IMAGERY

• Research type

  Research Study

• Full title

  Investigating Mri Autosegmentation for GynaE brachytheRapY: Validation of an auto-segmentation solution for the delineation of regions of interest in Image Guided Brachytherapy treatment of Cervix Cancers.

• IRAS ID

  300935

• Contact name

  Ceri Doherty

• Contact email

  ceri.doherty@wales.nhs.uk

• Sponsor organisation

  Velindre University NHS Trust

• Duration of Study in the UK

  1 years, 9 months, 1 days

• Research summary

  Radiotherapy is the use of ionising radiation to treat cancer. When planning a radiotherapy treatment we want to deliver the prescribed dose of radiation to the cancerous tumour so that it can be treated but we also want to minimise the radiation received by the surrounding healthy tissues to reduce the side effects the patient experiences. Brachytherapy is a type of radiotherapy that uses a small sealed source of radiation that is placed within the patient while the treatment is delivered. Brachytherapy is able to deliver a high dose to the tumour as the source is placed either close to or in the tumour itself, but is limited in application by its requirement to treat tumours that are relatively accessible by way of a natural cavity or close to the skins surface. For cervical cancer an applicator is inserted into the patient’s cervix and uterus under anaesthetic that the radiation source then travels within.
  To be able to fulfil our radiotherapy aims we need to know precisely where both the cancer and the organs we want to avoid are. We use 3D medical images of the patient to be able to see these, for cervix brachytherapy this is an MRI image. These images are then used in the treatment planning computer software where the tumour and healthy tissues are outlined manually so that later we can calculate how much radiation they receive. Outlining manually is time consuming and varies depending on who does the outlining. This projects aim is to use the computer to automate the process of identifying and outlining the regions of interest in the image. Therefore automating the outlining process aims to improve patient experience, by reducing the time the patient has to wait, and also to improve the consistency of outlining by minimising human variation.

• REC name

  N/A

• REC reference

  N/A