首页> 外文期刊>International Journal of Radiation Oncology, Biology, Physics >Automated patient identification and localization error detection using 2-dimensional to 3-dimensional registration of kilovoltage X-ray setup images
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Automated patient identification and localization error detection using 2-dimensional to 3-dimensional registration of kilovoltage X-ray setup images

机译:使用千伏X射线设置图像的2维到3维配准实现自动患者识别和定位错误检测

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Purpose To determine whether kilovoltage x-ray projection radiation therapy setup images could be used to perform patient identification and detect gross errors in patient setup using a computer algorithm. Methods and Materials Three patient cohorts treated using a commercially available image guided radiation therapy (IGRT) system that uses 2-dimensional to 3-dimensional (2D-3D) image registration were retrospectively analyzed: a group of 100 cranial radiation therapy patients, a group of 100 prostate cancer patients, and a group of 83 patients treated for spinal lesions. The setup images were acquired using fixed in-room kilovoltage imaging systems. In the prostate and cranial patient groups, localizations using image registration were performed between computed tomography (CT) simulation images from radiation therapy planning and setup x-ray images corresponding both to the same patient and to different patients. For the spinal patients, localizations were performed to the correct vertebral body, and to an adjacent vertebral body, using planning CTs and setup x-ray images from the same patient. An image similarity measure used by the IGRT system image registration algorithm was extracted from the IGRT system log files and evaluated as a discriminant for error detection. Results A threshold value of the similarity measure could be chosen to separate correct and incorrect patient matches and correct and incorrect vertebral body localizations with excellent accuracy for these patient cohorts. A 10-fold cross-validation using linear discriminant analysis yielded misclassification probabilities of 0.000, 0.0045, and 0.014 for the cranial, prostate, and spinal cases, respectively. Conclusions An automated measure of the image similarity between x-ray setup images and corresponding planning CT images could be used to perform automated patient identification and detection of localization errors in radiation therapy treatments.
机译:目的确定千伏x射线投影放射治疗设置图像是否可用于执行患者识别并使用计算机算法检测患者设置中的重大错误。方法和材料回顾性分析了使用市售图像引导放射治疗(IGRT)系统治疗的3个患者队列,该系统使用2维至3维(2D-3D)图像配准:一组100例颅骨放射治疗患者,一组100位前列腺癌患者,以及83位接受脊柱病变治疗的患者。使用固定的室内千伏成像系统获取设置图像。在前列腺和颅骨患者组中,使用图像配准在来自放射治疗计划的计算机断层扫描(CT)模拟图像和对应于同一患者以及不同患者的设置X射线图像之间进行定位。对于脊椎患者,使用计划CT和设置来自同一患者的X射线图像,将其定位到正确的椎体和相邻的椎体。从IGRT系统日志文件中提取了IGRT系统图像配准算法所使用的图像相似性度量,并将其评估为用于错误检测的判别式。结果可以选择相似性度量的阈值来区分正确和不正确的患者匹配以及对这些患者队列具有极高准确性的正确和不正确的椎体定位。使用线性判别分析的10倍交叉验证分别对颅,前列腺和脊柱病例产生了0.000、0.0045和0.014的错误分类概率。结论X射线设置图像和相应的计划CT图像之间的图像相似性的自动测量可用于执行自动患者识别和放射治疗中定位错误的检测。

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