Second-order grey-scale texture analysis of pleural ultrasound images to differentiate acute respiratory distress syndro
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ORIGINAL RESEARCH
Second‑order grey‑scale texture analysis of pleural ultrasound images to differentiate acute respiratory distress syndrome and cardiogenic pulmonary edema Claudia Brusasco1 · Gregorio Santori2 · Guido Tavazzi3 · Gabriele Via4 · Chiara Robba5 · Luna Gargani6 · Francesco Mojoli3 · Silvia Mongodi7 · Elisa Bruzzo8 · Rosella Trò8 · Patrizia Boccacci8 · Alessandro Isirdi9 · Francesco Forfori9 · Francesco Corradi1,9 · UCARE (Ultrasound in Critical care and Anesthesia Research Group)9 Received: 29 August 2020 / Accepted: 2 December 2020 © The Author(s) 2020
Abstract Discriminating acute respiratory distress syndrome (ARDS) from acute cardiogenic pulmonary edema (CPE) may be challenging in critically ill patients. Aim of this study was to investigate if gray-level co-occurrence matrix (GLCM) analysis of lung ultrasound (LUS) images can differentiate ARDS from CPE. The study population consisted of critically ill patients admitted to intensive care unit (ICU) with acute respiratory failure and submitted to LUS and extravascular lung water monitoring, and of a healthy control group (HCG). A digital analysis of pleural line and subpleural space, based on the GLCM with second order statistical texture analysis, was tested. We prospectively evaluated 47 subjects: 16 with a clinical diagnosis of CPE, 8 of ARDS, and 23 healthy subjects. By comparing ARDS and CPE patients’ subgroups with HCG, the one-way ANOVA models found a statistical significance in 9 out of 11 GLCM textural features. Post-hoc pairwise comparisons found statistical significance within each matrix feature for ARDS vs. CPE and CPE vs. HCG (P ≤ 0.001 for all). For ARDS vs. HCG a statistical significance occurred only in two matrix features (correlation: P = 0.005; homogeneity: P = 0.048). The quantitative method proposed has shown high diagnostic accuracy in differentiating normal lung from ARDS or CPE, and good diagnostic accuracy in differentiating CPE and ARDS. Gray-level co-occurrence matrix analysis of LUS images has the potential to aid pulmonary edemas differential diagnosis. Keywords Artificial intelligence · Computer aided diagnosis · Quantitative lung ultrasonography · Lung ultrasonography · Heart failure · Acute respiratory failure Abbreviations ARDS Acute respiratory distress syndrome CPE Cardiogenic pulmonary edema GLCM Gray-level co-occurrence matrix LUS Lung ultrasound ICU Intensive care unit HCG Healthy control group EVLW Extravascular lung water The work has been performed at Department of Anaesthesia and Intensive Care Unit, E.O. Ospedali Galliera, Genoa, Italy. Supplementary Information The online version of this article (https://doi.org/10.1007/s10877-020-00629-1) contains supplementary material, which is available to authorized users. * Francesco Corradi [email protected] Extended author information available on the last page of the article
LV Left ventricular PVPI Pulmonary vascular permeability index AUC Area under the ROC curve
1 Introduction Acute hypoxemic respiratory failu
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