A Diffusion Model for Simulation Ready Coronary Anatomy with Morpho-skeletal Control
This work addresses the need for device designers to simulate interventions with varied anatomies, though it appears incremental by extending existing diffusion methods to a specific domain.
The study tackled the problem of generating realistic and controllable coronary artery anatomies for virtual intervention simulations by using Latent Diffusion Models with morpho-skeletal conditioning, enabling custom synthesis based on anatomic constraints.
Virtual interventions enable the physics-based simulation of device deployment within coronary arteries. This framework allows for counterfactual reasoning by deploying the same device in different arterial anatomies. However, current methods to create such counterfactual arteries face a trade-off between controllability and realism. In this study, we investigate how Latent Diffusion Models (LDMs) can custom synthesize coronary anatomy for virtual intervention studies based on mid-level anatomic constraints such as topological validity, local morphological shape, and global skeletal structure. We also extend diffusion model guidance strategies to the context of morpho-skeletal conditioning and propose a novel guidance method for continuous attributes that adaptively updates the negative guiding condition throughout sampling. Our framework enables the generation and editing of coronary anatomy in a controllable manner, allowing device designers to derive mechanistic insights regarding anatomic variation and simulated device deployment.