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首页> 外文期刊>The Journal of Nuclear Medicine >Quantitative Evaluation of 2 Scatter-Correction Techniques for F-18-FDG Brain PET/MRI in Regard to MR-Based Attenuation Correction
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Quantitative Evaluation of 2 Scatter-Correction Techniques for F-18-FDG Brain PET/MRI in Regard to MR-Based Attenuation Correction

机译:F-18-FDG脑PET / MRI关于MR基衰减校正的2散射校正技术的定量评价

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摘要

In PET, corrections for photon scatter and attenuation are essential for visual and quantitative consistency. MR attenuation correction (MRAC) is generally conducted by image segmentation and assignment of discrete attenuation coefficients, which offer limited accuracy compared with CT attenuation correction. Potential inaccuracies in MRAC may affect scatter correction, because the attenuation image (mu-map) is used in single scatter simulation (SSS) to calculate the scatter estimate. We assessed the impact of MRAC to scatter correction using 2 scatter-correction techniques and 3 mu-maps for MRAC. Methods: The tail-fitted SSS (TF-SSS) and a Monte Carlo-based single scatter simulation (MC-SSS) algorithm implementations on the Philips Ingenuity TF PET/MR were used with 1 CT-based and 2 MR-based mu-maps. Data from 7 subjects were used in the clinical evaluation, and a phantom study using an anatomic brain phantom was conducted. Scatter-correction sinograms were evaluated for each scatter correction method and mu-map. Absolute image quantification was investigated with the phantom data. Quantitative assessment of PET images was performed by volume-of-interest and ratio image analysis. Results: MRAC did not result in large differences in scatter algorithm performance, especially with TF-SSS. Scatter sinograms and scatter fractions did not reveal large differences regardless of the mu-map used. TF-SSS showed slightly higher absolute quantification. The differences in volume-of-interest analysis between TF-SSS and MC-SSS were 3% at maximum in the phantom and 4% in the patient study. Both algorithms showed excellent correlation with each other with no visual differences between PET images. MC-SSS showed a slight dependency on the mu-map used, with a difference of 2% on average and 4% at maximum when a mu-map without bone was used. Conclusion: The effect of different MR-based mu-maps on the performance of scatter correction was minimal in non-time-of-flight F-18-FDG PET/MR brain imaging. The SSS algorithm was not affected significantly by MRAC. The performance of the MC-SSS algorithm is comparable but not superior to TF-SSS, warranting further investigations of algorithm optimization and performance with different radiotracers and time-of-flight imaging.
机译:在PET中,光子散射和衰减的校正对于视觉和定量一致性至关重要。 MR衰减校正(MRAC)通常通过图像分割和离散衰减系数的分配进行,与CT衰减校正相比,提供有限的准确性。 MRAC的潜在不准确可能会影响散点校正,因为衰减图像(MU-MAP)用于单散散仿真(SSS)以计算分散估计。我们评估了MRAC对MRAC的3个散射校正技术和3亩映射分散校正的影响。方法:在飞利浦Indenuey TF PET / MR上使用尾部安装SSS(TF-SSS)和基于蒙特卡罗的单散散射仿真(MC-SSS)算法实现,与基于1 CT的MR-2 MR地图。在临床评估中使用来自7个受试者的数据,并进行使用解剖脑体模的幻影研究。对每个散点校正方法和穆图评估散射校正铭文。用幻像数据研究了绝对图像量化。通过兴趣体积和比率图像分析进行PET图像的定量评估。结果:MRAC没有导致分散算法性能的巨大差异,尤其是TF-SSS。散射中音和散射级分没有透露不论使用的mu映射如何露出大的差异。 TF-SSS显示出略高的绝对量化。 TF-SSS和MC-SSS之间的兴趣体积分析的差异在患者研究中最多含量为3%,4%的患者研究。这两种算法彼此均显示出优异的相关性,并且PET图像之间没有视觉差异。 MC-SSS显示出对使用的MU映射的轻微依赖性,当使用没有骨的MU型图时,平均差异为2%,最大值为4%。结论:不同MR基MU映射对散射校正性能的影响在非飞行时间F-18-FDG PET / MR脑成像中最小。 MRAC的SSS算法不受影响。 MC-SSS算法的性能相当但不优于TF-SSS,需要进一步调查算法优化和具有不同的放射机构和飞行时间成像的性能。

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