title: Improving the efficiency of breast radiotherapy treatment planning using a semi-automated approach.
abstract: OBJECTIVE
  To reduce treatment planning times while maintaining plan quality through the introduction of semi-automated planning techniques for breast radiotherapy.
  
  
  METHODS
  Automatic critical structure delineation was examined using the Smart Probabilistic Image Contouring Engine (SPICE) commercial autosegmentation software (Philips Radiation Oncology Systems, Fitchburg, WI) for a cohort of ten patients. Semiautomated planning was investigated by employing scripting in the treatment planning system to automate segment creation for breast step-and-shoot planning and create objectives for segment weight optimization; considerations were made for three different multileaf collimator (MLC) configurations. Forty patients were retrospectively planned using the script and a planning time comparison performed.
  
  
  RESULTS
  The SPICE heart and lung outlines agreed closely with clinician-defined outlines (median Dice Similarity Coefficient > 0.9); median difference in mean heart dose was 0.0 cGy (range -10.8 to 5.4 cGy). Scripted treatment plans demonstrated equivalence with their clinical counterparts. No statistically significant differences were found for target parameters. Minimal ipsilateral lung dose increases were also observed. Statistically significant (P < 0.01) time reductions were achievable for MLCi and Agility MLC (Elekta Ltd, Crawley, UK) plans (median 4.9 and 5.9 min, respectively).
  
  
  CONCLUSIONS
  The use of commercial autosegmentation software enables breast plan adjustment based on doses to organs at risk. Semi-automated techniques for breast radiotherapy planning offer modest reductions in planning times. However, in the context of a typical department's breast radiotherapy workload, minor savings per plan translate into greater efficiencies overall.
authors.affiliation: Joint Department of Physics, The Royal Marsden NHS Foundation Trust/Institute of Cancer Research, Sutton, Surrey, UK.
authors.forename: Robert A
authors.initials: RA
authors.lastname: Mitchell
authors.affiliation: Joint Department of Physics, The Royal Marsden NHS Foundation Trust/Institute of Cancer Research, Sutton, Surrey, UK.
authors.forename: Philip
authors.initials: P
authors.lastname: Wai
authors.affiliation: Joint Department of Physics, The Royal Marsden NHS Foundation Trust/Institute of Cancer Research, Sutton, Surrey, UK.
authors.forename: Ruth
authors.initials: R
authors.lastname: Colgan
authors.affiliation: Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK.
authors.forename: Anna M
authors.initials: AM
authors.lastname: Kirby
authors.affiliation: Joint Department of Physics, The Royal Marsden NHS Foundation Trust/Institute of Cancer Research, Sutton, Surrey, UK.
authors.forename: Ellen M
authors.initials: EM
authors.lastname: Donovan
mesh_terms: D001331:Automation; D001943:Breast Neoplasms / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D058958:Organs at Risk / Q000528:radiation effects*; D010315:Particle Accelerators / Q000295:instrumentation*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods; D012189:Retrospective Studies; D012984:Software
keywords: automated planning; autosegmentation; breast; dosimetry; radiotherapy