Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters
Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters
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DOI：
10.1007/s00259-006-0224-1
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发表时间：
2007-03-01
影响因子：
9.1
通讯作者：
Boellaard, Ronald
中科院分区：
文献类型：
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作者：
Westerterp, Marinke;Pruim, Jan;Boellaard, Ronald
目的：标准化摄取值 (SUV) 取决于采集、重建和感兴趣区域 (ROI) 参数。因此，多中心试验中的 SUV 量化需要采集和分析方案的标准化。然而，由于使用不同的扫描仪、图像重建和数据分析软件，标准化很困难。在本研究中，我们评估了在三个不同机构获得的 SUV 在校准和校正机构间差异后是否可以直接进行比较。方法：首先，在每个机构对包含不同大小球体和活动的模拟肿瘤的拟人胸部模型进行扫描和处理，以评估扫描仪校准的差异。其次，研究了图像重建和ROI方法对恢复系数的影响。接下来，我们对 23 名受试者的肿瘤得出了 SUV。在这 23 名患者中，四名和十名患者在两个机构中使用 HR+PET 扫描仪进行了扫描，九名患者在一个机构中使用 ECAT EXACT PET 扫描仪进行了扫描。所有体模和临床数据均使用各种迭代的迭代重建进行重建，并采用测量 (MAC) 和分段衰减校正 (SAC) 以及各种图像分辨率。使用各种 ROI 等值线得出活动浓度 (AC) 或 SUV。结果：模型数据显示 SUV 量化差异高达 30%。经过特定应用校准后，每个研究所获得的回收系数均在 15% 以内。改变 ROI 等值线值会导致模型和临床数据的 SUV（或 AC）发生可预测的变化。图像分辨率的变化仅导致大球体/肿瘤（> 5 cc）的 SUV 量化发生可预测的变化。对于较小的肿瘤 (< 2 cc)，高 (7 毫米) 和低 (10 毫米) 分辨率图像之间的差异高达 40%。当通过少量迭代重建数据时，也会出现类似的差异。最后，除了膈肌附近的肿瘤外，MAC 和 SAC 重建数据之间没有观察到显着差异。结论：在多中心试验中，采集、重建和 ROI 方法的标准化是 SUV 量化的首选。通过进行模型研究来评估机构间校正因子，可以解决方法学上不可避免的微小差异。
Purpose: Standardised uptake values (SUVs) depend on acquisition, reconstruction and region of interest (ROI) parameters. SUV quantification in multicentre trials therefore requires standardisation of acquisition and analysis protocols. However, standardisation is difficult owing to the use of different scanners, image reconstruction and data analysis software. In this study we evaluated whether SUVs, obtained at three different institutes, may be directly compared after calibration and correction for inter-institute differences.Methods: First, an anthropomorphic thorax phantom containing variously sized spheres and activities, simulating tumours, was scanned and processed in each institute to evaluate differences in scanner calibration. Secondly, effects of image reconstruction and ROI method on recovery coefficients were studied. Next, SUVs were derived for tumours in 23 subjects. Of these 23 patients, four and ten were scanned in two institutes on an HR+PET scanner and nine were scanned in one institute on an ECAT EXACT PET scanner. All phantom and clinical data were reconstructed using iterative reconstruction with various iterations, with both measured ( MAC) and segmented attenuation correction ( SAC) and at various image resolutions. Activity concentrations (AC) or SUVs were derived using various ROI isocontours.Results: Phantom data revealed differences in SUV quantification of up to 30%. After application-specific calibration, recovery coefficients obtained in each institute were equal to within 15%. Varying the ROI isocontour value resulted in a predictable change in SUV ( or AC) for both phantom and clinical data. Variation of image resolution resulted in a predictable change in SUV quantification for large spheres/tumours (> 5 cc) only. For smaller tumours (< 2 cc), differences of up to 40% were found between high ( 7 mm) and low ( 10 mm) resolution images. Similar differences occurred when data were reconstructed with a small number of iterations. Finally, no significant differences between MAC and SAC reconstructed data were observed, except for tumours near the diaphragm.Conclusion: Standardisation of acquisition, reconstruction and ROI methods is preferred for SUV quantification in multi-centre trials. Small unavoidable differences in methodology can be accommodated by performing a phantom study to assess inter-institute correction factors.