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Purpose: To investigate characteristics of EDR2 film‐based IMRT QA with an eye towards moving from isodose line comparisons to more objective gamma statistical analysis. Methods: IMRT QA was performed on Siemens Linacs using a traditional ion‐chamber‐and‐film phantom setup for step‐and‐shoot IMRT plans. All beams were delivered at their actual gantry angles and to the same film. Fiducial beams were used to fix film location for comparison with calculated dose. Dose was calculated on the Pinnacle planning system (8.0m). The EDR2 films were developed using a Kodak PP‐XOMAT film processor that has been remanufactured by Picker. Films were scanned with a VIDAR VXR‐16 Dosimetry Pro film digitizer using RIT 113 v5.2 software. Calibration films were created using crossed step wedges with doses calculated by Pinnacle. Gamma was calculated using the standard software settings of 3% / 4 mm. Results: For each QA film, the normalization doses (target to measured), mean gamma, and percentage of points failing the gamma limit (gamma < 1) were recorded. These percentages were found to be considerably higher in many cases than the often‐used limit of 5%. This problem was reduced when a new calibration film was used every week and developed together with the QA films; however, the mean fraction of points failing the gamma criterion was still 7%, with 45% of films failing. The mean gamma was 0.4. The product of (target dose) * (mean gamma) * (3%/100%) was relatively constant and averaged 2.3 cGy. Conclusions: Various factors were found to be relevant to the deviations observed, especially film calibration and the target dose (which sets the dose scale for gamma). In many cases, the problem was due to a poorly functioning film processor, resulting in films with streaks and artifacts; this problem was solved by service but recurs on occasion.

Purpose: Many times a set of multiple Varian‐Truebeam (TB) linacs are acquired by an institution. Since “beam matching” is an important requirement for many facilities, we developed a strategy to perform a “simultaneous” commissioning between multiple linacs.Methods and Materials: We first commissioned the required photon beam data for eclipse on the 1st TB for all the energy modalities with a beam scanning system, while integrated measurements for output factors, of all field sizes (from 1×1 to 40×40cm2) were conducted on the 2nd TB. Care was exercised during small field dosimetry so the appropriate detectors were used with data taken between two detectors be “linked” to a larger field size (4×4cm2) with the “daisy‐chaining” technique via: OF=[M‐PTW(fs)×(M‐PTW(4×4))‐1]×[MA12s(4×4)×(M‐A12S(10×10))−1]. For all energy modalities, data that span the entire range of field size, was repeated on the next TB linac, for verification. The primarily energy‐dependent dosimetric leaf gap (DLG) which was measured separately on each TB. The modeled data was validated with special measurements conducted on both linacs during commissioning. Results: Our data agreed with the “TB representative beam data” to within 0.5% for all energy modalities and field sizes ≥3×3cm2. Sample depth‐doses and cross‐profiles of a 3×3cm2 between the linacs agreeing to within 1% between linacs. The measured DLGs were quite different with a uniform difference of 1.3% between the two linacs. The measured DLG values are independent of the average dose rate and medium used for the measurements. Conclusion: A comprehensive method of commissioning identical Varian‐TB linacs, outlining the critical issues, especially small field dosimetry and DLG. The dosimetric effect of different DLG values, when it comes to, dynamic delivery and data comparisons will be presented. The dependence of DLG value on the measurement medium (in‐air vs. water) or dose rate used will also be discussed. This work was supported by CAMC Cancer Center and Alliance Oncology

Purpose: To establish a centralized database platform for radiotherapy quality assurance (QA). This can be an interactive platform where physicists can download digital benchmark cases from, perform radiotherapy planning and QA measurements with various planning and delivery systems, and upload the results. Data retrieval and analysis functions can then be developed for the quality assessment of the radiation plan and measurement in the context of prior data with similar planning, delivery and measurement technologies. Data mining of the system can in turn generate quantitative guidance for clinical trial QA requirements that have the optimum combination of stringent mandates and realistic accommodations. Methods: Built upon prior experience of Task Group(TG) 119 from IMRT workgroup of AAPM, and digital data phantoms from EORTC, these groups collaborate with clinical trial work group of AAPM and advanced technology consortium (ATC) to establish a virtual QA environment within National Biomedical Imaging Archive (NBIA). Digital phantoms from TG 119 and EORTC dosimetric evaluation with DICOM image, structures, plan and dose were uploaded to the virtual QA environment for the established community to download and perform evaluation of basic dosimetric parameters including, structure volumes, geometric location of structure center, designated points on dose volume histogram (DVH). Nine different treatment planning or related systems with various versions are included in these evaluations. Results: Volume variations among versions of these nine systems are 2.7%, 4.2%, 14.7%, 4.7% for prostate PTV, prostate, rectum and bladder respectively. DVH reading differences are 0.1%, 2.4% and 1.5% for prostate D95, rectum D30 and bladder D30. DVH reading differences for cube 10 are 1%, 86% and 100% for V0, V20 and V30 respectively. Conclusions: A virtual QA environment has been established within NBIA for radiation oncology inter‐system and inter‐institution QA. Initial testing in reading geometric and dosimetric parameters identified significant variations among systems.