Cardiovascular disease (CVD) is the leading cause of death worldwide. In 2021, the number of CVD deaths worldwide was approximately 20.5 million. This number has been exacerbated in recent years due to the long-term effects of the COVID-19 pandemic. Cardiovascular simulations can be used to help doctors gain insight into their patient’s condition and to determine the appropriate diagnosis and the best treatment plan. Patient-specific cardiovascular simulations require geometric models and computational meshes of the heart and vascular system as well as any relevant implants, such as a pacemaker or stent. Patient-specific geometric models and meshes for use in computational simulations are typically generated from segmented patient medical images. There are numerous challenges in generating high-quality meshes of cardiac anatomies due to the complex geometry of the heart, its curvature, and its motion. When generating combined meshes of the patient anatomy and an implanted medical device, non-manifold topology meshes must be generated due to the embedded geometry. Another challenge is to generate meshes rapidly enough so they can be used in cardiovascular simulations in clinical settings. In this talk, we will present several examples from our research in patient-specific cardiovascular mesh generation. Examples will include our high-order mesh generation approaches and the meshes that are being generated for use in cardiac ablation simulations. They also include dynamic mesh generation methods and meshes of the inferior vena cava (IVC), IVC filter, and blood clots generated for use in simulations on the prevention of pulmonary embolism. Portions of the talk represent joint work with researchers from University of Michigan, Rochester Institute of Technology, Penn State, Penn State Hershey Medical Center, Penn State Applied Research Laboratory, and University of Utah.