Development of a video image-based QA system for the positional accuracy of dynamic tumor tracking irradiation in the Vero4DRT system

4D modeling in a gimbaled linear accelerator by using gold anchor markers

Purpose

The purpose of this study was to verify whether the dynamic tumor tracking (DTT) feature of a Vero4DRT system performs with 10-mm-long and 0.28 mm diameter gold anchor markers.

Methods

Gold anchor markers with a length of 10 mm and a diameter of 0.28 mm were used. Gold anchor markers were injected with short and long types into bolus material. These markers were sandwiched by a Tough Water (TW) phantom in the bolus material. For the investigation of 4-dimensional (4D) modeling feasibility under various phantom thicknesses, the TW phantom was added at 2 cm intervals (in upper and lower each by 1 cm). A programmable respiratory motion table was used to simulate breathing-induced organ motion, with an amplitude of 30 mm and a breathing cycle of 3 s. X-ray imaging parameters of 80 kV and 125 kV (320 mA and 5 ms) were used. The least detection error of the fiducial marker was defined as the 4D-modeling limitation.

Results

The 4D modeling process was attempted using short and long marker types and its limitation with the short and long types was with phantom thicknesses of 6 and 10 cm at 80 kV and 125 kV, respectively. However, the loss in detectability of the gold anchor because of 4D-modeling errors was found to be approximately 6% (2/31) with a phantom thickness of 2 cm under 125 kV. 4D-modeling could be performed except under the described conditions.

Conclusions

This work showed that a 10-mm-long gold anchor marker in short and long types can be used with DTT for short water equivalent path length site, such as lung cancer patients, in the Vero4DRT system.

Effect of tumor amplitude and frequency on 4D modeling of Vero4DRT system

BACKGROUND

An important issue in indirect dynamic tumor tracking with the Vero4DRT system is the accuracy of the model predictions of the internal target position based on surrogate infrared (IR) marker measurement. We investigated the predictive uncertainty of 4D modeling using an external IR marker, focusing on the effect of the target and surrogate amplitudes and periods.

METHODS

A programmable respiratory motion table was used to simulate breathing induced organ motion. Sinusoidal motion sequences were produced by a dynamic phantom with different amplitudes and periods. To investigate the 4D modeling error, the following amplitudes (peak-to-peak: 10-40 mm) and periods (2-8 s) were considered. The 95th percentile 4D modeling error (4D-E_95%) between the detected and predicted target position (μ + 2SD) was calculated to investigate the 4D modeling error.

RESULTS

4D-E_95% was linearly related to the target motion amplitude with a coefficient of determination R² = 0.99 and ranged from 0.21 to 0.88 mm. The 4D modeling error ranged from 1.49 to 0.14 mm and gradually decreased with increasing target motion period.

CONCLUSIONS

We analyzed the predictive error in 4D modeling and the error due to the amplitude and period of target. 4D modeling error substantially increased with increasing amplitude and decreasing period of the target motion.

Simple quality assurance method of dynamic tumor tracking with the gimbaled linac system using a light field

We proposed a simple visual method for evaluating the dynamic tumor tracking (DTT) accuracy of a gimbal mechanism using a light field. A single photon beam was set with a field size of 30×30 mm2 at a gantry angle of 90°. The center of a cube phantom was set up at the isocenter of a motion table, and 4D modeling was performed based on the tumor and infrared (IR) marker motion. After 4D modeling, the cube phantom was replaced with a sheet of paper, which was placed perpendicularly, and a light field was projected on the sheet of paper. The light field was recorded using a web camera in a treatment room that was as dark as possible. Calculated images from each image obtained using the camera were summed to compose a total summation image. Sinusoidal motion sequences were produced by moving the phantom with a fixed amplitude of 20 mm and different breathing periods of 2, 4, 6, and 8 s. The light field was projected on the sheet of paper under three conditions: with the moving phantom and DTT based on the motion of the phantom, with the moving phantom and non‐DTT, and with a stationary phantom for comparison. The values of tracking errors using the light field were 1.12±0.72, 0.31±0.19, 0.27±0.12, and 0.15±0.09 mm for breathing periods of 2, 4, 6, and 8 s, respectively. The tracking accuracy showed dependence on the breathing period. We proposed a simple quality assurance (QA) process for the tracking accuracy of a gimbal mechanism system using a light field and web camera. Our method can assess the tracking accuracy using a light field without irradiation and clearly visualize distributions like film dosimetry.

PACS number(s): 87.56 Fc, 87.55.Qr