TRAPS

Transmission - Radiotherapy Active Pixel System (TRAPS): Towards a Clinical Prototype for Real-Time 2D Verification of Intensity Modulated Radiotherapy 

Summary

A team of clinical scientists, medical physicists, radiographers and academics are developing a novel radiation detector with less attenuation and improved resolution compared with competing devices, to reduce the risks of errors during treatment of cancer with radiation (radiotherapy).

Advances in the way radiotherapy is delivered to patients means that tumours can be much more accurately targeted, greatly reducing the damage to surrounding tissue and sensitive organs. Finely engineered components in the treatment machine shape the radiation field directed at the tumour; if the beam components are misaligned or are delivered in the wrong sequence, it may not be easily recognised or immediately spotted. Errors can result in the wrong treatment being delivered, or as in some high-profile cases, delivery of a fatal overdose. Checks are made before, and ideally during, treatments to avoid such errors. The patient radiation dose needs reporting across the whole radiation field and the radiation beam monitored without perturbing it.

Our project team has developed a novel method for detecting errors during treatment using a thin silicon panel that does not interfere with the upstream radiation beam. The system, related to digital camera technology, is fast and cost-effective, has been proven to work for a range of standard radiotherapy treatments and will now be extended to work for new radiation delivery systems which move during treatment. The aim is to speed up data collection and validate the system for real-time intervention in cases of error. This will enable reporting of serious deviations from the planned treatment and provision of detailed dose distribution reports. Any errors can then be dealt with prior to treatment completion.

The team have expertise in the fabrication of radiation detectors and the modelling of clinical radiation equipment and are in discussion with several commercial companies to help bring the device to market.

Links to further information

https://app.dimensions.ai/details/grant/grant.5152680