Development and Validation of Spatial Coherence Beamformers for Lung Ultrasound Imaging

Lung ultrasonography is widely used for real-time diagnostics and monitoring in patients with respiratory and extrapulmonary diseases. However, the interpretation of diagnostic lung ultrasound images relies on the visualization of complex artifacts arising from the reverberation physics within the tissue/air interface at the lung surface. Here, we develop a lung-specific spatial coherence beamformer designed for better diagnostic accuracy in fluid retention in the lung. Experimentally validated simulations based on the first principles of wave-propagation physics (Fullwave 2) were performed in realistic maps of the human chest wall and swine lung histology to generate 60 ultrasound images with known ground truth. Short-Lag Spatial Coherence (SLSC) and conventional Delay-and-Sum (DAS) beamforming techniques were implemented and applied to the generated RF data. Detectability of key diagnostic indicators was significantly higher in SLSC images compared to DAS (gCNR 0.73±0.1 vs 0.58±0.06, p < 0.05). These results demonstrate that Short-Lag Spatial Coherence beamforming makes lung image quality higher due to exclusion of reverberating component and may improve diagnostic accuracy and reproducibility of lung ultrasound.