Optimising Radiotherapy Planning

Radiotherapy is one of the primary modalities of cancer treatment. Modern radiotherapy treatment planning involves solving very large and complex optimisation problems within tight clinical deadlines. Current methods face speed limitations and can get stuck in suboptimal solutions. This is especially problematic in adaptive radiotherapy, where treatment plans may need to be recalculated quickly in response to changes in the patient’s anatomy during a treatment course.

Quantum-inspired algorithms, like Quantum Tunnel Annealing (QTA), simulate quantum mechanics on classical computers. QTA's additional control parameter (barrier width) allows it to escape local minima and explore solutions more effectively than traditional approaches.

In tests, QTA optimised treatment plans up to 46.6% faster than conventional methods. This enables more efficient treatment planning and rapid reoptimisation in adaptive radiotherapy, potentially delivering better and faster patient care.