Chest digital tomosynthesis (DTS) provides a compromise between conventional radiography and computed tomography in terms of radiation dose and diagnostic capability. Most reconstruction algorithms used in DTS assume a stationary object during acquisition. However, projection data are acquired over a finite time interval, during which internal anatomical structures may exhibit temporal variability. In this study, projection-domain intensity variations were analyzed to assess temporal consistency of DTS data. Mean intensity values were measured across multiple regions of interest (ROIs), forming temporal intensity profiles for anatomically distinct regions. Additionally, intensity profiles across anatomical transitions were evaluated in both projection data and reconstructed slices. The results show that while global intensity variations are primarily driven by acquisition geometry, certain regions exhibit local fluctuations, indicating reduced temporal consistency. Comparative analysis revealed that regions with increased variability correspond to degraded contrast and broadened transition boundaries in reconstructed slices. In particular, the heart–lung interface showed a significant contrast reduction compared to the stomach–lung interface, despite similar contrast levels in projection images. These findings indicate that even small temporal inconsistencies in projection data can lead to cumulative reconstruction errors. The proposed ROI-based analysis provides a simple approach for identifying such regions directly from projection data and suggests directions for improving reconstruction quality, including more consistent 3-D reconstruction of cardiac slices across different phases of the cardiac cycle.