CT substitute derived from MRI sequences with ultrashort echo time
CT substitute derived from MRI sequences with ultrashort echo time
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DOI：
10.1118/1.3578928
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发表时间：
2011-05-01
期刊：
影响因子：
3.8
通讯作者：
Nyholm, Tufve
中科院分区：
文献类型：
--
作者：
Johansson, Adam;Karlsson, Mikael;Nyholm, Tufve
目的：PET/MRI应用中的衰减校正以及基于MRI的放射治疗工作流程中的患者定位和剂量规划需要用于从MRI导出计算机断层扫描（CT）等效信息的方法。本研究提出了一种方法，用于产生一个下降，在替代CT图像从一组磁共振（MR）images.Methods：高斯混合回归模型被用来连接的体素值在CT图像中的体素值的图像从三个MRI序列：一个T2加权三维自旋回波序列和两个双回波超短回波时间MRI序列具有不同的回波时间和翻转角。该方法使用匹配的MR和CT数据的训练集，训练后能够完全基于新患者的MR信息预测替代CT（s-CT）。方法验证是使用数据集，涵盖了5名患者的头部，并应用留一交叉验证（LOOCV）。在LOOCV期间，根据4名患者（训练集）的MR和CT数据估计模型，并将其应用于剩余患者（验证集）的MR数据，以生成s-CT图像。对所有五个训练和验证数据组合重复此过程。结果：在s-CT图像中的CT数的平均绝对误差为137 HU。不同患者的方法准确度无较大差异，表明方法稳健。在空气-组织和骨-组织界面发现s-CT图像中的最大误差。该模型可以准确区分空气和骨骼，以及软组织和非软组织。结论：由于该模型是基于体素的，因此s-CT方法有可能提供准确的CT信息估计，而不会出现几何不准确的风险。因此，s-CT图像非常适合作为CT图像的替代品，用于放射治疗中的剂量规划和PET/MRI中的衰减校正。(C)2011年美国医学物理学家协会。[DOI 10.1118/1.3578928]
Purpose: Methods for deriving computed tomography (CT) equivalent information from MRI are needed for attenuation correction in PET/MRI applications, as well as for patient positioning and dose planning in MRI based radiation therapy workflows. This study presents a method for generating a drop in substitute for a CT image from a set of magnetic resonance (MR) images.Methods: A Gaussian mixture regression model was used to link the voxel values in CT images to the voxel values in images from three MRI sequences: one T2 weighted 3D spin echo based sequence and two dual echo ultrashort echo time MRI sequences with different echo times and flip angles. The method used a training set of matched MR and CT data that after training was able to predict a substitute CT (s-CT) based entirely on the MR information for a new patient. Method validation was achieved using datasets covering the heads of five patients and applying leave-one-out cross-validation (LOOCV). During LOOCV, the model was estimated from the MR and CT data of four patients (training set) and applied to the MR data of the remaining patient (validation set) to generate an s-CT image. This procedure was repeated for all five training and validation data combinations.Results: The mean absolute error for the CT number in the s-CT images was 137 HU. No large differences in method accuracy were noted for the different patients, indicating a robust method. The largest errors in the s-CT images were found at air-tissue and bone-tissue interfaces. The model accurately discriminated between air and bone, as well as between soft tissues and nonsoft tissues.Conclusions: The s-CT method has the potential to provide an accurate estimation of CT information without risk of geometrical inaccuracies as the model is voxel based. Therefore, s-CT images could be well suited as alternatives to CT images for dose planning in radiotherapy and attenuation correction in PET/MRI. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3578928]