Nehmeh Sadek A, Erdi Yusuf E, Kalaigian Hovanes, Kolbert Katherine S, Pan Tinsu, Yeung Henry, Squire Olivia, Sinha Arvind, Larson Steve M, Humm John L
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA.
J Nucl Med. 2003 Dec;44(12):1940-4.
Recent studies have shown increased artifacts in CT attenuation-corrected (CTAC) PET images acquired with oral contrast agents because of misclassification of contrast as bone. We have developed an algorithm, segmented contrast correction (SCC), to properly transform CT numbers in the contrast regions from CT energies (40-140 keV) to PET energy at 511 keV.
A bilinear transformation, equivalent to that supplied by the PET/CT scanner manufacturer, for the conversion of linear attenuation coefficients of normal tissues from CT to PET energies was optimized for BaSO(4) contrast agent. This transformation was validated by comparison with the linear attenuation coefficients measured for BaSO(4) at concentrations ranging from 0% to 80% at 511 keV for PET transmission images acquired with (68)Ge rod sources. In the CT images, the contrast regions were contoured to exclude bony structures and then segmented on the basis of a minimum threshold CT number (300 Hounsfield units). The CT number in each pixel identified with contrast was transformed into the corresponding effective bone CT number to produce the correct attenuation coefficient when the data were translated by the manufacturer software into PET energy during the process of CT attenuation correction. CT images were then used for attenuation correction of PET emission data. The algorithm was validated with a phantom in which a lesion was simulated within a volume of BaSO(4) contrast and in the presence of a human vertebral bony structure. Regions of interest in the lesion, bone, and contrast on emission PET images reconstructed with and without the SCC algorithm were analyzed. The results were compared with those for images obtained with (68)Ge-based transmission attenuation-corrected PET.
The SCC algorithm was able to correct for contrast artifacts in CTAC PET images. In the phantom studies, the use of SCC resulted in an approximate 32% reduction in the apparent activity concentration in the lesion compared with data obtained from PET images without SCC and a <7.6% reduction compared with data obtained from (68)Ge-based attenuation-corrected PET images. In one clinical study, maximum standardized uptake value (SUV(max)) measurements for the lesion, bladder, and bowel were, respectively, 14.52, 13.63, and 13.34 g/mL in CTAC PET images, 59.45, 26.71, and 37.22 g/mL in (68)Ge-based attenuation-corrected PET images, and 11.05, 6.66, and 6.33 g/mL in CTAC PET images with SCC.
Correction of oral contrast artifacts in PET images obtained by combined PET/CT yielded more accurate quantitation of the lesion and other, normal structures. The algorithm was tested in a clinical case, in which SUV(max) measurements showed discrepancies of 2%, 1.3%, and 5% between (68)Ge-based attenuation-corrected PET images and CTAC PET images with SCC for the lesion, bladder, and bowel, respectively. These values correspond to 6.5%, 62%, and 66% differences between CTAC-based measurements and (68)Ge-based ones.
最近的研究表明，由于造影剂被误分类为骨骼，在使用口服造影剂采集的CT衰减校正（CTAC）PET图像中伪影增加。我们开发了一种算法，即分段造影剂校正（SCC），以将造影剂区域中的CT值从CT能量（40 - 140 keV）正确转换为511 keV的PET能量。
针对硫酸钡造影剂，优化了一种双线性变换，该变换等同于PET/CT扫描仪制造商提供的用于将正常组织的线性衰减系数从CT能量转换为PET能量的变换。通过与使用（68）Ge棒源采集的PET透射图像在511 keV下对浓度范围从0%至80%的硫酸钡测量的线性衰减系数进行比较，验证了这种变换。在CT图像中，勾勒出造影剂区域以排除骨骼结构，然后基于最小阈值CT值（300亨氏单位）进行分割。在CT衰减校正过程中，当数据通过制造商软件转换为PET能量时，将每个识别为造影剂的像素中的CT值转换为相应的有效骨CT值，以产生正确的衰减系数。然后使用CT图像对PET发射数据进行衰减校正。该算法在一个体模中进行了验证，在该体模中，在硫酸钡造影剂体积内且存在人体椎体骨骼结构的情况下模拟了一个病变。分析了使用和不使用SCC算法重建的发射PET图像中病变、骨骼和造影剂的感兴趣区域。将结果与基于（68）Ge的透射衰减校正PET获得的图像结果进行比较。
SCC算法能够校正CTAC PET图像中的造影剂伪影。在体模研究中，与未使用SCC的PET图像数据相比，使用SCC导致病变中的表观活性浓度降低约32%，与基于（68）Ge的衰减校正PET图像数据相比降低<7.6%。在一项临床研究中，CTAC PET图像中病变、膀胱和肠道的最大标准化摄取值（SUV(max)）测量分别为14.52、13.63和13.34 g/mL，基于（68）Ge的衰减校正PET图像中分别为59.45、26.71和37.22 g/mL, 使用SCC的CTAC PET图像中分别为11.05、6.66和6.33 g/mL。
对PET/CT联合采集的PET图像中的口服造影剂伪影进行校正，可对病变和其他正常结构进行更准确的定量分析。该算法在一个临床病例中进行了测试，其中SUV(max)测量显示，基于（68）Ge的衰减校正PET图像与使用SCC的CTAC PET图像之间，病变、膀胱和肠道的差异分别为2%、1.3%和5%。这些值对应于基于CTAC的测量与基于（68）Ge的测量之间6.5%、62%和66%的差异。
