Measurement of time delays in gated radiotherapy for realistic respiratory motions

Comprehensive beam delivery latency evaluation for gated proton therapy system using customized multi-channel signal acquisition platform

PURPOSE

Beam delivery latency in respiratory-gated particle therapy systems is a crucial issue to dose delivery accuracy. The aim of this study is to develop a multi-channel signal acquisition platform for investigating gating latencies occurring within RPM respiratory gating system (Varian, USA) and ProBeam proton treatment system (Varian, USA) individually.

METHODS

The multi-channel signal acquisition platform consisted of several electronic components, including a string position sensor for target motion detection, a photodiode for proton beam sensing, an interfacing board for accessing the trigger signal between the respiratory gating system and the proton treatment system, a signal acquisition device for sampling and synchronizing signals from the aforementioned components, and a laptop for controlling the signal acquisition device and data storage. RPM system latencies were determined by comparing the expected gating phases extracted from the motion signal with the trigger signal's state turning points. ProBeam system latencies were assessed by comparing the state turning points of the trigger signal with the beam signal. The total beam delivery latencies were calculated as the sum of delays in the respiratory gating system and the cyclotron proton treatment system. During latency measurements, simulated sinusoidal motion were applied at different amplitudes and periods for complete beam delivery latency evaluation under different breathing patterns. Each breathing pattern was repeated 30 times for statistical analysis.

RESULTS

The measured gating ON/OFF latencies in the RPM system were found to be 104.20 ± 13.64 ms and 113.60 ± 14.98 ms, respectively. The measured gating ON/OFF delays in the ProBeam system were 108.29 ± 0.85 ms and 1.20 ± 0.04 ms, respectively. The total beam ON/OFF latencies were determined to be 212.50 ± 13.64 ms and 114.80 ± 14.98 ms.

CONCLUSION

With the developed multi-channel signal acquisition platform, it was able to investigate the gating lags happened in both the respiratory gating system and the proton treatment system. The resolution of the platform is enough to distinguish the delays at the millisecond time level. Both the respiratory gating system and the proton treatment system made contributions to gating latency. Both systems contributed nearly equally to the total beam ON latency, with approximately 100 ms. In contrast, the respiratory gating system was the dominant contributor to the total beam OFF latency.

A simple method to measure the gating latencies in photon and proton based radiotherapy using a scintillating crystal

BACKGROUND

In respiratory gated radiotherapy, low latency between target motion into and out of the gating window and actual beam-on and beam-off is crucial for the treatment accuracy. However, there is presently a lack of guidelines and accurate methods for gating latency measurements.

PURPOSE

To develop a simple and reliable method for gating latency measurements that work across different radiotherapy platforms.

METHODS

Gating latencies were measured at a Varian ProBeam (protons, RPM gating system) and TrueBeam (photons, TrueBeam gating system) accelerator. A motion-stage performed 1 cm vertical sinusoidal motion of a marker block that was optically tracked by the gating system. An amplitude gating window was set to cover the posterior half of the motion (0-0.5 cm). Gated beams were delivered to a 5 mm cubic scintillating ZnSe:O crystal that emitted visible light when irradiated, thereby directly showing when the beam was on. During gated beam delivery, a video camera acquired images at 120 Hz of the moving marker block and light-emitting crystal. After treatment, the block position and crystal light intensity were determined in all video frames. Two methods were used to determine the gate-on (τ_on ) and gate-off (τ_off ) latencies. By method 1, the video was synchronized with gating log files by temporal alignment of the same block motion recorded in both the video and the log files. τ_on was defined as the time from the block entered the gating window (from gating log files) to the actual beam-on as detected by the crystal light. Similarly, τ_off was the time from the block exited the gating window to beam-off. By method 2, τ_on and τ_off were found from the videos alone using motion of different sine periods (1-10 s). In each video, a sinusoidal fit of the block motion provided the times T_min of the lowest block position. The mid-time, T_mid-light , of each beam-on period was determined as the time halfway between crystal light signal start and end. It can be shown that the directly measurable quantity T_mid-light - T_min  = (τ_off +τ_on )/2, which provided the sum (τ_off +τ_on ) of the two latencies. It can also be shown that the beam-on (i.e., crystal light) duration ΔT_light increases linearly with the sine period and depends on τ_off - τ_on : ΔT_light  = constant•period+(τ_off - τ_on ). Hence, a linear fit of ΔT_light as a function of the period provided the difference of the two latencies. From the sum (τ_off +τ_on ) and difference (τ_off - τ_on ), the individual latencies were determined.

RESULTS

Method 1 resulted in mean (±SD) latencies of τ_on  = 255 ± 33 ms, τ_off  = 82 ± 15 ms for the ProBeam and τ_on  = 84 ± 13 ms, τ_off  = 44 ± 11 ms for the TrueBeam. Method 2 resulted in latencies of τ_on  = 255 ± 23 ms, τ_off  = 95 ± 23 ms for the ProBeam and τ_on  = 83 ± 8 ms, τ_off  = 46 ± 8 ms for the TrueBeam. Hence, the mean latencies determined by the two methods agreed within 13 ms for the ProBeam and within 2 ms for the TrueBeam.

CONCLUSIONS

A novel, simple and low-cost method for gating latency measurements that work across different radiotherapy platforms was demonstrated. Only the TrueBeam fully fulfilled the AAPM TG-142 recommendation of maximum 100 ms latencies.

Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy

Background

Surface-guided radiation therapy can be used to continuously monitor a patient’s surface motions during radiotherapy by a non-irradiating, noninvasive optical surface imaging technique. In this study, machine learning methods were applied to predict external respiratory motion signals and predict internal liver motion in this therapeutic context.

Methods

Seven groups of interrelated external/internal respiratory liver motion samples lasting from 5 to 6 min collected simultaneously were used as a dataset, D_v. Long short-term memory (LSTM) and support vector regression (SVR) networks were then used to establish external respiratory signal prediction models (LSTMpred/SVRpred) and external/internal respiratory motion correlation models (LSTMcorr/SVRcorr). These external prediction and external/internal correlation models were then combined into an integrated model. Finally, the LSTMcorr model was used to perform five groups of model updating experiments to confirm the necessity of continuously updating the external/internal correlation model. The root-mean-square error (RMSE), mean absolute error (MAE), and maximum absolute error (MAX_AE) were used to evaluate the performance of each model.

Results

The models established using the LSTM neural network performed better than those established using the SVR network in the tasks of predicting external respiratory signals for latency-compensation (RMSE < 0.5 mm at a latency of 450 ms) and predicting internal liver motion using external signals (RMSE < 0.6 mm). The prediction errors of the integrated model (RMSE ≤ 1.0 mm) were slightly higher than those of the external prediction and external/internal correlation models. The RMSE/MAE of the fifth model update was approximately ten times smaller than that of the first model update.

Conclusions

The LSTM networks outperform SVR networks at predicting external respiratory signals and internal liver motion because of LSTM’s strong ability to deal with time-dependencies. The LSTM-based integrated model performs well at predicting liver motion from external respiratory signals with system latencies of up to 450 ms. It is necessary to update the external/internal correlation model continuously.

Accuracy of real-time respiratory motion tracking and time delay of gating radiotherapy based on optical surface imaging technique

Background

Surface-guided radiation therapy (SGRT) employs a non-invasive real-time optical surface imaging (OSI) technique for patient surface motion monitoring during radiotherapy. The main purpose of this study is to verify the real-time tracking accuracy of SGRT for respiratory motion and provide a fitting method to detect the time delay of gating.

Methods

A respiratory motion phantom was utilized to simulate respiratory motion using 17 cosine breathing pattern curves with various periods and amplitudes. The motion tracking of the phantom was performed by the Catalyst™ system. The tracking accuracy of the system (with period and amplitude variations) was evaluated by analyzing the adjusted coefficient of determination (A_R²) and root mean square error (RMSE). Furthermore, 13 actual respiratory curves, which were categorized into regular and irregular patterns, were selected and then simulated by the phantom. The Fourier transform was applied to the respiratory curves, and tracking accuracy was compared through the quantitative analyses of curve similarity using the Pearson correlation coefficient (PCC). In addition, the time delay of amplitude-based respiratory-gating radiotherapy based on the OSI system with various beam hold times was tested using film dosimetry for the Elekta Versa-HD and Varian Edge linacs. A dose convolution-fitting method was provided to accurately measure the beam-on and beam-off time delays.

Results

A_R² and RMSE for the cosine curves were 0.9990–0.9996 and 0.110–0.241 mm for periods ranging from 1 s to 10 s and 0.9990–0.9994 and 0.059–0.175 mm for amplitudes ranging from 3 mm to 15 mm. The PCC for the actual respiratory curves ranged from 0.9955 to 0.9994, which was not significantly affected by breathing patterns. For gating radiotherapy, the average beam-on and beam-off time delays were 1664 ± 72 and 25 ± 30 ms for Versa-HD and 303 ± 45 and 34 ± 25 ms for Edge, respectively. The time delay was relatively stable as the beam hold time increased.

Conclusions

The OSI technique provides high accuracy for respiratory motion tracking. The proposed dose convolution-fitting method can accurately measure the time delay of respiratory-gating radiotherapy. When the OSI technique is used for respiratory-gating radiotherapy, the time delay for the beam-on is considerably longer than the beam-off.

Quality assurance of gating response times for surface guided motion management treatment delivery using an electronic portal imaging detector

Gating response times of monitoring system/LINAC combinations for gated radiotherapy treatments are notoriously difficult to measure. This difficulty may reflect why the incorporation of gating response times is not thoroughly considered when creating treatment margins for gated radiotherapy treatments, however ignoring the effect of gating response time could lead to significant treatment inaccuracies. This study shows a methodology which measured gating response times for AlignRT/Varian Truebeam combination which appears to be applicable to any surface guided monitoring/Linac combination as well as those combinations which incorporate extended lag times (>200 ms). Beam on lag time appears to be measurably greater than beam off lag time. Although these gating response times are slower than other gating systems on the market, the advantages surface guided radiotherapy (SGRT) could potentially provide for treatment accuracy is discussed as well as demonstrating the lack of guidance regarding SGRT with respect to gated treatments.

A quality assurance for respiratory gated proton irradiation with range modulation wheel

The purpose of this study was to provide periodic quality assurance (QA) methods for respiratory-gated proton beam with a range modulation wheel (RMW) and to clarify the characteristics and long-term stability of the respiratory-gated proton beam. A two-dimensional detector array and a solid water phantom were used to measure absolute dose, spread-out Bragg peak (SOBP) width and proton range for monthly QA. SOBP width and proton range were measured using an oblique incidence beam to the lateral side of a solid water phantom and compared between with and without a gating proton beam. To measure the delay time of beam-on/off for annual QA, we collected the beam-on/off signals and the dose monitor-detected pulse. We analyzed the results of monthly QA over a 15-month period and investigated the delay time by machine signal analysis. The dose deviations at proximal, SOBP center and distal points were -0.083 ± 0.25%, 0.026 ± 0.20%, and -0.083 ± 0.35%, respectively. The maximum dose deviation between with and without respiratory gating was -0.95% at the distal point and other deviations were within ±0.5%. Proximal and SOBP center doses showed the same trend over a 15-month period. Delay times of beam-on/off for 200 MeV/SOBP 16 cm were 140.5 ± 0.8 ms and 22.3 ± 13.0 ms, respectively. Delay times for 160 MeV/SOBP 10 cm were 167.5 ± 15.1 ms and 19.1 ± 9.8 ms. Our beam delivery system with the RMW showed sufficient stability for respiratory-gated proton therapy and the system did not show dependency on the energy and the respiratory wave form. The delay times of beam-on/off were within expectations. The proposed QA methods will be useful for managing the quality of respiratory-gated proton beams and other beam delivery systems.

[Impact of Respiratory Waveform on Gate Signal Generation on Respiratory Gated Irradiation and Evaluation Method of Respiratory Waveform to Be Used]

PURPOSE

The respiratory gated irradiation using the real-time position management system (RPM) was used to clarify the generation of the gated signal when the respiration waveform changed, and also the evaluation method of the respiration waveform was also examined.

METHODS

The respiratory waveform was changed using a moving phantom. Respiratory waveform was analyzed from the data recorded in RPM, and the out-of-phase gated rate was examined. Analysis was made by focusing on the coefficient of variation of the respiratory wavelength in the evaluation of respiratory waveform.

RESULTS

Immediately after the change of respiratory wavelength from the short cycle to the long cycle, a gated signal was generated at a phase before the set gated phase, and a maximum advance of 1.259 ± 0.212 s occurred. Immediately after the change of respiratory wavelength from the long cycle to the short cycle, the gated signal was generated at the phase exceeding the set gated phase, and a delay of 0.997 ± 0.180 s occurred at the maximum. As the value of the coefficient of variation increased, the gated rate which was out of setting also increased.

CONCLUSION

In respiratory gated irradiation using RPM, it became clear that the gated signal is generated out of the phase set by the respiratory waveform change. Coefficient of variation of the respiratory wavelength is considered to be an indicator for evaluating the respiratory waveform to be used in the respiratory gated irradiation.

Technical Note: A novel quality assurance test to identify gantry angle inaccuracies in respiratory-gated VMAT treatments

PURPOSE

During respiratory-gated volumetric-modulated arc therapy (VMAT), the radiation beam is turned off each time the target exits the gating window. At the same time, the gantry slows, stops, and rewinds before the beam is turned back on. A quality assurance (QA) test was developed to detect inaccuracies in the gantry angle position between beam-off and beam-on events during respiratory-gated VMAT.

METHODS

Strips of Gafchromic™ EBT3 film were taped to the surface of a Capthan^® 504 phantom mounted at isocenter. A homogeneous dose was delivered to the films through a 2 cm × 10 cm slit in the jaws using a respiratory-gated VMAT arc without the multileaf collimator. A periodic breathing cycle was used. Errors in gated delivery ranging from 0.5 to 5° were simulated by delivering nongated arcs with the same field size with over- and underlapping sections of 0.5-5°. The simulated errors were used to define QA levels to analyze the gated delivery.

RESULTS

The QA test was capable of detecting errors as small as 0.5°. The test was delivered to three Varian TrueBeam™ linacs, and no gantry angle inaccuracies greater than or equal to 0.5° were detected on any of the films.

CONCLUSIONS

A QA test capable of detecting gantry angle inaccuracies at beam-off and subsequent beam-on as small as 0.5° was developed and implemented for Varian TrueBeam™ linacs.

Technical Note: High temporal resolution characterization of gating response time

PURPOSE

Low temporal latency between a gating ON/OFF signal and the LINAC beam ON/OFF during respiratory gating is critical for patient safety. Here the authors describe a novel method to precisely measure gating lag times at high temporal resolutions.

METHODS

A respiratory gating simulator with an oscillating platform was modified to include a linear potentiometer for position measurement. A photon diode was placed at linear accelerator isocenter for beam output measurement. The output signals of the potentiometer and diode were recorded simultaneously at 2500 Hz with an analog to digital converter for four different commercial respiratory gating systems. The ON and OFF of the beam signal were located and compared to the expected gating window for both phase and position based gating and the temporal lag times extracted.

RESULTS

For phase based gating, a real-time position management (RPM) infrared marker tracking system with a single camera and a RPM system with a stereoscopic camera were measured to have mean gate ON/OFF lag times of 98/90 and 86/44 ms, respectively. For position based gating, an AlignRT 3D surface system and a Calypso magnetic fiducial tracking system were measured to have mean gate ON/OFF lag times of 356/529 and 209/60 ms, respectively.

CONCLUSIONS

Temporal resolution of the method was high enough to allow characterization of individual gate cycles and was primary limited by the sampling speed of the data recording device. Significant variation of mean gate ON/OFF lag time was found between different gating systems. For certain gating devices, individual gating cycle lag times can vary significantly.

Technical Report: TG-142 compliant and comprehensive quality assurance tests for respiratory gating

PURPOSE

To develop and establish a comprehensive gating commissioning and quality assurance procedure in compliance with TG-142.

METHODS

Eight Varian TrueBeam Linacs were used for this study. Gating commissioning included an end-to-end test and baseline establishment. The end-to-end test was performed using a CIRS dynamic thoracic phantom with a moving cylinder inside the lung, which was used for carrying both optically simulated luminescence detectors (OSLDs) and Gafchromic EBT2 films while the target is moving, for a point dose check and 2D profile check. In addition, baselines were established for beam-on temporal delay and calibration of the surrogate, for both megavoltage (MV) and kilovoltage (kV) beams. A motion simulation device (MotionSim) was used to provide periodic motion on a platform, in synchronizing with a surrogate motion. The overall accuracy and uncertainties were analyzed and compared.

RESULTS

The OSLD readings were within 5% compared to the planned dose (within measurement uncertainty) for both phase and amplitude gated deliveries. Film results showed less than 3% agreement to the predicted dose with a standard sinusoid motion. The gate-on temporal accuracy was averaged at 139±10 ms for MV beams and 92±11 ms for kV beams. The temporal delay of the surrogate motion depends on the motion speed and was averaged at 54.6±3.1 ms for slow, 24.9±2.9 ms for intermediate, and 23.0±20.1 ms for fast speed.

CONCLUSIONS

A comprehensive gating commissioning procedure was introduced for verifying the output accuracy and establishing the temporal accuracy baselines with respiratory gating. The baselines are needed for routine quality assurance tests, as suggested by TG-142.