title: An open-source genetic algorithm for determining optimal seed distributions for low-dose-rate prostate brachytherapy.
abstract: OBJECTIVE
  An open source optimizer that generates seed distributions for low-dose-rate prostate brachytherapy was designed, tested, and validated.
  
  
  METHODS
  The optimizer was a simple genetic algorithm (SGA) that, given a set of prostate and urethra contours, determines the optimal seed distribution in terms of coverage of the prostate with the prescribed dose while avoiding hotspots within the urethra. The algorithm was validated in a retrospective study on 45 previously contoured low-dose-rate prostate brachytherapy patients. Dosimetric indices were evaluated to ensure solutions adhered to clinical standards. The SGA performance was further benchmarked by comparing solutions obtained from a commercial optimizer (inverse planning simulated annealing [IPSA]) with the same cohort of 45 patients.
  
  
  RESULTS
  Clinically acceptable target coverage by the prescribed dose (V100) was obtained for both SGA and IPSA, with a mean ± standard deviation of 98 ± 2% and 99.5 ± 0.5%, respectively. For the prostate D90, SGA and IPSA yielded 177 ± 8 Gy and 186 ± 7 Gy, respectively, which were both clinically acceptable. Both algorithms yielded reasonable dose to the rectum, with V100 < 0.3 cc. A reduction in dose to the urethra was seen using SGA. SGA solutions showed a slight prostate volume dependence, with smaller prostates (<25 cc) yielding less desirable, although still clinically viable, dosimetric outcomes. SGA plans used, on average, fewer needles than IPSA (21 vs. 24, respectively), which may lead to a reduction in urinary toxicity and edema that alters post-implant dosimetry.
  
  
  CONCLUSIONS
  An open source SGA was validated that provides a research tool for the brachytherapy community.
authors.affiliation: Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada; Department of Medical Physics, Tom Baker Cancer Center, Calgary, AB, Canada. Electronic address: philip.mcgeachy@albertahealthservices.ca.
authors.forename: P
authors.initials: P
authors.lastname: McGeachy
authors.affiliation: Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada; Department of Medical Physics, Tom Baker Cancer Center, Calgary, AB, Canada.
authors.forename: J
authors.initials: J
authors.lastname: Madamesila
authors.affiliation: Department of Medical Physics, Tom Baker Cancer Center, Calgary, AB, Canada.
authors.forename: A
authors.initials: A
authors.lastname: Beauchamp
authors.affiliation: Department of Physics and Astronomy, University of Calgary, Calgary, AB, Canada; Department of Medical Physics, Tom Baker Cancer Center, Calgary, AB, Canada; Department of Oncology, University of Calgary, AB, Canada.
authors.forename: R
authors.initials: R
authors.lastname: Khan
mesh_terms: D000465:Algorithms; D001918:Brachytherapy / Q000009:adverse effects / Q000379:methods*; D006801:Humans; D008297:Male; D009929:Organ Size; D058958:Organs at Risk; D011467:Prostate / Q000473:pathology; D011471:Prostatic Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D019919:Prosthesis Implantation; D011829:Radiation Dosage; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted; D012007:Rectum / Q000528:radiation effects; D012189:Retrospective Studies; D014521:Urethra / Q000528:radiation effects
keywords: Genetic algorithm; Low dose rate; Open source; Optimization; Prostate brachytherapy; Seed distribution