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利用MRI体素大小增强MR引导的PET图像重建中的部分容积校正

Enhancement of Partial Volume Correction in MR-Guided PET Image Reconstruction by Using MRI Voxel Sizes.

作者信息

Belzunce Martin A, Mehranian Abolfazl, Reader Andrew J

机构信息

School of Biomedical Engineering and Imaging SciencesKing's College London - St. Thomas' HospitalLondonSE1 7EHU.K.

出版信息

IEEE Trans Radiat Plasma Med Sci. 2018 Nov 15;3(3):315-326. doi: 10.1109/TRPMS.2018.2881248. eCollection 2019 May.

DOI:10.1109/TRPMS.2018.2881248
PMID:31245657
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6528651/
Abstract

Positron emission tomography (PET) suffers from poor spatial resolution which results in quantitative bias when evaluating the radiotracer uptake in small anatomical regions, such as the striatum in the brain which is of importance in this paper of neurodegenerative diseases. These partial volume effects need to be compensated for by employing partial volume correction (PVC) methods in order to achieve quantitatively accurate images. Two important PVC methods applied during the reconstruction are resolution modeling, which suffers from Gibbs artifacts, and penalized likelihood using anatomical priors. The introduction of clinical simultaneous PET-MR scanners has attracted new attention for the latter methods and brought new opportunities to use MRI information to assist PET image reconstruction in order to improve image quality. In this context, MR images are usually down-sampled to the PET resolution before being used in MR-guided PET reconstruction. However, the reconstruction of PET images using the MRI voxel size could achieve a better utilization of the high resolution anatomical information and improve the PVC obtained with these methods. In this paper, we evaluate the importance of the use of MRI voxel sizes when reconstructing PET images with MR-guided maximum (MAP) methods, specifically the modified Bowsher method. We also propose a method to avoid the artifacts that arise when PET reconstructions are performed in a higher resolution matrix than the standard for a given scanner. The MR-guided MAP reconstructions were implemented with a modified Lange prior that included anatomical information with the Bowsher method. The methods were evaluated with and without resolution modeling for simulated and real brain data. We show that the use of the MRI voxel sizes when reconstructing PET images with MR-guided MAP enhances PVC by improving the contrast and reducing the bias in six different regions of the brain using regional metrics for a single simulated data set and ensemble metrics for ten noise realizations. Similar results were obtained for real data, where a good enhancement of the contrast was achieved. The combination of MR-guided MAP reconstruction with point-spread function modeling and MRI voxel sizes proved to be an attractive method to achieve considerable enhancement of PVC, while reducing and controlling the noise level and Gibbs artifacts.

摘要

正电子发射断层扫描(PET)的空间分辨率较差,这导致在评估小解剖区域(如本文中对神经退行性疾病至关重要的大脑纹状体)的放射性示踪剂摄取时产生定量偏差。需要通过采用部分容积校正(PVC)方法来补偿这些部分容积效应,以获得定量准确的图像。在重建过程中应用的两种重要的PVC方法是分辨率建模(会产生吉布斯伪影)和使用解剖学先验的惩罚似然法。临床同步PET-MR扫描仪的引入引起了对后一种方法的新关注,并带来了利用MRI信息辅助PET图像重建以提高图像质量的新机会。在这种情况下,MR图像通常在用于MR引导的PET重建之前被下采样到PET分辨率。然而,使用MRI体素大小重建PET图像可以更好地利用高分辨率解剖信息,并改善通过这些方法获得的PVC。在本文中,我们评估了在使用MR引导的最大后验概率(MAP)方法(特别是改进的鲍舍尔方法)重建PET图像时使用MRI体素大小的重要性。我们还提出了一种方法,以避免在比给定扫描仪标准更高分辨率矩阵中进行PET重建时出现的伪影。MR引导的MAP重建是通过一种改进的兰格先验实现的,该先验使用鲍舍尔方法包含了解剖学信息。使用模拟和真实脑数据,对有无分辨率建模的方法进行了评估。我们表明,在使用MR引导的MAP重建PET图像时使用MRI体素大小,通过使用单个模拟数据集的区域指标和十个噪声实现的总体指标,在大脑的六个不同区域提高对比度并减少偏差,从而增强了PVC。对于真实数据也获得了类似结果,其中对比度得到了很好的增强。事实证明,将MR引导的MAP重建与点扩散函数建模和MRI体素大小相结合是一种有吸引力的方法,可以在降低和控制噪声水平以及吉布斯伪影的同时,显著增强PVC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa1/6528651/f7902fea62ef/belzu9-2881248.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa1/6528651/08322c8e4ace/belzu1abc-2881248.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa1/6528651/e7ae29620a83/belzu5-2881248.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa1/6528651/63e2ff6234da/belzu7-2881248.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa1/6528651/56b4d7a256ba/belzu8-2881248.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/daa1/6528651/f7902fea62ef/belzu9-2881248.jpg

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