Lemmens Catherine, Montandon Marie-Louise, Nuyts Johan, Ratib Osman, Dupont Patrick, Zaidi Habib
Department of Nuclear Medicine and Medical Imaging Center, University Hospital Gasthuisberg and Katholieke Universiteit Leuven, Leuven, Belgium.
Phys Med Biol. 2008 Aug 21;53(16):4417-29. doi: 10.1088/0031-9155/53/16/013. Epub 2008 Jul 31.
The goal of this study is to investigate the impact of electroencephalogram (EEG) electrodes on the visual quality and quantification of (18)F-FDG PET images in neurological PET/CT examinations. For this purpose, the scans of 20 epilepsy patients with EEG monitoring were used. The CT data were reconstructed with filtered backprojection (FBP) and with a metal artefact reduction (MAR) algorithm. Both data sets were used for CT-based attenuation correction (AC) of the PET data. Also, a calculated AC (CALC) technique was considered. A volume of interest (VOI)-based analysis and a voxel-based quantitative analysis were performed to compare the different AC methods. Images were also evaluated visually by two observers. It was shown with simulations and phantom measurements that from the considered AC methods, the MAR-AC can be used as the reference in this setting. The visual assessment of PET images showed local hot spots outside the brain corresponding to the locations of the electrodes when using FBP-AC. In the brain, no abnormalities were observed. The quantitative analysis showed a very good correlation between PET-FBP-AC and PET-MAR-AC, with a statistically significant positive bias in the PET-FBP-AC images of about 5-7% in most brain voxels. There was also good correlation between PET-CALC-AC and PET-MAR-AC, but in the PET-CALC-AC images, regions with both a significant positive and negative bias were observed. EEG electrodes give rise to local hot spots outside the brain and a positive quantification bias in the brain. However, when diagnosis is made by mere visual assessment, the presence of EEG electrodes does not seem to alter the diagnosis. When quantification is performed, the bias becomes an issue especially when comparing brain images with and without EEG monitoring.
本研究的目的是调查脑电图(EEG)电极对神经PET/CT检查中(18)F-FDG PET图像视觉质量和定量分析的影响。为此,使用了20例接受EEG监测的癫痫患者的扫描数据。CT数据采用滤波反投影(FBP)和金属伪影减少(MAR)算法进行重建。这两组数据集均用于PET数据的基于CT的衰减校正(AC)。此外,还考虑了一种计算衰减校正(CALC)技术。进行了基于感兴趣体积(VOI)的分析和基于体素的定量分析,以比较不同的AC方法。两名观察者还对图像进行了视觉评估。通过模拟和体模测量表明,在所考虑的AC方法中,MAR-AC可在此设置中用作参考。PET图像的视觉评估显示,使用FBP-AC时,大脑外对应电极位置处出现局部热点。在大脑中,未观察到异常。定量分析表明,PET-FBP-AC与PET-MAR-AC之间具有很好的相关性,在大多数脑体素中,PET-FBP-AC图像中存在约5-7%的统计学显著正偏差。PET-CALC-AC与PET-MAR-AC之间也具有良好的相关性,但在PET-CALC-AC图像中,观察到既有显著正偏差又有显著负偏差的区域。EEG电极在大脑外产生局部热点,并在大脑中产生正定量偏差。然而,当仅通过视觉评估进行诊断时,EEG电极的存在似乎不会改变诊断结果。当进行定量分析时,偏差就会成为一个问题,尤其是在比较有和没有EEG监测的脑图像时。