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Impact of DVH Outliers Registered in Knowledge-based Planning on Volumetric Modulated Arc Therapy Treatment Planning for Prostate Cancer
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- Kamima Tatsuya
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
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- Yoshioka Minoru
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
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- Takahashi Ryo
- Section of Radiation Safety and Quality Assurance, National Cancer Center Hospital East
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- Sato Tomoharu
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
Bibliographic Information
- Other Title
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- Knowledge-based planning における登録DVH の外れ値が前立腺VMAT 治療計画に与える影響について
- 臨床技術 Knowledge-based planningにおける登録DVHの外れ値が前立腺VMAT治療計画に与える影響について
- リンショウ ギジュツ Knowledge-based planning ニ オケル トウロク DVH ノ ハズレ チ ガ ゼンリツセン VMAT チリョウ ケイカク ニ アタエル エイキョウ ニ ツイテ
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Description
<p>RapidPlan, a knowledge-based planning software, uses a model library containing the dose-volume histogram (DVH) of previous treatment plans, and it automatically provides optimization objectives based on a trained model to future patients for volumetric modulated arc therapy treatment planning. However, it is unknown how DVH outliers registered in models influence the resulting plans. The purpose of this study was to investigate the effect of DVH outliers on the resulting quality of RapidPlan knowledge-based plans generated for patients with prostate cancer. First, 123 plans for patients with prostate cancer were used to populate the initial model (modelall). Next, modelall-20 and modelall-40 were created by excluding DVH outliers of bladder optimization contours 20 and 40 patients from modelall, respectively. These models were used to create plans for a 20-patient. The plans created using modelall-40 showed reductions of D30% and D50% in the bladder wall dose, and the DVH shape excluding outliers were affected. However, there were no significant differences in monitor units, target doses, or bladder wall doses between each treatment plan. Thus, we have shown that removal of DVH outliers from models does not affect the quality of plans created by the model.</p>
Journal
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- Japanese Journal of Radiological Technology
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Japanese Journal of Radiological Technology 75 (2), 151-159, 2019
Japanese Society of Radiological Technology
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Keywords
Details 詳細情報について
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- CRID
- 1390282763100345088
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- NII Article ID
- 130007602179
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- NII Book ID
- AN00197784
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- ISSN
- 18814883
- 03694305
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- NDL BIB ID
- 029539397
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- PubMed
- 30787221
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- Text Lang
- ja
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- Article Type
- journal article
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- Data Source
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- JaLC
- NDL Search
- Crossref
- PubMed
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed