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Adaptive intensity modulated radiation therapy planning optimization with changing tumor geometry and fraction size limits

机译:适应性强度调制的放射治疗计划优化,可改变肿瘤的几何形状和大小限制

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The modern approach of delivering radiation treatments through intensity modulated radiotherapy (IMRT) requires a computationally complex planning process. Intensities must be chosen for the many small unit grids into which the beams are divided to produce a desired distribution of dose at points throughout the body. To achieve desired aims, attention must be paid to both the cumulative doses and the doses delivered in each separate treatment session. The time horizon for the treatment allows for periodic re-imaging of the tumor geometry and for adapting the treatment plan accordingly. We present a promising iterative optimization approach that re-optimizes and updates the treatment plan periodically by incorporating the latest tumor geometry information. Two realistic lung cases simulating practice, based on anonymized archive datasets, are used to test the effectiveness of our adaptive planning approach. The computed plans both satisfy cumulative and per-session dose constraints while improving the objective (average tumor dose).View full textDownload full textKeywordsAdaptive planning, tumor geometry, fractionation, IMRT treatment plan re-optimization, mixed-integer programmingRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/19488300.2011.609871
机译:通过强度调制放射疗法(IMRT)进行放射治疗的现代方法需要计算复杂的计划过程。必须为许多小的单位网格选择强度,将光束分成许多小的单位网格以在整个人体的各个点产生所需的剂量分布。为了达到期望的目的,必须同时注意累积剂量和在每个单独的治疗阶段中递送的剂量。治疗的时间范围允许对肿瘤几何形状进行定期重新成像,并相应地调整治疗计划。我们提出了一种有前途的迭代优化方法,该方法通过合并最新的肿瘤几何形状信息来周期性地重新优化和更新治疗计划。基于匿名档案数据集的两个实际的肺部病例模拟实践被用来测试我们的自适应计划方法的有效性。计算的计划在满足目标(平均肿瘤剂量)的同时满足累积和每次使用剂量的限制。查看全文下载全文关键词自适应计划,肿瘤几何形状,分级,IMRT治疗计划重新优化,混合整数编程相关var addthis_config = {ui_cobrand :“ Taylor&Francis Online”,services_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more”,pubid:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/19488300.2011.609871

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