The Diagnostic Value of CEUS in Assessing Non-Ossified Thyroid Cartilage Invasion in Patients with Laryngeal Squamous Cell Carcinoma.
Milda PucėtaitėDavide FarinaSilvija RyškienėDalia MitraitėRytis TarasevičiusSaulius LukoseviciusEvaldas PadervinskisSaulius VaitkusPublished in: Journal of clinical medicine (2024)
Background: Accurate assessment of thyroid cartilage invasion in squamous cell carcinoma (SCC) of the larynx remains a challenge in clinical practice. The aim of this study was to assess the diagnostic performance of contrast-enhanced ultrasound (CEUS), contrast-enhanced computed tomography (CECT), and magnetic resonance imaging (MRI) in the detection of non-ossified thyroid cartilage invasion in patients with SCC. Methods: CEUS, CECT, and MRI scans of 27 male patients with histologically proven SCC were evaluated and compared. A total of 31 cases were assessed via CEUS and CECT. The MR images of five patients and six cases were excluded (one patient had two suspected sites), leaving twenty-five cases for analysis via MRI. Results: CEUS showed the highest accuracy and specificity compared with CECT and MRI (87.1% vs. 64.5% and 76.0% as well as 84.0% vs. 64.0% and 72.7%, respectively). The sensitivity and negative predictive value of CEUS and MRI were the same (100%). CEUS yielded four false-positive findings. However, there were no statistically significant differences among the imaging modalities ( p > 0.05). Conclusions: CEUS showed better diagnostic performance than CECT and MRI. Therefore, CEUS has the potential to accurately assess non-ossified thyroid cartilage invasion and guide appropriate treatment decisions, hopefully leading to improved patient outcomes.
Keyphrases
- contrast enhanced ultrasound
- contrast enhanced
- magnetic resonance imaging
- computed tomography
- diffusion weighted
- squamous cell carcinoma
- diffusion weighted imaging
- magnetic resonance
- cell migration
- clinical practice
- positron emission tomography
- dual energy
- extracellular matrix
- deep learning
- ejection fraction
- lymph node metastasis
- radiation therapy
- end stage renal disease
- climate change
- prognostic factors
- mass spectrometry
- convolutional neural network