-working model.

Results

Of the 308 patients with PTC included in the analysis, 158 (51.3%) were diagnosed as LNM and 150 (48.7%) as non-LNM. In the test set, when a triple-modality method (i.e., B-mode image, CEUS image, and ultrasound examination of cervical LNM) was used, accuracy was maximized at 80.65% (AUC =0.831; sensitivity =80.65%; specificity =82.26%), which showed an expected increased performance over B-mode alone (accuracy =69.00%; AUC =0.720; sensitivity =70.00%; specificity =73.00%) and a dual-modality method (B-mode image plus CEUS image: accuracy =75.81%; AUC =0.742; sensitivity =74.19%; specificity =77.42%). The heatmaps of our triple-modality model demonstrated a possible focus area and revealed the model's flaws.

Conclusions

The PTC lymph node prediction model based on the triple-modality features significantly outperformed all the other feature configurations. This deep learning model mimics the workflow of a human expert and leverages multimodal data from patients with PTC, thus further supporting clinical decision-making.

Integrating US-guided FNAB, BRAFV600E mutation, and clinicopathologic characteristics to predict cervical central lymph-node metastasis in preoperative patients with cN0 papillary thyroid carcinoma

BACKGROUND

The prevalence of cervical central lymph-node metastasis (CLNM) is high in patients with papillary thyroid carcinoma (PTC). There is considerable controversy surrounding the benefits of prophylactic central lymph-node dissection (pCLND) in patients with clinically negative central compartment lymph nodes (cN0). Therefore, it is crucial to accurately predict the likelihood of cervical CLNM before surgery to make informed surgical decisions.

METHODS

Date from 214 PTC patients (cN0) who underwent partial or total thyroidectomy and pCLND at the Guizhou Provincial People's Hospital were collected and retrospectively analyzed. They were divided into two groups in accordance with cervical CLNM or not. Their information, including clinical characteristics, ultrasound (US) features, pathological results of fine-needle aspirations biopsy (FNAB), and other characteristics of the groups, was analyzed and compared using univariate and multivariate logistic regression analyses.

RESULTS

A total of 214 patients were eligible in this study. Among them, 43.5% (93/214) of PTC patients had cervical CLNM, and 56.5% (121/214) did not. The two groups were compared using a univariate analyses, and there were no significant differences between the two groups in aspect ratio, boundary, morphology, component, and BRAFV600E (P > 0.05), and there were significant differences between gender, age, maximum tumor size, tumor location, capsule contact, microcalcifications, color Doppler flow imaging (CDFI), and Hashimoto's thyroiditis (HT) (P < 0.05). A multivariate logistic regression analysis was performed to further clarify the correlation of these indices. However, only age (OR = 2.455, P = 0.009), maximum tumor size (OR = 2.586, P = 0.010), capsule contact (OR = 3.208, P = 0.001), and CDFI (OR = 2.225, P = 0.022) were independent predictors of cervical CLNM. Combining these four factors, the area under the receiver-operating characteristic (ROC) curve for the joint diagnosis is 0.8160 (95% 0.7596-0.8725). Univariate analysis indicated that capsule contact (P = 0.001) was a possible predictive factor of BRAFV600E mutation.

CONCLUSIONS

In conclusion, four independent predictors of cervical CLNM, including age < 45 years, tumor size > 1.0 cm, capsule contact, and rich blood flow, were screened out. Therefore, a comprehensive assessment of these risk factors should be conducted when designing individualized treatment regimens for PTC patients.

Predictive factors of lymph node metastasis in papillary thyroid cancer

This study aimed to evaluate factors that predict lymph node metastasis (LNM) in papillary thyroid cancer (PTC). This retrospective cross-sectional study compared the demographic, clinical, and ultrasonographic findings of patients with PTC with and without LNM. Subgroup analysis was conducted for micro-PTCs (<1 cm). Among total (n = 512; mean age, 47.3 ± 12.7 years) and micro-PTC patients (n = 312), 35.7% and 19.6% had LNM, respectively. Younger age, male sex, tumor size, bilaterality, and suspicious ultrasound features of the tumor were associated with LNM. In multiple logistic regression analysis, among all patients, age, tumor size, and extrathyroidal extension were independent risk factors for LNM (all p<0.05). In the micro-PTC subgroup, age, extrathyroidal extension, bilaterality of tumor, and presence of autoimmune thyroid disease were independent risk and protective factors for LNM (all p<0.05). In the receiver operating characteristic analysis, the accuracy of the multivariable logistic regression model for predicting LNM among all patients and micro-PTC was acceptable (area under the curve = 0.729 and 0.733, respectively). Age, sex, tumor size, and extrathyroidal extension can assist in predicting LNM in PTC patients. Additionally, the bilaterality of tumors and presence of autoimmune thyroid disease can assist in predicting LNM in micro-PTCs.

Risk factors for central lymph node metastasis in patients with papillary thyroid carcinoma: a retrospective study

Introduction

Thyroid cancer is the most prevalent endocrine malignancy, with its global incidence increasing annually in recent years. Papillary carcinoma is the most common subtype, frequently accompanied by cervical lymph node metastasis early on. Central lymph node metastasis (CLNM) is particularly the common metastasis form in this subtype, and the presence of lymph node metastasis correlates strongly with tumor recurrence. However, effective preoperative assessment methods for CLNM in patients with papillary thyroid carcinoma (PTC) remain lacking.

Methods

Data from 400 patients diagnosed with PTC between January 1, 2018, and January 1, 2022, at the Shandong Provincial Hospital were retrospectively analyzed. This data included clinicopathological information of the patients, such as thyroid function, BRAF V600E mutation, whether complicated with Hashimoto's thyroiditis, and the presence of capsular invasion. Univariate and multivariate logistic regression analyses were performed to assess the risk factors associated with cervical CLNM in patients with PTC. Subsequently, a clinical prediction model was constructed, and prognostic risk factors were identified based on univariate and multivariate Cox regression analyses.

Results

Univariate and multivariate analyses identified that age >45 years (P=0.014), body mass index ≥25 (P=0.008), tumor size ≥1 cm (P=0.001), capsular invasion (P=0.001), and the presence of BRAF V600E mutation (P<0.001) were significantly associated with an increased risk of CLNM. Integrating these factors into the nomogram revealed an area-under-the-curve of 0.791 (95% confidence interval 0.735-0.846) and 0.765 (95% confidence interval: 0.677-0.852) for the training and validation sets, respectively, indicating strong discriminative abilities. Subgroup analysis further confirmed that patients with papillary thyroid microcarcinoma and BRAF V600E mutations who underwent therapeutic central compartment neck dissection had significantly better 3-year disease-free survival than those who had prophylactic central compartment neck dissection (P<0.001).

Conclusion

The study revealed that age >45 years, body mass index ≥25, tumor size ≥1 cm, BRAF V600E mutation, and capsular invasion are the related risk factors for CLNM in patients with PTC. For patients with clinically nodal-negative (cN0) papillary thyroid microcarcinoma, accurately identifying the BRAF V600E mutation is essential for guiding the central lymph node dissection approach and subsequent treatments.

Radiomics features from whole thyroid gland tissue for prediction of cervical lymph node metastasis in the patients with papillary thyroid carcinoma

OBJECTIVE

We aimed to develop a clinical-radiomics nomogram that could predict the cervical lymph node metastasis (CLNM) of patients with papillary thyroid carcinoma (PTC) using clinical characteristics as well as radiomics features of dual energy computed tomography (DECT).

METHOD

Patients from our hospital with suspected PTC who underwent DECT for preoperative assessment between January 2021 and February 2022 were retrospectively recruited. Clinical characteristics were obtained from the medical record system. Clinical characteristics and rad-scores were examined by univariate and multivariate logistic regression. All features were incorporated into the LASSO regression model, with penalty parameter tuning performed using tenfold cross-validation, to screen risk factors for CLNM. An easily accessible radiomics nomogram was constructed. Receiver Operating Characteristic (ROC) curve together with Area Under the Curve (AUC) analysis was conducted to evaluate the discrimination performance of the model. Calibration curves were employed to assess the calibration performance of the clinical-radiomics nomogram, followed by goodness-of-fit testing. Decision curve analysis (DCA) was performed to determine the clinical utility of the established models by estimating net benefits at varying threshold probabilities for training and testing groups.

RESULTS

A total of 461 patients were retrospectively recruited. The rates of CLNM were 49.3% (70 /142) in the training cohort and 53.3% (32/60) in the testing cohort. Out of the 960 extracted radiomics features, 192 were significantly different in positive and negative groups (p < 0.05). On the basis of the training cohort, 12 stable features with nonzero coefficients were selected using LASSO regression. LASSO regression identified 7 risk factors for CLNM, including male gender, maximum tumor size > 10 mm, multifocality, CT-reported central CLN status, US-reported central CLN status, rad-score, and TGAb. A nomogram was developed using these factors to predict the risk of CLNM. The AUC values in each cohort were 0.850 and 0.797, respectively. The calibration curve together with the Hosmer-Lemeshow test for the nomogram indicated good agreement between predicted and pathological CLN statuses in the training and testing cohorts. Results of DCA proved that the nomogram offers a superior net benefit for predicting CLNM compared to the "treat all or none" strategy across the majority of risk thresholds.

CONCLUSION

A nomogram comprising the clinical characteristics as well as radiomics features of DECT and US was constructed for the prediction of CLNM for patients with PTC, which in determining whether lateral compartment neck dissection is warranted.

Radiomics diagnostic performance in predicting lymph node metastasis of papillary thyroid carcinoma: A systematic review and meta-analysis

PURPOSE

To evaluate the diagnostic performance of radiomics in lymph node metastasis (LNM) prediction in patients with papillary thyroid carcinoma (PTC) through a systematic review and meta-analysis.

METHOD

A literature search of PubMed, EMBASE, and Web of Science was conducted to find relevant studies published until February 18th, 2023. Studies that reported the accuracy of radiomics in different imaging modalities for LNM prediction in PTC patients were selected. The methodological quality of included studies was evaluated by radiomics quality score (RQS) and quality assessment of diagnostic accuracy studies (QUADAS-2) tools. General characteristics and radiomics accuracy were extracted. Overall sensitivity, specificity, and area under the curve (AUC) were calculated for diagnostic accuracy evaluation. Spearman correlation coefficient and subgroup analysis were performed for heterogeneity exploration.

RESULTS

In total, 25 studies were included, of which 22 studies provided adequate data for meta-analysis. We conducted two types of meta-analysis: one focused solely on radiomics features models and the other combined radiomics and non-radiomics features models in the analysis. The pooled sensitivity, specificity, and AUC of radiomics and combined models were 0.75 [0.68, 0.80] vs. 0.77 [0.74, 0.80], 0.77 [0.74, 0.81] vs. 0.83 [0.78, 0.87] and 0.80 [0.73, 0.85] vs 0.82 [0.75, 0.88], respectively. The analysis showed a high heterogeneity level among the included studies. There was no threshold effect. The subgroup analysis demonstrated that utilizing ultrasonography, 2D segmentation, central and lateral LNM detection, automatic segmentation, and PyRadiomics software could slightly improve diagnostic accuracy.

CONCLUSIONS

Our meta-analysis shows that the radiomics has the potential for pre-operative LNM prediction in PTC patients. Although methodological quality is sufficient but we still need more prospective studies with larger sample sizes from different centers.

Unusual metastasis of papillary thyroid carcinoma to the spine: A case report

Papillary thyroid carcinoma (PTC) is the most common thyroid carcinoma and generally has an excellent prognosis. However, there are few cases of distant metastasis, especially to the spine, which are associated with significantly worse outcomes. Here, we present a 40-year-old male with back pain and weakness in both legs. The patient also complained of neck masses months prior to the neurological symptoms. On investigations, he was found to have multiple vertebral lesions with histopathology results of papillary thyroid carcinoma metastasis.

Clinical analysis of cervical lymph node metastasis patterns and multivariate factors in differentiated thyroid carcinoma

The incidence rate of thyroid cancer is rising rapidly in numerous parts of the world, but the mortality rate is relatively stable or even declining. The aim of the present study was to analyze the risk factors of cervical lymph node metastasis (LNM) in differentiated thyroid carcinoma (DTC). The clinical data of 846 patients with DTC were collected from the Department of General Surgery of Chifeng Municipal Hospital of Inner Mongolia Medical University (Chifeng, China) from June 2018 to June 2022. The relationship between central LNM (CLNM) and lateral LNM (LLNM) was explored in terms of sex, age, tumor diameter, multifocality, capsular invasion and Hashimoto's thyroiditis. It was revealed that male sex, age <35 years, tumor size >1 cm, multifocality and capsular invasion were associated with CLNM and LLNM (P<0.001), while there was no relationship between Hashimoto's thyroiditis, CLNM and LLNM (P>0.05). The number of positive lymph nodes in CLNM dissection, accounting for ≥50% of the total number of lymph nodes dissected, was significantly associated with LLNM (P<0.0001). In conclusion, there was no correlation between Hashimoto's thyroiditis and CLNM and LLNM. The present study revealed that patients with the characteristics of sex, age <35 years, tumor size >1 cm, multifocality and capsular invasion were associated with cervical LNM. The proportion of the number of central lymph node metastases to the total number of lymph nodes cleared during surgery is more than or equal to 50%, indicating a susceptibility to external cervical lymph node metastasis. The results of multivariate logistic analysis showed that male sex, multifocality, capsular invasion and CLNM were risk factors for LLNM, and age was a protective factor for LLNM in DTC.

Prediction model of cervical lymph node metastasis based on clinicopathological characteristics of papillary thyroid carcinoma: a dual-center retrospective study

Background

The overall prevalence of papillary thyroid carcinoma (PTC) patients is expanding along with an ongoing increase in thyroid cancer incidence. Patients with PTC who have lymph node metastases have a poor prognosis and a high death rate. There is an urgent need for indicators that can predict lymph node metastasis (LNM) before surgery as current imaging techniques, such as ultrasonography, do not have sufficient sensitivity to detect LNM. To predict independent risk factors for Central lymph node metastasis (CLNM) or Lateral lymph node metastasis (LLNM), we therefore developed two nomograms based on CLNM and LLNM, separately.

Methods

In two centers, the Second Affiliated Hospital of Nanchang University and Yichun People's Hospital, we retrospectively analyzed clinicopathological characteristics of PTC patients. We utilized multivariate analysis to screen for variables that might be suspiciously related to CLNM or LLNM. Furthermore, we developed nomograms to graphically depict the independent risk valuables connected to lymph node metastasis in PTC patients.

Result

Ultimately, 6068 PTC patients in all were included in the research. Six factors, including age<45, male, mETE, TSH>1.418, tumor size>4cm, and location (multicentric and lobe), were observed to be related to CLNM. Age<45, male, mETE (minimal extrathyroidal extension), multifocality, TSH≥2.910, CLNM positive, and tumor size>4cm were regarded as related risk factors for LLNM. The two nomograms developed subsequently proved to have good predictive power with 0.706 and 0.818 and demonstrated good clinical guidance functionality with clinical decision curves and impact curves.

Conclusion

Based on the successful establishment of this dual-institution-based visual nomogram model, we found that some clinical features are highly correlated with cervical lymph node metastasis, including CLNM and LLNM, which will better help clinicians make individualized clinical decisions for more effectively rationalizing managing PTC patients.

Ultrasound-based Nomogram for Predicting the Pathological Nodal Negativity of Unilateral Clinical N1a Papillary Thyroid Carcinoma in Adolescents and Young Adults

RATIONALE AND OBJECTIVES

To develop and validate a nomogram incorporating clinical and ultrasound (US) characteristics for predicting the pathological nodal negativity of unilateral clinically N1a (cN1a) papillary thyroid carcinoma (PTC) among adolescents and young adults.

MATERIALS AND METHODS

From December 2016 to August 2021, 278 patients aged ≤ 30 years from two medical centers were enrolled and randomly assigned to the training and validation cohorts at a ratio of 2:1. After performing univariate and multivariate analyses, a nomogram combining all independent predictive factors was constructed and applied to the validation cohort. The performance of the nomogram was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis .

RESULTS

Multivariate logistic regression analysis showed that unilateral cN1a PTC in young patients with Hashimoto's thyroiditis, T1 stage, no intra-tumoral microcalcification, and tumors located in the upper third of the thyroid gland was more likely to be free of central lymph node metastases. The nomogram revealed good calibration and discrimination in both cohorts, with areas under the receiver operating characteristic curve of 0.764 (95% confidence interval [CI]: 0.684-0.843) and 0.728 (95% CI: 0.602-0.853) in the training and validation cohorts, respectively. The clinical application of the nomogram was further confirmed using decision curve analysis.

CONCLUSION

This US-based nomogram may assist the assessment of central cervical lymph nodes in young patients with unilateral cN1a PTC, enabling improved risk stratification and optimal treatment management in clinical practice.

Can pre-operative ultrasound elastography predict aggressive features of solitary papillary thyroid carcinoma?

OBJECTIVE

To investigate whether pre-operative ultrasound elastography (USE) can be used to predict aggressive features of solitary papillary thyroid carcinomas (PTCs).

METHODS

Clinical and USE indices were retrospectively analyzed in 487 patients with surgically confirmed solitary PTCs. The patients were grouped per aggressive features on pathologic testing. Univariate and binary logistic regression analyses were performed to explore independent risk factors of aggressive features.

RESULTS

Univariate analysis revealed standard deviation (SD) values of the tumor shear-wave velocity (SWV) were associated with capsular invasion (p < 0.05). Further, shear-wave elasticity and SWV ratios correlated with extrathyroidal extension (all p < 0.05). The tumor shear-wave elasticity and SWV SD values were associated with cervical lymph node metastasis (CLNM) (all p < 0.05). Binary logistic regression analysis identified location and capsule contact as independent predictive risk factors for capsular invasion (all p < 0.05); size for extrathyroidal extension (all p < 0.05); and sex, age, margin, and suspected CLNM for CLNM (all p < 0.05). However, pre-operational USE indexes were not independent predictors of aggressive features (all p > 0.05).

CONCLUSION

Pre-operative USE indices were not independent risk factors of aggressive features of solitary PTCs. Thus, USE may have a limited value for predicting the aggressive features of PTC.

ADVANCES IN KNOWLEDGE

Pre-operative USE indices may have a limited value for predicting the aggressive features of PTC.

Predicting central lymph node metastasis in patients with papillary thyroid carcinoma based on ultrasound radiomic and morphological features analysis

OBJECTIVES

To build a combined model based on the ultrasound radiomic and morphological features, and evaluate its diagnostic performance for preoperative prediction of central lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC).

METHOD

A total of 295 eligible patients, who underwent preoperative ultrasound scan and were pathologically diagnosed with unifocal PTC were included at our hospital from October 2019 to July 2022. According to ultrasound scanners, patients were divided into the training set (115 with CLNM; 97 without CLNM) and validation set (45 with CLNM; 38 without CLNM). Ultrasound radiomic, morphological, and combined models were constructed using multivariate logistic regression. The diagnostic performance was assessed by the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, sensitivity, and specificity.

RESULTS

A combined model was built based on the morphology, boundary, length diameter, and radiomic score. The AUC was 0.960 (95% CI, 0.924-0.982) and 0.966 (95% CI, 0.901-0.993) in the training and validation set, respectively. Calibration curves showed good consistency between prediction and observation, and DCA demonstrated the clinical benefit of the combined model.

CONCLUSION

Based on ultrasound radiomic and morphological features, the combined model showed a good performance in predicting CLNM of patients with PTC preoperatively.

Construction and validation of nomograms to reduce completion thyroidectomy by predicting lymph node metastasis in low-risk papillary thyroid carcinoma

CONTEXT

More than 5 central lymph nodes metastases (CLNM) or lateral lymph node metastasis (LLNM) indicates a higher risk of recurrence in low-risk papillary thyroid carcinoma (PTC) and may lead to completion thyroidectomy (CTx) in patients initially undergoing lobectomy.

OBJECTIVE

To screen potentially high-risk patients from low-risk patients by using preoperative and intraoperative clinicopathological features to predict lymph node status.

METHODS

A retrospective analysis of 8301 PTC patients in Wuhan Union Hospital database (2009-2021) was performed according to the 2015 American Thyroid Association (ATA) and 2021 National Comprehensive Cancer Network (NCCN) guidelines, respectively. Logistic regression and best subsets regression were used to identify risk factors. Nomograms were established and externally validated using the Differentiated Thyroid Cancer in China cohort.

RESULTS

More than 5 CLNM or LLNM was detected in 1648 (19.9%) patients. Two predictive models containing age, gender, maximum tumor size, free thyroxine (FT4) and palpable node (all p < 0.05) were established. The nomogram based on NCCN criteria showed better discriminative power and consistency with a specificity of 0.706 and a sensitivity of 0.725, and external validation indicated that 76% of potentially high-risk patients could achieve preoperative conversion of surgical strategy.

CONCLUSIONS

Models based on large cohorts with good predictive performance were constructed and validated. Preoperative low-risk (T1-2N0M0) patients with age younger than 40 years, male gender, large tumor size, low FT4 and palpable nodes may be at high risk of LLNM or more than 5 CLNM, and they should receive more aggressive initial therapy to reduce CTx.

Multimodal predictive factors of metastasis in lymph nodes posterior to the right recurrent laryngeal nerve in papillary thyroid carcinoma

Objective

The lymph node posterior to the right recurrent laryngeal nerve (LN-prRLN) is a crucial component of the central lymph nodes (LNs). We aimed to evaluate multimodal predictive factors of LN-prRLN metastasis in patients with papillary thyroid carcinomas (PTCs), including the clinical data, pathologic data, and preoperative sonographic characteristics of PTCs.

Methods

A total of 403 diagnosed PTC patients who underwent unilateral, sub-total, or total thyroidectomy with central neck dissection were enrolled in this retrospective study. The clinical data, pathologic data, conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) characteristics of PTCs were collected and evaluated for predicting LN-prRLN metastasis.

Results

In this study, 96 PTC patients with LN-prRLN metastasis and 307 PTC patients without LN-prRLN metastasis were included. Univariate analysis demonstrated that PTC patients with LN-prRLN metastasis more often had younger age, larger size, multifocal cancers, A/T < 1, well-margins, microcalcification, petal-like calcification, internal vascularity, centripetal perfusion pattern and surrounding ring enhancement. Multivariate logistic regression analysis revealed that the CEUS centripetal perfusion pattern, central LN detected by ultrasound and LN-arRLN metastasis were independent characteristics for predicting LN-prRLN metastasis in PTC patients.

Conclusion

According to our research, it is essential for clinicians to thoroughly dissect central LNs, particularly LN-prRLNs.

Patient's age with papillary thyroid cancer: Is it a key factor for cervical lymph node metastasis?

BACKGROUND

Age is one of the important prognostic indicators of papillary thyroid cancer (PTC). However, the distinct metastatic patterns and prognosis of age-related lymph node metastasis (LNM) are unclear. This study aims to investigate the impact of age on LNM.

METHODS

We conducted two independent cohort studies to assess age-nodal disease association using logistic regression analysis and a restricted cubic splines model. A multivariable Cox regression model was utilized to test the impact of nodal disease on cancer-specific survival (CSS) after age stratification.

RESULTS

For this study, we included 7572 and 36,793 patients with PTC in Xiangya and SEER cohorts, respectively. After adjustment, advanced age was linearly associated with decreasing risk of central LNM. Patients of age ≤18 years (OR = 4.41, P < 0.001) and 19-45 years (OR = 1.97, P = 0.002) had a higher risk of developing lateral LNM than patients of age >60 years in both cohorts. Furthermore, CSS is significantly reduced in N1b disease (P < 0.001), not N1a disease, regardless of age. The incidence of high-volume LNM (HV-LNM) was significantly higher in patients of age ≤18 years and 19-45 years than in those of age >60 years (P < 0.001), in both cohorts. In addition, CSS was compromised in patients with PTC of age 46-60 years (HR = 1.61, P = 0.022) and those of age >60 (HR = 1.40, P = 0.021) after developing HV-LNM.

CONCLUSIONS

Patient age is significantly associated with LNM and HV-LNM. Patients with N1b disease or patients with HV-LNM of age >45 years have significantly shorter CSS. Age can, thus, be a useful guide for determining treatment strategies in PTC.

The Size of a Thyroid Nodule with ACR TI-RADS Does Not Provide a Better Prediction of the Nature of the Nodule: A Single-Center Retrospective Real-Life Observational Study

We investigated if thyroid nodule size has a predictive value of malignancy on a par with composition, echogenicity, shape, margin, and echogenic foci, and what would be the consequence of observing the rule of the American College of Radiology (ACR) to perform a fine-needle aspiration biopsy (FNAB). We conducted a retrospective real-life observational study on 86 patients who underwent surgery after a standardized diagnostic protocol. We divided the TR3, TR4, and TR5 classes into sub-classes according to the size threshold indicating FNAB (a: up to the threshold for no FNAB; b: over the threshold for FNAB suggested). We computed sensitivity, specificity, and positive (PPV) and negative predictive value (NPV) for the different sub-classes and Youden's index (Y) for the different possible cutoffs. Each sub-class showed the following PPV (0.67, 0.68, 0.70, 0.78, 0.72), NPV (0.56, 0.54, 0.51, 0.52, 0.59), and Y (0.20, 0.20, 0.22, 0.31, 0.30). In this real-life series, we did not find a significant difference in prediction of malignancy between the sub-categories according to the size threshold. All nodules have a pre-evaluation likelihood of being malignant, and the impact and utility of size thresholds may be less clear than suggested by the ACR TIRADS guidelines in patients undergoing standardized thyroid work up.

Lymph Node Ratio Predicts Recurrence in Patients with Papillary Thyroid Carcinoma with Low Lymph Node Yield

The American Thyroid Association risk stratification system suggests that having >5 metastatic lymph nodes (LNs) increase the recurrence risk in patients with papillary thyroid carcinoma (PTC). However, little is known about PTC with <5 harvested LNs. This study aimed to stratify patients with low-LN-yield (low-LNY) PTC based on lymph node ratios (LNRs). From 2007 to 2017, 6317 patients who underwent thyroidectomies were diagnosed with PTC at Seoul St. Mary's Hospital, and 909 patients with low LNYs were included in the study. Tumor recurrence was compared based on LNR. The LNR cutoff was determined using a receiver operating characteristic curve. Forty-six patients (5.1%) experienced recurrences over a mean follow-up period of 127.24 ± 33.6 months (range, 5-190 months). The cutoff for the low-LNR (n = 675) and high-LNR (n = 234) groups was 0.29 (AUC = 0.676, 95% CI = 0.591-0.761, p < 0.001). The recurrence rate was significantly higher in the high-LNR group compared to the rate in the low-LNR group (12.4% vs. 2.5%, p < 0.001). Multivariate analysis using Cox regression revealed that tumor size and LNR ≥ 0.29 were independent prognostic factors for recurrence. Therefore, LNR can be utilized to stratify the risk of recurrence in patients with low-LNY PTC.

Prediction of Cervical Lymph Node Metastasis in Clinically Node-Negative T1 and T2 Papillary Thyroid Carcinoma Using Supervised Machine Learning Approach

Papillary thyroid carcinoma (PTC) is generally considered an indolent cancer. However, patients with cervical lymph node metastasis (LNM) have a higher risk of local recurrence. This study evaluated and compared four machine learning (ML)-based classifiers to predict the presence of cervical LNM in clinically node-negative (cN0) T1 and T2 PTC patients. The algorithm was developed using clinicopathological data from 288 patients who underwent total thyroidectomy and prophylactic central neck dissection, with sentinel lymph node biopsy performed to identify lateral LNM. The final ML classifier was selected based on the highest specificity and the lowest degree of overfitting while maintaining a sensitivity of 95%. Among the models evaluated, the k-Nearest Neighbor (k-NN) classifier was found to be the best fit, with an area under the receiver operating characteristic curve of 0.72, and sensitivity, specificity, positive and negative predictive values, F1 and F2 scores of 98%, 27%, 56%, 93%, 72%, and 85%, respectively. A web application based on a sensitivity-optimized kNN classifier was also created to predict the potential of cervical LNM, allowing users to explore and potentially build upon the model. These findings suggest that ML can improve the prediction of LNM in cN0 T1 and T2 PTC patients, thereby aiding in individual treatment planning.