Clinical performance of lung ultrasound in predicting ARDS morphology

Andrea Costamagna; Emanuele Pivetta; Alberto Goffi; Irene Steinberg; Pietro Arina; Anna Teresa Mazzeo; Lorenzo Del Sorbo; Simona Veglia; Ottavio Davini; Luca Brazzi; V Marco Ranieri; Vito Fanelli

doi:10.1186/s13613-021-00837-1

Clinical performance of lung ultrasound in predicting ARDS morphology

Ann Intensive Care. 2021 Mar 29;11(1):51. doi: 10.1186/s13613-021-00837-1.

Authors

Andrea Costamagna¹, Emanuele Pivetta², Alberto Goffi^{3

4}, Irene Steinberg⁵, Pietro Arina⁵, Anna Teresa Mazzeo^{5

6}, Lorenzo Del Sorbo^{3

7}, Simona Veglia⁸, Ottavio Davini⁸, Luca Brazzi^{1

5}, V Marco Ranieri⁹, Vito Fanelli^{10

11}

Affiliations

¹ Department of Anaesthesia and Critical Care, AOU Città della Salute e della Scienza di Torino, University of Turin, Corso Dogliotti 14, 10126, Turin, Italy.
² Department of General and Specialized Medicine, Division of Emergency Medicine and High Dependency Unit, Cancer Epidemiology Unit - AOU Città Della Salute e Della Scienza di Torino, Turin, Italy.
³ Interdepartmental Division of Critical Care Medicine and Department of Medicine, University of Toronto, Toronto, ON, Canada.
⁴ Department of Medicine, Division of Critical Care Medicine, St. Michael's Hospital, Toronto, ON, Canada.
⁵ Department of Surgical Sciences, University of Turin, Turin, Italy.
⁶ Dipartimento di Patologia Umana Dell'adulto e Dell'età Evolutiva, Anestesia e Rianimazione, Univesity of Messina, Messina, Italy.
⁷ Department of Medicine, Division of Respirology (Critical Care), University Health Network, Toronto, ON, Canada.
⁸ Department of Diagnostic Imaging and Radiotherapy, AOU Città della Salute e della Scienza di Torino-University of Turin, Turin, Italy.
⁹ Alma Mater Studiorum, Dipartimento di Scienze Mediche e Chirurgiche, Anesthesia and Intensive Care Medicine, Policlinico di Sant'Orsola, Università di Bologna, Bologna, Italy.
¹⁰ Department of Anaesthesia and Critical Care, AOU Città della Salute e della Scienza di Torino, University of Turin, Corso Dogliotti 14, 10126, Turin, Italy. vito.fanelli@unito.it.
¹¹ Department of Surgical Sciences, University of Turin, Turin, Italy. vito.fanelli@unito.it.

Abstract

Background: To assess diagnostic performance of lung ultrasound (LUS) in identifying ARDS morphology (focal vs non-focal), compared with the gold standard computed tomography.

Methods: Mechanically ventilated ARDS patients undergoing lung computed tomography and ultrasound were enrolled. Twelve fields, were evaluated. LUS score was graded from 0 (normal) to 3 (consolidation) according to B-lines extent. Total and regional LUS score as the sum of the four ventral (LUS_V), intermediate (LUS_I) or dorsal (LUS_D) fields, were calculated. Based on lung CT, ARDS morphology was defined as (1) focal (loss of aeration with lobar distribution); (2) non-focal (widespread loss of aeration or segmental loss of aeration distribution associated with uneven lung attenuation areas), and diagnostic accuracy of LUS in discriminating ARDS morphology was determined by AU-ROC in training and validation set of patients.

Results: Forty-seven patients with ARDS (25 training set and 22 validation set) were enrolled. LUS_TOT, LUS_V and LUS_I but not LUS_D score were significantly lower in focal than in non-focal ARDS morphologies (p < .01). The AU-ROC curve of LUS_TOT, LUS_V, LUS_I and LUS_D for identification of non-focal ARDS morphology were 0.890, 0.958, 0.884 and 0.421, respectively. LUS_V value ≥ 3 had the best predictive value (sensitivity = 0.95, specificity = 1.00) in identifying non-focal ARDS morphology. In the validation set, an LUS_V score ≥ 3 confirmed to be highly predictive of non-focal ARDS morphology, with a sensitivity and a specificity of 94% and 100%.

Conclusions: LUS had a valuable performance in distinguishing ARDS morphology.

Keywords: ARDS; ARDS morphology; Bedside tests; Lung ultrasound; Point of care diagnostic tests; Respiratory monitoring.