Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients. Issue 138 (May 2021)

• Record Type: Journal Article
• Authors: Rizzetto, Francesco; Perillo, Noemi; Artioli, Diana; Travaglini, Francesca; Cuccia, Alessandra; Zannoni, Stefania; Tombini, Valeria; Di Domenico, Sandro Luigi; Albertini, Valentina; Bergamaschi, Marta; Cazzaniga, Michela; De Mattia, Cristina; Torresin, Alberto; Vanzulli, Angelo
• Is Part Of: European journal of radiology. Issue 138(2021)
• Publication Date: 2021-05
• Subjects: COVID-19 Coronavirus Disease 2019 -- IQR interquartile range -- LUS lung ultrasound -- NLR negative likelihood ratio -- PLR positive likelihood ratio -- SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 -- SE sensitivity -- SP specificity -- %WALV well-aerated lung percentage; COVID-19 -- Lung -- Ultrasonography -- Tomography -- X-Ray computed -- Diagnostic techniques and procedures; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2021.109650
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Lung ultrasound is a valuable tool for case identification in COVID-19. The correlation between lung ultrasounds and CT findings in COVID-19 is moderate. Lung ultrasounds can help to rule out extensive lung involvement in COVID-19. Abstract: Purpose: The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear. Methods: PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospectively analysed. In both modalities, twelve peripheral lung zones were identified and given a Severity Score basing on main lesion pattern. On CT scans the well-aerated lung volume (%WALV) was visually estimated. Per-patient and per-zone assessments of LUS classification performance taking CT findings as reference were performed, further revisioning the images in case of discordant results. Correlations between number of disease-positive lung zones, Severity Score and %WALV on both LUS and CT were assessed. The area under receiver operating characteristic curve (AUC) was calculated to determine LUS performance in detecting %WALV ≤ 70 %. Results: The study included 219 COVID-19 patients with abnormal chest CT. LUS correctly identified as positive 217 (99 %) patients, but per-zone analysis showed sensitivity = 75 % and specificity = 66 %. The revision of the 121 (55 %) cases with positive LUS and negative CT revealed COVID-compatible lesions in 42 (38 %) CT scans. Number of disease-positive zones, Severity Score and %WALV between LUS and CT showed moderate correlations. The AUCs for LUS Severity Score and number of LUS-positive zones did not differ in detecting %WALV ≤ 70 %. Conclusion: LUS in COVID-19 is valuable for case identification but shows only moderate correlation with CT findings as for lesion patterns and severity quantification. The number of disease-positive lung zones in LUS alone was sufficient to discriminate relevant disease burden.