Recent Advances in the Classification of Low-grade Papillary-like Thyroid Neoplasms and Aggressive Papillary Thyroid Carcinomas: Evolution of Diagnostic Criteria

Evaluation of the role of prophylactic bilateral central neck lymph node dissection in patients with papillary thyroid carcinoma: a case controlled study

Thyroid cancer is the most common malignancy in the endocrine system. Papillary thyroid carcinoma (PTC) is the most common differentiated thyroid cancer. There are considerable discrepancies regarding the role and extent of prophylactic central lymph node dissection (PCLND) for patients with PTC. Our primary goal was the evaluation of CLN involvement based on the tumor features and staging on the eight version of the American Joint Committee on Cancer and also the TNM method. Our secondary aim was to evaluate the features of the CLNs with tumoral features and also features associated with the development of transient hypoparathyroidism. This prospective case-controlled study was performed among PTC patients. Total thyroidectomy and bilateral dissection of the CLNs of the central compartment of the neck was performed, and samples were sent for pathological evaluation. CLN involvement, tumoral features and transient hypoparathyroidism were cross-evaluated and analyzed with SPSS version 26.0. In this study, out of 61 patients, 11 (18%) were male, the average age was 37.3 ± 13.7 years, based on AJCC staging, 53 (86.9%) were stage I and 8 (13.1%) were stage II, and based on TNM staging, 39 patients (66.1%) were T1, including 13 (22.0%) T1a and 26 (44.1%) T1b, 15 patients (25.4%) were T2, and five patients (8.5%) were T3. Based on permanent pathology evaluation, the majority of patients (n = 48; 78.7%) had CLN involvement. None of the preoperative and tumor features had a significant association with CLN involvement. 75% of stage I and 100% of stage two cases, while 76.9% of T1, 86.7% of T2, and 80.0% of T3 cases had CLN involvement. There was no significant association between the involvement of CLN and the AJCC staging (P = 0.184) or TNM staging (P = 0.875). The involved to dissected CLN ratio was significantly higher in stage II patients compared to stage I (72.5 vs. 34.8%; P = 0.006), and also with higher T staging (0.009). There was a statistically significant association between the larger CLN size and older patients' age, higher postoperative thyroglobulin levels, and smaller tumor size. Higher postoperative thyroglobulin level was significantly associated with larger tumors size and thyroid capsule invasion. Also, 26 (44.8%) of patients developed transient hypoparathyroidism, which was significantly associated with vascular invasion (P = 0.048), bilateral location of tumor (P = 0.048) or on the right side (0.005), and larger size of the tumor (P = 0.016). Tumor features and staging were not associated with CLN involvement features. Therefore, full extent PCLND should be carried out to avoid reoperation or metastasis in PTC patients.

Detecting Aggressive Papillary Thyroid Carcinoma Using Hyperspectral Imaging and Radiomic Features

Hyperspectral imaging (HSI) and radiomics have the potential to improve the accuracy of tumor malignancy prediction and assessment. In this work, we extracted radiomic features of fresh surgical papillary thyroid carcinoma (PTC) specimen that were imaged with HSI. A total of 107 unique radiomic features were extracted. This study includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. With the dilated hyperspectral images, the shape feature of least axis length was able to predict the tumor aggressiveness with a high accuracy. The HSI-based radiomic method may provide a useful tool to aid oncologists in determining tumors with intermediate to high risk and in clinical decision making.

Prophylactic central lymph node dissection performed selectively with cN0 papillary thyroid carcinoma according to a risk-scoring model

BACKGROUND

This study aimed to explore the risk factors of central lymph node metastasis (CLNM) in patients with clinical central lymph node-negative papillary thyroid carcinoma (PTC), and emphasize the guidance of the risk scoring model for prophylactic central lymph node dissection (pCLND) in patients with clinical lymph node-negative (cN0) PTC.

METHODS

A total of 582 patients with cN0 PTC who underwent unilateral/bilateral thyroidectomy and prophylactic central lymph node dissection (pCLND) in the Affiliated Hospital of Nantong University from January 2020 to February 2021 were retrospectively analyzed. Univariate and multivariate analyses were performed to determine the risk factors of cN0 PTC. According to the independent risk factors of patients with cN0 PTC, a risk-scoring model was established. Then, the rationality of this risk scoring model was verified by additional clinical data of 112 patients with cN0 PTC in the Affiliated Hospital of Nantong University from March 2021 to April 2021.

RESULTS

Among 582 cases of cN0 PTC, 53.6% of the patients with cN0 had CLNM. The independent risk factors for CLNM in patients with cN0 PTC included male gender, <45 years of age, tumor with a maximum diameter of ≥1.0 cm, tumor location: middle/lower poles of the thyroid gland, multifocality, and extrathyroidal extension (ETE), and some ultrasound features, such as intra-nodular vascularity, microcalcification, irregular shape, and infiltrative margin. According to independent risk factors, a 24-point risk scoring model was established to predict CLNM in patients with cN0 PTC.

CONCLUSIONS

Currently, prophylactic central neck lymph node dissection is a controversial operation, which should be selectively performed only for high-risk patients with cN0 PTC. For cN0 PTC patients with scores ≥14 and high-risk patients, even if no CLNM is found before surgery, routine prophylactic CLND is recommended. In addition, for cN0 PTC patients with a score of fewer than 14 points, it is recommended to perform fine-needle aspiration (FNA) before surgery, carefully assess the condition of the central lymph nodes, and then select the best surgical plan based on the results of the assessment.

The role of PI3K signaling pathway and its associated genes in papillary thyroid cancer

BACKGROUND

One of the well-differentiated types of thyroid cancer is papillary thyroid cancer (PTC), often developed by genetic mutations and radiation.

METHODS

In this study, the public NCBI-GEO database was systematically searched. The eligible datasets were the targets for biomarker discovery associated with PI3K signaling pathway.

RESULTS

Only two datasets were suitable and passed the inclusion criteria. The meta-analysis outcomes revealed eleven upregulation and thirteen downregulation genes differentially expressed between PTC and healthy tissues. Moreover, the outcomes for survival and disease-free rates for each gene were illustrated.

CONCLUSIONS

The present research suggests a panel signature of 24 gene biomarkers in diagnosing the PTC.

Radiomics based on multiparametric MRI for extrathyroidal extension feature prediction in papillary thyroid cancer

BACKGROUND

To determine the predictive capability of MRI-based radiomics for extrathyroidal extension detection in papillary thyroid cancer (PTC) pre-surgically.

METHODS

The present retrospective trial assessed individuals with thyroid nodules examined by multiparametric MRI and subsequently administered thyroid surgery. Diagnosis and extrathyroidal extension (ETE) feature of PTC were based on pathological assessment. The thyroid tumors underwent manual segmentation, for radiomic feature extraction. Participants were randomized to the training and testing cohorts, at a ratio of 7:3. The mRMR (maximum correlation minimum redundancy) algorithm and the least absolute shrinkage and selection operator were utilized for radiomics feature selection. Then, a radiomics predictive model was generated via a linear combination of the features. The model's performance in distinguishing the ETE feature of PTC was assessed by analyzing the receiver operating characteristic curve.

RESULTS

Totally 132 patients were assessed in this study, including 92 and 40 in the training and test cohorts, respectively). Next, the 16 top-performing features, including 4, 7 and 5 from diffusion weighted (DWI), T2-weighted (T2 WI), and contrast-enhanced T1-weighted (CE-T1WI) images, respectively, were finally retained to construct the radiomics signature. There were 8 RLM, 5 CM, 2 shape, and 1 SZM features. The radiomics prediction model achieved AUCs of 0.96 and 0.87 in the training and testing sets, respectively.

CONCLUSIONS

Our study indicated that MRI radiomics approach had the potential to stratify patients based on ETE in PTCs preoperatively.

Multiparametric Radiomics for Predicting the Aggressiveness of Papillary Thyroid Carcinoma Using Hyperspectral Images

Papillary thyroid carcinoma (PTC) is primarily treated by surgical resection. During surgery, surgeons often need intraoperative frozen analysis and pathologic consultation in order to detect PTC. In some cases pathologists cannot determine if the tumor is aggressive until the operation has been completed. In this work, we have taken tumor classification a step further by determining the tumor aggressiveness of fresh surgical specimens. We employed hyperspectral imaging (HSI) in combination with multiparametric radiomic features to complete this task. The study cohort includes 72 ex-vivo tissue specimens from 44 patients with pathology-confirmed PTC. A total of 67 features were extracted from this data. Using machine learning classification methods, we were able to achieve an AUC of 0.85. Our study shows that hyperspectral imaging and multiparametric radiomic features could aid in the pathological detection of tumor aggressiveness using fresh surgical spemens obtained during surgery.

Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma

PURPOSE

To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively.

METHODS

This prospective study enrolled consecutive patients who underwent neck MR scans and subsequent thyroidectomy during the study interval. The diagnosis and aggressiveness of PTC were determined by pathological evaluation of thyroidectomy specimens. Thyroid nodules were segmented manually on the MR images, and radiomic features were then extracted. Predictive machine learning modelling was used to evaluate the prediction of PTC aggressiveness. Area under the receiver operating characteristic curve (AUC) values for the model performance were obtained for radiomic features, clinical characteristics, and combinations of radiomic features and clinical characteristics.

RESULTS

The study cohort included 120 patients with pathology-confirmed PTC (training cohort: n = 96; testing cohort: n = 24). A total of 1393 features were extracted from T2-weighted, apparent diffusion coefficient (ADC) and contrast-enhanced T1-weighted MR images for each patient. The combination of Least Absolute Shrinkage and Selection Operator for radiomic feature selection and Gradient Boosting Classifier for classifying PTC aggressiveness achieving the AUC of 0.92. In contrast, clinical characteristics alone poorly predicted PTC aggressiveness, with an AUC of 0.56.

CONCLUSIONS

Our study showed that machine learning-based multiparametric MR imaging radiomics could accurately distinguish aggressive from non-aggressive PTC preoperatively. This approach may be helpful for informing treatment strategies and prognosis of patients with aggressive PTC.

Integrin β4 promotes invasion and anoikis resistance of papillary thyroid carcinoma and is consistently overexpressed in lymphovascular tumor thrombus

Although the majority of papillary thyroid cancers (PTC) are indolent, a subset of PTCs behaves aggressively due to extensive invasion and distant metastasis. Integrin β4, a member of the integrin family, has been shown to enhance the progression in some malignancies; however, its role in PTC remains unclear. Here, we demonstrated that β4 overexpression was associated with extrathyroid extension, lymph node metastasis, high TNM stage, and poor overall survival based on The Cancer Genome Atlas cohort. Immunohistochemistry showed that β4 expression was significantly upregulated in the tumors with infiltrating growth pattern, as well as those with positive lymphovascular invasion. Moreover, β4 was invariably overexpressed in the lymphovascular tumor thrombi, which has not been reported before. After shRNA-induced knockdown of β4 in vitro, the migration, invasion and scratch repair ability of the tumor cells were significantly reduced. Furthermore, β4 reduction decreased anchorage-independent growth and increased anoikis. The bioinformatics analysis revealed that approximately 70 pathways were significantly dysregulated in the high β4 expression group. The MAPK pathway and propanoate metabolism were located in the network center of those pathways. Taken together, our results suggest that β4 could promote the tumor's aggressiveness by enhancing invasion and antagonizing anoikis. The upregulated expression of β4 in the tumor thrombi is intrinsically linked to its role in strengthening the anoikis resistance.