OBJECTIVES: Lung CT is the reference imaging technique for acute respiratory distress syndrome, but requires transportation outside the intensive care and x-ray exposure. Lung ultrasound is a promising, inexpensive, radiation-free, tool for bedside imaging. Aim of the present study was to compare the global and regional diagnostic accuracy of lung ultrasound and CT scan. DESIGN: A prospective, observational study. SETTING: Intensive care and radiology departments of a University hospital. PATIENTS: Thirty-two sedated, paralyzed acute respiratory distress syndrome patients (age 65 ± 14 yr, body mass index 25.9 ± 6.5 kg/m, and PaO2/FIO2 139 ± 47). INTERVENTIONS: Lung CT scan and lung ultrasound were performed at positive end-expiratory pressure 5 cm H2O. A standardized assessment of six regions per hemithorax was used; each region was classified for the presence of normal aeration, alveolar-interstitial syndrome, consolidation, and pleural effusion. Agreement between the two techniques was calculated, and diagnostic variables were assessed for lung ultrasound using lung CT as a reference. MEASUREMENTS AND MAIN RESULTS: Global agreement between lung ultrasound and CT ranged from 0.640 (0.391-0.889) to 0.934 (0.605-1.000) and was on average 0.775 (0.577-0.973). The overall sensitivity and specificity of lung ultrasound ranged from 82.7% to 92.3% and from 90.2% to 98.6%, respectively. Similar results were found with regional analysis. The diagnostic accuracy of lung ultrasound was significantly higher when those patterns not reaching the pleural surface were excluded (area under the receiver operating characteristic curve: alveolar-interstitial syndrome 0.854 [0.821-0.887] vs 0.903 [0.852-0.954]; p = 0.049 and consolidation 0.851 [0.818-0.884] vs 0.896 [0.862-0.929]; p = 0.044). CONCLUSIONS: Lung ultrasound is a reproducible, sensitive, and specific tool, which allows for bedside detections of the morphologic patterns in acute respiratory distress syndrome. The presence of deep lung alterations may impact the diagnostic performance of this technique.
OBJECTIVES: Lung CT is the reference imaging technique for acute respiratory distress syndrome, but requires transportation outside the intensive care and x-ray exposure. Lung ultrasound is a promising, inexpensive, radiation-free, tool for bedside imaging. Aim of the present study was to compare the global and regional diagnostic accuracy of lung ultrasound and CT scan. DESIGN: A prospective, observational study. SETTING: Intensive care and radiology departments of a University hospital. PATIENTS: Thirty-two sedated, paralyzed acute respiratory distress syndromepatients (age 65 ± 14 yr, body mass index 25.9 ± 6.5 kg/m, and PaO2/FIO2 139 ± 47). INTERVENTIONS: Lung CT scan and lung ultrasound were performed at positive end-expiratory pressure 5 cm H2O. A standardized assessment of six regions per hemithorax was used; each region was classified for the presence of normal aeration, alveolar-interstitial syndrome, consolidation, and pleural effusion. Agreement between the two techniques was calculated, and diagnostic variables were assessed for lung ultrasound using lung CT as a reference. MEASUREMENTS AND MAIN RESULTS: Global agreement between lung ultrasound and CT ranged from 0.640 (0.391-0.889) to 0.934 (0.605-1.000) and was on average 0.775 (0.577-0.973). The overall sensitivity and specificity of lung ultrasound ranged from 82.7% to 92.3% and from 90.2% to 98.6%, respectively. Similar results were found with regional analysis. The diagnostic accuracy of lung ultrasound was significantly higher when those patterns not reaching the pleural surface were excluded (area under the receiver operating characteristic curve: alveolar-interstitial syndrome 0.854 [0.821-0.887] vs 0.903 [0.852-0.954]; p = 0.049 and consolidation 0.851 [0.818-0.884] vs 0.896 [0.862-0.929]; p = 0.044). CONCLUSIONS: Lung ultrasound is a reproducible, sensitive, and specific tool, which allows for bedside detections of the morphologic patterns in acute respiratory distress syndrome. The presence of deep lung alterations may impact the diagnostic performance of this technique.
Authors: V Fraile Gutiérrez; J M Ayuela Azcárate; D Pérez-Torres; L Zapata; A Rodríguez Yakushev; A Ochagavía Journal: Med Intensiva (Engl Ed) Date: 2020-05-04
Authors: Arif Hussain; Gabriele Via; Lawrence Melniker; Alberto Goffi; Guido Tavazzi; Luca Neri; Tomas Villen; Richard Hoppmann; Francesco Mojoli; Vicki Noble; Laurent Zieleskiewicz; Pablo Blanco; Irene W Y Ma; Mahathar Abd Wahab; Abdulmohsen Alsaawi; Majid Al Salamah; Martin Balik; Diego Barca; Karim Bendjelid; Belaid Bouhemad; Pablo Bravo-Figueroa; Raoul Breitkreutz; Juan Calderon; Jim Connolly; Roberto Copetti; Francesco Corradi; Anthony J Dean; André Denault; Deepak Govil; Carmela Graci; Young-Rock Ha; Laura Hurtado; Toru Kameda; Michael Lanspa; Christian B Laursen; Francis Lee; Rachel Liu; Massimiliano Meineri; Miguel Montorfano; Peiman Nazerian; Bret P Nelson; Aleksandar N Neskovic; Ramon Nogue; Adi Osman; José Pazeli; Elmo Pereira-Junior; Tomislav Petrovic; Emanuele Pivetta; Jan Poelaert; Susanna Price; Gregor Prosen; Shalim Rodriguez; Philippe Rola; Colin Royse; Yale Tung Chen; Mike Wells; Adrian Wong; Wang Xiaoting; Wang Zhen; Yaseen Arabi Journal: Crit Care Date: 2020-12-24 Impact factor: 9.097