In particle therapy sub-millimeter sized heterogeneities like lung tissue cause a Bragg peak degradation, which should be considered in treatment planning to ensure an optimal dose distribution in tumor tissue. To determine the magnitude of this degradation extensive experiments could be carried out. More convenient and reproducible is the use of our mathematical model to describe the degradation properties of lung tissue and to design 3D-printable substitutes based on high-resolution CT images of human lung samples. High-resolution CT images of human lung samples (resolution: 4 μm) were used to create binary cubic datasets with voxels corresponding to either air or lung tissue. The number of tissue voxels is calculated along the z-axis for every lateral position. This represents the “tissue length” for all particle paths through the dataset of a parallel beam. The square based lung substitute is divided into columns with different heights corresponding to the occurring tissue lengths. The columns lateral extend complies with the quantity of the corresponding tissue lengths present in the dataset. The lung substitutes were validated by Monte Carlo simulations with the Monte Carlo toolkit TOPAS. The Monte Carlo simulations proved that the depth dose distributions and hence the Bragg peak degradations of the lung substitutes mimics the degradation of the corresponding lung tissue sample.