Near-Infrared Theranostics: Cutting-Edge Innovations in Cancer Diagnosis and Therapy

Theranostics of near-infrared (NIR) imaging, which originated from the merging of diagnostic imaging and targeted therapy, is one of the most remarkable achievements in the early diagnosis and treatment of malignancies. The NIR is divided into two optical windows: the first NIR I (700-900 nm) and the second NIR II (1000-1700 nm), which enable improved tissue penetration, reduced autofluorescence, and higher resolution compared with visible light.

A literature search was conducted across databases, including PubMed, ScienceDirect, and the Cochrane Library. Eligibility criteria were randomized controlled trials (RCTs), preclinical/clinical studies, systematic reviews, and meta-analyses about NIR-related diagnosis and treatment modalities in oncology. Data extraction and synthesis focused on optical window properties (NIR-I and NIR-II), mechanisms of action, nanomaterial platforms, types of cancer treated, and clinical results.

NIR theranostic probes, including GBNPs, carbon nanotubes, and conjugated polymers, were found to possess good PTA and ROS generation capability, thus improving the therapeutic efficacy of PTTs and PDTs. NIR photoimmunotherapy (NIR-PIT) promoted ICD and enhanced CD8+ T cell-mediated tumor attack. NIR-II probes enabled deeper tissue penetration, allowing high tumor-to-background contrast imaging. Clinical trials in brain, breast, prostate, lung, and ovarian cancer revealed improved intraoperative guidance, tumor detection, and treatment.

Incorporation of NIR imaging into therapeutic nanoplatforms enables real-time, image-guided interventions, thereby improving treatment accuracy and minimizing systemic toxicity. However, regulatory approval, probe biocompatibility, and clinical scalability remain outstanding challenges.

NIR theranostics represent a new arena for precision oncology. Future directions involve biocompatible, degradable/activatable NIR-II probes and multimodal systems complemented by AI-guided imaging for clinical translation and personalized cancer therapy.