Predictors and a Prediction Model for Central Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma (cN0)

Application of ultrasound elastography and radiomic for predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma

Objective

This study aims to combine ultrasound (US) elastography (USE) and radiomic to predict central cervical lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC).

Methods

A total of 204 patients with 204 thyroid nodules who were confirmed with PTMC and treated in our hospital were enrolled and randomly assigned to the training set (n = 142) and the validation set (n = 62). US features, USE (gender, shape, echogenic foci, thyroid imaging reporting and data system (TIRADS) category, and elasticity score), and radiomic signature were employed to build three models. A nomogram was plotted for the combined model, and decision curve analysis was applied for clinical use.

Results

The combined model (USE and radiomic) showed optimal diagnostic performance in both training (AUC = 0.868) and validation sets (AUC = 0.857), outperforming other models.

Conclusion

The combined model based on USE and radiomic showed a superior performance in the prediction of CLNM of patients with PTMC, covering the shortage of low specificity of conventional US in detecting CLNM.

Score based on contrast-enhanced ultrasound predict central lymph node metastasis in papillary thyroid cancer

Objectives

To investigate the association between contrast-enhanced ultrasound (CEUS) features of PTC and central lymph node metastasis (CLNM) and to develop a predictive model for the preoperative identification of CLNM.

Methods

This retrospective study evaluated 750 consecutive patients with PTC from August 2020 to April 2023. Conventional ultrasound and qualitative CEUS features were analyzed for the PTC with or without CLNM using univariate and multivariate logistic regression analysis. A nomogram integrating the predictors was constructed to identify CLNM in PTC. The predictive nomogram was validated using a validation cohort.

Results

A total of 684 patients were enrolled. The 495 patients in training cohort were divided into two groups according to whether they had CLNM (pCLNM, n= 191) or not (nCLNM, n= 304). There were significant differences in terms of tumor size, shape, echogenic foci, enhancement direction, peak intensity, and score based on CEUS TI-RADS between the two groups. Independent predictive US features included irregular shape, larger tumor size (≥ 1.0cm), and score. Nomogram integrating these predictive features showed good discrimination and calibration in both training and validation cohort with an AUC of 0.72 (95% CI: 0.68, 0.77) and 0.79 (95% CI: 0.72, 0.85), respectively. In the subgroup with larger tumor size, age ≤ 35 years, irregular shape, and score > 6 were independent risk factors for CLNM.

Conclusion

The score based on preoperative CEUS features of PTC may help to identify CLNM. The nomogram developed in this study provides a convenient and effective tool for clinicians to determine an optimal treatment regimen for patients with PTC.

Predicting central cervical lymph node metastasis in papillary thyroid microcarcinoma using deep learning

Background

The aim of this study is to design a deep learning (DL) model to preoperatively predict the occurrence of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC).

Methods

This research collected preoperative ultrasound (US) images and clinical factors of 611 PTMC patients. The clinical factors were analyzed using multivariate regression. Then, a DL model based on US images and clinical factors was developed to preoperatively predict CLNM. The model's efficacy was evaluated using the receiver operating characteristic (ROC) curve, along with accuracy, sensitivity, specificity, and the F1 score.

Results

The multivariate analysis indicated an independent correlation factors including age ≥55 (OR = 0.309, p < 0.001), tumor diameter (OR = 2.551, p = 0.010), macrocalcifications (OR = 1.832, p = 0.002), and capsular invasion (OR = 1.977, p = 0.005). The suggested DL model utilized US images achieved an average area under the curve (AUC) of 0.65, slightly outperforming the model that employed traditional clinical factors (AUC = 0.64). Nevertheless, the model that incorporated both of them did not enhance prediction accuracy (AUC = 0.63).

Conclusions

The suggested approach offers a reference for the treatment and supervision of PTMC. Among three models used in this study, the deep model relied generally more on image modalities than the data modality of clinic records when making the predictions.

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.

Construction of a nomogram for central lymph node metastasis in papillary thyroid cancer based on gender grouping

BACKGROUND

The status of central lymph nodes is crucial for determining the surgical approach to papillary thyroid carcinoma (PTC). Because of the differences between genders in central lymph node metastasis (CLNM), we aimed to construct separate predictive models for CLNM according to gender.

METHODS

In our study, a total of 1258 PTC patients who underwent thyroid cancer surgery from September 2021 to March 2023 were analyzed retrospectively. The data were analysed univariately and multivariately using SPSS software grouped according to gender and nomograms of CLNM were plotted using R software. The variables included in this study were sex, Age, body mass index, Diabetes, chronic lymphocytic thyroiditis (CLT), Suspicious central lymph node (SCLN), A/T, Margin, Microcalcification (MC), BRAF, Number, Location, CLNM.

RESULTS

The preoperative nomogram in male patients included four clinical variables: CLT, Margin, Number, Size. The preoperative nomogram of female patients included six clinical variables: Age, SCLN, Margin, MC, Number, Size. The calibration curves showed great agreement in both the training group and the validation group. The decision curve analysis showed the feasibility of nomogram in predicting CLNM in both man and woman.

CONCLUSION

Based on the successful establishment of nomogram, we can analyze the variability of CLNM between male and female, which may provide clinicians with personalized clinical schemes in the treatment of PTC.

Gene mutations as predictors of central lymph mode metastasis in cN0 PTC: A meta-analysis

Gene mutations could predict the tumor progression and prognosis, which are us to predict CLNM in patients with cN0 PTC, however, these results are not consistent. This meta-analysis tried to identify gene mutations which could predict CLNM in patients with cN0 PTC. A systematic search was performed for identifying relevant literature published prior to July 2023 in three search engines: PubMed, EMBASE and Web of Science. Studies that investigated the gene mutations for CLNM in patients with cN0 PTC were included in our meta-analysis. Sixteen studies, including 6095 cN0 PTC with BRAF mutations were include in our meta-analysis. The prevalence of CLNM in cN0 PTC ranged from 13.7% to 50.6%. The pooled analysis demonstrated that BRAFV600E mutation is significantly associated with CLNM (OR = 2.01, 95% CI: 1.55-2.60, p < 0.001) in PTC and PTMC (OR = 1.70, 95% CI: 0.51-1.81, p < 0.001). Whereas, cN0 PTC with TERT (OR = 1.94, 95% CI: 0.51-7.36, p = 0.33) and KRAS (OR = 0.57, 95% CI: 0.51-1.81, p = 0.34) mutations might not contribute to predict CLNM. Our analysis identified that BRAF mutation was a predictive factor for cN0 PTC, as well as for cN0 PTMC, which could be useful for clinician to accurately choose prophylactic CLND and better manage cN0 PTC.

A nomogram based on multimodal ultrasound and clinical features for the prediction of central lymph node metastasis in unifocal papillary thyroid carcinoma

OBJECTIVES

To build a predictive model for central lymph node metastasis (CLNM) in unifocal papillary thyroid carcinoma (UPTC) using a combination of clinical features and multimodal ultrasound (MUS).

METHODS

This retrospective study, included 390 UPTC patients who underwent MUS between January 2017 and October 2022 and were divided into a training cohort (n = 300) and a validation cohort (n = 90) based on a cut-off date of June 2022. Independent indicators for constructing the predictive nomogram models were identified using multivariate regression analysis. The diagnostic yield of the 3 predictive models was also assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

Both clinical factors (age, diameter) and MUS findings (microcalcification, virtual touch imaging score, maximal value of virtual touch tissue imaging and quantification) were significantly associated with the presence of CLNM in the training cohort (all P < .05). A predictive model (MUS + Clin), incorporating both clinical and MUS characteristics, demonstrated favourable diagnostic accuracy in both the training cohort (AUC = 0.80) and the validation cohort (AUC = 0.77). The MUS + Clin model exhibited superior predictive performance in terms of AUCs over the other models (training cohort 0.80 vs 0.72, validation cohort 0.77 vs 0.65, P < .01). In the validation cohort, the MUS + Clin model exhibited higher sensitivity compared to the CLNM model for ultrasound diagnosis (81.2% vs 21.6%, P < .001), while maintaining comparable specificity to the Clin model alone (62.3% vs 47.2%, P = .06). The MUS + Clin model demonstrated good calibration and clinical utility across both cohorts.

CONCLUSION

Our nomogram combining non-invasive features, including MUS and clinical characteristics, could be a reliable preoperative tool to predict CLNM treatment of UPTC.

ADVANCES IN KNOWLEDGE

Our study established a nomogram based on MUS and clinical features for predicting CLNM in UPTC, facilitating informed preoperative clinical management and diagnosis.

Intraoperative frozen section for determining the extent of surgery in papillary thyroid carcinoma: comprehensive risk factor assessment

Background

There is much debate on the optimal treatment approach of papillary thyroid carcinoma (PTC). Different guidelines base recommendations on various risk factors. While diagnosing the various risk factors is difficult due to the technical limitations, intraoperative frozen section (IFS) may be a feasible method. We aim to real-time evaluate the multiple risk factors, including lymph node metastasis (LNM), extrathyroidal extension (ETE), multifocality using IFS, and then identify a more effective surgical plan, which may help avoid the need for a second surgery and improve prognosis of patients.

Methods

We retrospectively reviewed the medical records of 364 patients from January 1, 2021 to December 31, 2021. All the patients were initially recommended to undergo a hemithyroidectomy (HT) with isthmusectomy and ipsilateral central compartment neck dissection (CCND). IFS would be executed immediately. Further total thyroidectomies (TTs) would be performed if: (I) results of IFS showed >5 LNM, or (II) there are 1≤ LNM ≤5 but with ETE and/or multifocal carcinoma. The patients were divided and investigated according to the extent of surgery.

Results

Based on the results of IFS, 72 patients underwent TT. The TT group displayed larger average tumor diameter, greater age, higher average body mass index (BMI), and elevated incidence of hypertension and hyperlipidemia compared to the HT group. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of IFS were 77.61%, 100%, 100%, and 88.46%, respectively.

Conclusions

IFS is a highly reliable procedure. Comprehensively evaluating central compartment LNM, ETE, and multifocal carcinoma through IFS helps identify a more reasonable surgical option under the current clinical consensus, which may thus help avoid the need for a second surgery.

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.

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.

Metastatic differentiated thyroid cancer with negative serum stimulated Tg but positive post-therapeutic 131I-SPECT/CT scintigraphy: a single-center retrospective study

PURPOSE

This study aimed to describe the characteristics of patients with metastatic differentiated thyroid carcinoma (DTC) who had positive 131I-scintigraphy but negative stimulated thyroglobulin (sTg), and to evaluate their short-term response to radioiodine therapy (RAI).

METHODS

A total of 2250 consecutive postoperative DTC patients, who underwent RAI treatment from July 2019 to June 2022, were analyzed retrospectively. The target group was defined as stimulated Tg < 2 ng/mL with TgAb < 100 IU/mL but with post-therapeutic 131I-SPECT/CT metastases. The characteristics of these patients were analyzed and the metastatic profiles were compared with TgAb positive or sTg positive ones. A cross-sectional efficacy was evaluated 6-12 months after the RAI therapy and the treatment course until the end of the study was recorded.

RESULTS

105 (4.67%) DTC patients were post-therapeutic 131I-SPECT/CT positive and sTg negative (target group). Metastatic profiles were found significant differences between sTg negative and sTg positive ones (P < 0.001). Excellent response (ER) was achieved in 72.4% of the target group between 6-12 months of cross-sectional efficacy assessment, compared with only 12.8% in sTg positive ones (P < 0.001). The majority of the target group didn't require aggressive treatment in short-term follow-up compared with sTg positive group (P < 0.001).

CONCLUSION

The percentage of DTCs with negative sTg but positive post-therapeutic 131I-SPECT/CT was relatively low, but still significant. Moreover, the majority of these patients showed an ER to RAI and may not require the next course of therapy. Long-term follow-up is still necessary to assess recurrence and adapt surveillance in these patients.

Insight of novel biomarkers for papillary thyroid carcinoma through multiomics

Introduction

The overdiagnosing of papillary thyroid carcinoma (PTC) in China necessitates the development of an evidence-based diagnosis and prognosis strategy in line with precision medicine. A landscape of PTC in Chinese cohorts is needed to provide comprehensiveness.

Methods

6 paired PTC samples were employed for whole-exome sequencing, RNA sequencing, and data-dependent acquisition mass spectrum analysis. Weighted gene co-expression network analysis and protein-protein interactions networks were used to screen for hub genes. Moreover, we verified the hub genes' diagnostic and prognostic potential using online databases. Logistic regression was employed to construct a diagnostic model, and we evaluated its efficacy and specificity based on TCGA-THCA and GEO datasets.

Results

The basic multiomics landscape of PTC among local patients were drawn. The similarities and differences were compared between the Chinese cohort and TCGA-THCA cohorts, including the identification of PNPLA5 as a driver gene in addition to BRAF mutation. Besides, we found 572 differentially expressed genes and 79 differentially expressed proteins. Through integrative analysis, we identified 17 hub genes for prognosis and diagnosis of PTC. Four of these genes, ABR, AHNAK2, GPX1, and TPO, were used to construct a diagnostic model with high accuracy, explicitly targeting PTC (AUC=0.969/0.959 in training/test sets).

Discussion

Multiomics analysis of the Chinese cohort demonstrated significant distinctions compared to TCGA-THCA cohorts, highlighting the unique genetic characteristics of Chinese individuals with PTC. The novel biomarkers, holding potential for diagnosis and prognosis of PTC, were identified. Furthermore, these biomarkers provide a valuable tool for precise medicine, especially for immunotherapeutic or nanomedicine based cancer therapy.

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.

Predictors and a prediction model for positive fine needle aspiration biopsy in C-TIRADS 4 thyroid nodules

Objectives

To screen out the predictors and establish a prediction model of positive fine needle aspiration biopsy (FNAB) in the Chinese Guidelines for Malignant Risk Stratification of Thyroid Nodule Ultrasound (C-TIRADS) 4 thyroid nodules, and this nomogram can help clinicians evaluate the risk of positive FNAB and determine if FNAB is necessary.

Methods

We retrospectively analyzed data from 547 patients who had C-TIRADS 4 thyroid nodules and underwent fine-needle aspiration biopsy (FNAB) at the Second Affiliated Hospital of Chongqing Medical University between November 30, 2021 and September 5, 2022. Patients who met our inclusion criteria were divided into two groups based on positive or negative FNAB results. We compared their ultrasound (US) features, BRAF V600E status, thyroid function, and other general characteristics using univariate and multivariate logistic regression analyses to identify independent predictors. These predictors were then used to construct a nomogram. The calibration plot, area under the curve (AUC), and decision curve analysis were employed to evaluate the calibration, discrimination, and clinical utility of the prediction model.

Results

Out of 547 patients, 39.3% (215/547) had a positive result on fine-needle aspiration biopsy (FNAB), while 60.7% (332/547) had a negative result. Univariate logistic regression analysis revealed no significant differences in TPOAb, TgAb, TSH, Tg, nodule location, sex, or solid status between the two groups (P>0.05). However, age, nodule size, internal or surrounding blood flow signal, microcalcifications, aspect ratio, morphology, and low echo showed significant differences (P<0.05). Multivariate logistic regression analysis was conducted to explore the correlation between potential independent predictors. The results showed that only age (OR=0.444, 95% Cl=0.296~0.666, P<0.001), low echo (OR=3.549, 95% Cl=2.319~5.432, P<0.001), microcalcifications (OR=2.531, 95% Cl=1.661~3.856, P<0.001), aspect ratio (OR=3.032, 95% Cl=1.819~5.052, P<0.001), and morphology (OR=2.437, 95% Cl=1.586~3.745, P<0.001) were independent predictors for a positive FNAB. These variables were used to construct a prediction nomogram. An ROC curve analysis was performed to assess the accuracy of the nomogram, and AUC=0.793, which indicated good discrimination and decision curve analysis demonstrated clinical significance within a threshold range of 14% to 91%.

Conclusion

In conclusion, 5 independent predictors of positive FNAB, including age (≤45 years old), low echo (yes), microcalcifications (yes), aspect ratio (>1) and morphology (irregular), were identified. A nomogram was established based on the above 5 predictors, and the nomogram can be used as a complementary basis to help clinicians make decisions on FNAB of C-TI-RADS 4 thyroid nodules.

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.

Accuracy of papillary thyroid cancer prognostic nomograms: a systematic review

Objective

Current staging and risk-stratification systems for predicting survival or recurrence of patients with differentiated thyroid carcinoma may be ineffective at predicting outcomes in individual patients. In recent years, nomograms have been proposed as an alternative to conventional systems for predicting personalized clinical outcomes. We conducted a systematic review to evaluate the predictive performance of available nomograms for thyroid cancer patients.

Design and methods

PROSPERO registration (CRD42022327028). A systematic search was conducted without time and language restrictions. PICOT questions: population, patients with papillary thyroid cancer; comparator prognostic factor, single-arm studies; outcomes, overall survival, disease-free survival, cancer-specific survival, recurrence, central lymph node metastases, or lateral lymph node metastases; timing, all periods; setting, hospital setting. Risk of bias was assessed through PROBAST tool.

Results

Eighteen studies with a total of 20 prognostic models were included in the systematic review (90,969 papillary thyroid carcinoma patients). Fourteen models were at high risk of bias and four were at unclear risk of bias. The greatest concerns arose in the analysis domain. The accuracy of nomograms for overall survival was assessed in only one study and appeared limited (0.77, 95% CI: 0.75-0.79). The accuracy of nomograms for disease-free survival ranged from 0.65 (95% CI: 0.55-0.75) to 0.92 (95% CI: 0.91-0.95). The C-index for predicting lateral lymph node metastasis ranged from 0.72 to 0.92 (95% CI: 0.86-0.97). For central lymph node metastasis, the C-index of externally validated studies ranged from 0.706 (95% CI: 0.685-0.727) to 0.923 (95% CI: 0.893-0.946).

Conclusions

Our work highlights the extremely high heterogeneity among nomograms and the critical lack of external validation studies that limit the applicability of nomograms in clinical practice. Further studies ideally using commonly adopted risk factors as the backbone to develop nomograms are required.

Significance statement

Nomograms may be appropriate tools to plan treatments and predict personalized clinical outcomes in patients with papillary thyroid cancer. However, the nomograms developed to date are very heterogeneous, and their results seem to be closely related to the specific samples studied to generate the same nomograms. The lack of rigorous external validation procedures and the use of risk factors that sometimes appear to be far from those commonly used in clinical practice, as well as the great heterogeneity of the risk factors considered, limit the ability of nomograms to predict patient outcomes and thus their current introduction in clinical practice.

Nomogram for predicting central lymph node metastasis in T1-T2 papillary thyroid cancer with no lateral lymph node metastasis

OBJECTIVE

Whether routine central lymph node dissection (CLND) is necessary for T1-T2 papillary thyroid carcinoma (PTC) patients without certain lateral lymph node metastases (LLNM) remains controversial. This study aims to construct a nomogram that predicts central lymph node metastasis (CLNM) for T1-T2 PTC patients without LLNM.

METHODS

We retrospectively reviewed adult T1-T2 PTC patients with no LLNM retrieved from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. We also collected data from patients treated at the First Hospital of China Medical University between February and April 2021 for external validation. Logistic regression model was used to construct a risk prediction model nomogram. The receiver-operating characteristic (ROC) curve, calibration plot, and decision curve analyses (DCA) were used for assessing the nomogram.

RESULTS

5,094 patients from the SEER database and 300 patients from our department were finally included in this study. Variables such as age, gender, race, tumor size, multifocality, and minimal extrathyroidal extension (mETE) were found to be associated with CLNM and were subsequently incorporated into our nomogram. The C-index of our constructed model was 0.704, while the internal and external validation C-indexes were 0.693 and 0.745, respectively. The nomogram was then evaluated using calibration and decision curve analyses.

CONCLUSION

A visualized nomogram was successfully developed to predict CLNM in T1-T2 PTC patients without LLNM and assist clinicians in making personalized clinical decisions.

Preoperative strain ultrasound elastography can predict occult central cervical lymph node metastasis in papillary thyroid cancer: a single-center retrospective study

Objective

To determine whether preoperative ultrasound elastography can predict occult central cervical lymph node metastasis (CCLNM) in patients with papillary thyroid cancer.

Methods

This retrospective study included 541 papillary thyroid cancer patients with clinically negative lymph nodes prior to surgery between July 2019 and December 2021. Based on whether CCLNM was present on postoperative pathology, patients were categorized as CCLNM (+) or CCLNM (-). Preoperative clinical data, conventional ultrasound features, and ultrasound elastography indices were compared between the groups. Univariate and multivariate logistic regression analysis were performed to identify the independent predictors of occult CCLNM.

Results

A total of 36.60% (198/541) patients had confirmed CCLNM, while 63.40% (343/541) did not. Tumor location, bilaterality, multifocality, echogenicity, margin, shape, vascularity, capsule contact, extrathyroidal extension, aspect ratio, and shear wave elasticity parameters were comparable between the groups (all P > 0.05). Univariate analysis showed statistically significant differences between the two groups in age, sex, tumor size, calcification, capsule invasion, and strain rates ratio in strain ultrasound elastography (all P < 0.05). In multivariate logistic regression analysis, the independent predictors of occult CCLNM were age (OR = 0.975, 95% CI = 0.959-0.991, P = 0.002), sex (OR = 1.886, 95% CI = 1.220-2.915, P = 0.004), tumor size (OR = 1.054, 95% CI = 1.014-1.097, P = 0.008), and strain rates ratio (OR = 1.178, 95% CI = 1.065-1.304, P = 0.002).

Conclusion

Preoperative strain ultrasound elastography can predict presence of occult CCLNM in papillary thyroid cancer patients and help clinicians select the appropriate treatment strategy.

Lymph node microcalcifications after neoadjuvant chemotherapy: A therapeutic response marker

Lymph node microcalcifications are rare events, and when they are accompanied by neoplasia, they usually seem to be associated with a metastatic condition. We present a case of a patient with breast cancer and lymph node microcalcifications undergoing neoadjuvant chemotherapy (NCT). A change in the calcification pattern towards becoming coarse was observed. Calcification represented a marker of axillary disease, and it was resected after NCT. This is the first report of a patient with lymph node microcalcification undergoing NCT. We observed a change in the calcification format, which facilitated lymph node sentinel identification. Pathological evaluation indicated metastatic disease.

Risk factors of cervical lymph node metastasis in multifocal papillary thyroid cancer

Introduction

Identifying risk variables for cervical lymph node metastases in multifocality papillary thyroid cancer (MPTC) could assist surgeons in determining whether cervical lymph node dissection would be an appropriate surgical option.

Methods

A retrospective cohort of 2006 patients with papillary thyroid cancer were selected. MPTC (N = 460) was defined as the presence of two or more foci of PTC. The risk factors for central lymph node metastasis (CLNM) and lateral lymph node metastasis (LLNM) in MPTC were investigated by univariate and multivariate analyses, including the following items: age at diagnosis, gender, Hashimoto's thyroiditis, extrathyroidal extension (ETE), maximal axial diameter (MAD) and the sum of axial diameters (SAD) of tumor. In addition, CLNM was used to evaluate LLNM.

Results

The incidence of CLNM and LLNM was 44.57% and 17.17%, respectively. The multivariate analysis demonstrated that gender, extrathyroidal extension (ETE), age, maximal axial diameter (MAD), and the sum of axial diameters (SAD) were related to increased risk for CLNM in MPTC (p < 0.05). The area under the receiver operating characteristic (ROC) curve (AUC) for age at diagnosis of CLNM was 0.647, the cut-off value was 50 years old. Additionally, by multivariate analysis, CLNM, ETE, MAD, and SAD were independent risk factors for LLNM in MPTC (p < 0.05). ROC curve analysis demonstrates that AUC for MAD and SAD diagnosis of LLNM were 0.639 and 0.757, and the cut-off values were 16 and 26 mm, respectively.

Conclusions

MPTC patients who have risk factors for CLNM were advised to perform prophylactic central lymph node dissection (CLND). Additionally, the presence of risk factors for LLNM should be individually evaluated and analyzed for the necessity of lateral lymph node dissection.

NOMOGRAM COMBINING PREOPERATIVE ULTRASONOGRAPHY WITH CLINICAL FEATURES FOR PREDICTING LYMPH NODES POSTERIOR TO THE RIGHT RECURRENT LARYNGEAL NERVE METASTASIS IN PATIENTS WITH PAPILLARY THYROID CANCER

Aim

To establish a nomogram combining preoperative ultrasonic and clinical features for predicting lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) metastasis in papillary thyroid carcinoma (PTC) patients.

Methods

Preoperative ultrasonic and clinical variables of patients with PTC from 2014 to 2021 were retrospectively analyzed. The risk factors associated with LN-prRLN metastasis were identified and validated through a developed nomogram model based on univariate and multivariate logistic regression analysis.

Results

A total of 615 patients (690 lesions) were enrolled for the training dataset and 207 patients (226 lesions) for the validation dataset with 54 (6.57%) patients developing LN-prRLN metastasis. Multivariate logistic regression analysis demonstrated that the preoperative ultrasound measurement of larger tumors (≥20 mm), higher TI-RADS category (category 5), and higher thyroglobulin level (9.86 ng/mL) in patients with PTC were predictive factors for LN-prRLN metastasis. The nomogram model was established and verified yielding a relatively good predictive performance in the training and validation dataset (AUC: 0.868 vs. 0.851).

Conclusions

The nomogram combining preoperative ultrasonography with clinical features in this study is highly predictive of LN-prRLN metastasis in patients with PTC, which may provide more personalized recommendations for clinicians in preoperative decision-making for complete dissection of LN-prRLN.