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技术说明:运动中实时 3D MRI 在 MRI 引导放疗中的应用:具有超分辨率的 3D 动态关键孔成像。

Technical Note: Real-time 3D MRI in the presence of motion for MRI-guided radiotherapy: 3D Dynamic keyhole imaging with super-resolution.

机构信息

Department of Radiation Oncology, Washington University School of Medicine, St Louis, MO, 63110, USA.

Department of Radiology and Biomedical Engineering, Washington University in St. Louis, St Louis, MO, 63110, USA.

出版信息

Med Phys. 2019 Oct;46(10):4631-4638. doi: 10.1002/mp.13748. Epub 2019 Aug 27.

Abstract

PURPOSE

The purpose of this study was to present real-time three-dimensional (3D) magnetic resonance imaging (MRI) in the presence of motion for MRI-guided radiotherapy (MRgRT) using dynamic keyhole imaging for high-temporal acquisition and super-resolution generative (SRG) model for high-spatial reconstruction.

METHOD

We propose a unique real-time 3D MRI technique by combining a data sharing technique (3D dynamic keyhole imaging) with a SRG model using cascaded deep learning technique. 3D dynamic keyhole imaging utilizes the data sharing mechanism by combining keyhole central k-space data acquired in real-time with high-spatial, high-temporal resolution prior peripheral k-space data at various motion positions prepared by the SRG model. The efficacy of the 3D dynamic keyhole imaging with super-resolution (SR_dKeyhole) was compared to the ground-truth super-resolution images with the original full k-space data. It was also compared with the zero-filling reconstruction (zero-filling), conventional keyhole reconstruction with low-spatial high-temporal prior data (LR_cKeyhole), and conventional keyhole reconstruction with super-resolution prior data (SR_cKeyhole).

RESULTS

High-spatial, high-temporal resolution 3D MRI datasets (1.5 × 1.5 × 6 mm ) were generated from low-spatial, high-temporal resolution 3D MRI datasets (6 × 6 × 6 mm ) using the cascaded deep learning SRG framework (<100 ms/volume). 3D dynamic keyhole imaging with the SRG model provided high-spatial, high-temporal resolution images (1.5 × 1.5 × 6 mm , 455 ms) with the highest similarity to the ground-truth SR images without any noticeable artifacts. Structural similarity indices (SSIM) of the reconstructed 3D MRI to the original SR 3D MRI were 0.65, 0.66, 0.86, and 0.89 for zero-filling, LR_cKeyhole, SR_cKeyhole, and SR_dKeyhole, respectively (1 for identical image). In addition, average value of image relative error (IRE) of the reconstructed 3D MRI to the original SR 3D MRI were 0.169, 0.191, 0.079, and 0.067 for zero-filling, LR_cKeyhole, SR_cKeyhole, and SR_dKeyhole, respectively (0 for identical image).

CONCLUSIONS

We demonstrated that high-spatial, high-temporal resolution 3D MRI was feasible by combing 3D dynamic keyhole imaging with a SRG model in terms of image quality and imaging time. The proposed technique can be utilized for real-time 3D MRgRT.

摘要

目的

本研究旨在展示一种实时三维(3D)磁共振成像(MRI)技术,该技术在运动存在的情况下使用动态关键孔成像进行 MRI 引导放射治疗(MRgRT),以实现高时间采集和高空间重建的超分辨率生成(SRG)模型。

方法

我们提出了一种独特的实时 3D MRI 技术,该技术结合了数据共享技术(3D 动态关键孔成像)和使用级联深度学习技术的 SRG 模型。3D 动态关键孔成像利用数据共享机制,将实时采集的关键孔中心 k 空间数据与 SRG 模型预先准备的高空间、高时间分辨率的外围 k 空间数据相结合。比较了具有高空间、高时间分辨率的 3D 动态关键孔成像(SR_dKeyhole)与使用原始全 k 空间数据的真实高分辨率图像的效果。还将其与零填充重建(zero-filling)、使用低空间高时间分辨率先验数据的传统关键孔重建(LR_cKeyhole)和使用超分辨率先验数据的传统关键孔重建(SR_cKeyhole)进行了比较。

结果

使用级联深度学习 SRG 框架,从低空间、高时间分辨率的 3D MRI 数据集(6×6×6mm)中生成了高空间、高时间分辨率的 3D MRI 数据集(1.5×1.5×6mm)(<100ms/volume)。具有 SRG 模型的 3D 动态关键孔成像提供了高空间、高时间分辨率的图像(1.5×1.5×6mm,455ms),与真实的 SR 图像最为相似,没有任何明显的伪影。重建 3D MRI 与原始 SR 3D MRI 的结构相似性指数(SSIM)分别为 0.65、0.66、0.86 和 0.89,零填充、LR_cKeyhole、SR_cKeyhole 和 SR_dKeyhole,分别为 1(相同图像)。此外,重建 3D MRI 与原始 SR 3D MRI 的图像相对误差(IRE)的平均值分别为 0.169、0.191、0.079 和 0.067,零填充、LR_cKeyhole、SR_cKeyhole 和 SR_dKeyhole,分别为 0(相同图像)。

结论

我们证明了通过结合 3D 动态关键孔成像和 SRG 模型,可以在图像质量和成像时间方面实现高空间、高时间分辨率的 3D MRI。该技术可用于实时 3D MRgRT。

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