Engineering the Future of Radiotherapy: Innovations and Challenges
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 37
Special Issue Editors
Interests: medical physics in radiation oncology; stereotactic radiotherapy; TSEB; dosimetry; modern techniques and quality assurance in radiotherapy
Special Issues, Collections and Topics in MDPI journals
Interests: radiation oncology; bioengineering; stereotactic radiotherapy; radiobiology; quality assurance in radiotherapy; modern techniques
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Nowadays, radiation therapy (RT) has shown tremendous evolution in terms of technological achievements and novel techniques. Stereotactic radiosurgery and proton therapy have demonstrated excellent results by minimizing toxicity, while new image-guided techniques (IGRTs), such as surface-guided RT (SGRT) or MRI-based IGRT through MR-Linacs, have already been adopted worldwide. The new promising treatment of “flash” RT seems quite promising for minimizing toxicity.
The combination of nanoparticles (NPs) and RT opens up a new frontier in cancer treatment.
NPs can be used as contrast enhancement in IGRT and may lead to an increased local radiation dose by using particles with higher atomic numbers (Z). The various roles of NPs as radiosensitizers in radiotherapy may provide new directions for optimization and radiotherapy efficacy.
The introduction of AI in the routine clinical practice of radiation oncology focuses on two main goals. The first goal is to improve efficiency, mainly through automation, while the second is to provide predictive tools for the better personalization of treatment. Deep learning models are used for automatic delineation and the segmentation of tumors and organs at risk. AI has also been utilized in treatment planning and optimization. Knowledge-based treatment planning and deep learning techniques have been employed to produce treatment plans comparable to those generated by humans. Additionally, AI has potential applications in adaptive radiotherapy, in the quality control and assurance of treatment plans, the optimization of image-guided RT, and the monitoring of mobile tumors during treatment.
All innovations are driving the RT in the “era of excellence” in anticancer treatment, undertaking the challenge of developing more sophisticated and tailored RT.
Dr. Kalliopi Platoni
Dr. Vassilis Kouloulias
Guest Editors
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Keywords
- radiosurgery
- stereotactic radiotherapy
- proton therapy
- artificial intelligence (AI)
- flash therapy
- image/surface-guided radiotherapy
- nanoparticles
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