Zaidi Habib, Montandon Marie-Louise, Slosman Daniel O
Division of Nuclear Medicine, Geneva University Hospital, CH-1211 Geneva 4, Switzerland.
Med Phys. 2003 May;30(5):937-48. doi: 10.1118/1.1569270.
Reliable attenuation correction represents an essential component of the long chain of modules required for the reconstruction of artifact-free, quantitative brain positron emission tomography (PET) images. In this work we demonstrate the proof of principle of segmented magnetic resonance imaging (MRI)-guided attenuation and scatter corrections in three-dimensional (3D) brain PET. We have developed a method for attenuation correction based on registered T1-weighted MRI, eliminating the need of an additional transmission (TX) scan. The MR images were realigned to preliminary reconstructions of PET data using an automatic algorithm and then segmented by means of a fuzzy clustering technique which identifies tissues of significantly different density and composition. The voxels belonging to different regions were classified into air, skull, brain tissue and nasal sinuses. These voxels were then assigned theoretical tissue-dependent attenuation coefficients as reported in the ICRU 44 report followed by Gaussian smoothing and addition of a good statistics bed image. The MRI-derived attenuation map was then forward projected to generate attenuation correction factors (ACFs) to be used for correcting the emission (EM) data. The method was evaluated and validated on 10 patient data where TX and MRI brain images were available. Qualitative and quantitative assessment of differences between TX-guided and segmented MRI-guided 3D reconstructions were performed by visual assessment and by estimating parameters of clinical interest. The results indicated a small but noticeable improvement in image quality as a consequence of the reduction of noise propagation from TX into EM data. Considering the difficulties associated with preinjection TX-based attenuation correction and the limitations of current calculated attenuation correction, MRI-based attenuation correction in 3D brain PET would likely be the method of choice for the foreseeable future as a second best approach in a busy nuclear medicine center and could be applied to other functional brain imaging modalities such as SPECT.
可靠的衰减校正对于重建无伪影的定量脑正电子发射断层扫描(PET)图像所需的一长串模块来说是一个重要组成部分。在这项工作中,我们展示了在三维(3D)脑PET中基于分割磁共振成像(MRI)的衰减和散射校正的原理证明。我们开发了一种基于配准的T1加权MRI的衰减校正方法,无需额外的透射(TX)扫描。使用自动算法将MR图像重新对齐到PET数据的初步重建结果,然后通过模糊聚类技术进行分割,该技术可识别密度和组成显著不同的组织。属于不同区域的体素被分类为空气、颅骨、脑组织和鼻窦。然后根据ICRU 44报告中报道的内容,为这些体素分配理论上依赖于组织的衰减系数,接着进行高斯平滑并添加一个统计良好的空白图像。然后将MRI衍生的衰减图向前投影以生成用于校正发射(EM)数据的衰减校正因子(ACF)。该方法在10例有TX和MRI脑图像的患者数据上进行了评估和验证。通过视觉评估和估计临床相关参数,对TX引导和分割MRI引导的3D重建之间的差异进行了定性和定量评估。结果表明,由于减少了从TX到EM数据的噪声传播,图像质量有了虽小但明显的改善。考虑到基于注射前TX的衰减校正存在的困难以及当前计算衰减校正的局限性,在可预见的未来,3D脑PET中基于MRI的衰减校正可能会成为繁忙核医学中心的次优选择方法,并且可应用于其他功能性脑成像模态,如单光子发射计算机断层扫描(SPECT)。