Interior tomography is a promising technique that can be used to image large objects with high acquisition efficiency. However, it suffers from truncation artifacts and attenuation value bias due to the contribution from the parts of the object outside the ROI, which compromises its ability of quantitative evaluation in material or biological studies. In this paper, we present a hybrid source translation scanning mode for interior tomography, called hySTCT-where the projections inside the ROI and outside the ROI are finely sampled and coarsely sampled respectively to mitigate truncation artifacts and value bias within the ROI. Inspired by our previous work-virtual projection-based filtered backprojection (V-FBP) algorithm, we develop two reconstruction methods-interpolation V-FBP (iV-FBP) and two-step V-FBP (tV-FBP)-based on the linearity property of the inverse Radon transform for hySTCT reconstruction. The experiments demonstrate that the proposed strategy can effectively suppress truncated artifacts and improve the reconstruction accuracy within the ROI.