Lung ultrasound (LUS) imaging can be highly sensitive to disease. However, lung imaging depends on reverberation that occurs at the lung interface, which is complex and upends the conventional time-space relationship in delay-and-sum beamforming resulting in images that require the interpretation of artifacts. Establishing a clear link between ultrasound images and underlying alveolar or fibrotic state of the lung could improve the diagnostic accuracy and clinical deployment of lung ultrasound and potentially establish LUS as a gold-standard imaging modality. Here, it is shown how histology-derived acoustical maps of the lung, Visible Human maps of the abdomen, and Fullwave simulations of ultrasound propagation can accurately model the multiple scattering physics at the lung interface. Lung B-mode images are generated based on the first principles of propagation and multiple scattering and they are compared to clinical imaging. In silico modifications of the aeration/porosity and the fluid-to-tissue ratio in the lung parenchyma are related to the corresponding changes in B-mode images. Additionally, the patterns of superficial/subpleural air inclusions were analyzed and mapped to corresponding B-mode image markers (white lung, single and multiple B-lines, A-lines). This establishes a validated framework for quantitative imaging of lung disease and the development of LUS-specific beamforming.