American Association of Clinical Endocrinology And Associazione Medici Endocrinologi Thyroid Nodule Algorithmic Tool

Computer-interpretable guidelines: electronic tools to enhance the utility of thyroid nodule clinical practice guidelines and risk stratification tools

Clinicians seeking guidance for evaluating and managing thyroid nodules currently have several resources. The principal ones are narrative clinical guidelines and clinical risk calculators. This paper will review the strengths and weaknesses of both. The paper will introduce a concept of computer interpretable guideline, a novel way of transforming narrative guidelines in to a clinical decision support tool that can provide patient specific recommendations at the point of care. The paper then describes an experience of developing an interactive web based computer interpretable guideline for thyroid nodule management, called Thyroid Nodule Management App (TNAPP). The advantages of this approach and the potential barriers for widespread adaptation are discussed.

Molecular testing in indeterminate thyroid nodules: an additional tool for clinical decision-making

Thyroid nodules are commonly encountered in clinical practice, affecting up to 50% of the population. The large majority of thyroid lumps are benign incidental findings detected by imaging, while approximately 5-15% harbor malignancy. For a target patient's care, it is of paramount importance to identify and treat thyroid malignancy, while preventing unnecessary invasive surgery in patients with benign lesions. Although fine needle aspiration (FNA) associated with cytological examination provides malignant risk information, 20-30% of diagnoses fall into the "indeterminate thyroid nodule" (ITN) category. ITN clinical management remains a challenging issue for physicians since the ITN risk of malignancy varies from 5% to 40% and most thyroid nodules undergo overtreatment with surgery procedures. ITN molecular testing may better define malignant risk in the single nodule and is able to discriminate with accuracy benign from malignant nodules. Nowadays there are different technologies and different molecular panels, each with its own specificity, sensitivity and predictive values. In view of widespread introduction of molecular testing , some outstanding questions remain and are addressed in the present review such as the presence of molecular panels acting as "rule in" or "rule out" tools, the effective impact of testing results in the clinical decision-making process, and the prohibitive cost of commercial assays associated with the lack of test reimbursement in national health systems.

Paving the path toward multi-omics approaches in the diagnostic challenges faced in thyroid pathology

INTRODUCTION

Despite advancements in diagnostic methods, the classification of indeterminate thyroid nodules still poses diagnostic challenges not only in pre-surgical evaluation but even after histological evaluation of surgical specimens. Proteomics, aided by mass spectrometry and integrated with artificial intelligence and machine learning algorithms, shows great promise in identifying diagnostic markers for thyroid lesions.

AREAS COVERED

This review provides in-depth exploration of how proteomics has contributed to the understanding of thyroid pathology. It discusses the technical advancements related to immunohistochemistry, genetic and proteomic techniques, such as mass spectrometry, which have greatly improved sensitivity and spatial resolution up to single-cell level. These improvements allowed the identification of specific protein signatures associated with different types of thyroid lesions.

EXPERT COMMENTARY

Among all the proteomics approaches, spatial proteomics stands out due to its unique ability to capture the spatial context of proteins in both cytological and tissue thyroid samples. The integration of multi-layers of molecular information combining spatial proteomics, genomics, immunohistochemistry or metabolomics and the implementation of artificial intelligence and machine learning approaches, represent hugely promising steps forward toward the possibility to uncover intricate relationships and interactions among various molecular components, providing a complete picture of the biological landscape whilst fostering thyroid nodule diagnosis.

Application of machine learning methods to guide patient management by predicting the risk of malignancy of Bethesda III-V thyroid nodules

OBJECTIVE

Indeterminate thyroid nodules (ITN) are common and often lead to (sometimes unnecessary) diagnostic surgery. We aimed to evaluate the performance of two machine learning methods (ML), based on routinely available features to predict the risk of malignancy (RM) of ITN.

DESIGN

Multi-centric diagnostic retrospective cohort study conducted between 2010 and 2020.

METHODS

Adult patients who underwent surgery for at least one Bethesda III-V thyroid nodule (TN) with fully available medical records were included. Of the 7917 records reviewed, eligibility criteria were met in 1288 patients with 1335 TN. Patients were divided into training (940 TN) and validation cohort (395 TN). The diagnostic performance of a multivariate logistic regression model (LR) and its nomogram, and a random forest model (RF) in predicting the nature and RM of a TN were evaluated. All available clinical, biological, ultrasound, and cytological data of the patients were collected and used to construct the two algorithms.

RESULTS

There were 253 (19%), 693 (52%), and 389 (29%) TN classified as Bethesda III, IV, and V, respectively, with an overall RM of 35%. Both cohorts were well-balanced for baseline characteristics. Both models were validated on the validation cohort, with performances in terms of specificity, sensitivity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve of 90%, 57.3%, 73.4%, 81.4%, 84% (CI95%: 78.5%-89.5%) for the LR model, and 87.6%, 54.7%, 68.1%, 80%, 82.6% (CI95%: 77.4%-87.9%) for the RF model, respectively.

CONCLUSIONS

Our ML models performed well in predicting the nature of Bethesda III-V TN. In addition, our freely available online nomogram helped to refine the RM, identifying low-risk TN that may benefit from surveillance in up to a third of ITN, and thus may reduce the number of unnecessary surgeries.

A prospective comparison of ACR-TIRADS and EU-TIRADS in thyroid nodule assessment for FNA-US

OBJECTIVE

Prospective data on the accuracy of ultrasound (US) classification systems in thyroid nodules are still scarce. The aim of this study is to compare the accuracy of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) and European (EU)-TIRADS classification systems.

DESIGN AND PATIENTS

Consecutive patients with one or more thyroid nodule(s) who underwent fine-needle aspiration (FNA) under ultrasonographic guidance (FNA-US) were prospectively evaluated.

MEASUREMENTS

Clinical evaluation and US data were collected. The reference standard used for this study was FNA-US cytology and histopathological diagnosis.

RESULTS

A total of 186 thyroid nodules in 166 patients were evaluated, resulting in 168 nodules from 149 patients with conclusive benign or malignant results. Sensitivity, specificity, negative predictive value (NPV) and false negative (FN) were 100.0%, 28.7%, 100.0% and 0.0%, respectively, for ACR-TIRADS; and 90.0%, 19.1%, 96.8% and 9.1% (n = 1), respectively, for EU-TIRADS. The number of unnecessary FNA-US indicated by ACR-TIRADS was lower than EU-TIRADS (71.3% vs. 80.9%, p = .017), and the number of possibly avoided FNA-US was higher (26.7% vs. 17.8%). Using the same threshold of ACR-TIRADS to indicate FNA-US in EU-TIRADS 3 nodules (2.5 cm), there was an improvement in specificity (30.6%) and avoided FNA-US (28.6%). The best performance of both systems was demonstrated when FNA-US would be indicated only in highly suspicious nodules and/or in the presence of lymphadenopathy, with 85.7% and 89.3% of possibly avoided FNA-US for ACR-TIRADS and EU-TIRADS, respectively, without increasing FN.

CONCLUSION

Both systems presented high sensitivity, but low specificity in selecting nodules for FNA-US. The use of nodular size for FNA-US selection is questioned.

Risk stratification of cytologically indeterminate thyroid nodules with nondiagnostic or benign cytology on repeat FNA: Implications for molecular testing and surveillance

BACKGROUND

Evidence guiding the management of cytologically indeterminate thyroid nodules with nondiagnostic (ND) or benign cytology on repeat fine-needle aspiration (FNA) is limited. This study evaluates the utility of molecular testing and estimates the risk of noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and cancer among such nodules.

METHODS

This was a retrospective single-institution review of thyroid nodules from adults that were classified as atypia of undetermined significance (AUS) or follicular neoplasm (FN) on initial FNA and underwent repeat FNA for cytology and Afirma testing (June 2013-July 2021). The association between repeat FNA cytology and RNA yield for Afirma was determined. Histologic outcomes were integrated with Afirma results to define end points for each nodule.

RESULTS

A total of 691 AUS and FN nodules underwent repeat FNA and Afirma testing. Diagnostic Afirma results were obtained in 98% of cases overall and in 91% of nodules with ND cytology on repeat FNA. Using combined molecular and histologic end points, the NIFTP and/or cancer prevalence for nodules with ND cytology on repeat FNA was 9% (95% confidence interval [CI], 0.042-0.182), falling between those nodules classified as benign (5%; 95% CI, 0.029-0.094) and those classified as AUS or FN (18%; 95% CI, 0.140-0.218) on repeat FNA, although not reaching statistical significance from either subgroup (p = .38 and .10, respectively).

CONCLUSIONS

AUS and FN nodules that are ND on repeat FNA have low but nonnegligible risk of NIFTP and/or cancer and may benefit from molecular testing, given the low test failure rate in this subgroup. Conversely, AUS and FN nodules reclassified as benign on repeat FNA have a very low risk of NIFTP and/or cancer and are unlikely to benefit from molecular testing.

Comparing ATA guidelines vs TI-RADS for evaluation of pediatric thyroid lesions

OBJECTIVE

To compare TI-RADS vs ATA guidelines for pediatric thyroid lesions based on ultrasound, in a retrospective study over 10 years. The primary outcome measure was sensitivity of both guidelines in diagnosing a thyroid malignancy on Fine Needle Aspiration (FNA) results.

METHODS

Retrospective data collection of all pediatric patients who had an FNA at the Primary Children's Hospital for thyroid lesions. Both guidelines were compared to determine which set of guidelines is most sensitive based on final outcome of pathology.

RESULTS

Seventy-seven patients were included in the study. All 77 underwent FNA as recommended by the ATA guidelines. 54.5% were benign, 22.1% were suspicious, and 23.4% were malignant lesions. Following the TI-RADS guidelines, 40.5% of these patients could have skipped the FNA. Using the ATA guidelines, all malignant lesions would have undergone FNA. However, using the TI-RADS guidelines, some patients with malignant lesions would have been ignored (5.6%) and some followed (22.2%) showing overall less sensitivity (75%).

CONCLUSIONS

The ATA ultrasound guidelines for evaluation of thyroid nodules in children are more sensitive in screening for well-differentiated thyroid malignancy. Increased sensitivity is due in part to the size constraint within the TIRADS system. All providers who evaluate thyroid nodules in children should use the ATA pediatric guidelines to avoid missing smaller malignancies in children.

DIAGNOSIS OF ENDOCRINE DISEASE: Usefulness of genetic testing of fine-needle aspirations for diagnosis of thyroid cancer

OBJECTIVE

Genetic testing is increasingly used to diagnose or rule out thyroid cancer in indeterminate fine-needle aspirations. This review evaluates the usefulness of these methods with considerations of advantages and limitations.

DESIGN

Given the diagnostic problem associated with the increasing incidental detection of indeterminate thyroid nodules in the context of thyroid cancer overtreatment, we consider the conditions and respective necessary settings for the role of genetic testing to improve presurgical malignancy risk stratification.

METHODS

We review diagnostic pathway requirements and commercially available molecular tests with their respective advantages and disadvantages and discuss the prerequisites required for local application and implementation including quality assurance for local ultrasound and cytopathology practices.

RESULTS

Recent improvements in available molecular diagnostic tests have brought high sensitivity and specificity in initial validation studies, but whether these promising results translate to other clinical settings depends on the quality of the local thyroid nodule diagnostic pathway.

CONCLUSIONS

Genetic testing can meaningfully improve presurgical malignancy risk assessment, but more work is needed to implement and use genetic testing effectively in local settings.

A Case-Based Comparison of the American Thyroid Association and Thyroid Imaging Reporting & Data System Guidelines

Thyroid nodules are a common clinical finding. Approximately 4-7% of the population have a palpable nodule on physical exam,1 while up to 70% of the population have a nodule detected incidentally on ultrasound.2 The vast majority of nodules are benign, however, approximately 5-13% of thyroid nodules detected on imaging are at risk of malignancy.3 Some malignant nodules, especially those smaller than 1 cm, can exhibit indolent behavior and do not require aggressive treatment.4 Therefore, thyroid nodules need to be accurately assessed to avoid overdiagnosis and overtreatment of nodules which would not otherwise affect patient morbidity. The American Thyroid Association (ATA) addressed this challenge by developing a set of ultrasound pattern-based guidelines for thyroid nodule management in 2009, which were updated in 2015.5 Other societies have since published similar guidelines, such as the Thyroid Imaging Reporting & Data System (TI-RADS) by the American College of Radiology in 2017. TI-RADS was similarly intended to risk-stratify nodules based on ultrasound appearance, but uses a points-based approach. The purpose of this review is to provide an overview of thyroid nodule evaluation and management through a case-based comparison using the ATA and TI-RADS guidelines.

The TNAPP web-based algorithm improves thyroid nodule management in clinical practice: A retrospective validation study

BACKGROUND

The detection of thyroid nodules has been increasing over time, resulting in an extensive use of fine-needle aspiration (FNA) and cytology. Tailored methods are required to improve the management of thyroid nodules, including algorithms and web-based tools.

STUDY AIMS

To assess the performance of the Thyroid Nodule App (TNAPP), a web-based, readily modifiable, interactive algorithmic tool, in improving the management of thyroid nodules.

METHODS

One hundred twelve consecutive patients with 188 thyroid nodules who underwent FNA from January to December 2016 and thyroid surgery were retrospectively evaluated. Neck ultrasound images were collected from a thyroid nodule registry and re-examined to extract data to run TNAPP. Each nodule was evaluated for ultrasonographic risk and suitability for FNA. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of TNAPP were calculated and compared to the diagnostic performance of the other two algorithms by the American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi (AACE/ACE/AME), which it was derived from the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS).

RESULTS

TNAPP performed better in terms of sensitivity (>80%) and negative predictive value (68%) with an overall accuracy of 50.5%, which was similar to that found with the AACE/ACE/AME algorithm. TNAPP displayed a slightly better performance than AACE/ACE/AME and ACR TI-RADS algorithms in selectively discriminating unnecessary FNA for nodules with benign cytology (TIR 2 - Bethesda class II: TNAPP 32% vs. AACE/ACE/AME 31% vs. ACR TI-RADS 29%). The TNAPP reduced the number of missed diagnoses of thyroid nodules with suspicious and highly suspicious cytology (TIR 4 + TIR 5 - Bethesda classes V + VI: TNAPP 18% vs. AACE/ACE/AME 26% vs. ACR TI-RADS 20.5%). A total of 14 nodules that would not have been aspirated were malignant, 13 of which were microcarcinomas (92.8%).

DISCUSSION

The TNAPP algorithm is a reliable, easy-to-learn tool that can be readily employed to improve the selection of thyroid nodules requiring cytological characterization. The rate of malignant nodules missed because of inaccurate characterization at baseline by TNAPP was lower compared to the other two algorithms and, in almost all the cases, the tumors were microcarcinomas. TNAPP's use of size >20 mm as an independent determinant for considering or recommending FNA reduced its specificity.

CONCLUSION

TNAPP performs well compared to AACE/ACE/AME and ACR-TIRADS algorithms. Additional retrospective and, ultimately, prospective studies are needed to confirm and guide the development of future iterations that incorporate different risk stratification systems and targets for diagnosing malignancy while reducing unnecessary FNA procedures.

Point of Care Measurement of Body Mass Index and Thyroid Nodule Malignancy Risk Assessment

BACKGROUND

Large scale epidemiology studies have suggested obesity may increase the risk of thyroid cancer, though no prospective analyses using real-world measurement of BMI at a time proximate to initial thyroid nodule evaluation have been performed.

METHODS

We performed a prospective, cohort analysis over 3 years of consecutive patients presenting for thyroid nodule evaluation. We measured BMI proximate to the time of initial evaluation and correlated this with the final diagnosis of benign or malignant disease. We further correlated patient BMI with aggressivity of thyroid cancer, if detected.

RESULTS

Among 1,259 consecutive patients with clinically relevant nodules, 199(15%) were malignant. BMI averaged 28.6 kg/m² (SD: 6.35, range:16.46-59.26). There was no correlation between the measurement of BMI and risk of thyroid cancer (p=0.58) as mean BMI was 28.9 kg/m² and 28.6 kg/m² in cancerous and benign cohorts, respectively. Similarly, BMI did not predict aggressive thyroid cancer (p=0.15). While overall nodule size was associated with increased BMI (p<0.01), these data require further validation as obesity may hinder nodule detection until large.

CONCLUSION

In contrast to findings published from large scale association studies drawn from national databases, these prospective data of consecutive patients presenting for nodule evaluation detect no association of obesity (as measured by BMI) with thyroid cancer. Real time measurement of BMI at the time of thyroid nodule evaluation does not contribute to cancer risk assessment.

The impact of the use of the ACR-TIRADS as a screening tool for thyroid nodules in a cancer center

BACKGROUND

The Thyroid Imaging Reporting and Data System (TIRADS) was created to assess risk of thyroid nodules through ultrasound. Plenty classifications methods for thyroid nodules have already been created, but none of them have yet achieved global utilization. This study analyzed the performance of the American College of Radiology (ACR) TIRADS, its reproducibility and the impact of its utilization as a screening method in a large Cancer Center cohort.

METHODS

Thyroid nodules which underwent fine-needle aspiration (FNA) in a 1-year period were selected, with their ultrasound images retrospectively classified according to the ACR TI-RADS. Cytological evaluation of the nodules and final histology (whenever available) was used to assess risk of neoplasm (RON) and risk of malignancy (ROM) associated to each ACR-TIRADS category. Further analyses were also carried out according to recommendation or not of FNA by the ACR-TIRADS and nodule size. Inter-observer agreement for the system was also assessed.

RESULTS

A total of 1112 thyroid nodules were included. RON for each category according to final cytological diagnosis was 0% for TR1 and TR2, 2.1% for TR3; 15.6% for TR4 and 68.9% for TR5. No significant difference was observed between the RON of the categories for cases above or below 1.0 cm. Nodules that met the criteria for FNA had 3 times greater chance of a positive outcome. Substantial agreement (kappa 0.77) was seen between two different observers.

CONCLUSIONS

ACR TI-RADS scoring system has demonstrated to be an accurate method to stratify thyroid nodules in a Cancer Center, with a high reproducibility.