Ultrasound Classification of Thyroid Nodules: A Systematic Review

Abstract

Ultrasound (US) based classification systems exist for the stratification of thyroid nodules based on the risk for malignancy. This systematic review aimed to assess the evidence for the performance of US-based thyroid nodule classification systems through correlation with fine needle aspiration biopsy (FNAB). PubMed and Scopus were searched using keywords that included 'ultrasound classification', 'thyroid nodules', 'fine needle aspiration', and 'malignancy'. Inclusion criteria were as follows: studies/reviews reporting on US imaging for the classification of thyroid nodules. Exclusion criteria were as follows: no comparison between US imaging findings and histology reports based on FNAB, no full English text available/accessible. The database searches identified 66 publications. After evaluation, 12 studies met the inclusion criteria. Two US-based classification systems for thyroid nodules were assessed: the Thyroid Imaging Reporting and Data System (TIRADS) and the American Thyroid Association (ATA) guidelines. For TIRADS, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) ranged from 70.6% to 97.4%, 29.3% to 90.4%, 23.3% to 64.3%, and 87.1% to 99.0%, respectively. The median sensitivity, specificity, PPV, and NPV for TIRADS was 90.0%, 57.4%, 49.0%, and 91.0%, respectively. One study comparing TIRADS with the ATA guidelines demonstrated that TIRADS was superior in terms of sensitivity, whereas the ATA guidelines were superior in terms of specificity and PPV. The high sensitivity and NPV of the US-based TIRADS classification system have excellent utility for correctly classifying nodules as positive for malignant disease and for predicting the absence of malignant disease. The paucity of studies assessing the ATA guidelines highlights avenues for further research comparing TIRADS with other systems of thyroid nodule classification.

A Review of the Pathology, Diagnosis and Management of Colloid Goitre

“…comet tails are typically within, or at the edge of, the follicle; whereas microcalcifications occur scattered in solid tissue. 34,35 Occasionally, it can be difficult to distinguish the density of a comet tail from a microcalcification, leading to divergent opinions on how reassuring it is to observe the density of a comet tail within a nodule. Studies of thyroid ultrasound have shown that the harmonic option (display mode on ultrasound machine) improves the structural image quality of the colloid nodules in 75-85% of cases.…”

“…Nodules with large comet-tail artefacts, especially those around a cystic nodule, are almost always a benign lesion. 34 A biopsy can be remarkably avoided in most of these lesions unless other suspect features are present. 27 Therefore, radiologists need to systematically master the characteristics of the thyroid nodules to produce a reliable result.…”

Molecular Tests for Risk-Stratifying Cytologically Indeterminate Thyroid Nodules: An Overview of Commercially Available Testing Platforms in the United States

“…Specific ultrasound characteristics of thyroid tumors, such as hypoechogenicity, taller-than-wide shape on transverse view, irregular margins, microcalcifications/echogenic foci, and apparent extrathyroidal extension are associated with malignancy. These and other ultrasound features have been employed by various professional societies to develop ultrasound risk assessment schemes to select thyroid nodules for FNA biopsy [1,[8][9][10].…”

Facing Thyroid Nodules in Paediatric Patients Previously Treated with Radiotherapy for Non-Thyroidal Cancers: Are Adult Ultrasound Risk Stratification Systems Reliable?

“…Neck ultrasonography is the first-line imaging procedure, which is able to identify and classify the risk of the thyroid nodules [ 9 , 10 , 11 ]. Adult-based neck US risk stratification systems (RSSs) have been developed in recent years to integrate the US features in an effort to improve diagnostic accuracy and as an aid in the stratification of the risk of malignancy [ 9 , 12 , 13 ].…”