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将生物建模纳入个体化计划验证中。

Incorporating biological modeling into patient-specific plan verification.

机构信息

Department of Radiation Oncology, University of Texas Health Sciences Center, San Antonio, TX, USA.

Department of Radiation Oncology, University of North Carolina, Chapel Hill, NC, USA.

出版信息

J Appl Clin Med Phys. 2020 Mar;21(3):94-107. doi: 10.1002/acm2.12831. Epub 2020 Feb 26.

Abstract

PURPOSE

Dose-volume histogram (DVH) measurements have been integrated into commercially available quality assurance systems to provide a metric for evaluating accuracy of delivery in addition to gamma analysis. We hypothesize that tumor control probability and normal tissue complication probability calculations can provide additional insight beyond conventional dose delivery verification methods.

METHODS

A commercial quality assurance system was used to generate DVHs of treatment plan using the planning CT images and patient-specific QA measurements on a phantom. Biological modeling was performed on the DVHs produced by both the treatment planning system and the quality assurance system.

RESULTS

The complication-free tumor control probability, P , has been calculated for previously treated intensity modulated radiotherapy (IMRT) patients with diseases in the following sites: brain (-3.9% ± 5.8%), head-neck (+4.8% ± 8.5%), lung (+7.8% ± 1.3%), pelvis (+7.1% ± 12.1%), and prostate (+0.5% ± 3.6%).

CONCLUSION

Dose measurements on a phantom can be used for pretreatment estimation of tumor control and normal tissue complication probabilities. Results in this study show how biological modeling can be used to provide additional insight about accuracy of delivery during pretreatment verification.

摘要

目的

剂量-体积直方图 (DVH) 测量已集成到商业可用的质量保证系统中,除了伽马分析之外,还提供了一种评估输送准确性的指标。我们假设肿瘤控制概率和正常组织并发症概率计算可以提供超出传统剂量输送验证方法的额外见解。

方法

使用商业质量保证系统根据计划 CT 图像和体模上的患者特定 QA 测量值生成治疗计划的 DVH。对治疗计划系统和质量保证系统生成的 DVH 进行生物建模。

结果

已为以下部位的接受过调强放疗 (IMRT) 治疗的疾病患者计算了无并发症的肿瘤控制概率 P:脑(-3.9%±5.8%)、头颈部(+4.8%±8.5%)、肺(+7.8%±1.3%)、骨盆(+7.1%±12.1%)和前列腺(+0.5%±3.6%)。

结论

体模上的剂量测量可用于治疗前肿瘤控制和正常组织并发症概率的估计。本研究的结果表明,生物建模如何可用于在治疗前验证期间提供输送准确性的额外见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed14/7075379/4d4eaa237e61/ACM2-21-94-g001.jpg

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