Use of radiation to treat cancer
Use of AI in radiotherapy
One of the most challenging aspects which we need to overcome before beginning treatment is the delineation of the target volume. This involves creating a model of the tumour, outlining the target and any organs that may be at risk. Currently, this task is performed manually by an oncologist (a doctor who treats cancer) using specially designed software to draw contours around the regions of interest. While the task demands considerable clinical judgement, it is also laborious and repetitive. Consequently, it is an extremely time-consuming process, often taking up to several hours per patient.
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However, the recent implementation of a machine learning model to create auto segmented volumes showed a reduction in contouring time of 93%, as the planning oncologist was required only to edit the volumes [1].
This highlights the future potential of AI in reducing planning time whilst maintaining the high standard of treatment, allowing resources to be better used elsewhere alongside an increase in workflow efficiency.
Figure 1) Example of tumour volume delineation in two patients. A, B, and C are the observers (different physicians). The upper row shows a tumour with differences in the contouring of the volume, whereas the differences are more limited in the patient represented in the lower row.