Lung US (LUS) a valuable tool in identifying asbestos-exposed subjects who require chest-CT

No specific recommendations exist regarding when and for which asbestos-exposed patients chest CT should be conducted. In the last decades, LUS has proven to be a suitable first line tool to identify pleural and parenchymal disease. <bold>Aim:</bold> evaluate role of LUS in identifying signs of asbestos-related pleural-parenchymal disease in patients with asbestos exposure which may require further radiological investigations. <bold>Methods:</bold> subjects with an history of asbestos exposure were included and evaluated with LUS, 12 anatomic landmarks were sequenced and a score between 0-2 based on LUS impairment was assigned (Fig). US score≥1 even without respiratory symptoms were considered worthy of further investigation with chest CT. <bold>Results:</bold> We enrolled 50 patients. Mean age 67,1±10,6 yrs; 75,5% male, 53,1% had dyspnea. 25 patients had US score≥1 and 18 performed CT (7 refused): 15 (83,3%) had a pathological CT (10 pleural thickening and 5 interstitial lung disease). 6 out of 25 patients with US score<1 had CT performed for other reasons and 5 had a non-pathological CT. The prevalence of pathological CT was significantly higher in subjects with US score≥1 (p=0.003). Lung US showed a sensitivity of 93,7% and a specificity of 62,5% for pleural and parenchymal asbestosis. <bold>Conclusions:</bold> lung-US has shown a high sensitivity to detect pleural and interstitial lung alterations and can help to identify asbestos-exposed patients who need chest-CT.

Authors

Institutions

Publication Details

Published
2024-09-14
DOI
https://doi.org/10.1183/13993003.congress-2024.pa3449
Primary Topic
Occupational and environmental lung diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lung US (LUS) a valuable tool in identifying asbestos-exposed subjects who require chest-CT

Sara De Magistris, Gianfranco Puppo, Anna Maria Carletti, Valentina Pinelli et al.
Occupational and environmental lung diseases
article

Lung US (LUS) a valuable tool in identifying asbestos-exposed subjects who require chest-CT

Sara De Magistris, Gianfranco Puppo, Anna Maria Carletti, Valentina Pinelli, Luigi Chiaffi, N. Colombo, Federica Novelli, Massimiliano Sivori, Sofia Bailo
article en

Abstract

No specific recommendations exist regarding when and for which asbestos-exposed patients chest CT should be conducted. In the last decades, LUS has proven to be a suitable first line tool to identify pleural and parenchymal disease. <bold>Aim:</bold> evaluate role of LUS in identifying signs of asbestos-related pleural-parenchymal disease in patients with asbestos exposure which may require further radiological investigations. <bold>Methods:</bold> subjects with an history of asbestos exposure were included and evaluated with LUS, 12 anatomic landmarks were sequenced and a score between 0-2 based on LUS impairment was assigned (Fig). US score≥1 even without respiratory symptoms were considered worthy of further investigation with chest CT. <bold>Results:</bold> We enrolled 50 patients. Mean age 67,1±10,6 yrs; 75,5% male, 53,1% had dyspnea. 25 patients had US score≥1 and 18 performed CT (7 refused): 15 (83,3%) had a pathological CT (10 pleural thickening and 5 interstitial lung disease). 6 out of 25 patients with US score<1 had CT performed for other reasons and 5 had a non-pathological CT. The prevalence of pathological CT was significantly higher in subjects with US score≥1 (p=0.003). Lung US showed a sensitivity of 93,7% and a specificity of 62,5% for pleural and parenchymal asbestosis. <bold>Conclusions:</bold> lung-US has shown a high sensitivity to detect pleural and interstitial lung alterations and can help to identify asbestos-exposed patients who need chest-CT.

University of Pisa (IT), IMT School for Advanced Studies Lucca (IT), NATO Centre for Maritime Research and Experimentation (IT), University of Genoa (IT)
Zero hunger
Openalex Percentile: Top 63%
Occupational and environmental lung diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.