Deep learning enabled magnetic/rare earth hybrid nanorobots for multi-modal bioimaging and temperature sensing with surgical boundary determination

Abstract

Nanorobots, with miniature size, wireless operation, and flexible mobility, can access narrow spaces and are widely used in biomedicine. High-precision transport is vital for targeted drug delivery, disease diagnosis, and treatment, yet current research has limitations like insufficient single-imaging diagnosis and active tumor targeting. In this research, a magnetic nanorobot platform is proposed, combining magnetic ferric oxide substrate with rare earth nanoparticles (RENPs). This magnetic nanorobot features multi-modal imaging including NIR II fluorescence, MRI, and PA with high moving target effect (<5 s). After conjugated with antibodies against MET and VEGF, this platform enables multi-molecular targeting. Under an external magnetic field, the dual-targeting (active and physical magnetic) allows in vitro and in vivo precise tumor cell targeting with tumor imaging. Moreover, its NIR II luminescence enables enhanced real-time temperature detection (Region: 24.6–41.5℃). Especially, the deep learning allows NIR II imaging to simultaneously perform increased fluorescence imaging for surgical boundary definition and temperature sensing display (R²= 0.973, RMSE = 1.50℃). With high penetration and spatial resolution, this proposed magnetic/rare earth hybrid nanorobots holds great promise for precision biomedicine.