基于知识的前列腺癌调强放疗计划。

Knowledge-based IMRT treatment planning for prostate cancer.

机构信息

Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705, USA.

出版信息

Med Phys. 2011 May;38(5):2515-22. doi: 10.1118/1.3574874.

DOI:10.1118/1.3574874

PMID:21776786

Abstract

PURPOSE

To demonstrate the feasibility of using a knowledge base of prior treatment plans to generate new prostate intensity modulated radiation therapy (IMRT) plans. Each new case would be matched against others in the knowledge base. Once the best match is identified, that clinically approved plan is used to generate the new plan.

METHODS

A database of 100 prostate IMRT treatment plans was assembled into an information-theoretic system. An algorithm based on mutual information was implemented to identify similar patient cases by matching 2D beam's eye view projections of contours. Ten randomly selected query cases were each matched with the most similar case from the database of prior clinically approved plans. Treatment parameters from the matched case were used to develop new treatment plans. A comparison of the differences in the dose-volume histograms between the new and the original treatment plans were analyzed.

RESULTS

On average, the new knowledge-based plan is capable of achieving very comparable planning target volume coverage as the original plan, to within 2% as evaluated for D98, D95, and D1. Similarly, the dose to the rectum and dose to the bladder are also comparable to the original plan. For the rectum, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are 1.8% +/- 8.5%, -2.5% +/- 13.9%, and -13.9% +/- 23.6%, respectively. For the bladder, the mean and standard deviation of the dose percentage differences for D20, D30, and D50 are -5.9% +/- 10.8%, -12.2% +/- 14.6%, and -24.9% +/- 21.2%, respectively. A negative percentage difference indicates that the new plan has greater dose sparing as compared to the original plan.

CONCLUSIONS

The authors demonstrate a knowledge-based approach of using prior clinically approved treatment plans to generate clinically acceptable treatment plans of high quality. This semiautomated approach has the potential to improve the efficiency of the treatment planning process while ensuring that high quality plans are developed.

摘要

目的

展示使用先前治疗计划知识库生成新前列腺强度调制放射治疗 (IMRT) 计划的可行性。每个新病例将与知识库中的其他病例进行匹配。一旦确定了最佳匹配，就会使用该临床批准的计划来生成新计划。

方法

将 100 个前列腺 IMRT 治疗计划的数据库组装成一个信息论系统。实施了一种基于互信息的算法，通过匹配轮廓的 2D 射束眼视图投影来识别相似的患者病例。从先前临床批准的计划数据库中随机选择了 10 个查询病例，每个病例都与最相似的病例进行匹配。从匹配病例中提取治疗参数来开发新的治疗计划。分析新计划与原始计划之间剂量-体积直方图的差异。

结果

平均而言，新的基于知识的计划能够实现与原始计划非常相似的计划靶区覆盖，以 D98、D95 和 D1 评估的差异在 2%以内。同样，直肠和膀胱的剂量也与原始计划相似。对于直肠，D20、D30 和 D50 的剂量百分比差异的平均值和标准差分别为 1.8% +/- 8.5%、-2.5% +/- 13.9% 和 -13.9% +/- 23.6%。对于膀胱，D20、D30 和 D50 的剂量百分比差异的平均值和标准差分别为-5.9% +/- 10.8%、-12.2% +/- 14.6%和-24.9% +/- 21.2%。负百分比差异表示新计划与原始计划相比具有更大的剂量节省。