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Emerging Opportunities in Radiation Oncology: AI, Radiomics, and Particle Therapy Breakthroughs
Special Issue Information
Dear Colleagues,
Radiotherapy is undergoing a transformation driven by innovations in artificial intelligence, advanced imaging, and particle therapy technologies. This Special Issue aims to highlight emerging opportunities that elevate the precision, personalization, and effectiveness of cancer treatment. Topics include AI-guided treatment plan optimization, automated workflows to support adaptive radiotherapy, and predictive modeling integrating radiomics with clinical and molecular features. Additionally, the unique physical and biological benefits of proton and heavy-ion therapy offer new frontiers for improving tumor control and reducing toxicity across diverse malignancies.
Contributions addressing clinical validation, comparative effectiveness, long-term outcomes, and health-economic perspectives are encouraged, as well as research exploring ethical deployment and equitable access. By bringing together multidisciplinary perspectives, this collection will help accelerate the translation of cutting-edge technologies into patient-centered radiotherapy.
We invite you to contribute to this Special Issue focusing on transformative advances in radiotherapy. The Issue will explore the following topics:
- AI-enhanced treatment planning and adaptive workflows;
- Radiomics for precision outcome prediction;
- Integration of particle therapy (protons and heavy ions);
- New clinical evidence on particle therapies;
- Cost-effectiveness, accessibility, and ethical implications.
This Issue aims to highlight how emerging technologies and clinical data are reshaping radiation oncology. We welcome original research articles, reviews, and perspectives from across disciplines. The Issue will complement existing research by offering fresh insights into AI applications, radiomics-driven personalization, and the evolving role of particle therapy in clinical practice.
We look forward to your valuable submissions.
Dr. Antonio Pontoriero
Dr. Sara Lillo
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- radiotherapy
- artificial intelligence
- radiomics
- machine learning
- adaptive planning
- proton therapy
- hadron therapy
- precision oncology
- particle radiotherapy
- clinical outcomes
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