Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy.
Improved planning time and plan quality through multicriteria optimization for intensity-modulated radiotherapy.
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DOI：
10.1016/j.ijrobp.2010.12.007
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发表时间：
2012-01-01
影响因子：
7
通讯作者：
Bortfeld, Thomas R
中科院分区：
文献类型：
--
作者：
Craft, David L;Hong, Theodore S;Shih, Helen A;Bortfeld, Thomas R
目的：探讨多准则优化（MCO）在调强放射治疗（IMRT）中能否缩短治疗计划时间，提高计划质量。在马萨诸塞州总医院（MGH）目前使用的标准治疗计划程序期间，记录了10名IMRT患者（5名胶质母细胞瘤患者和5名局部晚期胰腺癌患者）。记录计划持续时间和其他相关计划信息。同时，使用MCO计划系统对患者进行计划，并收集类似的计划时间数据。患者接受标准计划治疗，但每个MCO计划也得到了医生的批准。然后由治疗医生在计划后3周对计划进行盲态审查。在所有病例中，MCO计划的治疗计划时间大大缩短（平均MCO治疗计划时间为12分钟;平均标准计划时间为135分钟）。医生参与计划过程的时间从标准过程的平均4.8分钟增加到MCO过程的8.6分钟。在所有情况下，MCO计划都被盲目地确定为上级计划。这提供了第一个具体的证据表明，基于MCO的计划是优于计划效率和剂量分布质量相比，目前的试验和误差为基础的调强放射治疗计划的方法。
To test whether multicriteria optimization (MCO) can reduce treatment planning time and improve plan quality in intensity-modulated radiotherapy (IMRT). Ten IMRT patients (5 with glioblastoma and 5 with locally advanced pancreatic cancers) were logged during the standard treatment planning procedure currently in use at Massachusetts General Hospital (MGH). Planning durations and other relevant planning information were recorded. In parallel, the patients were planned using an MCO planning system, and similar planning time data were collected. The patients were treated with the standard plan, but each MCO plan was also approved by the physicians. Plans were then blindly reviewed 3 weeks after planning by the treating physician. In all cases, the treatment planning time was vastly shorter for the MCO planning (average MCO treatment planning time was 12 min; average standard planning time was 135 min). The physician involvement time in the planning process increased from an average of 4.8 min for the standard process to 8.6 min for the MCO process. In all cases, the MCO plan was blindly identified as the superior plan. This provides the first concrete evidence that MCO-based planning is superior in terms of both planning efficiency and dose distribution quality compared with the current trial and error–based IMRT planning approach.