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Registration free automatic identification of gold fiducial markers in MRI target delineation images for prostate radiotherapy

机译:免费自动识别mRI目标描绘图像中的金基准标记用于前列腺放疗

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摘要

Purpose: The superior soft tissue contrast of magnetic resonance imaging (MRI) compared to computed tomography (CT) has urged the integration of MRI and elimination of CT in radiotherapy treatment (RT) for prostate. An intraprostatic gold fiducial marker (GFM) appears hyperintense on CT. On T2-weighted (T2w) MRI target delineation images, the GFM appear as a small signal void similar to calcifications and post biopsy fibrosis. It can therefore be difficult to identify the markers without CT. Detectability of GFMs can be improved using additional MR images, which are manually registered to target delineation images. This task requires manual labor, and is associated with interoperator differences and image registration errors. The aim of this work was to develop and evaluate an automatic method for identification of GFMs directly in the target delineation images without the need for image registration. Methods: T2w images, intended for target delineation, and multiecho gradient echo (MEGRE) images intended for GFM identification, were acquired for prostate cancer patients. Signal voids in the target delineation images were identified as GFM candidates. The GFM appeared as round, symmetric, signal void with increasing area for increasing echo time in the MEGRE images. These image features were exploited for automatic identification of GFMs in a MATLAB model using a patient training dataset (n = 20). The model was validated on an independent patient dataset (n = 40). The distances between the identified GFM in the target delineation images and the GFM in CT images were measured. A human observatory study was conducted to validate the use of MEGRE images. Results: The sensitivity, specificity, and accuracy of the automatic method and the observatory study was 84%, 74%, 81% and 98%, 94%, 97%, respectively. The mean absolute difference in the GFM distances for the automatic method and observatory study was 1.28 ± 1.25 mm and 1.14 ± 1.06 mm, respectively. Conclusions: Multiecho gradient echo images were shown to be a feasible and reliable way to perform GFM identification. For clinical practice, visual inspection of the results from the automatic method is needed at the current stage.
机译:目的:与计算机断层扫描(CT)相比,磁共振成像(MRI)优越的软组织对比度促使前列腺癌在放射治疗(RT)中整合了MRI和消除了CT。前列腺内金基准标记(GFM)在CT上表现为高强度。在T2加权(T2w)MRI目标轮廓图像上,GFM表现为类似于钙化和活检后纤维化的小信号空隙。因此,在没有CT的情况下很难识别标记。使用其他MR图像可以改善GFM的可检测性,这些图像可以手动配准到目标轮廓图像。此任务需要体力劳动,并且与互操作员的差异和图像配准错误有关。这项工作的目的是开发和评估一种直接在目标轮廓图像中直接识别GFM的自动方法,而无需进行图像配准。方法:针对前列腺癌患者,获取用于靶标描绘的T2w图像和用于GFM识别的多回波梯度回波(MEGRE)图像。目标轮廓图像中的信号空隙被识别为GFM候选。 GFM显示为圆形,对称的信号空隙,其面积随着MEGRE图像回波时间的增加而增大。利用患者训练数据集(n = 20),利用这些图像特征在MATLAB模型中自动识别GFM。该模型在独立的患者数据集中进行了验证(n = 40)。测量目标轮廓图像中识别的GFM与CT图像中的GFM之间的距离。进行了人类天文台研究,以验证MEGRE图像的使用。结果:自动方法和天文台研究的敏感性,特异性和准确性分别为84%,74%,81%和98%,94%,97%。自动方法和天文台研究的GFM距离的平均绝对差分别为1.28±1.25 mm和1.14±1.06 mm。结论:多回波梯度回波图像被证明是进行GFM识别的可行和可靠的方法。对于临床实践,当前阶段需要目视检查自动方法的结果。

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