Metastasis Of Thyroid Carcinoma Research Articles

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

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. 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. 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. 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.

Sternal Metastasis in Follicular Thyroid Carcinoma: An Atypical Presentation

Follicular Thyroid Carcinoma (FTC), the second most common type of thyroid cancer, accounts for 10-20% of thyroid cancers, primarily affecting individuals over 40, and it tends to spread hematogenously to various organs. It often metastasizes to the lungs (49%) and bones (7-28%), including the spine, pelvis, skull, long bones, and rarely, the sternum. Metastatic FTC carries a poor prognosis, with a 3-21% ten-year survival rate when bone metastases are present. Sternal metastasis from thyroid carcinoma is exceptionally rare and significantly impacts prognosis. In this article, we present an unusual case of a 65-year-old patient who presented with a year-long compressive goiter. Examination revealed a firm, painless nodular goiter and a sternal mass. Tests showed a low TSH, normal T4, and thyroid nodules. Following thyroidectomy, a 7cm vesicular thyroid carcinoma was diagnosed. Sternal metastasis was confirmed through biopsy. The patient underwent sternal mass excision, responded well, and was referred for radioactive iodine therapy. Treatment options for metastases in FTC include surgery, radioactive iodine therapy and radiation. Surgical removal of metastases is crucial in such cases, as it can enhance the effectiveness of subsequent treatments and improve patient outcomes. This comprehensive management approach can offer a better quality of life and extended survival for patients facing this uncommon but challenging situation.

Constructing a nomogram based on the distribution of thyroid nodules and suspicious lateral cervical lymph nodes in fine-needle aspiration biopsies to predict metastasis in papillary thyroid carcinoma.

Elevated concentrations of thyroglobulin eluent is a risk factor for lateral cervical lymph node metastasis (LLNM) in patients with papillary thyroid cancer (PTC). We aimed to develop a practical nomogram based on the distribution of thyroid nodules and the presence of suspicious lateral cervical lymph nodes in fine-needle aspiration biopsies (LN-FNABs), including the cytopathology and the suspicious lateral cervical lymph node (LLN) thyroglobulin eluent (Tg), to predict the possibility of LLNM preoperatively in patients with PTC. The clinical data of PTC patients who were admitted to the Third Affiliated Hospital of Soochow University from January 2022 to May 2023 to undergo fine-needle aspiration biopsy (FNAB) were included in this study. A total of 208 patients in 2022 served as the training set (70%), and 89 patients in 2023 served as the validation set (30%). The clinical characteristics and LN-FNAB results were collected to determine the risk factors of LLNM. A preoperative nomogram was developed for predicting LLNM based on the results of the univariate and multivariate analyses. Internal calibration, external calibration, and decision curve analysis (DCA) were performed for these models. The multivariate logistic regression analysis showed that the maximum thyroid nodule diameter (Odds Ratio (OR) 2.323, 95% CI 1.383 to 3.904; p = 0.001), Tg level (OR 1.007, 95% CI 1.005 to 1.009; p = 0.000), Tg divided by serum thyroglobulin, (Tg/sTg) [odds ratio (OR) 1.005, 95% CI 1.001 to 1.008; p = 0.009], and cytopathology (OR 9.738, 95% CI 3.678 to 25.783; p = 0.000) (all p < 0.05) had a significant impact on the LLNM of patients with suspicious LLNs. The nomogram showed a better predictive value in both the training cohort [area under the curve, (AUC) 0.937, 95% CI 0.895 to 0.966] and the validation cohort (AUC 0.957, 95% CI 0.892 to 0.989). The nomogram also showed excellent internal and external calibration in predicting LLNM. According to the DCA, the diagnostic performance of this model was dependent on the following variables: maximum thyroid nodule diameter, Tg level, Tg/sTg, and cytopathology. Based on the aforementioned risk factors, we believe that it is necessary to establish a personalized LLNM model for patients with PTC. Using this practical nomogram, which combines clinical and Tg risk factors, surgeons could accurately predict the possibility of LLNM preoperatively. The nomogram will also help surgeons to establish personalized treatment plans before surgery.

Prediction of papillary thyroid metastases to the central compartment: proposal of a model taking into consideration other thyroid conditions.

To construct risk prediction models for cervical lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) under different thyroid disease backgrounds and to analyze and compare risk factors among different groups. This retrospective study included 518 patients with PTC that was pathologically confirmed post-operatively from January 2021 to November 2021. Demographic, ultrasound and pathological data were recorded. Univariate and multivariate logistic regression analyses were performed to identify factors associated with CLNM in the whole patient cohort and in patients grouped according to diagnoses of Hashimoto's thyroiditis (HT), nodular goiter (NG), and no background disease. Prediction models were constructed for each group, and their performances were compared. Analysis of the whole PTC patient cohort identified NG as independently associated with CLNM. The independent risk factors for patients with no background disease were the maximum thyroid nodule diameter and American College of Radiology Thyroid Imaging Reporting & Data System score; those for patients with HT were the maximum thyroid nodule diameter, ACR TI-RADS score, and multifocality; and those for patients with NG were the maximum thyroid nodule diameter, ACR TI-RADS score, multifocality and gender. Background thyroid disease impacts CLNM in PTC patients, and risk factors for CLNM vary among PTC patients with different background diseases. Ultrasound is useful for diagnosing background thyroid disease, which can inform treatment planning. Different prediction models are recommended for PTC cases with different thyroid diseases.

Effect and Interactions of BRAF on Lymph Node Metastasis in Papillary Thyroid Carcinoma With Hashimoto Thyroiditis.

The role of B-Raf proto-oncogene (BRAF) in papillary thyroid carcinoma (PTC) with Hashimoto thyroiditis (HT) is unknown. We aimed to explore risk factors affecting lymph node (LN) metastasis and interaction effect of BRAF in PTC patients with HT. We retrospectively collected the data of 994 PTC patients with HT who underwent surgery at the West China Hospital. We analyzed the correlations between preoperative characteristics and LN metastasis in overall, and different BRAFV600E-mutation patients. Logistic regression was applied to analyze the risk factors for LN metastasis. Finally, we performed an interaction effect analysis to identify the interaction effect of BRAF. The overall LN metastasis rate was 52.71% (524/994); the overall BRAF mutation rate was 26.9% (268/994). BRAF mutation rates were significantly different in LN metastasis and nonmetastasis patients (31.7% vs 21.5%; P < .001). In all 994 patients, age, body mass index (BMI), hypertension, tumor maximum diameter, BRAF mutation, tumor location, aspect ratio, calcification, and extrathyroidal invasion were risk factors for LN metastasis (P < .05). In BRAF-mutant patients, smoking, hypertension, maximum diameter, calcification, and multifocality were risk factors for LN metastasis (P < .05). In BRAF wild-type patients, age, BMI, maximum diameter, tumor location, aspect ratio, tumor shape, calcification, and extrathyroidal invasion were risk factors (P < .05). Additionally, we found statistically significant interactions between BRAF and BMI, hypertension, maximum diameter, and calcification (P < .05), suggesting the potential interaction effect of BRAF. BRAF is a risk factor for LN metastasis in PTC with HT. Meanwhile, BRAF can interact with age, BMI, hypertension, and calcification, which together influence LN metastasis.

Central node dissection from the perspective of lateral neck node metastasis in papillary thyroid carcinoma

ObjectivesControversy exists on how to handle central lymph nodes in papillary thyroid carcinoma, particularly regarding indications for prophylactic central neck dissection (CND). Central node metastases are more difficult to diagnose preoperatively than lateral node metastases. MethodsWe enrolled 493 patients with papillary thyroid carcinoma treated at our department in the past 22 years. Metastatic lymph nodes were diagnosed preoperatively mainly by ultrasonography. In principle, CND was performed for all cases; ipsilateral CND was performed for hemithyroidectomy, and bilateral CND was performed for total thyroidectomy. Lateral neck dissection (levels II to V; LND) was performed for metastases to lateral neck lymph nodes (clinical node (cN) 1b). ResultsThe cN stage was cN0 in 365 patients, cN1a in 10, and cN1b in 118. Of the 357 patients with stage cN0 who underwent CND, 42.9 % had pathologically positive nodes (pN+) in level VI, and of the 118 with stage cN1b who underwent CND, 78.0 % had pN+ in level VI. Cases with advanced T stage were significantly more common with pN+ in level VI. Level VI metastases were significantly associated with pN+ in level IV. As the total number of pN+ at each level of the lateral neck increased, the rate of patients with pN+ in level VI increased, and in patients with 3 or more pN+, about 85 % had level VI metastases. ConclusionBecause about half of the patients with cN0 patients had pN+ in level VI, and the rate of pN+ in level VI in each clinical T stage was 46 to 65 %, prophylactic CND should be performed, considering the various clinical benefits. Central nodes will have metastases in about 80 % of cases with lateral node metastases, requiring more accurate dissection. In lateral node metastases, there is a significant association between metastases in levels IV and VI.

Epigenetic signature discriminates lymphatic metastasis in BRAF wild-type thyroid carcinoma: methylation role of GRIK2.

Aim: Conservative treatment approaches for thyroid carcinoma (TC) patients with wild-type B-type Raf kinase (BRAF) pose risks of long-term recurrence. The association of DNA methylation with TC metastasis is unclear. Patients & methods: Here we analyzed data from 179 BRAF wild-type TC patients in the The Cancer Genome Atlasdatabase, identifying significant metastasis-associated CpGs. A logistic regression model was developed and validated for discriminating lymphatic metastasis in BRAF wild-type TC. Results: The model showed high accuracy (AUC: 0.924 training set; 0.812 and 0.773 external cohorts). TAGLN, MRPL4, CLDN10 and GRIK2 emerged as diagnostic markers. GRIK2, downregulated due to promoter hypermethylation, acted as a TC suppressor. Conclusion: Our 5-CpG epigenetic signature effectively discriminates lymphatic metastasis in BRAF wild-type TC, highlighting GRIK2's tumor-suppressive role influenced by promoter hypermethylation.

Shared-Specific Feature Learning With Bottleneck Fusion Transformer for Multi-Modal Whole Slide Image Analysis.

The fusion of multi-modal medical data is essential to assist medical experts to make treatment decisions for precision medicine. For example, combining the whole slide histopathological images (WSIs) and tabular clinical data can more accurately predict the lymph node metastasis (LNM) of papillary thyroid carcinoma before surgery to avoid unnecessary lymph node resection. However, the huge-sized WSI provides much more high-dimensional information than low-dimensional tabular clinical data, making the information alignment challenging in the multi-modal WSI analysis tasks. This paper presents a novel transformer-guided multi-modal multi-instance learning framework to predict lymph node metastasis from both WSIs and tabular clinical data. We first propose an effective multi-instance grouping scheme, named siamese attention-based feature grouping (SAG), to group high-dimensional WSIs into representative low-dimensional feature embeddings for fusion. We then design a novel bottleneck shared-specific feature transfer module (BSFT) to explore the shared and specific features between different modalities, where a few learnable bottleneck tokens are utilized for knowledge transfer between modalities. Moreover, a modal adaptation and orthogonal projection scheme were incorporated to further encourage BSFT to learn shared and specific features from multi-modal data. Finally, the shared and specific features are dynamically aggregated via an attention mechanism for slide-level prediction. Experimental results on our collected lymph node metastasis dataset demonstrate the efficiency of our proposed components and our framework achieves the best performance with AUC (area under the curve) of 97.34%, outperforming the state-of-the-art methods by over 1.27%.

Interpretable machine learning model based on the systemic inflammation response index and ultrasound features can predict central lymph node metastasis in cN0T1-T2 papillary thyroid carcinoma.

It is arguable whether individuals with T1-T2 papillary thyroid cancer (PTC) who have a clinically negative (cN0) diagnosis should undergo prophylactic central lymph node dissection (pCLND) on a routine basis. Many inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammatory index (SII), have been reported in PTC. However, the associations between the systemic inflammation response index (SIRI) and the risk of central lymph node metastasis (CLNM) remain unclear. Retrospective research involving 1,394 individuals with cN0T1-T2 PTC was carried out, and the included patients were randomly allocated into training (70%) and testing (30%) subgroups. The preoperative inflammatory indices and ultrasound (US) features were used to train the models. To assess the forecasting factors as well as drawing nomograms, the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were utilized. Then eight interpretable models based on machine learning (ML) algorithms were constructed, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). The performance of the models was evaluated by incorporating the area under the precision-recall curve (auPR) and the area under the receiver operating characteristic curve (auROC), as well as other conventional metrics. The interpretability of the optimum model was illustrated via the shapley additive explanations (SHAP) approach. Younger age, larger tumor size, capsular invasion, location (lower and isthmus), unclear margin, microcalcifications, color Doppler flow imaging (CDFI) blood flow, and higher SIRI (≥0.77) were independent positive predictors of CLNM, whereas female sex and Hashimoto thyroiditis were independent negative predictors, and nomograms were subsequently constructed. Taking into account both the auROC and auPR, the RF algorithm showed the best performance, and superiority to XGBoost, CatBoost and ANN. In addition, the role of key variables was visualized in the SHAP plot. An interpretable ML model based on the SIRI and US features can be used to predict CLNM in individuals with cN0T1-T2 PTC.

Related factors of high-volume lymph node metastasis in multifocal papillary thyroid carcinoma

Objective: To explore the related factors of high-volume lymph node metastasis (HVM) in multifocality papillary thyroid carcinoma (MPTC). Methods: The clinical and pathological data of multifocality papillary thyroid carcinoma (MPTMC, d≤10 mm) and MPTC (d>10 mm) collected from Hangzhou First People's Hospital from January 2010 to March 2023 were retrospectively analyzed. Univariate and multivariate logistic regression analysis were used to analyze the relevant factors of HVM. Results: Among 566 cases of MPTMC and 381 cases of MPTC, there were 72 males and 494 females in MPTMC, 106 males and 275 females in MPTC, respectively. The median age of the patients was 47 (39, 54) and 47 (34, 56) years, respectively, and the incidence of HVM was 4.6% (26/566) and 21.5% (82/381), respectively (χ2=64.588, P<0.001). Univariate analysis showed that in patients with MPTMC and MPTC, the incidence of HVM in males was higher than that in females [15.3% (11/72) vs 3.0% (15/494) (χ2=21.487, P<0.001) in MPTMC, 33.2% (35/106) vs 17.1% (47/275) (χ2=11.492, P=0.001) in MPTC]. The age of the HVM group was lower than that of the non-HVM group [41 (33, 50) vs 48 (39, 54) years (Z=-2.128, P=0.033) in MPTMC, 38 (29, 48) vs 48 (36, 57) years (Z=-4.987, P<0.001) in MPTC]. The maximum diameter of tumors in the HVM group were higher than those in the non-HVM group [7.0 (5.0, 10.0) mm vs 6.0 (5.0, 8.0) mm (Z=-2.558, P=0.011) in MPTMC, 17.5 (13.0, 25.0) mm vs 15.0 (12.0, 20.0) mm (Z=-2.871, P=0.004) in MPTC]. Multivariate logistic regression analysis showed that larger tumor size (OR=3.027, 2.378; 95%CI: 1.287-7.117, 1.404-4.030; P=0.011, 0.001), male (OR=5.398, 1.909; 95%CI: 2.284-12.758, 1.113-3.274; P<0.001, P=0.019), and younger age (OR=3.889, 3.136; 95%CI: 1.686-8.969, 1.837-5.355; P=0.001, P<0.001) were all risk factors for the occurrence of HVM in MPTMC and MPTC. Conclusion: The proportion of HVM in MPTC patients was higher than that in MPTMC, and larger maximum diameter, male gender and younger age are related factors for HVM in MPTMC and MPTC.

Risk factors associated with preferential lateral lymph node metastasis in papillary thyroid carcinoma.

Lateral lymph node metastasis (LLNM) is common in patients with papillary thyroid cancer (PTC), usually occurring after central lymph node metastasis (CLNM). However, some patients experience LLNM without first developing CLNM. This study aimed to identify the risk factors for developing LLNM without CLNM. We retrospectively reviewed 421 patients diagnosed with PTC who underwent lobectomy or total thyroidectomy with central and ipsilateral lateral lymph node dissection. We collected clinicopathological data and used univariate and multivariate logistic regression analyses to determine the risk factors associated with LLNM without CLNM. The LLNM without CLNM frequency was 18.3% (77/421). Univariate analyses demonstrated that age over 55 years, primary tumor in the upper portion of the thyroid, the number of central lymph node (CLN) and LLNM, primary tumor size, and the summed size of multi-foci tumors smaller than 1 cm were significantly associated with LLNM without CLNM (p < 0.05). Multivariate analysis revealed that LLNM without CLNM was more likely to occur in patients aged ≥55 years (odds ratio [OR], 2.309; 95% confidence interval [CI], 1.133-4.704; p = 0.021), and primary tumor in the upper portion of the thyroid (OR, 0.524; 95% CI, 0.295-0.934; p = 0.028). The lymph node metastasis pattern in patients with PTC is not constant. Therefore, surgeons should evaluate the lateral lymph nodes, especially in patients older than 55 years or when the primary tumor is in the upper portion of the thyroid.

RARγ promotes the invasion and metastasis of thyroid carcinoma by activating the JAK1-STAT3-CD24/MMPs axis

The nuclear receptor superfamily RAR is generally considered to play a crucial role in the development of tumors by regulating the transcription of target genes. Nevertheless, whether RARγ performs tumor-promoting or tumor-suppressing functions and its specific mechanism in thyroid carcinoma (TC) remain unknown. Here, our study demonstrated that RARγ was abnormally overexpressed in TC tissues compared with normal thyroid tissues. Moreover, RARγ expression was remarkably correlated with cell phenotypes such as cell proliferation, migration and invasion. Mechanistically, RARγ knockdown effectively decreased the phosphorylation levels of JAK1 and STAT3, leading to decreased expression of the membrane protein CD24. In a coculture system, TC cells with high levels of CD24 in the membrane were more likely to escape phagocytosis by macrophages via the combination of CD24 with the inhibitory receptor Siglec-10 in the membrane of macrophages. In contrast, the ability of macrophages to engulf TC cells was notably elevated through exogenous addition of CD24 antibody. Collectively, our study revealed a previously undiscovered molecular mechanism of RARγ in promoting the development of TC, shedding light on RARγ as a promising therapeutic target for TC.

Relationship between sonographic features, clinicopathological characteristics and lymph node metastasis of papillary thyroid carcinoma in children

Objective: This study aimed to evaluate the relationship between sonographic features, clinicopathological characteristics and lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) in children ( 18 years). S ≤ ubject and method: A total of 46 pediatric patients who were histopathologically diagnosed with PTC from January 2015 to March 2022 were included in this study. The preoperative ultrasonography, histological, and LNM features after surgery were retrospectively analyzed. Result: PTC in children accounted for 0.6% of all PTC, with a higher rate of females (67.4%), aged 15-18 years was 71.7%. The tumors weremostly classic type (87.0%), tumor size &gt; 10mm (76.1%), with high rates of central and lateral LNM (69.6% and 45.7%, respectively). Central LNM was significantly related to extrathyroidal extension (ETE). A significant relationship was observed between lateral LNM and tumor size, multifocality, ETE, intrathyroidal spread, microcalcification, and abnormal lymph nodes on ultrasound. Conclusion: Central and lateral LNM in pediatric PTC were common (69.6% and 45.7%, respectively). Several sonographic and clinicopathologic features had a significant relationship with LNM, especially lateral LNM. Patients with risk factors should undergo both clinical and neck ultrasound examinations in order to find evidence of LNM.

Diagnostic value of contrast-enhanced ultrasonography in the preoperative evaluation of lymph node metastasis in papillary thyroid carcinoma: a single-center retrospective study

BackgroundContrast-enhanced ultrasound (CEUS) has been recently used for the assessment of cervical lymph node metastasis (LNM) to guide surgical operation in patients with papillary thyroid carcinoma (PTC). However, the specificity and sensitivity of CEUS reported from previous studies are not consistent. The objective of this study was to evaluate the diagnostic value of CEUS for the metastasis of cervical lymph nodes in PTC patients based on data from one regional central hospital.MethodsThe diagnostic value of CEUS in preoperative LNM of PTC patients was concluded by comparing the results of CEUS on lymph node status with postoperative pathology examination. In addition, this study conducted hierarchical analysis of PTC patients to explore whether tumor size, different lymph node regions, and Hashimoto’s thyroiditis influence the assessment of CEUS.ResultsThis research study ultimately enrolled 965 PTC patients, including 266 males and 699 females with a mean age of 42.27 ± 11.34 years. A total of 527 patients were considered clinical-node negative, and 438 were clinical-node positive before surgery. The specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of CEUS in the assessment of LNM in PTC patients were 56.00%, 71.00%, 57.06%, 69.76% and 62.59%, respectively. For central and lateral lymph nodes, the accuracy of CEUS in PTC patients was 49.43% and 54.30%, respectively. In addition, it was shown that the accuracy of CEUS in PTC patients with Hashimoto’s thyroiditis (HT) slightly decreased to 58.44%, and the accuracy of CEUS in PTC patients with non-HT in turn increased to 64.17%. The accuracy of CEUS in non-papillary thyroid microcarcinoma (PTMC) and PTMC patients was 65.68% and 61.24%, respectively. The accuracy of CEUS in predicting central LNM was significantly different between PTC patients with or without HT (P < 0.001) in this study but not for lateral lymph nodes (P = 0.114).ConclusionThe accuracy of CEUS in the assessment of LNM in PTC is not consistently satisfactory, especially for central lymph nodes, small tumor diameters, or patients with HT. More diagnostic technologies for abnormal lymph nodes should be considered in PTC patients.

Retracted: Mst2 Overexpression Inhibits Thyroid Carcinoma Growth and Metastasis by Disrupting Mitochondrial Fitness and Endoplasmic Reticulum Homeostasis.

[This retracts the article DOI: 10.1155/2021/1262291.].

Risk factors for cervical lymph node metastasis in the central or lateral cervical region in medullary thyroid carcinoma: a systematic review and meta-analysis.

Compared with other types of thyroid carcinoma, patients with medullary thyroid carcinoma (MTC) are more likely to develop cervical lymph node metastasis. This study was conducted to clarify the risk factors for cervical lymph node metastasis (central lymph node metastasis or lateral cervical lymph node metastasis) in MTC by meta-analysis, and to provide evidence-based basis for the treatment and prognosis of MTC. The literatures related to cervical lymph node metastasis in medullary thyroid carcinoma were searched in PubMed, Embase, Web of Science, Cochrane, CNKI and Wanfang databases, and statistical analysis was performed using Revman 5.3 and Stata 14.0 software. A total of 28 papers were included in this paper, and meta-analysis showed that the occurrence of central lymph node metastasis (CLNM) in MTC patients was significantly associated with tumor size (OR = 3.07, 95%CI: 2.04-4.63, P < 0.00001), multifocality (OR = 0.29, 95%CI: 0.19-0.44, P < 0.00001), bilaterality (OR = 3.75, 95% CI: 1.95-7.14, P < 0.0001), capsular invasion (OR = 9.88, 95% CI: 5.93-16.45, P < 0.00001) and extrathyroidal extension (OR = 5.48, 95% CI: 2.61-11.51, P < 0.00001). While the occurrence of lateral cervical lymph node metastasis (LLNM) in MTC patients was strongly correlated with gender (OR = 2.97, 95%CI: 2.46-3.58, P < 0.00001), tumor size (OR = 3.88, 95%CI: 1.90-7.92, P = 0.0002 < 0.05), multifocality (OR = 0.43, 95%CI: 0.35-0.51, P < 0.00001), bilaterality (OR = 2.93, 95% CI: 1.72-4.98, P < 0.0001), capsular invasion (OR = 8.44, 95% CI: 6.11-11.64, P < 0.00001), extrathyroidal extension (OR = 7.04, 95% CI: 5.54-8.94, P < 0.00001), margin of the tumor (OR = 4.47, 95% CI: 2.37-8.44, P < 0.00001), shape of the tumor (OR = 6.81, 95% CI: 3.64-12.73, P < 0.00001), preoperative calcitonin level (SMD = 1.39, 95% CI: 0.98-1.80, P < 0.00001), preoperative carcinoembryonic antigen level (SMD = 0.97, 95% CI: 0.74-1.20, P < 0.00001) and CLNM (OR = 19.70, 95% CI: 14.16-27.43, P < 0.00001). Tumor size, multifocality, bilaterality, capsular invasion and extrathyroidal extension are the main risk factors for developing CLNM in MTC patients; And risk factors for developing LLNM in MTC patients include: gender, tumor size, multifocality, bilaterality, capsular invasion, extrathyroidal extension, margin of the tumor, shape of the tumor, preoperative calcitonin level, preoperative carcinoembryonic antigen level and central lymph node metastasis. These risk factors can guide the individualized treatment plan and improve the prognosis of MTC patients.

SAT543 A Case of Non-iodine-Avid Papillary Thyroid Cancer With a Rare Distant Metastasis to the Pancreas

Abstract Disclosure: A.H. Alcain: None. M.C. Isidro: None. Papillary Thyroid Carcinoma is the most common type of differentiated thyroid cancer. Distant metastasis is rare occurring only in 5% of patients and typically involves the lungs and bones. Metastasis to the pancreas is extremely rare with few cases reported over the years. We present a case of a 65-year-old female, who presented with sudden onset of abdominal pain. A review of the patient’s medical history revealed a history of a non-iodine avid Papillary Thyroid Carcinoma in 2015. The patient underwent Radioactive Iodine (RAI) ablation therapy twice due to elevated Thyroglobulin (Tg) levels. Despite RAI, Tg levels were still elevated with no recurrence nor metastasis noted on scan. Chemotherapy was offered but the patient opted for Tomotherapy. The patient completed Tomotherapy in 2017 but afterward was lost to follow-up. A CT scan of the abdomen showed findings of a pancreatic tail and body mass (10 x 7 cm) with an invasion of the mid-descending colon with pulmonary nodules which are possibly metastatic. The patient underwent an endoscopic ultrasound-guided biopsy, and pathology showed findings of a pancreatic papillary neoplasm (CK and beta-catenin positive, synaptophysin negative). Chemotherapy was given (FOLFOX) and a PET scan was requested to monitor the response to treatment. However, PET-scan showed FDG-avid (SUV 32.1) mass in the pancreatic tail (7.2 x 7.8 x 13.3 cm), FDG-avid (SUV 17.61) nodules in the lungs, and an ill-defined heterogeneous mass in the left surgical site (2.2 x 2.6 x 5.3 cm). Given that patient had a thyroidectomy in 2015, recurrence was considered. The possibility of probable metastasis to the pancreas was entertained hence re-biopsy was done. Serum Tg levels were elevated (4,115 ng/ml NV: 1.59-50.0) and negative for Anti-Tg. Biopsy showed high-grade neoplasm with papillary features. IHC staining showed positive for CK7, Tg, and TTF-1, and negative for CK20 which was consistent with metastatic papillary thyroid carcinoma. The patient was given Lenvatinib and is at present tolerating the treatment well with evidence of decreasing Tg levels suggesting a response to treatment. This is a case of a rare site of distant metastasis of a non-iodine avid papillary thyroid carcinoma. Targeted therapy such as Tyrosine kinase inhibitors can improve the survival rate of patients with Radioiodine Refractory Thyroid cancers. Metastasis should be considered especially in patients with a history of prior malignancy. Presentation Date: Saturday, June 17, 2023

A novel wavelet-transform-based convolution classification network for cervical lymph node metastasis of papillary thyroid carcinoma in ultrasound images.

Preoperative assessment of cervical lymph nodes metastasis (CLNM) for accurate qualitative and locating diagnosis is important for choosing the best treatment option for patients with papillary thyroid cancer. Non-destructive, non-invasive ultrasound is currently the imaging method of choice for lymph node metastatic assessment. For lymph node characteristics and ultrasound images, this paper proposes a multitasking network framework for diagnosing metastatic lymph nodes in ultrasound images, in which localization module not only provides information on the location of lymph nodes to focus on the peripheral and self regions of lymph nodes, but also provides structural features of lymph nodes for subsequent classification module. In the classification module, we design a novel wavelet-transform-based convolution network. Wavelet transform is introduced into the deep learning convolution module to analyze ultrasound images in both spatial and frequency domains, which effectively enriches the feature information and improves the classification performance of the model without increasing the model parameters. We collected 510 patient data (N = 1376) from Shanghai Sixth People's Hospital regarding ultrasound lymph nodes in the neck, as well as used three publicly available ultrasound datasets, including SCUI2020 (N = 2914), DDTI (N = 480), and BUSI (N = 780). Compared to the optimal two-stage model, our model has improved its accuracy and AUC indexes by 5.83% and 4%, which outperforms the two-stage architectures and also surpasses the latest classification networks.

Ultrasonography features and American college of radiology thyroid imaging reporting and data system category in the prediction of central lymph node metastasis in papillary thyroid carcinoma

Ultrasonography features and American college of radiology thyroid imaging reporting and data system category in the prediction of central lymph node metastasis in papillary thyroid carcinoma

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

PurposeTo 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. MethodA 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. ResultsIn 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. ConclusionsOur 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.