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New Approaches in Radiotherapy
by
, , , , , and
Matthew Webster
1,*
,
Alexander Podgorsak
1,
Fiona Li
1,
Yuwei Zhou
1,
Hyunuk Jung
1,
Jihyung Yoon
1,
Olga Dona Lemus
2 and
Dandan Zheng
1 1
Department of Radiation Oncology, University of Rochester, Rochester, NY 14627, USA
2
Department of Radiation Oncology, University of Miami, Coral Gables, FL 33146, USA
*
Author to whom correspondence should be addressed.
Cancers 2025, 17(12), 1980; https://doi.org/10.3390/cancers17121980
Submission received: 2 May 2025
/
Revised: 3 June 2025
/
Accepted: 11 June 2025
/
Published: 13 June 2025
(This article belongs to the Special Issue New Approaches in Radiotherapy for Cancer)
Simple Summary
Radiation therapy is one of the most common and powerful tools used to treat cancer. Over the past century, it has been continuously evolving into highly advanced treatments that can target tumors very precisely while protecting nearby healthy tissues. In this review, we explore the latest developments that are changing how radiation therapy is delivered and becoming more powerful than ever. These include new imaging tools that allow us to more clearly see the patient’s anatomy, computer systems that can adjust treatments in real time, and smart technologies like artificial intelligence that help plan treatments more accurately. We also look at new ways of treating, such as using ultra-fast doses, more precise delivery methods, and using heavy particles like protons. Other methods combine radiation with the body’s immune system or personalized medicines for better results. These innovations are especially important for treating cancers that are difficult to reach, resistant to standard treatments, or found in children and other sensitive populations. As radiation therapy becomes more targeted and adaptive, it opens the door to more personalized care. By summarizing these cutting-edge approaches, our work supports the ongoing effort to make radiation therapy safer, smarter, and more successful for people facing cancer.
Abstract
Radiotherapy (RT) has undergone transformative advancements since its inception over a century ago. This review highlights the most promising and impactful innovations shaping the current and future landscape of RT. Key technological advances include adaptive radiotherapy (ART), which tailors treatment to daily anatomical changes using integrated imaging and artificial intelligence (AI), and advanced image guidance systems, such as MR-LINACs, PET-LINACs, and surface-guided radiotherapy (SGRT), which enhance targeting precision and minimize collateral damage. AI and data science further support RT through automation, improved segmentation, dose prediction, and treatment planning. Emerging biological and targeted therapies, including boron neutron capture therapy (BNCT), radioimmunotherapy, and theranostics, represent the convergence of molecular targeting and radiotherapy, offering personalized treatment strategies. Particle therapies, notably proton and heavy ion RT, exploit the Bragg peak for precise tumor targeting while reducing normal tissue exposure. FLASH RT, delivering ultra-high dose rates, demonstrates promise in sparing normal tissue while maintaining tumor control, though clinical validation is ongoing. Spatially fractionated RT (SFRT), stereotactic techniques and brachytherapy are evolving to treat challenging tumor types with enhanced conformality and efficacy. Innovations such as 3D printing, Auger therapy, and hyperthermia are also contributing to individualized and site-specific solutions. Across these modalities, the integration of imaging, AI, and novel physics and biology-driven approaches is redefining the possibilities of cancer treatment. This review underscores the multidisciplinary and translational nature of modern RT, where physics, engineering, biology, and informatics intersect to improve patient outcomes. While many approaches are in various stages of clinical adoption and investigation, their collective impact promises to redefine the therapeutic boundaries of radiation oncology in the coming decade.
