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Lung Ultrasound in COVID‐19 and Post‐COVID‐19 Patients, an Evidence‐Based Approach

Articolo
Data di Pubblicazione:
2021
Abstract:
Objectives: Worldwide, lung ultrasound (LUS) was utilized to assess coronavirus disease 2019 (COVID-19) patients. Often, imaging protocols were however defined arbitrarily and not following an evidence-based approach. Moreover, extensive studies on LUS in post-COVID-19 patients are currently lacking. This study analyses the impact of different LUS imaging protocols on the evaluation of COVID-19 and post-COVID-19 LUS data. Methods: LUS data from 220 patients were collected, 100 COVID-19 positive and 120 post-COVID-19. A validated and standardized imaging protocol based on 14 scanning areas and a 4-level scoring system was implemented. We utilized this dataset to compare the capability of 5 imaging protocols, respectively based on 4, 8, 10, 12, and 14 scanning areas, to intercept the most important LUS findings. This to evaluate the optimal trade-off between a time-efficient imaging protocol and an accurate LUS examination. We also performed a longitudinal study, aimed at investigating how to eventually simplify the protocol during follow-up. Additionally, we present results on the agreement between AI models and LUS experts with respect to LUS data evaluation. Results: A 12-areas protocol emerges as the optimal trade-off, for both COVID-19 and post-COVID-19 patients. For what concerns follow-up studies, it appears not to be possible to reduce the number of scanning areas. Finally, COVID-19 and post-COVID-19 LUS data seem to show differences capable to confuse AI models that were not trained on post-COVID-19 data, supporting the hypothesis of the existence of LUS patterns specific to post-COVID-19 patients. Conclusions: A 12-areas acquisition protocol is recommended for both COVID-19 and post-COVID-19 patients, also during follow-up.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
COVID-19; SARS-CoV-2; artificial intelligence; lung ultrasound; post-COVID-19
Elenco autori:
Demi, Libertario; Mento, Federico; Di Sabatino, Antonio; Fiengo, Anna; Sabatini, Umberto; Macioce, Veronica Narvena; Robol, Marco; Tursi, Francesco; Sofia, Carmelo; Di Cienzo, Chiara; Smargiassi, Andrea; Inchingolo, Riccardo; Perrone, Tiziano
Autori di Ateneo:
DI SABATINO ANTONIO
Link alla scheda completa:
https://iris.unipv.it/handle/11571/1514513
Pubblicato in:
JOURNAL OF ULTRASOUND IN MEDICINE
Journal
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