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一种使用 3D 次级剂量验证来提高个体化 SRS 和 SBRT QA 效率的混合方法。

A hybrid method to improve efficiency of patient specific SRS and SBRT QA using 3D secondary dose verification.

机构信息

Scripps MD Anderson Cancer Center, San Diego, California, USA.

出版信息

J Appl Clin Med Phys. 2023 Mar;24(3):e13858. doi: 10.1002/acm2.13858. Epub 2022 Dec 30.

DOI:10.1002/acm2.13858
PMID:36583305
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10018667/
Abstract

PURPOSE

Patient Specific QA (PSQA) by direct phantom measurement for all intensity modulated radiation therapy (IMRT) cases is labor intensive and an inefficient use of the Medical Physicist's time. The purpose of this work was to develop a hybrid quality assurance (QA) technique utilizing 3D dose verification as a screening tool to determine if a measurement is necessary.

METHODS

This study utilized Sun Nuclear DoseCHECK (DC), a 3D secondary verification software, and Fraction 0, a trajectory log IMRT QA software. Twenty-two Lung stereotactic body radiation therapy (SBRT) and thirty single isocentre multi-lesion SRS (MLSRS) plans were retrospectively analysed in DC. Agreement of DC and the TPS dose for selected dosimetric criteria was recorded. Calculated 95% confidence limits (CL) were used to establish action limits. All cases were delivered and measured using the Sun Nuclear stereotactic radiosurgery (SRS) MapCheck. Trajectory logs of the delivery were used to calculate Fraction 0 results for the same criteria calculated by DC. Correlation of DC and Fraction 0 results were calculated. Phantom measured QA was compared to Fraction 0 QA results for the cases which had DC criteria action limits exceeded.

RESULTS

Correlation of DC and Fraction 0 results were excellent, demonstrating the same action limits could be used for both and DC can predict Fraction 0 results. Based on the calculated action limits, zero lung SBRT cases and six MLSRS cases were identified as requiring a measurement. All plans that passed the DC screening had a passing measurement based PSQA and agreed with Fraction 0 results.

CONCLUSION

Using 95% CL action limits of dosimetric criteria, a 3D secondary dose verification can be used to determine if a measurement is required for PSQA. This method is efficient for it is part of the normal clinical workflow when verifying any clinical treatment. In addition, it can drastically reduce the number of measurements needed for PSQA.

摘要

目的

对所有调强放射治疗(IMRT)病例进行特定于患者的 QA(PSQA)直接通过体模测量,这是一项劳动密集型工作,并且对医学物理学家的时间效率低下。本研究的目的是开发一种混合 QA 技术,利用 3D 剂量验证作为筛选工具,以确定是否需要进行测量。

方法

本研究利用 Sun Nuclear 的 DoseCHECK(DC),这是一种 3D 二次验证软件,以及 Fraction 0,一种轨迹日志 IMRT QA 软件。对 22 例肺部立体定向体部放射治疗(SBRT)和 30 例单一等中心多病变 SRS(MLSRS)计划进行了回顾性分析。记录了 DC 和 TPS 剂量在选定剂量学标准上的一致性。使用计算的 95%置信限(CL)建立行动限。所有病例均采用 Sun Nuclear 立体定向放射外科(SRS)MapCheck 进行交付和测量。使用交付的轨迹日志来计算 DC 计算的相同标准的 Fraction 0 结果。计算了 DC 和 Fraction 0 结果的相关性。对于 DC 标准行动限超过的病例,将体模测量 QA 与 Fraction 0 QA 结果进行了比较。

结果

DC 和 Fraction 0 结果的相关性非常好,表明可以对两者使用相同的行动限,并且 DC 可以预测 Fraction 0 的结果。根据计算的行动限,零肺 SBRT 病例和 6 例 MLSRS 病例被确定为需要进行测量。通过 DC 筛选的所有计划都通过了基于 PSQA 的通过测量,并与 Fraction 0 结果一致。

结论

使用剂量学标准的 95%CL 行动限,可以使用 3D 二次剂量验证来确定是否需要进行 PSQA 测量。该方法效率高,因为它是验证任何临床治疗时正常临床工作流程的一部分。此外,它可以大大减少 PSQA 所需的测量次数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/ec688b89b09f/ACM2-24-e13858-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/719e82e5ace9/ACM2-24-e13858-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/bd82a8942216/ACM2-24-e13858-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/201bd327e26f/ACM2-24-e13858-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/0e9612e3df3c/ACM2-24-e13858-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/a566266a9118/ACM2-24-e13858-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/4aa0acf70586/ACM2-24-e13858-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/ec688b89b09f/ACM2-24-e13858-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/719e82e5ace9/ACM2-24-e13858-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/bd82a8942216/ACM2-24-e13858-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/201bd327e26f/ACM2-24-e13858-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/0e9612e3df3c/ACM2-24-e13858-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/a566266a9118/ACM2-24-e13858-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/4aa0acf70586/ACM2-24-e13858-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65f4/10018667/ec688b89b09f/ACM2-24-e13858-g007.jpg

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