In this paper, we investigate multiphase flow monitoring inside metallic pipes by qualitative microwave imaging, where foreign objects inside the liquid flow are monitored to eliminate contamination. The motivation stems from the fact that conventional tomographic approaches of microwave imaging are inherently not suitable for real-time flow monitoring due to their computational requirements as these techniques aim to retrieve the dielectric permittivity profile inside the pipeline. In this context, we envision that the factorization method of qualitative inverse scattering theory, which is a shape retrieval algorithm from scattered field measurements, provides a better alternative for flow monitoring. To demonstrate the feasibility of such an approach, we first reformulate the factorization method by considering dyadic Green's functions inside a cuboid cavity with perfectly conducting walls. Later, the formulation is simplified for a specific microwave measurement configuration to accelerate the reconstructions for real-time flow monitoring. Finally, flow monitoring is realized as a differential imaging procedure where foreign objects are detected by using differences of multi-static scattering parameters that are measured consecutively. The simulation studies performed for food and petroleum flows reveal the capabilities of the technique as a viable solution for different industrial flows.