A Pragmatic Approach to the Indeterminate Thyroid Nodule

Role of Genetic Testing in the Management of Indeterminate Thyroid Nodules in the Indian Setting

The increased detection of thyroid nodules in the human population has led to an increase in the number of thyroid surgeries without an improvement in survival outcomes. Though the choice for surgery is straightforward in malignant thyroid nodules, the decision is far more complex in those nodules that get categorized into indeterminate thyroid nodules (ITN) by fine needle aspiration. Therefore, there is a pressing need to develop a tool that will aid in decision-making among the ITN. In this context, the development of various molecular testing (MT) panels has helped to confirm or rule out malignancy, reducing unnecessary surgeries and potentially guiding the extent of surgery as well. Currently, such tests are widely used among the Western population but these MT panels are not used by the South Asian population because of non-availability of validated panels and the high cost involved. There is a need to develop a suitable panel which is population-specific and validate the same. In this review, we would focus on current trends in the management of ITN among the South Asian population and how to develop a novel MT panel which is cost-effective, with high diagnostic accuracy obviating the need for expensive panels that already exist.

Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions

The diagnosis and management of thyroid cancer is fraught with challenges despite the advent of innovative diagnostic, surgical, and chemotherapeutic modalities. Challenges like inaccuracy in prognostication, uncertainty in cytopathological diagnosis, trouble in differentiating follicular neoplasms, intra-observer and inter-observer variability on ultrasound imaging preclude personalised treatment in thyroid cancer. Artificial intelligence (AI) is bringing a paradigm shift to the healthcare, powered by quick advancement of the analytic techniques. Several recent studies have shown remarkable progress in thyroid cancer diagnostics based on AI-assisted algorithms. Application of AI techniques in thyroid ultrasonography and cytopathology have shown remarkable impro-vement in sensitivity and specificity over the traditional diagnostic modalities. AI has also been explored in the development of treatment algorithms for indeterminate nodules and for prognostication in the patients with thyroid cancer. The benefits of high repeatability and straightforward implementation of AI in the management of thyroid cancer suggest that it holds promise for clinical application. Limited clinical experience and lack of prospective validation studies remain the biggest drawbacks. Developing verified and trustworthy algorithms after extensive testing and validation using prospective, multi-centre trials is crucial for the future use of AI in the pipeline of precision medicine in the management of thyroid cancer.

Evaluation of the diagnostic performance of contrast-enhanced ultrasound combined with BRAF V600E gene detection in nodules of unclear significance by thyroid fine-needle aspiration

Background

Our study aims to test the diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with the detection of serine/threonine-protein kinase V600E (BRAF V600E) in nodules of unclear significance by thyroid fine-needle aspiration (FNA).

Methods

From January 2015 to December 2019, 244 patients were subjected to ultrasonic strain imaging and elastography, CEUS, and BRAF V600E gene detection at Lishui Hospital of Zhejiang University. Thyroid FNA does not confirm the benignancy and malignancy of the thyroid nodules. With postoperative pathology as the gold standard, the diagnostic value of CEUS, BRAF V600E detection, and the combination in differentiating benign and malignant thyroid nodules were evaluated. The negative predictive value (NPV) and accuracy of CEUS, BRAF V600E detection, and the combination were calculated along with sensitivity, specificity, and positive predictive value (PPV).

Results

In this study, the sensitivity, specificity, PPV, NPV, accuracy, and AUC of CEUS alone in predicting benign and malignant thyroid nodules were 69.8%, 94.9%, 98.6%, 37.4%, 73.8% and 0.884, respectively. The sensitivity, specificity, PPV, NPV, accuracy and AUC of BRAF V600E detection alone were 65.4%, 100%, 100%, 35.5%, 70.9% and 0.827, respectively. The sensitivity, specificity, PPV, NPV, accuracy and AUC of the combination were 73.2%, 94.9%, 98.7%, 40.2%, 76.6% and 0.923, respectively.

Conclusions

Therefore, compared with CEUS or BRAF V600E gene detection alone, the combination of CEUS and BRAF V600E gene detection has a higher sensitivity, NPV, and accuracy in the diagnosis of thyroid nodules.

Systems of Risk Stratification of Malignancy by Ultrasound of Thyroid Nodules

Thyroid nodules (TN) are more frequently identified with the use of thyroid ultrasonography, and they have a low risk of malignancy. Ultrasonographic features have been established that increase the probability of being faced with thyroid carcinoma; however, individually, these characteristics do not perform adequately in the diagnosis of malignancy, limiting their usefulness when indicating cytological studies by means of fine-needle aspiration (FNC). This situation motivated the development of risk stratification systems for thyroid nodules, which unified their ultrasound characteristics, with the aim of establishing risk categories, standardizing the preparation of reports, and providing the clinician with useful tools to define the surveillance option or form invasive studies.

The objective of this review is to compare the different systems developed by some scientific societies for the stratification of thyroid nodules, with respect to their predictive capacities for malignancy, their operational characteristics for diagnosis, and, to suggest recommendations for the implementation of these systems, placing emphasis on those with the best ability to reduce the performance of unnecessary invasive studies and to guide decision-making in the face of undetermined cytological results.

American Thyroid Association Sonographic Risk and Afirma Gene Expression Classifier Alone and in Combination for the Diagnosis of Thyroid Nodules with Bethesda Category III Cytology

Background: The Afirma gene expression classifier (GEC) has been used to aid in the diagnosis and management of thyroid nodules having Bethesda category III fine-needle aspiration cytologic diagnosis (B3 nodules). The American Thyroid Association sonographic risk stratification system for thyroid nodules (ATA-US) may stratify B3 nodules and aid in the decision to order a molecular test. The aim of this study was to assess the association between ATA-US and GEC as well as to determine their individual and combined diagnostic performances when applied to B3 nodules. Methods: A retrospective single-center study included B3 nodules that had undergone evaluation by GEC. Each ultrasound was reviewed by three radiologists, and nodules were classified using the 2015 ATA sonographic risk categories. Nodules were determined to be benign or malignant based on surgical pathology or minimum 11 months of follow-up. Positive predictive values (PPV) and negative predictive values (NPV) were calculated for GEC, ATA-US, and GEC across all ATA-US categories. Results: One hundred twenty-six B3 nodules with GEC results were included and deemed benign or malignant based on final pathology or follow-up. Prevalence of malignancy was 32%. The rate of malignancy was similar in the ATA-US high suspicion (HS) and intermediate suspicion (IS) categories at 42% and 38%, respectively; and lower in nodules with low suspicion sonography (LS) and very low suspicion sonography (VLS) at 23% and 11%, respectively. The PPV and NPV of ATA-US was calculated by designating HS or IS sonography as a "positive" test and the lower risk categories as "negative." ATA-US had a PPV of 40% and NPV of 79%. The GEC PPV was 40% and NPV was 83%. The PPV of GEC was 50% in nodules with HS or IS ATA-US and lower at 28% and 20%, respectively, in LS and VLS nodules. The NPV of GEC was 80% in HS, 77% in IS, 84% in LS, and 100% in VLS sonography categories. Conclusions: In B3 nodules, ATA-US and GEC have similar diagnostic performance. The PPV of GEC varies across ATA-US categories, while the NPV remains similar. These data support the need for future prospective studies.

Developing a tool that could reliably refute total thyroidectomy for solitary Bethesda IV thyroid nodules

PURPOSE

To assess the reliability of a simple, accessible, cost-effective rule-out tool, for use in triaging patients with Bethesda IV nodules to appropriate surgery.

METHODS

The diagnostic tool was assembled by combining the negativity for suspicious ultrasound features (irregular margins, microcalcification, and a taller-than-wide orientation), and mutational marker negativity (BRAF and NRAS). The tool, (US^-/mutation^-), was tested on 167 patients with solitary Bethesda IV nodules. The primary outcome was its negative predictive value (NPV) for lesions requiring total thyroidectomy (TT). The impact of mutational marker negativity, as part of the tool, was evaluated by comparing the NPV of (US^-/mutation^-) to that of (US^-/mutation⁺).

RESULTS

10 out of 167 lesions were positive for a mutational marker. These underwent TT, and only 2/10 (20%) were benign, on final histology. In 6/8 malignant lesions, TT was concordant with current clinical guidelines. 157 patients comprised the negative study cohort, for both mutational markers and suspicious US features. These underwent thyroid lobectomy, and 17 cases resulted in malignancy, only 8 of which required completion thyroidectomy. Accordingly, the NPV of (US^-/mutation^-) for malignancy was 89% (140/157), and 95% (149/157) for malignancy requiring TT. However, the NPV of (US^-/mutation⁺) was 20% for malignancy, and 40% for malignancy requiring TT. These differences were statistically significant (89% vs. 20%; p < 0.0001, and 95% vs. 40%; p < 0.0001).

CONCLUSION

US^-/mutation^- is a reliable rule-out tool, with sufficient diagnostic accuracy to spare patients, with Bethesda IV nodules, an overly radical TT.

Role of Strain Elastography and Shear-Wave Elastography in a Multiparametric Clinical Approach to Indeterminate Cytology Thyroid Nodules

Background

In thyroid nodules with indeterminate cytology, further clinical assessment aimed at ruling out malignancy is often mandatory. Ancillary imaging techniques and genetic mutation analysis can improve the risk stratification of such lesions, thereby facilitating the clinician’s decision to undertaken surgery or simple follow-up. The aim of this study was to evaluate the diagnostic performance of shear-wave elastography (SW), strain elastography (ELX 2/1), conventional ultrasound (US), contrast-enhanced ultrasound (CEUS), and BRAF V600E mutation analysis in the aforementioned lesions.

Material/Methods

We enrolled 81 patients, each with 1 indeterminate-cytology thyroid nodule. Thyroid function, thyroperoxidase antibodies and calcitonin were known in each case. SW, ELX 2/1, US, CEUS, and BRAF mutation analysis were subsequently performed, followed by a second FNAB. If the lesion was not downgraded to benign, surgery was recommended and histological reports collected.

Results

There were 28 nodules (34%) that proved benign on the second FNAB; 38 nodules (47%) underwent surgery (17 benign, 21 malignant), and 15 nodules (19%) refused surgery. The only techniques related to histological outcome were US (AUC=0,766), ELX 2/1 (AUC=0.701), and BRAF analysis (AUC=0.762). ELX 2/1 and SW reports were not correlated with each other (P=0.45). A scoring system taking into account all the variables considered performed better than the single variables alone (AUC=0.831).

Conclusions

In indeterminate-cytology thyroid lesions, repeating FNAB can avoid unnecessary surgery. ELX 2/1 seems to perform better than SW in distinguishing malignancy; these techniques could, however, be complementary in describing such lesions. A multiparametric approach appears the most accurate in predicting nodule histology.