Over the past several decades, ultrasonography has evolved into an essential tool in the evaluation and management of pleural disease. Thoracic ultrasonography (TUS) now plays a vital role in pleural procedures. The increasing affordability and accessibility of point-of-care ultrasound (POCUS) have further reinforced its value as a cost-effective tool for the rapid assessment of pleural effusions.
Notably, prior studies have demonstrated that TUS is comparable in accuracy to CT scan imaging for the evaluation of pleural effusions.1 Furthermore, TUS has better diagnostic performance than CT scans or X-rays for predicting complicated parapneumonic effusion.2 This is likely because of better visualization of septation with TUS. Despite these advances, substantial opportunities remain to further expand its applications in the assessment of pleural disease.
Pleural effusions traditionally have been classified as transudate or exudate based on Light’s criteria from more than five decades ago, but few studies have examined the utility of TUS in classifying transudate or exudate. In previous studies, TUS was found to be inadequately reliable in the diagnosis of transudative pleural effusion, as 56% of anechoic effusions were exudative; but complex-appearing pleural effusion on TUS was found to have high predictive value for the diagnosis of exudative pleural effusion.3 Recently, Gardiner and colleagues described a TUS-based scoring system called DUETS (Diaphragmatic nodularity, Unilateral, Echogenicity, pleural Thickening, and Septations).4 DUETS ≥2 was found to outperform Light’s criteria with fewer misclassifications.
Contrast-enhanced ultrasound (CEUS) is an emerging tool for the evaluation of pleural and parenchymal disease. CEUS uses a microbubble contrast agent that is intravenously injected to dynamically visualize pleural tissue perfusion. CEUS can aid in differentiating benign pleural disease from malignant pleural disease, as well as lung abscess from pleural infection.5
Finally, no discussion of technological advancement is complete without acknowledging the impact of artificial intelligence (AI).6 AI is reshaping TUS through multiple avenues, with one of the most immediate being its integration into POCUS. While POCUS remains operator-dependent and influenced by user experience and technical skill, AI-assisted guidance has the potential to improve image acquisition and interpretation, particularly among less-experienced operators, thereby enhancing diagnostic yield.
These advancements highlight potential pathways for further integrating TUS in the evaluation and management of pleural effusions. As the accuracy of ultrasound-based effusion assessment continues to improve, there is potential to reduce reliance on CT scan imaging and reduce patient radiation exposure while also decreasing the need for invasive diagnostic procedures and enhancing overall diagnostic precision.
References
1. Yang PC, Luh KT, Chang DB, Wu HD, Yu CJ, Kuo SH. Value of sonography in determining the nature of pleural effusion: analysis of 320 cases. AJR Am J Roentgenol. 1992;159(1):29-33. doi:10.2214/ajr.159.1.1609716
2. Svigals PZ, Chopra A, Ravenel JG, Nietert PJ, Huggins JT. The accuracy of pleural ultrasonography in diagnosing complicated parapneumonic pleural effusions. Thorax. 2017;72(1):94-95. doi:10.1136/thoraxjnl-2016-208904
3. Shkolnik B, Judson MA, Austin A, et al. Diagnostic accuracy of thoracic ultrasonography to differentiate transudative from exudative pleural effusion. Chest. 2020;158(2):692-697. doi:10.1016/j.chest.2020.02.051
4. Gardiner A, Ling R, Chan YH, et al. DUETS for Light’s in separating exudate from transudate. Respirology. 2024;29(11):976-984. doi:10.1111/resp.14780
5. Boccatonda A, Brighenti A, Piamonti D, et al. The role of CEUS in the diagnosis and follow-up of pleuropulmonary diseases and interventional procedures. J Clin Med. 2026;15(6):2292. doi:10.3390/jcm15062292
6. Baloescu C, Bailitz J, Cheema B, et al. Artificial intelligence-guided lung ultrasound by nonexperts. JAMA Cardiol. 2025;10(3):245-253. doi:10.1001/jamacardio.2024.4991
