1*Assistant Professor, Department of Radiological Imaging Techniques, Teerthanker Mahaveer University College of Paramedical Sciences, Teerthanker Mahaveer University, Moradabad, U.P, INDIA (244001). Email: rahulgangwar.paramedical@tmu.ac.in
2Assistant Professor, College of Allied and Healthcare Sciences, GIMS, Greater Noida, U.P. 201310
3M.Sc. Research Scholar, Department of Radiological Imaging Techniques, SRMS institute of allied and healthcare sciences bhojipura-Bareilly, U.P.
4Assistant Professor, Department of Radiological Imaging Techniques, Mangalayatan University, Aligarh, U.P.
5Tutor, Department of Radiological Imaging Techniques, GD Goenka Health Care Academy, Bareilly, U.P.
6PhD Research Scholar, Department of Biotechnology, Vikrant University, Gwalior, M.P.
7M.Sc. Research Scholar, Department of Radiological Imaging Techniques, Teerthanker Mahaveer University College of Paramedical Sciences, Teerthanker Mahaveer University, Moradabad, U.P, INDIA (244001)
Nano-radiomics integrates nanotechnology with radiomics to revolutionize diagnostic imaging by enhancing contrast agents' efficiency, thereby substantially reducing radiation exposure across multiple imaging modalities — including computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI). Engineered nanoparticles, including quantum dots (QDs), gold nanoparticles (AuNPs), superparamagnetic iron oxide nanoparticles (SPIONs), and mesoporous silica nanoparticles, offer superior signal-to-noise ratios, organ-specific targeting capabilities, and tunable surface chemistry that renders them ideal contrast agents for low-dose imaging protocols compliant with the As Low As Reasonably Achievable (ALARA) principle. This comprehensive review systematically examines the physicochemical mechanisms of nanoparticle-based contrast agents, their preclinical and emerging clinical applications in oncology, cardiovascular imaging, and neuroimaging, and the translational challenges impeding widespread adoption — including biocompatibility concerns, regulatory pathways, scalability, and inter-scanner variability. We further explore the synergistic potential of nano-radiomics with artificial intelligence (AI) and deep learning, which enables real-time dose optimization, automated radiomic feature extraction, and predictive clinical modelling. Radiation dose reductions of 30–50% have been documented in multiple studies without compromising diagnostic accuracy. A forward-looking analysis of future research directions, emerging nanoparticle classes, and personalized medicine applications is presented.
Keywords: Nano-radiomics; nanoparticles; low-dose imaging; contrast agents; radiology; ALARA; computed tomography; PET; MRI; SPIONs; AuNPs; quantum dots; artificial intelligence; biocompatibility; radiomic features; oncology; personalized medicine.
How to cite this article: Gangwar R, Rani S, Shalu, Kumari K, Raghav AS, Sachan D, Singh R. Nano-Radiomics: Leveraging Nanoparticles for Targeted Low-Dose Imaging — A Comprehensive Review. Int J Drug Deliv Technol. 2026;16(15s): 956-965. DOI: 10.25258/ijddt.16.15s.107
Source of support: Nil.
Conflict of interest: None