Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and
Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany; and.
J Nucl Med. 2019 Sep;60(9):1277-1283. doi: 10.2967/jnumed.118.224055. Epub 2019 Mar 8.
Our aim was to introduce and validate qPSMA, a semiautomatic software package for whole-body tumor burden assessment in prostate cancer patients using Ga-prostate-specific membrane antigen (PSMA) 11 PET/CT. qPSMA reads hybrid PET/CT images in DICOM format. Its pipeline was written using Python and C++ languages. A bone mask based on CT and a normal-uptake mask including organs with physiologic Ga-PSMA11 uptake are automatically computed. An SUV threshold of 3 and a liver-based threshold are used to segment bone and soft-tissue lesions, respectively. Manual corrections can be applied using different tools. Multiple output parameters are computed, that is, PSMA ligand-positive tumor volume (PSMA-TV), PSMA ligand-positive total lesion (PSMA-TL), PSMA SUV, and PSMA SUV Twenty Ga-PSMA11 PET/CT data sets were used to validate and evaluate the performance characteristics of qPSMA. Four analyses were performed: validation of the semiautomatic algorithm for liver background activity determination, assessment of intra- and interobserver variability, validation of data from qPSMA by comparison with Syngo.via, and assessment of computational time and comparison of PSMA PET-derived parameters with serum prostate-specific antigen. Automatic liver background calculation resulted in a mean relative difference of 0.74% (intraclass correlation coefficient [ICC], 0.996; 95%CI, 0.989;0.998) compared with METAVOL. Intra- and interobserver variability analyses showed high agreement (all ICCs > 0.990). Quantitative output parameters were compared for 68 lesions. Paired testing showed no significant differences between the values obtained with the 2 software packages. The ICC estimates obtained for PSMA-TV, PSMA-TL, SUV, and SUV were 1.000 (95%CI, 1.000;1.000), 1.000 (95%CI, 1.000;1.000), 0.995 (95%CI, 0.992;0.997), and 0.999 (95%CI, 0.999;1.000), respectively. The first and second reads for intraobserver variability resulted in mean computational times of 13.63 min (range, 8.22-25.45 min) and 9.27 min (range, 8.10-12.15 min), respectively ( = 0.001). Highly significant correlations were found between serum prostate-specific antigen value and both PSMA-TV ( = 0.72, < 0.001) and PSMA-TL ( = 0.66, = 0.002). Semiautomatic analyses of whole-body tumor burden in Ga-PSMA11 PET/CT is feasible. qPSMA is a robust software package that can help physicians quantify tumor load in heavily metastasized prostate cancer patients.
我们的目的是介绍和验证 qPSMA,这是一种用于使用 Ga-前列腺特异性膜抗原(PSMA)11 PET/CT 对前列腺癌患者全身肿瘤负担进行评估的半自动软件包。qPSMA 以 DICOM 格式读取混合 PET/CT 图像。其管道是使用 Python 和 C++语言编写的。基于 CT 的骨骼蒙版和包括具有生理性 Ga-PSMA11 摄取的器官的正常摄取蒙版会自动计算。使用 3 的 SUV 阈值和基于肝脏的阈值分别用于分割骨骼和软组织病变。可以使用不同的工具进行手动校正。计算了多个输出参数,即 PSMA 配体阳性肿瘤体积(PSMA-TV)、PSMA 配体阳性总病变(PSMA-TL)、PSMA SUV 和 PSMA SUV。使用 20 个 Ga-PSMA11 PET/CT 数据集对 qPSMA 进行验证和性能特征评估。进行了 4 项分析:对用于确定肝脏背景活动的半自动算法进行验证,评估内部和观察者之间的变异性,通过与 Syngo.via 的比较来验证 qPSMA 的数据,以及评估计算时间并比较血清前列腺特异性抗原的 PSMA PET 衍生参数。与 METAVOL 相比,自动肝脏背景计算导致平均相对差异为 0.74%(组内相关系数[ICC],0.996;95%CI,0.989;0.998)。观察者内和观察者间的变异性分析显示出高度一致(所有 ICC 均> 0.990)。对 68 个病变进行了定量输出参数比较。配对检验显示,两种软件包获得的值无显着差异。PSMA-TV、PSMA-TL、SUV 和 SUV 的 ICC 估计值分别为 1.000(95%CI,1.000;1.000)、1.000(95%CI,1.000;1.000)、0.995(95%CI,0.992;0.997)和 0.999(95%CI,0.999;1.000)。观察者内变异性的第一次和第二次读取导致的平均计算时间分别为 13.63 分钟(范围,8.22-25.45 分钟)和 9.27 分钟(范围,8.10-12.15 分钟)( = 0.001)。发现血清前列腺特异性抗原值与 PSMA-TV( = 0.72, < 0.001)和 PSMA-TL( = 0.66, = 0.002)之间存在高度显著的相关性。Ga-PSMA11 PET/CT 中全身肿瘤负担的半自动分析是可行的。qPSMA 是一种强大的软件包,可以帮助医生定量评估转移性前列腺癌患者的肿瘤负荷。