Update in thyroid fine needle aspiration

Artificial intelligence defines protein-based classification of thyroid nodules

Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy; FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.

Needle tract seeding of papillary thyroid carcinoma after fine-needle capillary biopsy: A case report

BACKGROUND

Fine-needle biopsy is an accurate and cost-efficient tool for the assessment of thyroid nodules. It includes two primary methods: Fine-needle capillary biopsy (FNCB) and fine-needle aspiration biopsy. Needle tract seeding (NTS) is a rare complication of thyroid fine-needle biopsy mainly caused by fine-needle aspiration biopsy rather than FNCB. Here, we present an extremely rare case of a papillary thyroid carcinoma (PTC) patient with FNCB-derived NTS.

CASE SUMMARY

We report a 32-year-old woman with PTC who showed subcutaneous NTS 1 year after FNCB and thyroidectomy. NTS was diagnosed based on clinical manifestations, biochemistry indices, and imaging (computed tomography and ultrasound). Pathological identification of PTC metastases consistent with the puncture path is the gold standard for diagnosis. Surgical resection was the main method used to treat the disease. After surgery, thyroid function tests and ultrasound scans were performed every 3-6 mo. To date, no evidence of tumor recurrence has been observed.

CONCLUSION

FNCB is a safe procedure as NTS is rare, and can be easily removed surgically with no recurrence. Accordingly, NTS should not limit the usefulness of FNCB.

Impact of a genomic classifier on indeterminate thyroid nodules: an institutional experience

INTRODUCTION

Indeterminate thyroid cytology (ITC) occurs in 20% to 25% of cases, and the associated risk of malignancy ranges from 5% to 30%. The genomic classifier ThyroSeq (CBLPath/UPMC, Rye Brook, NY), a targeted next-generation sequencing technology, could classify ITC nodules as malignant and nonmalignant. We sought to characterize our institutional experience with ThyroSeq testing.

MATERIALS AND METHODS

We retrospectively identified all patients seen from January 2015 through November 2019 who had ITC nodules analyzed with ThyroSeq. Relevant clinical, pathologic, and resection data were reviewed.

RESULTS

Of the 133 cases identified, diagnostic categories included atypia (or follicular lesion) of undetermined significance) (n = 65 [48.9%]), suspicious for follicular neoplasm (SFN) (n = 48 [36.1%]), and suspicious for Hürthle cell neoplasm (n = 20 [15.0%]). About half of the papillary thyroid carcinoma (PTC) cases (n = 9 [56.3%]) and more than one-third of the noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) cases (n = 3/8 [37.5%]) were classified as SFN. Most patients (n = 87 [65.4%]) did not undergo resection; of these, 73 (83.9%) were negative for all molecular alterations. Of the 54 cases with molecular alterations, isolated RAS or RAS-like variants were most common (n = 35 [64.8%]); 9 (25.7%) were identified in PTC and 8 (22.9%) in NIFTP. NRAS was the most common alteration (n = 20 [37.0%]), followed by HRAS (n = 6 [11.1%]), which was mostly detected in NIFTP cases (n = 4 of 6 [66.7%]).

CONCLUSION

Resection was avoided in 73 patients (54.9%) because of negative ThyroSeq results. ThyroSeq v2 and v3 offered a more accurate categorization of ITC nodules, improved patient management, and reduced unnecessary surgical procedures.

The diagnosis of primary thyroid lymphoma by fine-needle aspiration, cell block, and immunohistochemistry technique

AIM

Primary thyroid lymphoma (PTL) is a rare malignant disease. Its prognosis depends on early diagnosis. The role of fine-needle aspiration (FNA), including smear cytology, cell block (CB) techniques, and immunohistochemistry (IHC) sections in the diagnosis of PTL is still unclear. Here we reported 19 cases of PTL and literature review to evaluate the diagnostic accuracy for lymphoma by cytology.

METHODS

Our study retrospectively reviewed 19 patients diagnosed with PTL at the affiliated hospital of Southwest Medical University in China from June 2011 to May 2019. According to the Bethesda system for reporting thyroid cytopathology, the CB sections were evaluated for the presence of single tumor cells. IHC was performed on CB.

RESULTS

The diagnostic accuracy for PTL of FNA, CB with smears, and the joint application of the three methods (FNA + CB + IHC) of our study with 19 cases was 68.4% (13/19), 83.3% (15/18), and 100% (17/17), respectively.

CONCLUSION

The present study demonstrates that FNA has low sensitivity in diagnosing PTL, but the joint application of FNA, CB, and IHC might provide high diagnostic accuracy for lymphoma and should be applied in all cases where the clinical suspicion is high regardless of the FNA findings.

A Thyroid Genetic Classifier Correctly Predicts Benign Nodules with Indeterminate Cytology: Two Independent, Multicenter, Prospective Validation Trials

Background: Although most thyroid nodules with indeterminate cytology are benign, in most of the world, surgery remains as the most frequent diagnostic approach. We have previously reported a 10-gene thyroid genetic classifier, which accurately predicts benign thyroid nodules. The assay is a prototype diagnostic kit suitable for reference laboratory testing and could potentially avoid unnecessary diagnostic surgery in patients with indeterminate thyroid cytology. Methods: Classifier performance was tested in two independent, ethnically diverse, prospective multicenter trials (TGCT-1/Chile and TGCT-2/USA). A total of 4061 fine-needle aspirations were collected from 15 institutions, of which 897 (22%) were called indeterminate. The clinical site was blind to the classifier score and the clinical laboratory blind to the pathology report. A matched surgical pathology and valid classifier score was available for 270 samples. Results: Cohorts showed significant differences, including (i) clinical site patient source (academic, 43% and 97% for TGCT-1 and -2, respectively); (ii) ethnic diversity, with a greater proportion of the Hispanic population (40% vs. 3%) for TGCT-1 and a greater proportion of African American (11% vs. 0%) and Asian (10% vs. 1%) populations for TGCT-2; and (iii) tumor size (mean of 1.7 and 2.5 cm for TGCT-1 and -2, respectively). Overall, there were no differences in the histopathological profile between cohorts. Forty-one of 155 and 45 of 115 nodules were malignant (cancer prevalence of 26% and 39% for TGCT-1 and -2, respectively). The classifier predicted 37 of 41 and 41 of 45 malignant nodules, yielding a sensitivity of 90% [95% confidence interval; CI 77-97] and 91% [95% CI 79-98] for TGCT-1 and -2, respectively. One hundred one of 114 and 61 of 70 nodules were correctly predicted as benign, yielding a specificity of 89% [95% CI 82-94] and 87% [95% CI 77-94], respectively. The negative predictive values for TGCT-1 and TGCT-2 were 96% and 94%, respectively, whereas the positive predictive values were 74% and 82%, respectively. The overall accuracy for both cohorts was 89%. Conclusions: Clinical validation of the classifier demonstrates equivalent performance in two independent and ethnically diverse cohorts, accurately predicting benign thyroid nodules that can undergo surveillance as an alternative to diagnostic surgery.

Development and validation of an individualized diagnostic signature in thyroid cancer

New molecular signatures are needed to improve the diagnosis of thyroid cancer (TC) and avoid unnecessary surgeries. In this study, we aimed to develop a robust and individualized diagnostic signature in TC. Gene expression profiles of tumor and nontumor samples were from 13 microarray datasets of Gene Expression Omnibus (GEO) database and one RNA‐sequencing dataset of The Cancer Genome Atlas (TCGA). A total of 1246 samples were divided into a training set (N = 435), a test set (N = 247), and one independent validation set (N = 564). In the training set, 115 most frequent differentially expressed genes (DEGs) among the included datasets were used to construct 6555 gene pairs, and 19 significant pairs were detected to further construct the diagnostic signature by a penalized generalized linear model. The signature showed a good diagnostic ability for TC in the training set (area under receiver operating characteristic curve (AUC) = 0.976), test set (AUC = 0.960), and TCGA dataset (AUC = 0.979). Subgroup analyses showed consistent results when considering the type of nontumor samples and microarray platforms. When compared with two existing molecular signatures in the diagnosis of thyroid nodules, the signature (AUC = 0.933) also showed a higher diagnostic ability (AUC = 0.886 for a 7‐gene signature and AUC = 0.892 for a 10‐gene signature). In conclusion, our study developed and validated an individualized diagnostic signature in TC. Large‐scale prospective studies were needed to further validate its diagnostic ability.

Genetic testing for indeterminate thyroid cytology: review and meta-analysis

Thyroid cancer is the most frequent endocrine malignancy, and its incidence is increasing. A current limitation of cytological evaluation of thyroid nodules is that 20-25% are reported as indeterminate. Therefore, an important challenge for clinicians is to determine whether an indeterminate nodule is malignant, and should undergo surgery, or benign, and should be recommended to follow-up. The emergence of precision medicine has offered a valuable solution for this problem, with four tests currently available for the molecular diagnosis of indeterminate cytologies. However, efforts to critically analyze the quality of the accumulated evidence are scarce. This systematic review and meta-analysis is aimed to contribute to a better knowledge about the four available molecular tests, their technical characteristics, clinical performance, and ultimately to help clinicians to make better decisions to provide the best care options possible. For this purpose, we address three critical topics: (i) the proper theoretical accuracy, considering the intended clinical use of the test (rule-in vs rule-out) and the impact on clinical decisions; (ii) the quality of the evidence reported for each test (iii) and how accurate and effective have the tests proved to be after their clinical use. Together with the upcoming evidence, this work provides significant and useful information for healthcare system decision-makers to consider the use of molecular testing as a public health need, avoiding unnecessary surgical risks and costs.

A 10-Gene Classifier for Indeterminate Thyroid Nodules: Development and Multicenter Accuracy Study

BACKGROUND

In most of the world, diagnostic surgery remains the most frequent approach for indeterminate thyroid cytology. Although several molecular tests are available for testing in centralized commercial laboratories in the United States, there are no available kits for local laboratory testing. The aim of this study was to develop a prototype in vitro diagnostic (IVD) gene classifier for the further characterization of nodules with an indeterminate thyroid cytology.

METHODS

In a first stage, the expression of 18 genes was determined by quantitative polymerase chain reaction (qPCR) in a broad histopathological spectrum of 114 fresh-tissue biopsies. Expression data were used to train several classifiers by supervised machine learning approaches. Classifiers were tested in an independent set of 139 samples. In a second stage, the best classifier was chosen as a model to develop a multiplexed-qPCR IVD prototype assay, which was tested in a prospective multicenter cohort of fine-needle aspiration biopsies.

RESULTS

In tissue biopsies, the best classifier, using only 10 genes, reached an optimal and consistent performance in the ninefold cross-validated testing set (sensitivity 93% and specificity 81%). In the multicenter cohort of fine-needle aspiration biopsy samples, the 10-gene signature, built into a multiplexed-qPCR IVD prototype, showed an area under the curve of 0.97, a positive predictive value of 78%, and a negative predictive value of 98%. By Bayes' theorem, the IVD prototype is expected to achieve a positive predictive value of 64-82% and a negative predictive value of 97-99% in patients with a cancer prevalence range of 20-40%.

CONCLUSIONS

A new multiplexed-qPCR IVD prototype is reported that accurately classifies thyroid nodules and may provide a future solution suitable for local reference laboratory testing.

Avoidance of unnecessary fine-needle aspiration with the use of the Thyroid Imaging Reporting Data System classification and strain elastography based on The Bethesda System for Reporting Thyroid Cytopathology

Thyroid fine-needle aspiration (FNA) biopsy has been widely accepted as an accurate and cost-effective tool in the management of thyroid nodules. To avoid unnecessary FNAs and provide appropriate management, patient evaluation should be based on a multidisciplinary approach. For this purpose, the Thyroid Imaging Reporting and Data System (TI-RADS) and strain elastography (SE) were proposed as tools for the risk assessment of malignancy in thyroid nodules. The aim of the present study was to analyze the utility of TI-RADS system and SE, along with FNA, and prospectively evaluate 369 consecutive patients referred for FNA of a thyroid nodule. TI-RADS was tested against The Bethesda System for Reporting Thyroid Cytopathology to determine whether there was an agreement between the two classification systems; statistically, some agreement was observed. Medians of the maximum SE values (E-max) were obtained for benign and malignant FNA results and found to be 1.97 [interquartile range (IQR): 1.87] and 2.8 (IQR: 3.42), respectively (P=0.004). The number of studies investigating the utility of TI-RADS and SE along with TBSRCT is currently limited. Our study demonstrated that a multidisciplinary approach with the use of TI-RADS and SE may mildly improve the management of thyroid nodules.

Diagnostic value of BRAF (V600E)-mutation analysis in fine-needle aspiration of thyroid nodules: a meta-analysis

Fine-needle aspiration (FNA) is a reliable method for preoperative diagnosis of thyroid nodules; however, about 10%–40% nodules are classified as indeterminate. The BRAF^V600E mutation is the most promising marker for thyroid FNA. This meta-analysis was conducted to investigate the diagnostic value of BRAF^V600E analysis in thyroid FNA, especially the indeterminate cases. Systematic searches were performed in PubMed, Web of Science, Scopus, Ovid, Elsevier, and the Cochrane Library databases for relevant studies prior to June 2015, and a total of 88 studies were ultimately included in this meta-analysis. Compared with FNA cytology, the synergism of BRAF^V600E testing increased the diagnostic sensitivity from 81.4% to 87.4% and decreased the false-negative rate from 8% to 5.2%. In the indeterminate group, the mutation rate of BRAF^V600E was 23% and varied in different subcategories (43.2% in suspicious for malignant cells [SMC], 13.77% in atypia of undetermined significance/follicular lesion of undetermined significance [AUS/FLUS], and 4.43% in follicular neoplasm/suspicious for follicular neoplasm [FN/SFN]). The sensitivity of BRAF^V600E analysis was higher in SMC than that in AUS/FLUS and FN/SFN cases (59.4% vs 40.1% vs 19.5% respectively), while specificity was opposite (86.1% vs 99.5% vs 99.7% respectively). The areas under the summary receiver-operating characteristic curve also confirmed the diagnostic value of BRAF^V600E testing in SMC and AUS/FLUS rather than FN/SFN cases. Therefore, BRAF^V600E analysis can improve the diagnostic accuracy of thyroid FNA, especially indeterminate cases classified as SMC, and select malignancy to guide the extent of surgery.

DIAGNOSIS OF ENDOCRINE DISEASE: High-yield thyroid fine-needle aspiration cytology: an update focused on ancillary techniques improving its accuracy

Thyroid fine-needle aspiration (FNA) cytology is a fast growing field. One of the most developing areas is represented by molecular tests applied to cytological material. Patients that could benefit the most from these tests are those that have been diagnosed as 'indeterminate' on FNA. They could be better stratified in terms of malignancy risk and thus oriented with more confidence to the appropriate management. Taking in to consideration the need to improve and keep high the yield of thyroid FNA, professionals from various fields (i.e. molecular biologists, endocrinologists, nuclear medicine physicians and radiologists) are refining and fine-tuning their diagnostic instruments. In particular, all these developments aim at increasing the negative predictive value of FNA to improve the selection of patients for diagnostic surgery. These advances involve terminology, the application of next-generation sequencing to thyroid FNA, the use of immunocyto- and histo-chemistry, the development of new sampling techniques and the increasing use of nuclear medicine as well as molecular imaging in the management of patients with a thyroid nodule. Herein, we review the recent advances in thyroid FNA cytology that could be of interest to the 'thyroid-care' community, with particular focus on the indeterminate diagnostic category.

Value of immunohistochemistry in the detection of BRAF(V600E) mutations in fine-needle aspiration biopsies of papillary thyroid carcinoma

BACKGROUND

Fine-needle aspiration biopsy (FNAB) is important in the diagnostic establishment of suspicious thyroid nodules. In thyroid neoplasms, mutation of the BRAF gene occurs rather exclusively in papillary thyroid carcinoma (PTC) and results in>98% of the cases in V600E amino acid substitution. In the current study, the authors investigated the diagnostic value of a recently described monoclonal antibody that detects this specific mutation on FNAB specimens from patients with PTC.

METHODS

BRAF(V600E) status of FNAB cell blocks from 55 patients with PTC was analyzed by immunohistochemistry (IHC) with the new BRAF(V600E) antibody (clone VE1) and by Sanger sequencing (SaS). In discrepant cases, ultra-deep sequencing was also performed. Available corresponding histological specimens were investigated by IHC and, in selected cases, with SaS as well.

RESULTS

All cases yielded evaluable IHC staining results of the cell block sections with good interobserver agreement (kappa value, 0.650). Ten tumors (18.2%) demonstrated no staining, 10 tumors (18.2%) demonstrated equivocal staining, 25 tumors (45.4%) demonstrated moderate staining, and 10 tumors (18.2%) demonstrated strong staining. SaS was able to be performed in 48 cases. Nineteen cases demonstrated wild-type BRAF and 29 cases were found to have the BRAF(V600E) mutation. After performing ultra-deep sequencing 1 false-positive and 2 false-negative VE1 IHC cases remained, resulting in a sensitivity of 93.8% and a specificity of 93.8%.

CONCLUSIONS

BRAF(V600E) mutations in FNAB specimens from patients with PTC can be reliably detected in most cases by IHC with a new mutation-specific antibody. Interpretation of VE1 IHC staining results on cell block slides of PTC can be difficult in some cases.

A simplified economic approach to thyroid FNA cytology and surgical intervention in thyroid nodules

Objective

Few studies have modelled the economics of thyroid FNA.

Methods

A simple spreadsheet economic model for delivery of thyroid fine needle aspiration (FNA) cytology is described using the UK Royal College of Pathologists’ Classification for thyroid FNA which is based on The Bethesda System for Reporting Thyroid Cytopathology.

Results

We show an estimated 27.8% cost treatment reduction per patient if low rates of non-diagnostic for cytological diagnosis (Thy 1) and neoplasm possible atypia/non-diagnostic (Thy 3a) are achieved, which require rapid onsite FNA adequacy assessment of aspiration samples. If we assume that the number of thyroid FNAs performed in the UK annually is around 500 per million, and the UK population is 62 million, this could save the UK National Health Service significant sums, as the additional cost per patient treated in this model varies from £781 for a scenario with ultrasound guided FNA and inclinic cell adequacy assessment to £998 where aspirates are taken in conventional fashion without any inclinic adequacy assessment.

Conclusions

This model makes a strong economic case for the introduction of rapid onsite assessment of thyroid FNA across cancer networks, to improve the diagnostic efficacy of thyroid FNA.