To validate new imaging modalities for prostate cancer, images must be three-dimensionally correlated with the histological ground truth. In this work, an interpolation algorithm is described to construct a reliable three-dimensional reference from two-dimensional (2D) histological slices. Eight clinically relevant in silico phantoms were designed to represent difficult-to-reconstruct tumour structures. These phantoms were subjected to different slicing procedures. Additionally, controlled errors were added to investigate the impact of varying slicing distance, front-face orientation, and inter-slice misalignment on the reconstruction performance. Using a radial-basis-function interpolation algorithm, the 2D data were reconstructed in three dimensions. Our results demonstrate that slice thicknesses up to 4 mm can be used to reliably reconstruct tumours of clinically significant size; the surfaces lay within a 1.5 mm 90%-error margin from each other and the volume difference between the original and reconstructed tumour structures does not exceed 10%. With these settings, Dice coefficients above 0.85 are obtained. The presented interpolation algorithm is able to reconstruct clinically significant tumour structures from 2D histology slices. Errors occurring are in the order of magnitude of common registration artefacts. The method’s applicability to real histopathological data is also shown in two resected prostates. An inter-slice spacing of 4 mm or less is recommended during histopathology; the use of a 1.5 mm error margin along the tumour contours can then ensure reliable mapping of the ground truth.