Clinical comparison of dose calculation using the enhanced collapsed cone algorithm vs. a new Monte Carlo algorithm

Irina Fotina, Gabriele Kragl, Bernhard Kroupa, Robert Trausmuth, Dietmar Georg

Результат исследования: Материалы для журналаСтатья

17 Цитирования (Scopus)


Purpose: Comparison of the dosimetric accuracy of the enhanced collapsed cone (eCC) algorithm with the commercially avail-able Monte Carlo (MC) dose calculation for complex treatment techniques. Material and Methods: A total of 8 intensity-modulated radiotherapy (IMRT) and 2 stereotactic body radiotherapy (SBRT) lung cases were calculated with eCC and MC algorithms with the treatment planning systems (TPS) Oncentra MasterPlan 3.2 (Nucle-tron) and Monaco 2.01 (Elekta/CMS). Fluence optimization as well as sequencing of IMRT plans was primarily performed us-ing Monaco. Dose prediction errors were calculated using MC as reference. The dose-volume histrogram (DVH) analysis was complemented with 2D and 3D gamma evaluation. Both algorithms were compared to measurements using the Delta4 system (Scandidos). Results: Recalculated with eCC IMRT plans resulted in lower planned target volume (PTV) coverage, as well as in lower organs-at-risk (OAR) doses up to 8%. Small deviations between MC and eCC in PTV dose (1-2%) were detected for IMRT cases, while larger deviations were observed for SBRT (up to 5%). Conformity indices of both calculations were similar; however, the homogeneity of the eCC calculated plans was slightly better. Delta4 measurements confirmed high dosimetric accuracy of both TPS. Conclusion: Mean dose prediction errors < 3% for PTV suggest that both algorithms enable highly accurate dose calculations under clinical conditions. However, users should be aware of slightly underestimated OAR doses using the eCC algorithm.

Язык оригиналаАнглийский
Страницы (с... по...)433-441
Количество страниц9
ЖурналStrahlentherapie und Onkologie
Номер выпуска7
Статус публикацииОпубликовано - июл 2011
Опубликовано для внешнего пользованияДа


ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Oncology