In radiosurgery (SRS), the geometric uncertainties of machine-related delivery including image-guidance and hence the planning target volume (PTV) are often evaluated by the end-to-end gamma (γ) comparison that carries no information about the clinical relevance of deviations of individual SRS plans during delivery quality assurance (DQA). A proof-of-concept method was proposed to derive the PTV against both the plan- and the machine-specific delivery errors directly from the clinically relevant dose-volume histograms (DVHs) using measured-guided dose reconstruction (MGDR) during DQA. A liquid-filled detector array and a rotating phantom were used to measure sixteen arc-based radiosurgery treatments with 1 and 2 mm gross tumor volume (GTV)-to-PTV margins, producing MGDR-3D dose distribution on both the phantom and the patient CT for γ index and clinical DVH evaluations, respectively. The PTV was considered optimal when the MGDR showed the desired prescription dose coverage (V pres ) of the GTV (100% in this study). Associations of the binary V pres outcomes (<or =100%) of the GTV with the acceptance level of percent γ pass rate (γPR%) at 90 versus 95% were assessed. Further receiver operator characteristic (ROC) analysis was performed to assess the distance-to-agreement (DTA) and local dose difference (ΔD) criteria that may be suitable for treatment acceptance. From the MGDR, 100% GTV V pres was achieved in 68.8% and 100% of plans with 1 and 2 mm PTV, respectively. V pres outcomes were neither associated with γPR% at 1-2 mm DTA and 1%-3% ΔD nor the acceptance level for MGDR in the patient CT. ROC analysis shows statistically significant AUC values from 0.78-0.84 and 0.79-0.80 for MGDR phantom and patient doses, respectively. DQA by MGDR-DVH objectives offers the unique opportunity of direct assessment of the dose delivery accuracy and hence the optimal PTV without subject to the statistical correlation between γPR% and clinical metrics. Based on multi-criteria DVH objectives, clinical decision can be instantly made to adjust the treatment plan prescription.