Department of Biomedicine, Universitat de Barcelona, Barcelona, Spain. Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain.
Phys Med Biol. 2018 Apr 13;63(8):085009. doi: 10.1088/1361-6560/aab799.
The aim of this work was to obtain a set of parameters to be applied in [I]FP-CIT SPECT reconstruction in order to minimize the error between standardized and true values of the specific uptake ratio (SUR) in dopaminergic neurotransmission SPECT studies. To this end, Monte Carlo simulation was used to generate a database of 1380 projection data-sets from 23 subjects, including normal cases and a variety of pathologies. Studies were reconstructed using filtered back projection (FBP) with attenuation correction and ordered subset expectation maximization (OSEM) with correction for different degradations (attenuation, scatter and PSF). Reconstruction parameters to be optimized were the cut-off frequency of a 2D Butterworth pre-filter in FBP, and the number of iterations and the full width at Half maximum of a 3D Gaussian post-filter in OSEM. Reconstructed images were quantified using regions of interest (ROIs) derived from Magnetic Resonance scans and from the Automated Anatomical Labeling map. Results were standardized by applying a simple linear regression line obtained from the entire patient dataset. Our findings show that we can obtain a set of optimal parameters for each reconstruction strategy. The accuracy of the standardized SUR increases when the reconstruction method includes more corrections. The use of generic ROIs instead of subject-specific ROIs adds significant inaccuracies. Thus, after reconstruction with OSEM and correction for all degradations, subject-specific ROIs led to errors between standardized and true SUR values in the range [-0.5, +0.5] in 87% and 92% of the cases for caudate and putamen, respectively. These percentages dropped to 75% and 88% when the generic ROIs were used.
这项工作的目的是获得一组参数,应用于[I]FP-CIT SPECT 重建中,以最小化多巴胺能神经传递 SPECT 研究中标准化和真实特异性摄取比(SUR)值之间的误差。为此,使用蒙特卡罗模拟生成了一个由 23 个受试者的 1380 个投影数据集组成的数据库,包括正常病例和各种病变。使用带衰减校正的滤波反投影(FBP)和带不同衰减、散射和 PSF 校正的有序子集期望最大化(OSEM)对研究进行重建。要优化的重建参数是 FBP 中二维巴特沃斯预滤波器的截止频率,以及 OSEM 中三维高斯后滤波器的迭代次数和半峰全宽。使用从磁共振扫描和自动解剖标记图中提取的感兴趣区(ROI)对重建图像进行量化。结果通过应用从整个患者数据集获得的简单线性回归线进行标准化。我们的研究结果表明,我们可以为每种重建策略获得一组最佳参数。当重建方法包含更多校正时,标准化 SUR 的准确性会提高。使用通用 ROI 而不是特定于受试者的 ROI 会增加显著的不准确性。因此,在使用 OSEM 进行重建并校正所有退化之后,在 87%和 92%的情况下,对于尾状核和壳核,使用特定于受试者的 ROI 会导致标准化和真实 SUR 值之间的误差在[-0.5,+0.5]范围内。当使用通用 ROI 时,这些百分比分别下降到 75%和 88%。