Mr. Asif Rauf1, Dr Khalid Iqbal2, Mr. Khurram Khan3.
Shaukat Khanum Memorial Cancer Hospital and Research Centre
Introduction
Radiotherapy is entering a new era shaped by the integration of artificial intelligence (AI), adaptive
imaging, and precision particle delivery, fundamentally advancing its role in personalized
oncology. These innovations aim to overcome limitations of conventional static planning by
enhancing accuracy, biological relevance, and real-time adaptability.
Methods
This review synthesizes emerging technological developments in adaptive radiotherapy (ART),
image-guided systems, and proton/heavy-ion therapy through critical evaluation of recent
literature. Key focus areas include AI-enabled segmentation, dose prediction and online plan
adaptation; MR-LINAC and PET-LINAC–based functional imaging for biologically guided dose
modulation; and particle therapy innovations such as AI-assisted range prediction, Monte Carlo
dose computation, and LET-optimized planning. Additional modalities such as FLASH
radiotherapy, spatially fractionated techniques, theranostics, and radioimmunotherapy are also
examined. The review consolidates these developments to provide a comprehensive reference for
clinicians, trainees, and researchers.
Results
AI-driven ART demonstrated improved target conformity, reduced margins, and decreased normal
tissue toxicity across multiple clinical applications. Advanced IGRT platforms enhanced real-time
tumor visualization and supported biologically adaptive dose delivery. Proton and heavy-ion
therapies demonstrated substantial gains in dose localization and treatment robustness through
integration of AI-assisted optimization techniques. Emerging modalities showed strong potential
to further enhance therapeutic precision by combining imaging, radiobiology, and machine
learning innovations.
Conclusion
Collectively, these developments highlight a major paradigm shift toward intelligent, adaptive, and
data-centric radiotherapy. The convergence of physics, engineering, biology, and informatics is
accelerating the transition to highly personalized cancer treatment. Although these technologies
remain at varying stages of clinical adoption and validation, their combined progress is poised to
redefine the therapeutic boundaries and clinical capabilities of radiation oncology in the coming
decade.