Monte Carlo simulations are extensively used in PET to evaluate the accuracy with which PET images can yield reliable estimates of parameters of interest. For such applications, the simulated images should be as realistic as possible so that conclusions can be extrapolated to clinical PET images. In this work, we describe a method for introducing realistic modeling of radiotracer heterogeneity into Monte Carlo simulations of patient PET scans. The modeling of the complex physiological activity distribution in healthy regions is directly based on real patient PET/CT images, and realistic tumor shapes can be included into these regions. This method represents a competitive alternative to the use of complex anthropomorphic phantoms such as the XCAT, that require a fixed activity per structure. The method is extended to the simulation of serial PET scans with tumor changes, as acquired in the context of therapy monitoring, and this extension is validated using a patient study. Using the proposed method, very realistic patient PET images can be produced for evaluation purposes.In addition, a strategy to efficiently simulate many sets of pathological cases, based on a unique background physiological activity distribution, is described and carefully assessed using a numerical phantom. The background activity is simulated only once, while tumors are simulated separately. The data are then recombined in a specific way so that the final image has the same properties as images produced by simulating pathological and tumor activities at the same time.