qPSMA: a semi-automatic software for whole-body tumor burden assessment in prostate cancer using 68Ga-PSMA11 PET/CT

To introduce and validate qPSMA, a semi-automatic software 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. Bone mask, based on computer tomography (CT) and normal uptake mask including organs with physiological Ga-PSMA11 uptake are automatically computed. A standardized uptake value (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, i.e. PSMA-ligand positive tumor volume (PSMA-TV), PSMA-ligand positive total lesion (PSMA-TL), PSMA-SUVmean and PSMA-SUV Twenty Ga-PSMA11 PET/CT datasets were used to validate and evaluate the performance characteristics of qPSMA. Four analyses were performed: (1) validation of the semi-automatic algorithm for liver background activity determination, (2) assessment of intra- and interobserver variability, (3) validation of data from qPSMA by comparison with Syngo.via (Siemens Medical Solutions), and (4) assessment of computational time and comparison of PSMA PET-derived parameters with serum prostate-specific antigen (PSA). 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 to METAVOL. Intra- and interobserver variability analyses showed high agreement (all ICC above 0.990). Comparison of quantitative output parameters was performed for 68 lesions. Paired t test showed no significant differences between the values obtained with the two software packages. The ICC (95%CI) estimates obtained for PSMA-TV, PSMA-TL, SUVmean and SUV were 1.000 (1.000;1.000), 1.000 (1.000;1.000), 0.995 (0.992;0.997) and 0.999 (0.999;1.000), respectively. The first and second read for intra-observer variability resulted in mean computational times of 13.63 (range: 8.22-25.45) and 9.27 (range: 8.10-12.15) minutes, respectively ( = 0.001). High significant correlations were found between serum PSA-value and both PSMA-TV (r=0.72, p<0.001) and PSMA-TL (r=0.66, = 0.002). Semi-automatic analyses of whole-body tumor burden in Ga-PSMA11 PET/CT is feasible. qPSMA is a robust software that can assist physicians to quantify tumor load in heavily metastasized prostate cancer patients.