Premium
Use of a constrained hierarchical optimization dataset enhances knowledge‐based planning as a quality assurance tool for prostate bed irradiation
Author(s) -
Lin Yen Hwa,
Hong Linda X.,
Hunt Margie A.,
Berry Sean L.
Publication year - 2018
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13163
Subject(s) - quality assurance , computer science , radiation treatment planning , process (computing) , artificial intelligence , data mining , medical physics , radiation therapy , medicine , surgery , external quality assessment , operating system , pathology
Purpose To investigate whether building a knowledge‐based planning ( KBP ) model with prostate bed plans constructed from constrained hierarchical optimization ( CHO ) would result in more efficient model construction with more consistent output than a model built using plans from a traditional, trial‐and‐error‐based optimization ( TEO ) technique. Methods Three KBP models were constructed from plans from subsets of 58 post‐prostatectomy patients treated with intensity‐modulated radiation therapy. TEO 54 was built from 54 TEO plans, selected to represent typical clinical variations in target and organ‐at‐risk sizes and shapes. CHO 30 and TEO 30 were built from the same 30 patients populated with CHO and TEO plans, respectively. The three models were each applied to a new set of 18 patient scans and dose–volume histogram estimates ( DVHE s) were generated for rectal and bladder walls and compared for each patient. Results CHO 30 resulted in a significantly tighter range in DVHE s ( P < 0.01) for both the rectal and bladder walls compared with either of the TEO models, indicating less uncertainty in the dose estimation. Plans resulting from KBP optimization using each model were very similar. Conclusion Populating a KBP model with CHO data resulted in a high quality model. Since CHO plans can be generated automatically offline in a process that necessitates little to no user interaction, a CHO ‐ KBP model can quickly adapt to changes in plan evaluation criteria or planning techniques without the need to wait to accrue sufficient numbers of clinical TEO plans. This may facilitate the use of KBP approaches for initial or ongoing quality assurance procedures and plan quality audits.