Thoracic ultrasound elastography to differentiate between malignant and benign lesions
Year: 2024
Type: conference-paper
Study design: Observational Study
Abstract: Background: Thoracic ultrasound (TUS) can be used to detect lesions with a wide array of underlying aetiologies, including those with benign and malignant origin. While visual distinction is complicated, it is conceivable that tissue elasticity varies between aetiologies. This study aimed to investigate the optimal cut-off for differentiating malignant from benign thoracic lesions with transthoracic shear wave elastography (SWE). Methods: Patients assessed at the Department of Respiratory Medicine, Odense University Hospital, Denmark, between March 2023 and September 2023, were included if at least one thoracic lesion was detectable with TUS. All enrolled patients were examined with a 14-zone TUS protocol and SWE was performed at the location of the thoracic lesion. Three-month blinded journal audit by two independent assessors was used as reference test for the aetiology of the lesion. SWE cut-off value was determined by optimizing Youdens index. Results: In total, 100 patients (56 male, 44 female) were included with a median age of 75 years (IQR: 63-80). Malignant origin was concluded in 45 of 100 lesions. The receiver operating characteristic curve yielded an optimal cut-off point at 1.90 m/s with a sensitivity of 73.3% (95% CI: 58.1-85.4) and specificity of 72.7% (95% CI: 59.0-83.9) The associated positive and negative predictive values were 68.8% (95% CI: 53.7-81.3) and 76.9% (95% CI: 63.2-87.5), respectively. Discussion: This study suggests that SWE as a stand-alone modality is not reliable in differentiating between malignant and benign thoracic lesions. SWE used as part of a multiparametric ultrasound approach might still prove useful for the evaluation of thoracic lesions.
Authors: Christian Kildegaard, Casper Falster, Dinesh Addala, Marianne S. Jepsen, Martine S. Nielsen, Rune Wiig, Christian B, Laursen
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4404104758