质量保证
接收机工作特性
软件
工作流程
计算机科学
放射治疗计划
直方图
剂量学
医学物理学
核医学
数据挖掘
算法
医学
放射治疗
人工智能
机器学习
放射科
病理
程序设计语言
图像(数学)
数据库
外部质量评估
作者
Cassandra Stambaugh,Gary A. Ezzell
摘要
Purpose The purpose of this study was to determine clinically relevant pass/question/fail criteria for gamma analysis of intensity‐modulated radiation therapy quality assurance ( IMRT QA ) plans, identify which plans should be further analyzed with dose–volume histogram ( DVH ) metrics, and create a workflow for performing that DVH ‐based analysis. Methods A total of 11 plans, 5 prostate and 6 head/neck, were selected to represent known good plans based on their high‐passing rate using conventional IMRT QA criteria. These were modified by moving the programmed MLC positions to underdose the target or overdose important structures by varying amounts. Commercially available hardware/software was used to measure and analyze all plans (76 total) using 4%/3 mm, 3%/3 mm, 3%/2 mm, and 2%/2 mm gamma criteria. Two receiver operator characteristic ( ROC ) curves per criterion were created to assess effective passing rates. One ROC curve was to find a higher threshold that determined a clear pass and the second to find a lower threshold to determine a clear failure. Plans between these two thresholds need DVH ‐based analysis to assess the clinical consequence of the dose difference. The modified plans were analyzed in the planning system and reconstructed in commercially available DVH ‐based analysis software to access the accuracy and usefulness of the software. Results Analysis of the ROC curves showed optimal pass and fail thresholds for plan error detection per criterion to achieve clinically relevant sensitivity and specificity. Based on measurement uncertainty and pass/fail ranges, 3%/2 mm gamma criteria with a pass threshold of 95% and a fail threshold of 90% were most optimal. DVH analysis showed good agreement with all reconstructed plans except where the changes to the MLC patterns caused the periphery of the target to be underdosed. For questionable plans, comparing the organ‐specific DVH s to the physician‐provided planning constraints proved to be an efficient and effective workflow since plans for which the target dose was slightly high or where organs at risk were underdosed could be released for the treatment without consulting the physician for a clinical decision. Conclusion This work indicates the potential for appreciable improvement in error detection for IMRT QA . Using effective pass/fail thresholds to determine plans that need DVH ‐based analysis minimizes the need for excessive, time‐consuming, analysis, and making use of the dosimetric constraints of the plan minimizes the burden on physicians. Overall, DVH ‐based analysis is a powerful tool that can provide substantial insight over the traditional approach that does not provide structure‐specific data.
科研通智能强力驱动
Strongly Powered by AbleSci AI