Objectives: To determine if Limbus, an AI auto-contouring software, can offer meaningful time savings for prostate radiotherapy treatment planning.
Methods: Three clinical oncologists recorded the time taken to contour prostate and seminal vesicles, lymph nodes, bladder, rectum, bowel and femoral heads on CT scans for 30 prostate patients (15 prostate, 15 prostate and nodes). Limbus 1.6.0 was used to generate these contours on the 30 CT scans. The time taken by the oncologists to modify individual Limbus contours was noted and compared with manual contouring times. The geometric similarity of Limbus and expert contours was assessed using the Dice Similarity Coefficient (DSC), and the dosimetric impact of using un-edited Limbus OAR contours was studied.
Results: Limbus reduced the time to produce clinically acceptable contours by 26 minutes for prostate and nodes patients and by 13 minutes for the prostate only patients. DSC values of greater than 0.7 were calculated for all contours, demonstrating good initial agreement. A dosimetric study showed that 5 of the 20 plans optimised using unmodified AI structures required unnecessary compromise of PTV coverage, highlighting the importance of expert review.
Conclusions: Limbus offers significant time saving and has become an essential part of our clinical practice.
Advances in knowledge: This paper is the first paper to include bowel and lymph nodes when assessing potential time savings using Limbus software. It demonstrates that Limbus can be used as an aid for prostate and node radiotherapy treatment planning.
Keywords: AI; Machine learning; Prostate; contour; oncology; planning; radiotherapy.
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