Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction.
dc.contributor.author | Yang, Yun | |
dc.contributor.author | Li, Taoran | |
dc.contributor.author | Yuan, Lunlin | |
dc.contributor.author | Ge, Yaorong | |
dc.contributor.author | Yin, Fang-Fang | |
dc.contributor.author | Lee, W Robert | |
dc.contributor.author | Wu, Q Jackie | |
dc.date.accessioned | 2019-10-04T16:02:06Z | |
dc.date.available | 2019-10-04T16:02:06Z | |
dc.date.issued | 2015-03-08 | |
dc.date.updated | 2019-10-04T16:02:04Z | |
dc.description.abstract | A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF-predicted objectives as guidance for prostate were evaluated. Three different optimization methods were compared.1) Expert Plan: Ten prostate cases (16 plans) were planned by an expert planner using conventional trial-and-error approach started with institutional modified OAR and PTV constraints. Optimization was stopped at 150 iterations and that plan was saved as Expert Plan. 2) Clinical Plan: The planner would keep working on the Expert Plan till he was satisfied with the dosimetric quality and the final plan was referred to as Clinical Plan. 3) PAF Plan: A third sets of plans for the same ten patients were generated fully automatically using predicted DVHs as guidance. The optimization was based on PAF-based predicted objectives, and was continued to 150 iterations without human interaction. DMAX and D98% for PTV, DMAX for femoral heads, DMAX, D10cc, D25%/D17%, and D40% for bladder/rectum were compared. Clinical Plans are further optimized with more iterations and adjustments, but in general provided limited dosimetric benefits over Expert Plans. PTV D98% agreed within 2.31% among Expert, Clinical, and PAF plans. Between Clinical and PAF Plans, differences for DMAX of PTV, bladder, and rectum were within 2.65%, 2.46%, and 2.20%, respectively. Bladder D10cc was higher for PAF but < 1.54% in general. Bladder D25% and D40% were lower for PAF, by up to 7.71% and 6.81%, respectively. Rectum D10cc, D17%, and D40% were 2.11%, 2.72%, and 0.27% lower for PAF, respectively. DMAX for femoral heads were comparable (< 35 Gy on average). Compared to Clinical Plan (Primary + Boost), the average optimization time for PAF plan was reduced by 5.2 min on average, with a maximum reduction of 7.1min. Total numbers of MUs per plan for PAF Plans were lower than Clinical Plans, indicating better delivery efficiency. The PAF-guided planning process is capable of generating clinical-quality prostate IMRT plans with no human intervention. Compared to manual optimization, this automatic optimization increases planning and delivery efficiency, while maintainingplan quality. | |
dc.identifier.issn | 1526-9914 | |
dc.identifier.issn | 1526-9914 | |
dc.identifier.uri | ||
dc.language | eng | |
dc.publisher | Wiley | |
dc.relation.ispartof | Journal of applied clinical medical physics | |
dc.relation.isversionof | 10.1120/jacmp.v16i2.5204 | |
dc.subject | Humans | |
dc.subject | Prostatic Neoplasms | |
dc.subject | Radiotherapy Planning, Computer-Assisted | |
dc.subject | Radiometry | |
dc.subject | Automation | |
dc.subject | Male | |
dc.subject | Radiotherapy, Intensity-Modulated | |
dc.subject | Organs at Risk | |
dc.title | Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction. | |
dc.type | Journal article | |
duke.contributor.orcid | Yin, Fang-Fang|0000-0002-2025-4740|0000-0003-1064-2149 | |
duke.contributor.orcid | Lee, W Robert|0000-0002-3545-0170 | |
pubs.begin-page | 5204 | |
pubs.issue | 2 | |
pubs.organisational-group | School of Medicine | |
pubs.organisational-group | Duke | |
pubs.organisational-group | Duke Cancer Institute | |
pubs.organisational-group | Institutes and Centers | |
pubs.organisational-group | Radiation Oncology | |
pubs.organisational-group | Clinical Science Departments | |
pubs.organisational-group | Surgery, Urology | |
pubs.organisational-group | Surgery | |
pubs.organisational-group | Duke Kunshan University Faculty | |
pubs.organisational-group | Duke Kunshan University | |
pubs.publication-status | Published | |
pubs.volume | 16 |
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