Sonographic Features Differentiating Follicular Thyroid Cancer from Follicular Adenoma-A Meta-Analysis

A bibliometric analysis of follicular thyroid carcinoma: Current situation, hot spots, and global trends

BACKGROUND

Follicular thyroid carcinoma (FTC), the second most prevalent thyroid cancer after papillary thyroid cancer (PTC), tends to metastasize distantly, leading to poorer outcomes. Despite substantial research, a holistic bibliometric analysis of FTC literature is lacking. This study aims to fill this gap by employing bibliometric methods to track FTC research evolution.

METHODS

English FTC publications were systematically gathered from the Web of Science. Bibliometric analysis, using R, VOSviewer, CiteSpace, and Excel, synthesized data and explored global research trends and topics.

RESULTS

From 2000 to 2023, 9086 authors from 1953 institutions across 75 countries contributed to 1776 papers in 491 academic journals on FTC. The last two decades have witnessed a steady increase in publications related to FTC, with the United States leading in terms of publication volume. The United States dominated both in publications and citations, with the National Cancer Institute and Sheue-Yann Cheng as leading contributors. The journal 'Thyroid' featured the most publications, while the 'Journal of Clinical Endocrinology and Metabolism' ranked highest in citation frequency. Research focused on gene expression analysis and preoperative diagnostics, with recent trends shifting toward prognosis management and machine learning due to advances in medical technology and increased health awareness.

CONCLUSION

This comprehensive bibliometric analysis has mapped the landscape of FTC research, highlighting key contributors, institutions, and thematic trends. Current discourse predominantly revolves around genetic analysis, prognostic determinants, and preoperative diagnostics in FTC. This foundational work guides future FTC research, providing insights into its evolution.

Role of Ultrasound and Ultrasound-Based Prediction Model in Differentiating Follicular Thyroid Carcinoma From Follicular Thyroid Adenoma

OBJECTIVES

This study aims to identify distinct ultrasound (US) characteristics for distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA), and construct a user-friendly preoperative risk stratification model for thyroid follicular neoplasms.

METHODS

In this retrospective study, patients diagnosed with pathologically confirmed FTA or FTC and undergoing US examinations between July 2017 and June 2021 were designated as the training cohort, and those from July 2021 to June 2023 were enrolled as the external validation set. We systematically assessed and compared the sonographic and clinical characteristics of FTC and FTA. Univariable and multivariable logistic regression analyses were used to assess the association of US features with FTC in the training set. A prediction nomogram model, incorporating US features independently associated with FTC, was developed and validated externally to assess its performance.

RESULTS

A total of 645 patients (FTA/FTC = 530/115) were included in the training set, while 197 patients (FTA/FTC = 165/32) constituted the validation set. In the training set, solid composition, hypo-echogenicity, irregular margin, calcification, protrusion sign, trabecular formation, absent or thick halo, and mainly central hypervascularity were identified as independent factors associated with FTC. The prediction nomogram model constructed using these variables showed good performance in differentiating FTC from FTA with an area under the curve of 0.948 in the training set and 0.915 in the validation set.

CONCLUSIONS

The preoperative nomogram model constructed based on US features serves as an effective tool for the risk stratification of thyroid follicular neoplasms.

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate

BACKGROUND

To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.

METHODS

A retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions.

RESULTS

Among the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2-87.5, P < 0.001; OR = 38.0, 95% CI = 20.4-70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861-0.909), 0.945 (95% CI: 0.926-0.961), 0.947 (95% CI: 0.928-0.962), 0.945 (95% CI: 0.926-0.961) and 0.951 (95% CI: 0.932-0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%.

CONCLUSIONS

MRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.

Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI

The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups. Employing univariate and multivariate logistic regression, we identified independent predictors of FTN and MFTN, and subsequently develop a nomogram for FTN and a risk score system (RSS) for MFTN prediction. We assessed performance of nomogram through its discrimination, calibration, and clinical utility. The diagnostic performance of the RSS for MFTN was further compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS). The nomogram, integrating independent predictors, demonstrated robust discrimination and calibration in differentiating FTN from non-FTN in both training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Key risk factors for differentiating MFTN from BFTN included tumor size, restricted diffusion, and cystic degeneration. The AUC of the RSS for MFTN prediction was 0.902 (95% CI 0.798-0.971), outperforming five TIRADS with a sensitivity of 73.3%, specificity of 95.1%, accuracy of 92.4%, and positive and negative predictive values of 68.8% and 96.1%, respectively, at the optimal cutoff. MRI-based models demonstrate excellent diagnostic performance for preoperative predicting of FTN and MFTN, potentially guiding clinicians in optimizing therapeutic decision-making.

Correlation of pN Stage and Hypoechogenicity with Tumour Encapsulation and Vascular Invasion in Thyroid Cancer (TC): A Comprehensive Analysis and Clinical Outcomes

In this retrospective study, the relationship between the pN stage of TC and the ultrasound hypoechogenicity of tumour encapsulation and vascular invasion was investigated. The data of a total of 678 TC patients were analysed. The goal of this study was to assess the significance of the pTNM score and preoperative ultrasound features in predicting cancer prognosis and guiding therapeutic decisions in patients with TC. The main research methods included a retrospective analysis of patient data, mainly the pTNM score and presence of tumour encapsulation and vascular invasion obtained from histopathological results and preoperative ultrasound imaging. Patients with well-differentiated TCs (papillary and follicular) were extracted from TC patients to better unify the results because of similar clinical strategies for these TCs. Significant associations were observed between advanced pN stage and the presence of encapsulation and vessel invasion. The majority of pN1a patients exhibited encapsulation (77.71%; p < 0.0001) and vascular invasion (75.30%; p < 0.0001), as did the majority of pN1b patients (100%; p < 0.0001 and 100%; p < 0.0001, respectively). Less than half of the patients with hypoeghogenic patterns presented with encapsulation (43.30%; p < 0.0001) and vascular invasion (43.52%; p < 0.0001), while the vast majority of patients without hypoechogenicity did not present with encapsulation (90.97%; p < 0.0001) or vascular invasion (90.97%; p < 0.0001). Hypoechogenicity was found to be indicative of aggressive tumour behaviour. The results of this study underscore the importance of accurate N staging in TC and suggests the potential use of ultrasound features in predicting tumour behaviour. Further research is needed to confirm these findings and explore additional prognostic markers to streamline TC management strategies and improve patient outcomes.

US Risk Stratification System for Follicular Thyroid Neoplasms

Background Preoperative assessment of follicular thyroid neoplasms is challenging using the current US risk stratification systems (RSSs) that are applicable to papillary thyroid neoplasms. Purpose To develop a US feature-based RSS for differentiating between follicular thyroid adenoma (FTA) and follicular thyroid carcinoma (FTC) in biopsy-proven follicular neoplasm and compare it with existing RSSs. Materials and Methods This retrospective multicenter study included consecutive adult patients who underwent conventional US and received a final diagnosis of follicular thyroid neoplasm from seven centers between January 2018 and December 2022. US images from a pretraining data set were used to improve readers' understanding of the US characteristics of the FTC and FTA. Univariable and multivariable logistic regression analyses were used to assess the association of qualitative US features with FTC in a training data set. Features with P < .05 were used to construct a prediction model (follicular tumor model, referred to as F model) and RSS for follicular neoplasms using the Thyroid Imaging Reporting and Data System (TI-RADS). Area under the receiver operating characteristic curve (AUC) was compared between follicular TI-RADS (hereafter, F-TI-RADS) and existing RSS (American College of Radiology [ACR] TI-RADS, Korean Society of Thyroid Radiology and Korean Society of Radiology TI-RADS [hereafter, referred to as K-TI-RADS], and Chinese TI-RADS [hereafter, referred to as C-TI-RADS]) in a validation data set. Results The pretraining, training, and validation data sets included 30 (mean age, 47.6 years ± 16.0 [SD]; 16 male patients; FTCs, 30 of 60 [50.0%]), 703 (mean age, 47.9 years ± 14.5; 530 female patients; FTCs, 188 of 703 [26.7%]), and 155 (mean age, 49.9 years ± 13.3 [SD]; 155 female patients; FTCs, 43 of 155 [27.7%]) patients. In the validation data set, the F-TI-RADS showed improved performance for differentiating between FTA and FTC (AUC, 0.81; 95% CI: 0.71, 0.86) compared with ACR TI-RADS (AUC, 0.74; 95% CI: 0.66, 0.80; P = .02), K-TI-RADS (AUC, 0.69; 95% CI: 0.61, 0.76; P = .002), and C-TI-RADS (AUC, 0.68; 95% CI: 0.60, 0.75; P = .002). Conclusion F-TI-RADS outperformed existing RSSs for differentiating between FTC and FTA. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Baumgarten in this issue.

Ultrasound characteristics of follicular and parafollicular thyroid neoplasms: diagnostic performance of artificial neural network

BACKGROUND

Ultrasound is the first-line imaging modality for detection and classification of thyroid nodules. Certain features observable by ultrasound have recently been equated with potential malignancy. This retrospective cohort study was conducted to test the hypothesis that radiomics of the four categorical divisions (medullary [MTC], papillary [PTC], or follicular [FTC] carcinoma and follicular thyroid adenoma [FTA]) demonstrate distinctive sonographic characteristics. Using an artificial neural network model for proof of concept, these sonographic features served as input.

METHODS

A total of 148 patients were enrolled for study, all with confirmed thyroid pathology in one of the four named categories. Preoperative ultrasound profiles were obtained via standardized protocols. The neural network consisted of seven input neurons; three hidden layers with 50, 250, and 100 neurons, respectively; and one output layer.

RESULTS

Radiomics of contour, structure, and calcifications differed significantly according to nodule type (p = 0.025, p = 0.032, and p = 0.0002, respectively). Levels of accuracy shown by artificial neural network analysis in discriminating among categories ranged from 0.59 to 0.98 (95% confidence interval [CI]: 0.57-0.99), with positive and negative predictive ranges of 0.41-0.99 and 0.78-0.97, respectively.

CONCLUSIONS

Our data indicate that some MTCs, PTCs, FTCs, and FTAs have distinctive sonographic characteristics. However, a significant overlap of these characteristics may impede an explicit classification. Further prospective investigations involving larger patient and nodule numbers and multicenter access should be pursued to determine if neural networks of this sort are beneficial, helping to classify neoplasms of the thyroid gland.

Design and analysis of high-sensitivity tunable graphene sensors for cancer detection

A new metamaterial refractive index sensor based on the impedance matching idea is suggested to provide an ultra-narrowband absorption response at terahertz frequencies. In order to accomplish this, the graphene layer has been modeled as circuit components using the recently developed transmission line method and the recently proposed circuit model of Periodic Arrays of Graphene Disks. The given research gives a flowchart and equations for designing a sensor, greatly simplifying the sensor design approach. This study only explores Periodic Arrays of Graphene Disks but we think the offered technique is extensible to any available graphene forms that past designers supplied with a circuit model. We compare and contrast the full-wave simulation results with the suggested circuit model. The metallic ground prohibited the transmission of the episode wave, and all occurrence electromagnetic waves are restricted in the basic design between the graphene disk. As a consequence, a perfect narrowband absorption peak is obtained. Disk absorption spectra have been discovered for a variety of refractive lists. The findings of the circuit model and full-wave simulations appear to be balanced. This RI sensor is suitable for biomedical sensing because of the combination of its features. The proposed sensor's performance as a cancer early detection sensor was evaluated among biomedical sensors, and the findings indicated that the proposed sensor is an excellent candidate for this application.

Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma-A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study

Pre- and postsurgical differentiation between follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC) represents a significant diagnostic challenge. Furthermore, it remains unclear whether they share a common or distinct background and what the mechanisms underlying follicular thyroid lesions malignancy are. The study aimed to compare FTA and FTC by the comprehensive microarray and to identify recurrent regions of loss of heterozygosity (LOH). We analyzed formalin-fixed paraffin-embedded (FFPE) samples acquired from 32 Caucasian patients diagnosed with FTA (16) and FTC (16). We used the OncoScan™ microarray assay (Affymetrix, USA), using highly multiplexed molecular inversion probes for single nucleotide polymorphism (SNP). The total number of LOH was higher in FTC compared with FTA (18 vs. 15). The most common LOH present in 21 cases, in both FTA (10 cases) and FTC (11 cases), was 16p12.1, which encompasses many cancer-related genes, such as TP53, and was followed by 3p21.31. The only LOH present exclusively in FTA patients (56% vs. 0%) was 11p11.2-p11.12. The alteration which tended to be detected more often in FTC (6 vs. 1 in FTA) was 12q24.11-q24.13 overlapping FOXN4, MYL2, PTPN11 genes. FTA and FTC may share a common genetic background, even though differentiating rearrangements may also be detected.

Virtual touch tissue imaging for differential diagnosis in ACR TI-RADS category 3-4 thyroid nodules: Conservative and aggressive methods

PURPOSE

Many Thyroid Imaging Reporting and Data System (TI-RADS) category 3-4 nodules are benign. Our study aimed to add virtual touch tissue imaging (VTI) to TI-RADS using two methods, namely conservative and aggressive, and to explore which method had better diagnostic performance and which method avoided more unnecessary biopsies.

METHODS

From January 2016 to December 2021, we included 121 thyroid nodules classified as TI-RADS category 3-4 in 115 consecutive patients in this retrospective study. This study used the reference standard for pathological diagnosis by surgical resection or biopsy. The diagnostic performance of the different methods was evaluated and compared by receiver operating characteristic (ROC) and area under the ROC curve (AUC).

RESULTS

In this study, the aggressive approach had the best diagnostic performance among TI-RADS alone, the conservative approach, and the aggressive approach (AUC: 0.863 versus 0.598, P = 0.0007; 0.863 versus 0.755, P = 0.0067). When we used an aggressive approach, 75.44% (43/57) of the 57 false-positive nodes diagnosed by TI-RADS were appropriately downgraded from TI-RADS category 4 to category 3, avoiding unnecessary biopsies.

CONCLUSION

VTI improves the diagnostic performance of TI-RADS. The aggressive approach of combining the TI-RADS with VTI would help reduce unnecessary biopsies.

Cancer Diagnosis Using Terahertz-Graphene-Metasurface-Based Biosensor with Dual-Resonance Response

Owing to the outstanding physical properties of graphene, its biosensing applications implemented by the terahertz metasurface are widely concerned and studied. Here, we present a novel design of the graphene metasurface, which consists of an individual graphene ring and an H-shaped graphene structure. The graphene metasurface exhibits a dual-resonance response, whose resonance frequency strongly varies with the geometrical parameters of the proposed metasurface, the carrier density of graphene, and the analyte composition. The transparency window, including width and position, can be artificially controlled by adjusting the geometrical parameters or the Fermi energy. Furthermore, the sensing parameters of the graphene metasurface for cancerous and normal cells are investigated, focusing on two factors, namely cell quantity and position on the metasurface. The simulated results clearly show that the theoretical sensitivity, figure of merit, and quantity of the graphene metasurface for breast cells reach 1.21 THz/RIU, 2.75 RIU-1, and 2.43, respectively. Our findings may open up new avenues for promising applications in the diagnosis of cancers.

Performance of current ultrasound-based malignancy risk stratification systems for thyroid nodules in patients with follicular neoplasms

OBJECTIVES

To investigate the ability of the currently used ultrasound-based malignancy risk stratification systems for thyroid neoplasms (ATA, AACE/ACE/AME, K-TIRADS, EU-TIRADS, ACR-TIRADS and C-TIRADS) in distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA). Additionally, we evaluated the ability of these systems in correctly determining the indication for biopsy.

METHODS

Three hundred twenty-nine follicular neoplasms with definitive postoperative histopathology were included. The nodules were categorized according to each of six stratification systems, based on ultrasound findings. We dichotomized nodules into the positive predictive group of FTC (high and intermediate risk) and negative group of FTC based on the classification results. Missed biopsy was defined as neoplasms that were diagnosed as FTCs but for which biopsy was not indicated based on lesion classification. Unnecessary biopsy was defined as neoplasms that were diagnosed as FTAs but for whom biopsy was considered indicated based on classification. The diagnostic performance and missed and unnecessary biopsy rates were evaluated for each stratification system.

RESULTS

The area under the curve of each system for distinguishing follicular neoplasms was < 0.700 (range, 0.511-0.611). The missed biopsy rates were 9.0-22.4%. The missed biopsy rates for lesions ≤ 4 cm and lesions sized 2-4 cm were 16.2-35.1% and 0-20.0%, respectively. Unnecessary biopsy rates were 65.3-93.1%. In ≤ 4 cm group, the unnecessary biopsy rates were 62.2-89.7%.

CONCLUSION

The malignancy risk stratification systems can select appropriate nodules for biopsy in follicular neoplasms, while they have limitations in distinguishing follicular neoplasms and reducing unnecessary biopsy. Specific stratification systems and recommendations should be established for follicular neoplasms.

KEY POINTS

• Current ultrasound-based malignancy risk stratification systems of thyroid nodules had low efficiency in the characterization of follicular neoplasms. • The adopted stratification systems showed acceptable performance for selecting FTC for biopsy but unsatisfactory performance for reducing unnecessary biopsy.

Value of Contrast-Enhanced Ultrasound in Adjusting the Classification of Chinese-TIRADS 4 Nodules

OBJECTIVES

To explore the value of applying contrast-enhanced ultrasound (CEUS) in adjusting the classification of category 4 nodules in the Chinese-Thyroid Imaging Report and Data System (C-TIRADS).

METHODS

The data of preoperative conventional ultrasound and CEUS examinations of 125 C-TIRADS 4 nodules in 109 patients were retrospectively analyzed. We divided the thyroid nodules into two groups based on whether recommend by the guide fine-needle aspiration (FNA). Group I included C-TIRADS 4A nodules with a maximum diameter ≤15 mm and C-TIRADS 4B and 4C nodules with a maximum diameter ≤10 mm, and Group II included C-TIRADS 4A nodules with a maximum diameter >15 mm and C-TIRADS 4B and 4C nodules with a maximum diameter >10 mm. In CEUS, thyroid nodules showing suspicious malignant features such as hypoenhancement or early washout were adjusted to a level higher in the C-TIRADS classification; thyroid nodules showing possible benign features such as iso- or hyperenhancement were adjusted to a level lower; and thyroid nodules showing no enhancement were adjusted to C-TIRADS 3. Taking the pathological results as the gold standard, the receiver operating characteristic (ROC) curves of the C-TIRADS classification before and after the adjustment based on CEUS were plotted, and the diagnostic efficiency was compared.

RESULTS

The sensitivity, specificity, accuracy, and positive and negative predictive values of the C-TIRADS classification for the diagnosis of thyroid nodule malignancy before the adjustment based on the CEUS results were 83.6%, 63.8%, 74.4%, 72.7%, and 77.1%, respectively, and these values were 91.0%, 82.8%, 87.2%, 85.9%, and 88.9%, respectively, after the adjustment. The area under the ROC curve (AUC) was 0.737 and 0.869, respectively, showing a significant difference (Z = 3.288, P=0.001). The diagnostic efficiency of C-TIRADS classification after the adjustment based on the CEUS results in both groups was improved compared with the result before the adjustment, and the difference in Group II was significant (Z = 2.931, P=0.003).

CONCLUSIONS

CEUS significantly improved the diagnostic performance in the adjustment of C-TIRADS 4 nodule classification, especially for the nodules which needs FNA recommended by the C-TIRADS.

The Value of Sonography in Distinguishing Follicular Thyroid Carcinoma from Adenoma

Purpose

Differentiation between follicular thyroid carcinomas (FTCs) and follicular thyroid adenomas (FTAs) is difficult and the sonographic features of FTC are not yet fully established. The purpose of this study is to explore the sonographic features of FTC and the value of sonography in differentiating FTCs from FTAs.

Patients and Methods

A total of 28 pathologically proven FTCs and 53 FTAs in 78 patients who were performed thyroid surgery were included in this retrospective study. The sonographic features of each tumor including an interrupted halo, satellite nodule(s) with or without halo ring, local irregularity of margin and cluster of grapes sign were evaluated. A mode image of FTC halo was built up in our study. The frequencies of the sonographic features were compared by chi-square test or Fisher exact test between FTCs and FTAs. The relative risk of malignancy was assessed by logistic regression analysis.

Results

Logistic regression analysis showed that a thick, irregular and/or interrupted halo with or without satellite nodule(s), hypoechoic or marked hypoechoic echogenicity, a predominantly solid pattern, cluster of grapes sign, micro-or macro-calcifications, rim calcifications correlated with significant increases in relative risk for FTCs (odds ratio 11.48 (1.37-96.56), 6.74 (1.05-43.30), 17.51 (1.78-172.53), 9.55 (1.44-63.46), 9.36 (1.25-70.15) and 17.45 (1.04-292.65), respectively, p<0.05). Two new sonographic features, an interrupted halo and satellite nodule(s) with or without halo ring, can only be found in FTCs.

Conclusion

An interrupted halo and satellite nodule(s) with or without halo ring are specific sonographic features for FTCs. Sonography could play a role in differentiating follicular thyroid carcinoma from adenoma.