The challenge in cancer treatment lies in the precise application of radiotherapy, which uses high-energy rays to destroy cancer cells.
While patients are being treated, their bodies may change in ways that affect how radiation should be administered. Tumours may shrink and organs may shift slightly. Adapting treatment plans to these changes could significantly improve the effectiveness and safety of therapy. However, the treatment planning systems (TPS) currently used in radiotherapy are limited by insufficient speed and automation. As a result, opportunities to improve patient care during treatment are being missed.
Our project aims to overcome these challenges by developing a new system that uses advanced artificial intelligence (AI) to make radiotherapy more personalised, efficient and adaptable in real time. The cornerstone of our approach is the creation of a fully automated planning software system that works independently of the conventional software currently in use. This innovative system will use deep learning (DL), a type of AI that learns from large amounts of data, to automatically generate treatment plans without the need for manual input. In addition, we are exploring the potential of reinforcement learning (RL), another AI method in which the system learns to find the best course of action through trial and error. RL will help AI optimise the settings of radiotherapy equipment so that it can attack cancer cells more effectively while sparing the surrounding healthy tissue. Another key component of our solution is the development of a workflow that allows treatment plans to be adjusted immediately as soon as changes in the patient's anatomy are detected. This approach ensures that each radiotherapy session is tailored to the patient's current condition, leading to more effective and safer treatment outcomes.
Why is this important? First and foremost, this system promises to improve patient care by enabling radiotherapy that quickly adapts to anatomical changes, allows for more precise targeting of cancer cells and reduces side effects. In addition, automating the planning process frees up valuable time for doctors and other healthcare professionals, allowing them to focus more on patient care. Finally, by streamlining and automating the treatment planning process, we can enable more medical centres to access advanced radiotherapy, ultimately benefiting patients everywhere.
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