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Correlation model error (CME) between the internal target and the external surrogate, and marker-tumor correlation error (MTCE) between the tumor and the implanted marker occur during marker-based real-time tumor tracking. The effects of these intrafraction and interfraction errors on the dose coverage in the clinical target volume (CTV) and on tumor control probability (TCP) for hepatocellular carcinoma (HCC) were evaluated in this study. Eight HCC patients treated with non-isocentric dose delivery by a robotic radiosurgery system were enrolled. The CMEs were extracted from the treatment log file, and the MTCEs were calculated from the preceding study. The CMEs and MTCEs were randomly added to each beam's robot position, and the changes in the TCP and the 2%, 95% and 99% dose coverage values for the CTV (D2, D95 and D99) were simulated. The data were statistically analyzed as a function of the CTV to planning target volume (PTV) margin, the dose fraction and the marker-tumor distance. Significant differences were observed in the majority of the CTV D2, D95 and D99 values and the TCP values. However, a linear regression revealed that ∆CTV D2, D95 and D99 have a weak correlation with ∆TCP. A dose-difference metric would be unable to detect a critical error for tumor control if the coverage changes for the CTV and ∆TCP were weakly correlated. Because the simulated TCP-based parameter determination was based on the dose simulation, including predicted interfraction and intrafraction errors, we concluded that a 95th percentile TCP-based parameter determination would be a robust strategy for ensuring tumor control while reducing doses to normal structures.

In this CyberKnife® dose verification study, we investigated the effectiveness of the novel potential error (PE) concept when applied to the determination of a robust measurement point for targeting errors. PE was calculated by dividing the differences between the maximum increases and decreases in dose distributions by the original distribution after obtaining the former by shifting the source-to-axis and off-axis distances of each beam by ±1.0 mm. Thus, PE values and measurement point dose heterogeneity were analyzed in 48 patients who underwent CyberKnife radiotherapy. Sixteen patients who received isocentric dose delivery were set as the control group, whereas 32 who received non-isocentric dose delivery were divided into two groups of smaller PE (SPE) and larger PE (LPE) by using their median PE value. The mean dose differences (± standard deviations) were 1.0 ± 0.9%, 0.5 ± 1.4% and 4.1 ± 2.8% in the control, SPE and LPE groups, respectively. We observed significant correlations of the dose difference with the PE value (r = 0.582, P < 0.001) and dose heterogeneity (r = 0.471, P < 0.001). We concluded that when determining a robust measurement point for CyberKnife point dose verification, PE evaluation was more effective than the conventional dose heterogeneity-based method that introduced optimal measurement point dose heterogeneity of <10% across the detector.

Technical developments in radiotherapy (RT) have created a need for systematic quality assurance (QA) to ensure that clinical institutions deliver prescribed radiation doses consistent with the requirements of clinical protocols. For QA, an ideal dose verification system should be independent of the treatment-planning system (TPS). This paper describes the development and reproducibility evaluation of a Monte Carlo (MC)-based standard LINAC model as a preliminary requirement for independent verification of dose distributions. The BEAMnrc MC code is used for characterization of the 6-, 10- and 15-MV photon beams for a wide range of field sizes. The modeling of the LINAC head components is based on the specifications provided by the manufacturer. MC dose distributions are tuned to match Varian Golden Beam Data (GBD). For reproducibility evaluation, calculated beam data is compared with beam data measured at individual institutions. For all energies and field sizes, the MC and GBD agreed to within 1.0% for percentage depth doses (PDDs), 1.5% for beam profiles and 1.2% for total scatter factors (Scps.). Reproducibility evaluation showed that the maximum average local differences were 1.3% and 2.5% for PDDs and beam profiles, respectively. MC and institutions' mean Scps agreed to within 2.0%. An MC-based standard LINAC model developed to independently verify dose distributions for QA of multi-institutional clinical trials and routine clinical practice has proven to be highly accurate and reproducible and can thus help ensure that prescribed doses delivered are consistent with the requirements of clinical protocols.