ESTRO 2023 - Abstract Book

S1361

Digital Posters

ESTRO 2023

Conclusion We showed a limit of Ethos template-based dose optimization for our 10 test plans. Both EG_init and EG_upd resulted in sub-optimized clinical metrics, due to sub-optimal goals template and to the iteration restriction set by the manufacturer, respectively. DP outperformed both EG_init and EG_upd showing that a more patient-specific automatic dose optimization is possible at cost of a longer and less user-friendly implementation workflow.

PO-1659 The impact of LIMBUS AI based contouring on the efficiency of prostate radiotherapy planning

K. Patel 1,2 , P. Rudd 3 , K. Palmer 1 , A. Starke 4 , J. Poxon 4 , P. Wells 5 , K. Tipples 5 , N. MacDougall 4

1 St Bartholomew's Hospital , Clinical Oncology , London, United Kingdom; 2 University College London, Cancer Institute, Faculty of Medical Sciences, London, United Kingdom; 3 St Bartholomew's Hospital , Clinical Oncology, London, United Kingdom; 4 St Bartholomew's Hospital, Physics, London, United Kingdom; 5 St Bartholomew's Hospital, Clinical Oncology, London, United Kingdom Purpose or Objective One in eight men in the UK will be diagnosed with prostate cancer and of those, 30% will have radiotherapy as part of their treatment. Due to the volume of patients being treated, efficient workflow is vital to the prostate radiotherapy treatment pathway. Expert manual contouring (EC) of the prostate gland, draining lymph nodes and organs at risk (OAR), is required; which is a time consuming process. Deep learning based automatic contouring artificial intelligence (AI) software, such as Limbus AI, has been developed to help alleviate this workload pressure by automatically generating contours required for the radiotherapy planning process. We aimed to assess whether AI generated contours (AIC) can be used to reduce prostate radiotherapy contouring times compared with EC and the technical quality of the resulting AI generated contours. Materials and Methods Two Barts Health clinical oncology consultants recorded their contouring times taken for the prostate and seminal vesicles (CTV), lymph nodes (LN) and each OAR for 10 prostate (PR) and 10 prostate and lymph node plans (PLN). Limbus AI version 1.0.6 was used to generate 10 PR and 10 PLN plans from previously treated patients. Time taken by each consultant to amend each AIC to optimal volume was recorded. The secondary outcome was to assess the geometric similarity between an EC and AIC for each patient. Contours were compared using the dice similarity coefficient (DSC). DSC represents the overlap of volumes with a value of 0 indicating no overlap and 1 a perfect overlap. Values >0.7 suggest excellent agreement. Results The median time to complete all EC for a prostate plan was 26 minutes. The median time to amend an AIC PR contour set was 7 minutes, representing a time saving benefit of 19 minutes: a 73% reduction in contouring time. The median time to complete all EC for prostate and nodes was 1 hour 4 minutes. The median time to amend an AIC PLN contour set was 12 minutes, representing a time saving benefit of 52 minutes: an 81% reduction in contouring time. Table 1. EC times compared to amending AIC times