Nanoprobe-Enabled Precision Imaging and Panoramic Boundary Delineation in Retinoblastoma.
Authors
Affiliations (3)
Affiliations (3)
- Department of Ophthalmology, Ningbo No.2 Hospital Wenzhou Medical University Ningbo China.
- Ningbo Key Laboratory of Biomedical Imaging Probe Materials and Technology, Zhejiang International Cooperation Base of Biomedical Materials Technology and Application, Zhejiang Engineering Research Center for Biomedical Materials at Ningbo Cixi Institute of Biomedical Engineering Laboratory of Advanced Theranostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences Ningbo China.
- University of Chinese Academy of Sciences Beijing China.
Abstract
Retinoblastoma is the most common primary intraocular malignancy in children. Its prognosis depends critically on accurate delineation of the tumor and its margins, early detection of small lesions, and timely monitoring of therapeutic response. Traditional single-modality imaging techniques are inherently constrained by trade-offs among spatial resolution, molecular sensitivity, and dynamic imaging capability, making them insufficient for the demands of precision diagnosis and treatment. In recent years, nanomedicine-based imaging strategies have emerged as promising approaches to overcome these limitations. Through rational design of nanoprobes with tunable physicochemical properties, active targeting capabilities, and integrated multimodal signaling, researchers have achieved more comprehensive visualization and diagnostic evaluation of retinoblastoma lesions. In this review, we systematically summarize the major imaging modalities applied to retinoblastoma, including optical imaging, ultrasound (US), magnetic resonance imaging (MRI), and photoacoustic imaging (PAI). Subsequently, the corresponding imaging probes and targeting strategies were discussed, which were developed to enhance the imaging contrast and improve the spatiotemporal resolution of tumor visualization. Furthermore, we highlight the emerging role of artificial intelligence (AI) in the rational design of high-performance imaging nanoprobes and in multimodal image analysis, emphasizing its potential to enable quantitative tumor and boundary delineation. Finally, we outline the key challenges that must be addressed to advance the clinical translation of nanoprobes, including the identification of novel targeting strategies, AI-assisted image analysis, the development of models that more accurately recapitulate the human ocular microenvironment, and the application of new biocompatible materials. Overall, this review aims to provide comprehensive and insightful guidance for the development of next-generation nanoprobes for the precise visualization and boundary delineation of retinoblastoma.