Cancer therapies such as chemotherapy, radiopharmaceutical therapy, and transarterial embolization rely on effective drug or radiation delivery through the bloodstream. Understanding how various drugs and particles, which form and size span multiple scales, are transported through blood and tissue is essential for optimizing treatment. Computational fluid dynamics (CFD) is a powerful tool to simulate blood flow and drug transport, solving flow governing equations under biologically realistic conditions. This review explores CFD applications in cancer therapy, focusing on transarterial embolization, tumor perfusion, and organ-on-a-chip systems. In radioembolization, CFD can predict microsphere transport and dose distribution to spare vital functions. Tumor perfusion modeling and organ-on-a-chip systems benefit from CFD by replicating vascular dynamics and drug dispersion. Despite its versatility and established mechanical principles, CFD faces challenges, including the need for patient-specific data, computational demands, and multiscale modeling. This review highlights opportunities for integrating CFD with imaging modalities and artificial intelligence tools to overcome these barriers and advance personalized cancer treatment.
Roncali et al. (Mon,) studied this question.