Assessing the sensitivity and suitability of a range of detectors for SIMT PSQA

Abstract

Purpose: Single-isocenter multi-target intracranial stereotactic radiotherapy (SIMT) is an effective treatment for brain metastases with complex treatment plans and delivery optimization necessitating rigorous quality assurance. This work aims to assess five methods for quality assurance of SIMT treatment plans in terms of their suitability and sensitivity to delivery errors.

Methods: Sun Nuclear ArcCHECK and SRS MapCHECK, GafChromic EBT Radiochromic Film, machine log files, and Varian Portal Dosimetry were all used to measure 15 variations of a single SIMT plan. Variations of the original plan were created with Python. They comprised various degrees of systematic MLC offsets per leaf up to 2 mm, random per-leaf variations with differing minimum and maximum magnitudes, simulated collimator, and dose miscalibrations (MU scaling). The erroneous plans were re-imported into Eclipse and plan-quality degradation was assessed by comparing each plan variation to the original clinical plan in terms of the percentage of clinical goals passing relative to the original plan. Each erroneous plan could be then ranked by the plan-quality degradation percentage following recalculation in the TPS so that the effects of each variation could be correlated with γ pass rates and detector suitability.

Results & conclusions: It was found that 2%/1 mm is a good starting point for the ArcCHECK, Portal Dosimetry, and the SRS MapCHECK methods, respectively, and provides clinically relevant error detection sensitivity. Looser dose criteria of 5%/1 mm or 5%/1.5 mm are suitable for film dosimetry and log-file-based methods. The statistical methods explored can be expanded to other areas of patient-specific QA and detector assessment.

Keywords: ArcCHECK; PSQA; SIMT; SRS; SRS MapCHECK; SRT; detector; external beam; film; log file; portal dosimetry; quality assurance; sensitivity; stereotactic.

FIGURE 1

3D Visualization of the treatment case in Eclipse v16.1. As the distribution was throughout the brain, the plan had 180° arcs at couch angles of 0°, 315°, 45°, and 90° respectively. The plan was created without jaw tracking to enable introducing errors in the plan as discussed in Section 2.3.

FIGURE 2

Mosaic showing the degree of plan quality degradation compared to the original plan (a), when the errors from Table 1 are introduced to the plan files and re‐imported into Eclipse. (b) shows the dose distribution of a single slice with 0.01–0.1 mm random offsets applied to each MLC leaf per control point. The arrows point to features of the isodose distribution that change relative to the original plan. (c)—(m) show continuous degradation with larger errors introduced from cases: Brain 6−10 and Brain 13−16, respectively. The percentage of clinical goals passing is shown in the bottom right box in each image.

FIGURE 3

Eclipse screenshot of the plan transferred to the ArcCHECK.

FIGURE 4

PD predicted image for the composite dose distribution of the four fields.

FIGURE 5

CIRS Multi‐Lesion Brain QA phantom at −4.0 cm (anterior of isocenter) showing the location of the measurement slice and the isodose distribution. Six lesions can be seen.

FIGURE 6

Three coronal dose plane locations and visual isodoses as depicted in Eclipse. The three planes captured 10 out of 22 PTVs. Every error‐laden plan from Table 1 was measured and compared to the TPS dose distribution as the reference.

FIGURE 7

Boxplot distributions for the γ results per criteria for each detector. A larger range of GPR in this work is favorable since the GPR should decrease in proportion to the severity of the error introduced to the delivery. An ideal detector would pass for the original plan (Brain 0) and fail for all other plans (Brain 1–15) in Table 1.

FIGURE 8

Summary of the measurement results grouped by γ‐criteria. 5%/1 mm or 2%/1 mm are the most suitable criteria across all detectors providing the best error detection.

FIGURE 9

ArcCHECK results for 1%/1 mm (top), 2%/1 mm, 3%/3 mm, 5%/1.5 mm, and 5%/1 mm (bottom) respectively. Each measurement point corresponds to a planned delivery from Table 1. The measurement points are represented by circles, with a linear model fit to the data along with confidence intervals for the model shown in a solid and dashed red line, respectively. The green dashed line indicates ideal linearity.

FIGURE 10

Results from Varian's PD software. Each figure's title shows the γ criteria used for the analysis. Each data point is a comparison of the composite dose from four fields analyzed in PD for the plans in Table 1. Each measurement of the original and erroneous plan is compared to the original plan's portal dose image prediction composite.

FIGURE 11

Radiochromic film results. Higher uncertainty for this case relative to the other detectors can be seen.

FIGURE 12

Results from TrueBeam trajectory log files compared to the treatment plan generated fluence. Each figure's title shows the γ criteria used for the analysis. Each data point is a comparison of the composite fluence (intensity map) from four fields for the plans in Table 1. Each measurement of the original and erroneous plan is compared to the original plan's composite fluence image.

FIGURE 13

Results from TrueBeam trajectory log files. Each figure's title shows the γ criteria used for the analysis. Each data point is a comparison of the composite fluence (intensity map) from four fields for the plans in Table 1. The actual fluence based on the recorded MLC positions for each plan is compared to the expected fluence from the log file of the original plan.

FIGURE 14

Results from Sun Nuclear's SRS MapCHECK. Each figure's title shows the γ criteria used for the analysis. Each data point is a comparison of the composite dose from four fields analyzed in SNC Patient for each plan in Table 1. Each measurement of the original and erroneous plan is compared to the original plan's dose distribution.