Ultrasound often represents the first diagnostic step for thyroid nodule evaluation in clinical practice, but baseline US alone is not always effective enough to achieve thyroid nodule characterization. In the last decades new ultrasound techniques, such as CEUS, have been introduced to evaluate thyroid parenchyma as recommended by EFSUMB guidelines, for use in clinical research field, although its role is not yet clear. Several papers show the potential utility of CEUS in the differential diagnosis of benign and malignant thyroid nodules and in the analysis of lymph node involvement in neoplastic pathology. Therefore, we carried out an evaluation of the literature concerning the role of CEUS in three specific areas: the characterization of the thyroid nodule, the evaluation of minimally invasive treatment and loco-regional staging of the lymph node in proven thyroid cancer. According to evidence reported, CEUS can also play an operative role in nodular thyroid pathology as it is able to guide ablation procedures on thyroid nodule and metastatic lymph nodes, to assess the radicality of surgery, to evaluate disease relapse at the level of the margins of ablated regions and to monitor the clinical evolution of necrotic areas in immediate post-treatment setting.

Ultrasound (US) is the first imaging modality for thyroid parenchyma evaluation. In the last decades, the role of ultrasound has been improved with the introduction of new US software, such as contrast-enhanced ultrasound (CEUS) and US-elastography (USE). USE is nowadays recognized as an essential part of the multiparametric ultrasound (MPUS) examination, in particular for the indeterminate thyroid nodule with possible fine-needle aspiration cytology (FNAC) number reduction; even if further and larger studies are needed to validate it. More controversial is the role of CEUS in thyroid evaluation, due to its high variability in sensitivity and specificity. Semi-automatic US systems based on the computer-aided diagnosis (CAD) system are producing interesting results, especially as an aid to less experienced operators. New knowledge on the molecular mechanisms involved in thyroid cancer is allowing practitioners to identify new genomic thyroid markers that could reduce the number of “diagnostic” thyroidectomies. We have therefore drawn up an updated representation of the current evidence in the literature for thyroid nodule multiparametric ultrasound (MPUS) evaluation with particular regard to USE, the US CAD system and CEUS.

Machine learning (ML) is an interdisciplinary sector in the subset of artificial intelligence (AI) that creates systems to set up logical connections using algorithms, and thus offers predictions for complex data analysis. In the present review, an up-to-date summary of the current state of the art regarding ML and AI implementation for thyroid nodule ultrasound characterization and cancer is provided, highlighting controversies over AI application as well as possible benefits of ML, such as, for example, training purposes. There is evidence that AI increases diagnostic accuracy and significantly limits inter-observer variability by using standardized mathematical algorithms. It could also be of aid in practice settings with limited sub-specialty expertise, offering a second opinion by means of radiomics and computer-assisted diagnosis. The introduction of AI represents a revolutionary event in thyroid nodule evaluation, but key issues for further implementation include integration with radiologist expertise, impact on workflow and efficiency, and performance monitoring.

Purpose Our purpose is to assess Multiparametric Ultrasound (MPUS) efficacy for evaluation of carotid plaque vulnerability and carotid stenosis degree in comparison with Computed Tomography angiography (CTA) and histology. Material and methods 3D-Arterial Analysis is a 3D ultrasound software that automatically provides the degree of carotid stenosis and a colorimetric map of carotid plaque vulnerability. We enrolled 106 patients who were candidates for carotid endarterectomy. Prior to undergoing surgery, all carotid artery plaques were evaluated with Color-Doppler-US (CDUS), Contrast-Enhanced Ultrasound (CEUS), and 3D Arterial analysis (3DAA) US along with Computerized Tomographic Angiography (CTA) to assess the carotid artery stenosis degree. Post-surgery, the carotid specimens were fixed with 10% neutral buffered formalin solution, embedded in paraffin and used for light microscopic examination to assess plaque vulnerability morphological features. Results The results of the CTA examinations revealed 91 patients with severe carotid stenoses with a resultant diagnostic accuracy of 82.3% for CDUS, 94.5% for CEUS, 98.4% for 3DAA, respectively. The histopathological examination showed 71 vulnerable plaques with diagnostic accuracy values of 85.8% for CDUS, 93.4% for CEUS, 90.3% for 3DAA, 92% for CTA, respectively. Conclusions The combination of CEUS and 3D Arterial Analysis may provide a powerful new clinical tool to identify and stratify “at-risk” patients with atherosclerotic carotid artery disease, identifying vulnerable plaques. These applications may also help in the postoperative assessment of treatment options to manage cardiovascular risks.