Factor 10 Expedience of Monthly Linac Quality Assurance via an Ion Chamber Array and Automation Scripts

Abstract

Purpose: While critical for safe and accurate radiotherapy, monthly quality assurance of medical linear accelerators is time-consuming and takes physics resources away from other valuable tasks. The previous methods at our institution required 5 hours to perform the mechanical and dosimetric monthly linear accelerator quality assurance tests. An improved workflow was developed to perform these tests with higher accuracy, with fewer error pathways, in significantly less time.

Methods: A commercial ion chamber array (IC profiler, Sun Nuclear, Melbourne, Florida) is combined with automation scripts to consolidate monthly linear accelerator QA. The array was used to measure output, flatness, symmetry, jaw positions, gated dose constancy, energy constancy, collimator walkout, crosshair centering, and dosimetric leaf gap constancy. Treatment plans were combined with automation scripts that interface with Sun Nuclear's graphical user interface. This workflow was implemented on a standard Varian clinac, with no special adaptations, and can be easily applied to other C-arm linear accelerators.

Results: These methods enable, in 30 minutes, measurement and analysis of 20 of the 26 dosimetric and mechanical monthly tests recommended by TG-142. This method also reduces uncertainties in the measured beam profile constancy, beam energy constancy, field size, and jaw position tests, compared to our previous methods. One drawback is the increased uncertainty associated with output constancy. Output differences between IC profiler and farmer chamber in plastic water measurements over a 6-month period, across 4 machines, were found to have a 0.3% standard deviation for photons and a 0.5% standard deviation for electrons, which is sufficient for verifying output accuracy according to TG-142 guidelines. To minimize error pathways, automation scripts which apply the required settings, as well as check the exported data file integrity were employed.

Conclusions: The equipment, procedure, and scripts used here reduce the time burden of routine quality assurance tests and in most instances improve precision over our previous methods.

Keywords: IC profiler; automation; linac QA; monthly QA; quality assurance.

Figure 1.

A, Ion chamber array layout of IC profiler. B, Schematic monthly QA example setup conditions of detector surface at SDD: 106 cm with varying thickness solid water on top and additional 5 cm solid water underneath. SDD indicates source to detector distance; QA, quality assurance.

Figure 2.

Top, Comparison of a measured 6 MV inline photon profile for a 25 × 25 cm² field with 2 different array calibrations: Red lines are the calibration at 34 × 34 cm², the black lines with circles are the 27 × 27 cm² calibration. Inset, Close-up of the same data, the measurement with the 34 × 34 cm² calibration contains significantly more error. Bottom, Several field sizes all with the 34 × 34 cm² calibration. The arrows indicate the increasing erroneous structure as field size gets further away from the calibration field size. Crossline profiles (not shown) showed the exact same behavior.

Figure 3.

Flow chart of automation script. Blue boxes indicate automated steps. Black text indicates manual user input or confirmation steps.

Figure 4.

Central axis dose measurements from the IC profiler. A, Difference of repeated central axis measurements from their average value (same day, no setup changes). This has standard deviations of 0.05% (6E) and 0.1% (6X). B-D, Differences of measured IC profiler output constancy and farmer chamber output over 6 months, on 4 different linacs using (see Methods section for setup detail). Each data point is corrected for machine output as measured by a TG51 protocol in solid water. The results were collected for 6 months.

Figure 5.

Beam profile measurements compared to the treatment planning system. A) 6MV X-ray field 25 × 25 cm² field at SSD: 102 and depth 5 cm. B) 12 MeV electron field with 25 × 25 cm² applicator cone, SSD 105 cm, depth 1.9 cm. The noise in the difference is dominated by the random uncertainty of the eclipse eMC (electron Monte Carlo) calculation. SSD indicates source to detector distance.

Figure 6.

Collimator walkout measured by IC profiler on 4 different linacs.

Figure 7.

Dose difference to baseline for sliding leaf gap test. Results from 4 machines of the same type over 1 year.