Quantitative lung ultrasonography: a putative new algorithm for automatic detection and quantification of B-lines

BackgroundThis pilot study was designed to develop a fully automatic and quantitative scoring system of B-lines (QLUSS: quantitative lung ultrasound score) involving the pleural line and to compare it with previously described semi-quantitative scores in the measurement of extravascular lung water as determined by standard thermo-dilution.MethodsThis was a prospective observational study of 12 patients admitted in the intensive care unit with acute respiratory distress and each provided with 12 lung ultrasound (LUS) frames. Data collected from each patient consisted in five different scores, four semi-quantitative (nLUSS, cLUSS, qLUSS, %LUSS) and quantitative scores (QLUSS). The association between LUS scores and extravascular lung water (EVLW) was determined by simple linear regression (SLR) and robust linear regression (RLR) methods. A correlation analysis between the LUS scores was performed by using the Spearman rank test. Inter-observer variability was tested by computing intraclass correlation coefficient (ICC) in two-way models for agreement, basing on scores obtained by different raters blinded to patients' conditions and clinical history.ResultsIn the SLR, QLUSS showed a stronger association with EVLW (R-2=0.57) than cLUSS (R-2=0.45) and nLUSS (R-2=0.000), while a lower association than qLUSS (R-2=0.85) and %LUSS (R-2=0.72) occurred. By applying RLR, QLUSS showed an association for EVLW (R-2=0.86) comparable to qLUSS (R-2=0.85) and stronger than %LUSS (R-2=0.72). QLUSS was significantly correlated with qLUSS (r=0.772; p=0.003) and %LUSS (r=0.757; p=0.005), but not with cLUSS (r=0.561; p=0.058) and nLUSS (r=0.105; p=0.744). Moreover, QLUSS showed the highest ICC (0.998; 95%CI from 0.996 to 0.999) among the LUS scores.ConclusionsThis study demonstrates that computer-aided scoring of the pleural line percentage affected by B-lines has the potential to assess EVLW. QLUSS may have a significant impact, once validated with a larger dataset composed by multiple real-time frames. This approach has the potentials to be advantageous in terms of faster data analysis and applicability to large sets of data without increased costs. On the contrary, it is not useful in pleural effusion or consolidations.