Prostate specific membrane antigen (PSMA) targeting Positron Emission Tomography (PET) imaging is becoming the reference standard for prostate cancer (PC) staging, especially in advanced disease. Yet, the implications of PSMA-PET derived whole-body tumor volume for overall survival are poorly elucidated to date. This might be due to the fact that (semi-) automated quantification of whole-body tumor volume as PSMA-PET biomarker is an unmet clinical challenge. Therefore, a novel semi-automated software is proposed and evaluated by the present study, which enables the semi-automated quantification of PSMA-PET biomarkers such as whole-body tumor volume. Methods: The proposed quantification is implemented as a research prototype (MI Whole Body Analysis Suite, v1.0, Siemens Medical Solutions USA, Inc., Knoxville, TN). PSMA accumulating foci were automatically segmented by a percental threshold (50% of local SUVmax). Neural networks were trained to segment organs in PET-CT acquisitions (training CTs: 8,632, validation CTs: 53). Thereby, PSMA foci within organs of physiologic PSMA uptake were semi-automatically excluded from the analysis. Pretherapeutic PSMA-PET-CTs of 40 consecutive patients treated with 177Lu-PSMA-617 therapy were evaluated in this analysis. The volumetric whole-body tumor volume (PSMATV50), SUVmax, SUVmean and other whole-body imaging biomarkers were calculated for each patient. Semi-automatically derived results were compared with manual readings in a sub-cohort (by one nuclear medicine physician using syngo.MM Oncology software, Siemens Healthineers, Knoxville, TN). Additionally, an inter-observer evaluation of the semi-automated approach was performed in a sub-cohort (by two nuclear medicine physicians). Results: Manually and semi automatically derived PSMA metrics were highly correlated (PSMATV50: R2=1.000; ptextless0.001; SUVmax: R2=0.988; ptextless0.001). The inter-observer agreement of the semi-automated workflow was also high (PSMATV50: R2=1.000; ptextless0.001; ICC=1.000; SUVmax: R2=0.988; ptextless0.001; ICC=0.997). PSMATV50 [ml] was a significant predictor of overall survival (HR: 1.004; 95%CI: 1.001-1.006, P = 0.002) and remained so in a multivariate regression including other biomarkers (HR: 1.004; 95%CI: 1.001-1.006 P = 0.004). Conclusion: PSMATV50 is a promising PSMA-PET biomarker that is reproducible and easily quantified by the proposed semi-automated software. Moreover, PSMATV50 is a significant predictor of overall survival in patients with advanced prostate cancer that receive 177Lu-PSMA-617 therapy.