Offline Modeling and Mixed Reality Based Remote Diagnosis System for Patient-Specific Cardiovascular Diseases

This paper presents a mixed reality (MR) based, high-performance-computing supported, remotely connected collaborative platform for the diagnosis of and the surgical planning for cardiovascular diseases. Recognizing the fact that the human cardiovascular system is an interconnected network where pathological alterations in one organ (e.g., the heart) may critically impact the others (e.g., the brain), our study emphasizes the multi-organ hemodynamic coupling for the purpose of surgical planning. The system combines offline numerical modeling and MR-guided online collaboration, i.e., physics based simulations of hemodynamics involving multiple organs using patient-specific vascular geometry reconstructed from computed tomography (CT) or magnetic resonance imaging (MRI) images, high resolution numerical modeling, and a remote interface allowing doctors to interactively view and modify 3D holograms of a cardiovascular network and numerical simulation results with hand gestures or voice commands via head-mount displays. As an example, we investigate the perioperative ischemic stroke risk during a coronary revascularization procedure. The study shows how a stent-induced coronary geometry change propagates hemodynamic perturbations to the cerebral vascular, validates through synchronized multi-experts exploration of the virtual anatomy. By unifying high performance computing, multi-organ coupled numerical simulation, geographically distributed MR collaboration, and an interactive visualization, this system provides a diagnosis and surgical planning platform with a precision and convenience beyond existing approaches in medical practices.