Next-Generation Automation in Radiation Oncology: Innovations in Planning, Informatics, and Clinical Workflow
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".
Deadline for manuscript submissions: 22 May 2026 | Viewed by 7
Special Issue Editors
Interests: radiation oncology; adaptive radiation therapy; motion management; pediatric cancers
Special Issue Information
Dear Colleagues,
Advances in automation are rapidly reshaping the practice of radiation oncology, driving improvements in efficiency, precision, and safety while promoting equity of cancer care. From intelligent contouring and automated treatment planning to quality assurance, data curation, and workflow orchestration, automated systems are evolving into critical components of modern radiotherapy and cancer research. As the field moves toward integrated, learning health care systems, there is an increasing need to evaluate and refine automation strategies that span the entire cancer care continuum—simulation, planning, delivery, verification, adaptation, follow-up, and outcomes assessment.
This Special Issue invites original research articles, technical developments, clinical evaluations, and comprehensive reviews focused on automation across all aspects of radiation oncology. Submissions may include, but are not limited to, the following:
- Autosegmentation and automated contour review;
- Knowledge-based, model-informed, or fully autonomous treatment planning;
- Oncology workflow informatics, interoperability, and process automation;
- Automated image guidance and intra- and inter-fractional decision support;
- Automated workflows for offline, online, and real-time adaptive therapy ;
- Automated quality assurance, plan checking, and error prevention;
- Regulatory, ethical, and workforce considerations for the implementation of automation.
Our objective is to highlight emerging innovation, catalyze interdisciplinary collaboration, and showcase clinically meaningful automation that improves patient outcomes. Through this special compilation, we aim to advance the conversation about the future of radiation oncology—one where automation complements clinical expertise and elevates cancer care for all patients.
Dr. Ozgur Ates
Dr. Jared Becksfort
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 100 words) can be sent to the Editorial Office for announcement on this website.
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
- radiation oncology
- radiotherapy automation
- autosegmentation
- rapid automated treatment planning
- zero-click quality assurance
- fast clinical workflow
- artificial intelligence
- machine learning
- clinical decision support
- radiomics
- image-guided radiotherapy
- adaptive radiation therapy
- human-in-the-loop automation
- healthcare informatics
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