ReviewFrontiers in surgery2025
Role of VATS-US in identifying and characterizing pulmonary nodules: a narrative review.
Review in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Metabolomics-assisted evaluation of differences and clinical value between ablation and surgical treatment for lung adenocarcinoma.Frontiers in oncology · 2026Article
- Microbubbles at the bedside: intracavitary CEUS to confirm chest-drain position and loculations.Journal of ultrasound · 2025Article
- Feasibility of intraoperative Doppler ultrasound for intersegmental plane identification in pulmonary segmentectomy: a retrospective preliminary validation study.Journal of thoracic disease · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to show the efficacy described in the scientific literature of lung ultrasound (LU) during video-assisted thoracic surgery (VATS) to determine the location and characterization of pulmonary nodules. The results showed that intraoperative LU is especially useful in localizing lung lesions by VATS with a sensitivity close to 100%. It was also shown to be useful in planning very precise lung resections, reducing the resection of healthy lung tissue. Although general criteria could be established for the degree of benignity/malignancy of lung lesions based on the ultrasound patterns obtained, the great variability observed in these patterns does not offer sufficient guarantees to make a reliable diagnosis. In this sense, the application of Doppler ultrasound or the utilization of Intraoperative Contrast-Enhanced Ultrasound (Io-CEUS) in a completely collapsed lung can be advantageous for the accurate localization and characterization of pulmonary lesions. Even so, at present, definitive confirmation of the nature of lung lesions usually requires biopsy and histopathological study. The development of artificial intelligence algorithms that integrate the results of histological analyses with various types of ultrasonographic patterns (based on pulmonary aeration obtained, as well as Doppler and Io-CEUS records) will likely represent the future of ultrasonographic differentiation of these lesions.
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