Technical Note: Evaluation of the latency and the beam characteristics of a respiratory gating system using an Elekta linear accelerator and a respiratory indicator device, Abches

A novel internal target volume definition based on velocity and time of respiratory target motion for external beam radiotherapy

This study aimed to develop a novel internal target volume (ITV) definition for respiratory motion targets, considering target motion velocity and time. The proposed ITV was evaluated in respiratory-gated radiotherapy. An ITV modified with target motion velocity and time (ITVvt) was defined as an ITV that includes a target motion based on target motion velocity and time. The target motion velocity was calculated using four-dimensional computed tomography (4DCT) images. The ITVvts were created from phantom and clinical 4DCT images. The phantom 4DCT images were acquired using a solid phantom that moved with a sinusoidal waveform (peak-to-peak amplitudes of 10 and 20 mm and cycles of 2-6 s). The clinical 4DCT images were obtained from eight lung cancer cases. In respiratory-gated radiotherapy, the ITVvt was compared with conventional ITVs for beam times of 0.5-2 s within the gating window. The conventional ITV was created by adding a uniform margin as the maximum motion within the gating window. In the phantom images, the maximum volume difference between the ITVvt and conventional ITV was -81.9%. In the clinical images, the maximum volume difference was -53.6%. Shorter respiratory cycles and longer BTs resulted in smaller ITVvt compared with the conventional ITV. Therefore, the proposed ITVvt plan could be used to reduce treatment volumes and doses to normal tissues.

Use of a pressure sensor array for multifunctional patient monitoring in radiotherapy: A feasibility study

BACKGROUND

Modern radiotherapeutic techniques, such as intensity-modulated radiation therapy or stereotactic body radiotherapy, require high-dose delivery precision. However, the precise localization of tumors during patient respiration remains a challenge. Therefore, it is essential to investigate effective methods for monitoring respiration to minimize potential complications. Despite several systems currently in clinical use, there are drawbacks, including the complexity of the setup, the discomfort to the patient, and the high cost.

PURPOSE

This study investigated the feasibility of using a novel pressure sensor array (PSA) as a tool to monitor respiration during radiotherapy treatments. The PSA was positioned between the treatment couch and the back of the patient lying on it and was intended to overcome some limitations of current methods. The main objectives included assessing the PSA's capability in monitoring respiratory behavior and to investigate prospective applications that extend beyond respiratory monitoring.

METHODS

A PSA with 31 pressure-sensing elements was used in 12 volunteers. The participants were instructed to breathe naturally while lying on a couch without any audio or visual guidance. The performance of the PSA was compared to that of a camera-based respiratory monitoring system (RPM, Varian, USA), which served as a reference. Several metrics, including pressure distribution, weight sensitivity, and correlations between PSA and RPM signals, were analyzed. The PSA's capacity to provide information on potential applications related to patient stability was also investigated.

RESULTS

The linear relationship between the weight applied to the PSA and its output was demonstrated in this study, confirming its sensitivity to pressure changes. A comparison of PSA and RPM curves revealed a high correlation coefficient of 0.9391 on average, indicating consistent respiratory cycles. The PSA also effectively measured the weight distribution at the volunteer's back in real-time, which allows for monitoring the patient's movements during the radiotherapy.

CONCLUSION

PSA is a promising candidate for effective respiratory monitoring during radiotherapy treatments. Its performance is comparable to the established RPM system, and its additional capabilities suggest its multifaceted utility. This paper shows the potential use of PSA for patient monitoring in radiotherapy and suggests possibilities for further research, including performance comparisons with other existing systems and real-patient applications with respiratory training.

Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study

PURPOSE

Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lung cancer provides important information for the feasibility of the individualized radiotherapy and allows to select the appropriate treatment strategy based on the risk of recurrence. In this study, we evaluated the performance of both machine learning models using positron emission tomography (PET) and computed tomography (CT) radiomic features for predicting recurrence after SBRT.

METHODS

Planning CT and PET images of 82 non-small cell lung cancer patients who performed SBRT at our hospital were used. First, tumors were delineated on each CT and PET of each patient, and 111 unique radiomic features were extracted, respectively. Next, the 10 features were selected using three different feature selection algorithms, respectively. Recurrence prediction models based on the selected features and four different machine learning algorithms were developed, respectively. Finally, we compared the predictive performance of each model for each recurrence pattern using the mean area under the curve (AUC) calculated following the 0.632+ bootstrap method.

RESULTS

The highest performance for local recurrence, regional lymph node metastasis, and distant metastasis were observed in models using Support vector machine with PET features (mean AUC = 0.646), Naive Bayes with PET features (mean AUC = 0.611), and Support vector machine with CT features (mean AUC = 0.645), respectively.

CONCLUSIONS

We comprehensively evaluated the performance of prediction model developed for recurrence following SBRT. The model in this study would provide information to predict the recurrence pattern and assist in making treatment strategies.

Clinical practicality and patient performance for surface-guided automated VMAT gating for DIBH breast cancer radiotherapy

BACKGROUND AND PURPOSE

To evaluate the performance of automated surface-guided gating for left-sided breast cancer with DIBH and VMAT.

MATERIALS AND METHODS

Patients treated in the first year after introduction of DIBH with VMAT were retrospectively considered for analysis. With automated surface-guided gating the beam automatically switches on/off, if the surface region of interest moved in/out the gating tolerance (±3 mm, ±3°). Patients were coached to hold their breath as long as comfortably possible. Depending on the patient's preference, patients received audio instructions during treatment delivery. Real-time positional variations of the breast/chest wall surface with respect to the reference surface were collected, for all three orthogonal directions. The durations and number of DIBHs needed to complete dose delivery, and DIBH position variations were determined. To evaluate an optimal gating window threshold, smaller tolerances of ±2.5 mm, ±2.0 mm, and ±1.5 mm were simulated.

RESULTS

525 fractions from 33 patients showed that median DIBH duration was 51 s (range: 30-121 s), and median 4 DIBHs per fraction were needed to complete VMAT dose delivery. Median intra-DIBH stability and intrafractional DIBH reproducibility approximated 1.0 mm in each direction. No large differences were found between patients who preferred to perform the DIBH procedure with (n = 21) and without audio-coaching (n = 12). Simulations demonstrated that gating window tolerances could be reduced from ±3.0 mm to ±2.0 mm, without affecting beam-on status.

CONCLUSION

Independent of the use of audio-coaching, this study demonstrates that automated surface-guided gating with DIBH and VMAT proved highly efficient. Patients' DIBH performance far exceeded our expectations compared to earlier experiences and literature. Furthermore, gating window tolerances could be reduced.

Biomedical advances and future prospects of high-precision three-dimensional radiotherapy and four-dimensional radiotherapy

Biomedical advances of external-beam radiotherapy (EBRT) with improvements in physical accuracy are reviewed. High-precision (±1 mm) three-dimensional radiotherapy (3DRT) can utilize respective therapeutic open doors in the tumor control probability curve and in the normal tissue complication probability curve instead of the one single therapeutic window in two-dimensional EBRT. High-precision 3DRT achieved higher tumor control and probable survival rates for patients with small peripheral lung and liver cancers. Four-dimensional radiotherapy (4DRT), which can reduce uncertainties in 3DRT due to organ motion by real-time (every 0.1-1 s) tumor-tracking and immediate (0.1-1 s) irradiation, have achieved reduced adverse effects for prostate and pancreatic tumors near the digestive tract and with similar or better tumor control. Particle beam therapy improved tumor control and probable survival for patients with large liver tumors. The clinical outcomes of locally advanced or multiple tumors located near serial-type organs can theoretically be improved further by integrating the 4DRT concept with particle beams.

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.

Measurement of the temporal latency of a respiratory gating system using two distinct approaches

Purpose

To develop a methodology that can be used to measure the temporal latency of a respiratory gating system.

Methods

The gating system was composed of an automatic gating interface (Response) and an in‐house respiratory motion monitoring system featuring an optically tracked surface marker. Two approaches were used to measure gating latencies. A modular approach involved measuring separately the latency of the gating system's complementary metal–oxide–semiconductor tracking camera, tracking software, and a gating latency of the LINAC. Additionally, an end‐to‐end approach was used to measure the total latency of the gating system. End‐to‐end latencies were measured using the displacement of a radiographic target moving at known velocities during the gating process.

Results

Summing together the latencies of each of the modular components investigated yielded a total beam‐on latency of 1.55 s and a total beam‐off latency of 0.49 s. End‐to‐end beam‐on and beam‐off latency was found to be 1.49 and 0.34 s, respectively. In each case, no statistically significant differences were found between the end‐to‐end latency of the gating system and the summation of the individually measured components.

Conclusion

Two distinct approaches to quantify gating latencies were presented. Measuring the end‐to‐end latency of the gating system provided an independent means of validating the modular approach. It is expected that the beam‐on latencies reported in this work could be reduced by altering the control system configuration of the LINAC. The modular approach can be used to decouple the individual latencies of the gating system, but future improvements in the temporal resolution of the service graphing feature are needed to reduce the uncertainty of LINAC‐related gating latencies measured using this approach. Both approaches are generalizable and can be used together when designing a quality assurance program for a respiratory gating system.

Individual pulse monitoring and dose control system for pre-clinical implementation of FLASH-RT

Objective.Existing ultra-high dose rate (UHDR) electron sources lack dose rate independent dosimeters and a calibrated dose control system for accurate delivery. In this study, we aim to develop a custom single-pulse dose monitoring and a real-time dose-based control system for a FLASH enabled clinical linear accelerator (Linac).Approach.A commercially available point scintillator detector was coupled to a gated integrating amplifier and a real-time controller for dose monitoring and feedback control loop. The controller was programmed to integrate dose for each radiation pulse and stop the radiation beam when the prescribed dose was delivered. Additionally, the scintillator was mounted in a solid water phantom and placed underneath mice skin forin vivodose monitoring. The scintillator was characterized in terms of its radiation stability, mean dose-rate (Ḋm), and dose per pulse (Dp) dependence.Main results.TheDpexhibited a consistent ramp-up period across ∼4-5 pulse. The plastic scintillator was shown to be linear withḊm(40-380 Gy s-1) andDp(0.3-1.3 Gy Pulse-1) to within +/- 3%. However, the plastic scintillator was subject to significant radiation damage (16%/kGy) for the initial 1 kGy and would need to be calibrated frequently. Pulse-counting control was accurately implemented with one-to-one correspondence between the intended and the actual delivered pulses. The dose-based control was sufficient to gate on any pulse of the Linac.In vivodosimetry monitoring with a 1 cm circular cut-out revealed that during the ramp-up period, the averageDpwas ∼0.045 ± 0.004 Gy Pulse-1, whereas after the ramp-up it stabilized at 0.65 ± 0.01 Gy Pulse-1.Significance.The tools presented in this study can be used to determine the beam parameter space pertinent to the FLASH effect. Additionally, this study is the first instance of real-time dose-based control for a modified Linac at ultra-high dose rates, which provides insight into the tool required for future clinical translation of FLASH-RT.

Reproducibility of deep inspiration breath-hold technique for left-side breast cancer with respiratory monitoring device, Abches

PURPOSE

This study aimed to evaluate the reproducibility of deep inspiration breath-hold (DIBH) using a respiratory control device, Abches, in patients with left-sided breast cancer.

MATERIAL AND METHODS

Abches comprises a main body, an indicator panel, and two fulcrums, one each on the chest and abdomen. Forty left side breast cancer patients treated with DIBH using abches were enrolled in this study. For all patients, CT images were taken three times to confirm the target position inside the body and to check the breath-hold reproducibility. Three anatomical points on the nipple, sternum, and heart were selected as measurement points on CT images. After measuring the coordinates, breath-hold reproducibility was defined as the mean of the absolute difference in the coordinates between the three CT images. The maximum differences were also investigated. In addition, the dice similarity coefficient (DSC) was calculated to examine the displacement of the heart volume in detail. Moreover, digitally reconstructed radiographs (DRRs) and linac graphs (LGs) were used to measure the positional accuracy of the chest and heart.

RESULTS

The reproducibility in all patients was within 0.75 mm for the nipple, 0.78 mm for the sternum, and 2.18 mm for the heart in each direction. Similarly, the maximum displacements for all patients were within 1.90 mm, 1.69 mm, and 4.75 mm, respectively, in each direction. For heart volume, the average DSC for all cases was 0.93 ± 0.01. The differences between the DRR and LG images were 1.70 ± 1.10 mm and 2.10 ± 1.60 mm, for the chest and heart, respectively.

CONCLUSION

Our study showed that DIBH using Abches can be performed with good target reproducibility of less than 3 mm with proper breath-hold practice, whereas the heartbeat-derived reproducibility of the cardiac position is poor and needs to be monitored carefully during treatment simulation.

Clinical experience of MRI4D QUASAR motion phantom for latency measurements in 0.35T MR-LINAC

PURPOSE

In MRgRT, accuracy of treatment depends on the gating latency, when real-time targeting and gating is enabled. Gating latency is dependent on image acquisition, processing time, accuracy, efficacy of target tracking algorithms, and radiation beam delivery latency. In this report, clinical experience of the MRI4D QUASAR motion phantom for latency measurements on a 0.35-T magnetic resonance-linear accelerator (MR-LINAC) with two imaging speeds and four tracking algorithms was studied.

MATERIALS/METHODS

Beam-control latency was measured on a 0.35-T MR-LINAC system with four target tracking algorithms and two real-time cine imaging sequences [four and eight frames per second (FPS)]. Using an MR-compatible motion phantom, the delays between phantom beam triggering signal and linac radiation beam control signal were evaluated for three motion periods with a rigid target. The gating point was set to be 8 mm above the full exhalation position. The beam-off latency was measured for a total of 24 combinations of tracking algorithm, imaging FPS, and motion periods. The corresponding gating target margins were determined using the target motion speed multiplied by the beam-off latency.

RESULTS

The largest measured beam-off latency was 302 ± 20 ms with the Large Deforming Targets (LDT) algorithm and 4 s motion period imaged with 8-FPS cine MRI. The corresponding gating uncertainty based on target motion speed was 3.0 mm. The range of the average beam-off latency was 128-243 ms in 4-FPS imaging and 47-302 ms in 8-FPS imaging.

CONCLUSIONS

The gating latency was measured using an MRI4D QUASAR motion phantom in a 0.35-T MR-LINAC. The latency measurements include time delay related to MR imaging method, target tracking algorithm and system delay. The gating uncertainty was estimated based on the beam-off latency measurements and the target motion.

New method for measurement of chest surface motion in lung cancer patients: Quantification using a technique of deformable image registration

The purpose of this study was to measure the motion of the chest surface during breath-holding treatment for lung cancer using deformable image registration (DIR). Forty non-small-cell lung cancer patients treated with breath-holding stereotactic body radiation therapy were retrospectively examined. First, intensity-based DIR between 2 breath-holding computed tomography (CT) images was performed. Subsequently, deformation vector field (DVF) for all dimensions (left-right, anterior-posterior, and superior-inferior) was calculated from the result. For the analysis of chest surface, the DVF value of the only chest surface area was extracted after the chest surface was divided into 12 regions of interest (ROI) based on anatomy. Additionally, for the analysis of the correlation with the internal tumor motion, the median value of DVF for each surface ROI and the motion of the center of gravity of the tumor volume were used. It was possible to calculate the motion of chest surface without any outliers for all patients. For the average of 12 surface ROIs, the motion of 3D chest surface was within 2 mm (30 cases), 3 mm (8 cases), and 4 mm (2 cases). There was no correlation between the motion of the chest surface and that of the tumor for all 12 surface ROIs. We proposed a technique to evaluate the surface motion using DIR between multiple CT images. It could be a useful tool to calculate the motion of chest surface.

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.

Evaluation of the target dose coverage of stereotactic body radiotherapy for lung cancer using helical tomotherapy: A dynamic phantom study

Aim

To evaluate the target dose coverage for lung stereotactic body radiotherapy (SBRT) using helical tomotherapy (HT) with the internal tumor volume (ITV) margin settings adjusted according to the degree of tumor motion.

Background

Lung SBRT with HT may cause a dosimetric error when the target motion is large.

Materials and methods

Two lung SBRT plans were created using a tomotherapy planning station. Using these original plans, five plans with different ITV margins (4.0-20.0 mm for superior-inferior [SI] dimension) were generated. To evaluate the effects of respiratory motion on HT, an original dynamic motion phantom was developed. The respiratory wave of a healthy volunteer was used for dynamic motion as the typical tumor respiratory motion. Five patterns of motion amplitude that corresponded to five ITV margin sizes and three breathing cycles of 7, 14, and 28 breaths per minute were used. We evaluated the target dose change between a static delivery and a dynamic delivery with each motion pattern.

Results

The target dose difference increased as the tumor size decreased and as the tumor motion increased. Although a target dose difference of <5 % was observed at ≤10 mm of tumor motion for each condition, a maximum difference of -9.94 % ± 7.10 % was observed in cases of small tumors with 20 mm of tumor motion under slow respiration.

Conclusions

Minimizing respiratory movement is recommended as much as possible for lung SBRT with HT, especially for cases involving small tumors.

Prediction-Based Compensation for Gate On/Off Latency during Respiratory-Gated Radiotherapy

During respiratory-gated radiotherapy (RGRT), gate on and off latencies cause deviations of gating windows, possibly leading to delivery of low- and high-dose radiations to tumors and normal tissues, respectively. Currently, there are no RGRT systems that have definite tools to compensate for the delays. To address the problem, we propose a framework consisting of two steps: (1) multistep-ahead prediction and (2) prediction-based gating. For each step, we have devised a specific algorithm to accomplish the task. Numerical experiments were performed using respiratory signals of a phantom and ten volunteers, and our prediction-based RGRT system exhibited superior performance in more than a few signal samples. In some, however, signal prediction and prediction-based gating did not work well, maybe due to signal irregularity and/or baseline drift. The proposed approach has potential applicability in RGRT, and further studies are needed to verify and refine the constituent algorithms.