Graduate School of Radiological Technology, Gunma Prefectural College of Health Science, 323-1 Kamioki-machi, Maebashi, Gunma, 371-0052, Japan.
Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan.
Sci Rep. 2021 Apr 19;11(1):8517. doi: 10.1038/s41598-021-87942-0.
This study assessed the possibility of semi-automatic harmonization of standardized uptake values (SUVs) in multicenter studies. Phantom data were acquired using 16 PET/CT scanners (including 3 PET/CT scanners with a silicon photomultiplier detector). PET images obtained using 30-min/bed scans for optimum harmonization filter calculations and using 90-180-s/bed scans for SUV validation under clinical conditions were obtained. Time of flight and a reconstruction method with point-spread function correction were allowed. The optimal full width at half maximum of the 3D-Gaussian filter that minimizes the root mean square error with the median value of the JSNM harmonization range was calculated semi-automatically. The SUVmax and the SUVpeak of the hot spheres were measured, and the inter-scanner coefficient of variation (COV) was calculated before and after harmonization. The harmonization filter was applied to 11 of the 15 PET/CT scanners in which the SUV calibration accuracy had been verified, but not in the remaining 4 scanners. Under noiseless conditions before harmonization, the inter-scanner COVs of the SUVmax and the SUVpeak were as high as 21.57% and 12.20%, respectively, decreasing to 8.79% and 5.73% after harmonization, respectively. Harmonization brought the SUVmax of all the hot spheres to within the harmonization range. Even under clinical conditions affected by image noise, the inter-scanner COVs for the SUVmax and SUVpeak were as high as 8.83% and 5.18% after harmonization, respectively. By applying an optimal harmonization filter that is calculated semi-automatically, the harmonization of SUVs according to the JSNM strategy is possible in multicenter studies, thereby reducing inter-scanner COVs.
本研究评估了在多中心研究中半自动统一标准化摄取值(SUV)的可能性。使用 16 台 PET/CT 扫描仪(包括 3 台具有硅光电倍增器探测器的 PET/CT 扫描仪)采集了体模数据。使用最佳的谐滤波器计算,采集了 30 分钟/床位扫描的 PET 图像,并在临床条件下采集了 90-180 秒/床位扫描的 SUV 验证。允许使用飞行时间和具有点扩散函数校正的重建方法。使用 3D 高斯滤波器的半最大值全宽(FWHM)自动计算,该滤波器使均方根误差与 JSNM 谐范围的中值最小。测量了热球的 SUVmax 和 SUVpeak,并计算了谐前后的扫描仪间变异系数(COV)。将谐滤波器应用于 11 台已验证 SUV 校准精度的 PET/CT 扫描仪,但未应用于其余 4 台扫描仪。在谐化前无噪声的情况下,SUVmax 和 SUVpeak 的扫描仪间 COV 高达 21.57%和 12.20%,谐化后分别降低至 8.79%和 5.73%。谐化将所有热球的 SUVmax 都带入了谐化范围。即使在受图像噪声影响的临床条件下,SUVmax 和 SUVpeak 的扫描仪间 COV 分别高达谐化后的 8.83%和 5.18%。通过应用自动计算的最佳谐滤波器,可以根据 JSNM 策略在多中心研究中实现 SUV 的谐化,从而降低扫描仪间 COV。