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一种用于估计宫颈癌半自动计划初始等效均匀剂量的新型基于知识的预测模型。

A novel knowledge-based prediction model for estimating an initial equivalent uniform dose in semi-auto-planning for cervical cancer.

机构信息

Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440, Jiyan Road, Jinan, 250117, China.

出版信息

Radiat Oncol. 2022 Aug 29;17(1):151. doi: 10.1186/s13014-022-02120-4.

DOI:10.1186/s13014-022-02120-4
PMID:36038941
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9426003/
Abstract

BACKGROUND

We developed a novel concept, equivalent uniform length (EUL), to describe the relationship between the generalized equivalent uniform dose (EUD) and the geometric anatomy around a tumor target. By correlating EUL with EUD, we established two EUD-EUL knowledge-based (EEKB) prediction models for the bladder and rectum that predict initial EUD values for generating quality treatment plans.

METHODS

EUL metrics for the rectum and bladder were extracted and collected from the intensity-modulated radiotherapy therapy (IMRT) plans of 60 patients with cervical cancer. The two EEKB prediction models were built using linear regression to establish the relationships between EUL and EUD (EUL and EUD of rectum) and EUL, and EUD (EUL and EUD of bladder), respectively. The EE plans were optimized by incorporating the predicted initial EUD parameters for the rectum and bladder with the conventional pinnacle auto-planning (PAP) initial dose parameters for other organs. The efficiency of the predicted initial EUD values were then evaluated by comparing the consistency and quality of the EE plans, PAP plans (based on default PAP initial parameters), and manual plans (designed manually by different dosimetrists) for a sample of 20 patients.

RESULTS

Linear regression analyses showed a significant correlation between EUL and EUD (R = 0.79 and 0.69 for EUD and EUD, respectively). In a sample of 20 patients, the average bladder V40 and V50 derived from the EE plans were significantly lower (V40: 30.00 ± 5.76, V50: 14.36 ± 4.00) than the V40 and V50 values derived from manual plans (V40: 36.03 ± 8.02, V50: 19.02 ± 5.42). Compared with the PAP plans, the EE plans produced significantly lower average V30 and Dmean values for the bladder (V30: 50.55 ± 6.33, Dmean: 31.48 ± 1.97 Gy).

CONCLUSIONS

Our EEKB prediction models predicted reasonable initial EUD values for the rectum and bladder based on patient-specific geometric EUL values, thereby improving optimization and planning efficiency.

摘要

背景

我们提出了一个新的概念,等效均匀长度(EUL),用于描述广义等效均匀剂量(EUD)与肿瘤靶区周围几何解剖结构之间的关系。通过将 EUL 与 EUD 相关联,我们建立了两个基于 EUL-EUD 知识的(EEKB)预测模型,用于预测生成高质量治疗计划的初始 EUD 值。

方法

从 60 例宫颈癌调强放疗(IMRT)计划中提取和收集直肠和膀胱的 EUL 指标。使用线性回归建立了两个 EEKB 预测模型,分别建立 EUL 与 EUD(直肠的 EUL 和 EUD)和 EUL、EUD(膀胱的 EUL 和 EUD)之间的关系。通过将预测的初始 EUD 参数与其他器官的常规 Pinnacle 自动计划(PAP)初始剂量参数相结合,对直肠和膀胱的 EE 计划进行优化。然后,通过比较 20 例患者的 EE 计划、PAP 计划(基于默认 PAP 初始参数)和手动计划(由不同剂量师手动设计)的一致性和质量,评估预测的初始 EUD 值的效率。

结果

线性回归分析显示 EUL 与 EUD 之间存在显著相关性(EUD 与 EUD 分别为 R=0.79 和 0.69)。在 20 例患者的样本中,EE 计划得出的膀胱 V40 和 V50 明显低于手动计划(V40:30.00±5.76,V50:14.36±4.00)(V40:36.03±8.02,V50:19.02±5.42)。与 PAP 计划相比,EE 计划为膀胱产生的平均 V30 和 Dmean 值明显较低(V30:50.55±6.33,Dmean:31.48±1.97 Gy)。

结论

我们的 EEKB 预测模型基于患者特定的几何 EUL 值预测了直肠和膀胱的合理初始 EUD 值,从而提高了优化和规划效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/6f735c644c80/13014_2022_2120_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/63f4e4fe038a/13014_2022_2120_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/b5510bffd941/13014_2022_2120_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/7d3d0d6b1056/13014_2022_2120_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/9df13eb9f4cf/13014_2022_2120_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/6f735c644c80/13014_2022_2120_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/63f4e4fe038a/13014_2022_2120_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/b5510bffd941/13014_2022_2120_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/7d3d0d6b1056/13014_2022_2120_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/9df13eb9f4cf/13014_2022_2120_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8227/9426003/6f735c644c80/13014_2022_2120_Fig5_HTML.jpg

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