Implementation of free breathing respiratory amplitude-gated treatments

Accuracy of four models and update strategies to estimate liver tumor motion from external respiratory motion

Background

This study investigates different strategies for estimating internal liver tumor motion during radiotherapy based on continuous monitoring of external respiratory motion combined with sparse internal imaging.

Methods

Fifteen patients underwent three-fraction stereotactic liver radiotherapy. The 3D internal tumor motion (INT) was monitored by electromagnetic transponders while a camera monitored the external marker block motion (EXT). The ability of four external-internal correlation models (ECM) to estimate INT as function of EXT was investigated: a simple linear model (ECM1), an augmented linear model (ECM2), an augmented quadratic model (ECM3), and an extended quadratic model (ECM4). Each ECM was constructed by fitting INT and EXT during the first 60s of each fraction. The fit accuracy was calculated as the root-mean-square error (RMSE) between ECM-estimated and actual tumor motion. Next, the RMSE of the ECM-estimated tumor motion throughout the fractions was calculated for four simulated ECM update strategies: (A) no update, 0.33Hz internal sampling with continuous update of either (B) all ECM parameters based on the last 2 minutes samples or (C) only the baseline term based on the last 5 samples, (D) full ECM update every minute using 20s continuous internal sampling.

Results

The augmented quadratic ECM3 had best fit accuracy with mean (± SD)) RMSEs of 0.32 ± 0.11mm (left-right, LR), 0.79 ± 0.30mm (cranio-caudal, CC) and 0.56 ± 0.31mm (anterior-posterior, AP). However, the simpler augmented linear ECM2 combined with frequent baseline updates (update strategy C) gave best motion estimations with mean RMSEs of 0.41 ± 0.14mm (LR), 1.02 ± 0.33mm (CC) and 0.78 ± 0.48mm (AP). This was significantly better than all other ECM-update strategy combinations for CC motion (Wilcoxon signed rank p<0.05).

Conclusion

The augmented linear ECM2 combined with frequent baseline updates provided the best compromise between fit accuracy and robustness towards irregular motion. It allows accurate internal motion monitoring by combining external motioning with sparse 0.33Hz kV imaging, which is available at conventional linacs.

Impact of different respiratory gating methods on target delineation and a radiotherapy plan for solitary pulmonary tumors

BACKGROUND AND PURPOSE

Respiratory movement has an important impact on the radiotherapy for lung tumor. Respiratory gating technology is helpful to improve the accuracy of target delineation. This study investigated the value of prospective and retrospective respiratory gating simulations in target delineation and radiotherapy plan design for solitary pulmonary tumors (SPTs) in radiotherapy.

METHODS

The enrolled patients underwent CT simulation with three-dimensional (3D) CT non gating, prospective respiratory gating, and retrospective respiratory gating simulation. The target volumes were delineated on three sets of CT images, and radiotherapy plans were prepared accordingly. Tumor displacements and movement information obtained using the two respiratory gating approaches, as well as the target volumes and dosimetry parameters in the radiotherapy plan were compared.

RESULTS

No significant difference was observed in tumor displacement measured using the two gating methods (p > 0.05). However, the internal gross tumor volumes (IGTVs), internal target volumes (ITVs), and planning target volumes (PTVs) based on the retrospective respiratory gating simulation were larger than those obtained using prospective gating (group A: pIGTV = 0.041, pITV = 0.003, pPTV = 0.008; group B: pIGTV = 0.025, pITV = 0.039, pPTV = 0.004). The two-gating PTVs were both smaller than those delineated on 3D non gating images (p < 0.001). V5Gy, V10Gy, V20Gy, V30Gy, and mean lung dose in the two gated radiotherapy plans were lower than those in the 3D non gating plan (p < 0.001); however, no significant difference was observed between the two gating plans (p > 0.05).

CONCLUSIONS

The application of respiratory gating could reduce the target volume and the radiation dose that the normal lung tissue received. Compared to prospective respiratory gating, the retrospective gating provides more information about tumor movement in PTV.

Explicitly encoding the cyclic nature of breathing signal allows for accurate breathing motion prediction in radiotherapy with minimal training data

Background and purpose

Active breathing motion management in radiotherapy consists of motion monitoring, quantification and mitigation. It is impacted by associated latencies of a few 100 ms. Artificial neural networks can successfully predict breathing motion and eliminate latencies. However, they require usually a large dataset for training. The objective of this work was to demonstrate that explicitly encoding the cyclic nature of the breathing signal into the training data enables significant reduction of training datasets which can be obtained from healthy volunteers.

Material and methods

Seventy surface scanner breathing signals from 25 healthy volunteers in anterior-posterior direction were used for training and validation (ratio 4:1) of long short-term memory models. The model performance was compared to a model using decomposition into phase, amplitude and a time-dependent baseline. Testing of the models was performed on 55 independent breathing signals in anterior-posterior direction from surface scanner (35 lung, 20 liver) of 30 patients with a mean breathing amplitude of (5.9 ± 6.7) mm.

Results

Using the decomposed breathing signal allowed for a reduction of the absolute root-mean square error (RMSE) from 0.34 mm to 0.12 mm during validation. Testing using patient data yielded an average absolute RMSE of the breathing signal of (0.16 ± 0.11) mm with a prediction horizon of 500 ms.

Conclusion

It was demonstrated that a motion prediction model can be trained with less than 100 datasets of healthy volunteers if breathing cycle parameters are considered. Applied to 55 patients, the model predicted breathing motion with a high accuracy.

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.

Adoption of respiratory motion management in radiation therapy

Background and Purpose

A survey on the patterns of practice of respiratory motion management (MM) was distributed to 111 radiation therapy facilities to inform the development of an end-to-end dosimetry audit including respiratory motion.

Materials and methods

The survey (distributed via REDCap) asked facilities to provide information specific to the combinations of MM techniques (breath-hold gating – BHG, internal target volume – ITV, free-breathing gating – FBG, mid-ventilation – MidV, tumour tracking – TT), sites treated (thorax, upper abdomen, lower abdomen), and fractionation regimes (conventional, stereotactic ablative body radiation therapy – SABR) used in their clinic.

Results

The survey was completed by 78% of facilities, with 98% of respondents indicating that they used at least one form of MM. The ITV approach was common to all MM-users, used for thoracic treatments by 89% of respondents, and upper and lower abdominal treatments by 38%. BHG was the next most prevalent (41% of MM users), with applications in upper abdominal and thoracic treatment sites (28% vs 25% respectively), but minimal use in the lower abdomen (9%). FBG and TT were utilised sparingly (17%, 7% respectively), and MidV was not selected at all.

Conclusions

Two distinct treatment workflows (including use of motion limitation, imaging used for motion assessment, dose calculation, and image guidance procedures) were identified for the ITV and BHG MM techniques, to form the basis of the initial audit. Thoracic SABR with the ITV approach was common to nearly all respondents, while upper abdominal SABR using BHG stood out as more technically challenging. Other MM techniques were sparsely used, but may be considered for future audit development.

A standardized workflow for respiratory-gated motion management decision-making

Purpose

Motion management of tumors within the lung and abdomen is challenging because it requires balancing tissue sparing with accuracy of hitting the target, while considering treatment delivery efficiency. Physicists can play an important role in analyzing four‐dimensional computed tomography (4DCT) data to recommend the optimal respiratory gating parameters for a patient. The goal of this work was to develop a standardized procedure for making recommendations regarding gating parameters and planning margins for lung and gastrointestinal stereotactic body radiotherapy (SBRT) treatments. In doing so, we hoped to simplify decision‐making and analysis, and provide a tool for troubleshooting complex cases.

Methods

Factors that impact gating decisions and planning target volume (PTV) margins were identified. The gating options included gating on exhale with approximately a 50% duty cycle (Gate3070), exhale gating with a reduced duty cycle (Gate4060), and treating for most of respiration, excluding only extreme inhales and exhales (Gate100). A standard operating procedure was developed, as well as a physics consult document to communicate motion management recommendations to other members of the treatment team. This procedure was implemented clinically for 1 year and results are reported below.

Results

Identified factors that impact motion management included the magnitude of motion observed on 4DCT, the regularity of breathing and quality of 4DCT data, and ability to observe the target on fluoroscopy. These were collated into two decision tables—one specific to lung tumors and another for gastrointestinal tumors—such that a physicist could answer a series of questions to determine the optimal gating and PTV margin. The procedure was used clinically for 252 sites from 213 patients treated with respiratory‐gated SBRT and standardized practice across our 12‐member physics team.

Conclusion

Implementation of a standardized procedure for respiratory gating had a positive impact in our clinic, improving efficiency and ease of 4DCT analysis and standardizing gating decision‐making amongst physicists.