MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration
MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration
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DOI：
10.2967/jnumed.107.049353
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发表时间：
2008-11-01
影响因子：
9.3
通讯作者：
Pichler, Bernd J.
中科院分区：
文献类型：
--
作者：
Hofmann, Matthias;Steinke, Florian;Pichler, Bernd J.
对于定量正电子发射断层扫描（PET）信息，组织光子衰减校正必不可少。一般在常规PET中，衰减图是通过使用旋转放射性核素源的透射扫描获得的，或者在PET/CT联合扫描仪中从CT扫描获得。对于目前正在研发的PET/磁共振成像（MRI）扫描仪，没有足够空间放置旋转源；衰减图可以由磁共振图像计算得出。这项任务具有挑战性，因为磁共振强度与质子密度和组织弛豫特性相关，而不是与衰减相关的质量密度相关。
方法：我们结合局部模式识别和图谱配准（图谱配准可捕捉解剖结构的全局变化），从给定的磁共振图像预测伪CT图像。然后将这些伪CT图像用于衰减校正，就像在PET/CT扫描仪中进行的操作一样。
结果：对于人脑扫描，我们在一个包含17对磁共振/CT图像的数据库上表明，我们的方法能够仅从磁共振图像可靠地估计出伪CT图像。在其他人脑扫描的磁共振成像/正电子发射断层扫描/CT三联数据集上，我们将基于磁共振成像的衰减校正与基于CT的校正进行了比较。我们的方法能够对预定义的感兴趣区域进行正电子发射断层扫描定量，平均误差为3.2%，我们发现这在临床上不显著。然而，我们的方法并非专门针对脑成像，并且我们在一个全身动物数据集上展示了有前景的初步结果。
结论：这种方法能够对人脑扫描进行可靠的基于磁共振成像的衰减校正。需要进一步的工作来验证该方法在全身成像中的有效性。
For quantitative PET information, correction of tissue photon attenuation is mandatory. Generally in conventional PET, the attenuation map is obtained from a transmission scan, which uses a rotating radionuclide source, or from the CT scan in a combined PET/CT scanner. In the case of PET/MRI scanners currently under development, insufficient space for the rotating source exists; the attenuation map can be calculated from the MR image instead. This task is challenging because MR intensities correlate with proton densities and tissue-relaxation properties, rather than with attenuation-related mass density. Methods: We used a combination of local pattern recognition and atlas registration, which captures global variation of anatomy, to predict pseudo-CT images from a given MR Image. These pseudo-CT images were then used for attenuation correction, as the process would be performed in a PET/CT scanner. Results: For human brain scans, we show on a database of 17 MR/CT image pairs that our method reliably enables estimation of a pseudo-CT image from the MR image alone. On additional datasets of MRI/PET/ CT triplets of human brain scans, we compare MRI-based attenuation correction with CT-based correction. Our approach enables PET quantification with a mean error of 3.2% for predefined regions of interest, which we found to be clinically not significant. However, our method is not specific to brain imaging, and we show promising Initial results on 1 whole-body animal dataset. Conclusion: This method allows reliable MRI-based attenuation correction for human brain scans. Further work is necessary to validate the method for whole-body imaging.