Douglas H. Kelley

This study maps glymphatic transport in the spinal cord using imaging and shows that it is disrupted after injury, with impaired clearance and worsened outcomes in AQP4-knockout mice.

This paper introduces MR-AIV, a physics-informed AI method to reconstruct brain-wide fluid velocity fields from MRI, revealing distinct transport mechanisms in health and disease.

This paper improves and evaluates MR-AIV, a physics-informed neural network for inferring brain fluid dynamics from MRI, showing stable results across different modeling choices.

This paper develops an AI velocimetry method to infer 3D CSF flow in mice, including pressure, shear stress, and flow rates, with uncertainty quantification.

The paper presents image analysis techniques for in vivo quantification of cerebrospinal fluid flow using fluorescent microspheres and discusses methods for measuring arterial diameter changes and applying these techniques to cervical lymphatic vessels.

The paper models glymphatic flow as a network of hydraulic resistances under different parametric scenarios to identify key parameters influencing CSF dynamics.

The paper demonstrates that bulk CSF flow in periarterial spaces is not an artifact of injection, using a dual-syringe system that prevents volume changes and pressure increases.

The paper reconciles fluid dynamics theory, simulation, and in vivo measurements of CSF flow in mouse brains by applying realistic boundary conditions.

The paper shows that the observed shapes of perivascular spaces (PVSs) in the brain have lower hydraulic resistance than concentric, circular annuli, allowing faster cerebrospinal fluid flow.