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采用手动计划或 Lightning 剂量优化器方法对 Gamma Knife Icon™治疗的单脑病变进行计划,研究计划质量的可变性。

A study on inter-planner plan quality variability using a manual planning- or Lightning dose optimizer-approach for single brain lesions treated with the Gamma Knife Icon™.

机构信息

Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, USA.

Department of Radiation Oncology, Herbert Wertheim College of Medicine, Florida International University, Miami, USA.

出版信息

J Appl Clin Med Phys. 2023 Nov;24(11):e14088. doi: 10.1002/acm2.14088. Epub 2023 Jul 6.

DOI:10.1002/acm2.14088
PMID:37415385
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10647977/
Abstract

PURPOSE

The purpose of this study is to investigate inter-planner plan quality variability using a manual forward planning (MFP)- or fast inverse planning (FIP, Lightning)-approach for single brain lesions treated with the Gamma Knife (GK) Icon™.

METHODS

Thirty patients who were previously treated with GK stereotactic radiosurgery or radiotherapy were selected and divided into three groups (post-operative resection cavity, intact brain metastasis, and vestibular schwannoma [10 patients per group]). Clinical plans for the 30 patients were generated by multiple planners using FIP only (1), a combination of FIP and MFP (12), and MFP only (17). Three planners (Senior, Junior, and Novice) with varying experience levels re-planned the 30 patients using MFP and FIP (two plans per patient) with planning time limit of 60 min. Statistical analysis was performed to compare plan quality metrics (Paddick conformity index, gradient index, number of shots, prescription isodose line, target coverage, beam-on-time (BOT), and organs-at-risk doses) of MFP or FIP plans among three planners and to compare plan quality metrics between each planner's MFP/FIP plans and clinical plans. Variability in FIP parameter settings (BOT, low dose, and target max dose) and in planning time among the planners was also evaluated.

RESULTS

Variations in plan quality metrics of FIP plans among three planners were smaller than those of MFP plans for all three groups. Junior's MFP plans were the most comparable to the clinical plans, whereas Senior's and Novice's MFP plans were superior and inferior, respectively. All three planners' FIP plans were comparable or superior to the clinical plans. Differences in FIP parameter settings among the planners were observed. Planning time was shorter and variations in planning time among the planners were smaller for FIP plans in all three groups.

CONCLUSIONS

The FIP approach is less planner dependent and more time-honored than the MFP approach.

摘要

目的

本研究旨在使用手动正向计划(MFP)或快速逆计划(FIP,Lightning)方法,针对使用 Gamma Knife(GK)Icon 治疗的单个脑病变,研究不同计划者之间计划质量的变异性。

方法

选择了 30 名先前接受 GK 立体定向放射外科或放射治疗的患者,并将其分为三组(术后切除腔、完整脑转移瘤和前庭神经鞘瘤[每组 10 名患者])。30 名患者的临床计划由多名计划者使用仅 FIP(1)、FIP 和 MFP 组合(12)和仅 MFP(17)生成。三名经验水平不同的计划者(高级、中级和初级)使用 MFP 和 FIP(每位患者两个计划)重新计划了 30 名患者,计划时间限制为 60 分钟。对 MFP 或 FIP 计划的计划质量指标(Paddick 适形指数、梯度指数、射束数、处方等剂量线、靶区覆盖率、照射时间(BOT)和危及器官剂量)进行统计分析,比较三位计划者之间的 MFP/FIP 计划质量指标,以及比较每位计划者的 MFP/FIP 计划与临床计划之间的计划质量指标。还评估了计划者之间 FIP 参数设置(BOT、低剂量和靶区最大剂量)和计划时间的变化。

结果

对于所有三组,三位计划者的 FIP 计划的计划质量指标的变化均小于 MFP 计划。中级的 MFP 计划与临床计划最为相似,而高级和初级的 MFP 计划则分别更优和更差。所有三位计划者的 FIP 计划均与临床计划相似或更优。观察到计划者之间 FIP 参数设置的差异。在所有三组中,FIP 计划的计划时间更短,计划者之间的计划时间变化更小。

结论

FIP 方法比 MFP 方法更依赖计划者,更耗时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/cddf39dc59df/ACM2-24-e14088-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/b88677d79e2c/ACM2-24-e14088-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/b37e0d93339b/ACM2-24-e14088-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/ad160535c184/ACM2-24-e14088-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/9f720f12423f/ACM2-24-e14088-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/cff1ae8da11b/ACM2-24-e14088-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/cddf39dc59df/ACM2-24-e14088-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/b88677d79e2c/ACM2-24-e14088-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/b37e0d93339b/ACM2-24-e14088-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/ad160535c184/ACM2-24-e14088-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/e01b9b96962d/ACM2-24-e14088-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/22dd273e6376/ACM2-24-e14088-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/8231b2016442/ACM2-24-e14088-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/9f720f12423f/ACM2-24-e14088-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/cff1ae8da11b/ACM2-24-e14088-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/088c/10647977/cddf39dc59df/ACM2-24-e14088-g001.jpg

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