Deep Learning Enhanced Near Infrared-II Imaging and Image-Guided Small Interfering Ribonucleic Acid Therapy of Ischemic Stroke.

Abstract

Small interfering RNA (siRNA) targeting the NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome has emerged as a promising therapeutic strategy to mitigate infarct volume and brain injury following ischemic stroke. However, the clinical translation of siRNA-based therapies is significantly hampered by the formidable blood-brain barrier (BBB), which restricts drug penetration into the central nervous system. To address this challenge, we have developed an innovative long-circulating near-infrared II (NIR-II) nanoparticle platform YWFC NPs, which is meticulously engineered to enhance BBB transcytosis and enable efficient delivery of siRNA targeting NLRP3 (siNLRP3@YWFC NPs) in preclinical models of ischemic stroke. Furthermore, we integrated advanced deep learning neural network algorithms to optimize <i>in vivo</i> NIR-II imaging of the cerebral infarct penumbra, achieving an improved signal-to-background ratio at 72 h poststroke. <i>In vivo</i> studies employing middle cerebral artery occlusion (MCAO) mouse models demonstrated that image-guided therapy with siNLRP3@YWFC NPs, guided by prolonged NIR-II imaging, resulted in significant therapeutic benefits.