Comparison of modeling accuracy between Radixact®and CyberKnife®Synchrony®respiratory tracking system

A novel external/internal tumor tracking approach to compensate for respiratory motion baseline drifts

Objective.Real-time respiratory tumor tracking as implemented in a robotic treatment unit is based on continuous optical measurement of the position of external markers and a correlation model between them and internal target positions, which are established with X-ray imaging of the tumor, or fiducials placed in or around the tumor. Correlation models are created with fifteen simultaneously measured external/internal marker position pairs divided over the respiratory cycle. Every 45-150 s, the correlation model is updated by replacing the three first acquired data pairs with three new pairs. Tracking simulations for >120.000 computer-generated respiratory tracks demonstrated that this tracking approach resulted in relevant inaccuracies in internal target position predictions, especially in case of presence of respiratory motion baseline drifts.Approach.To better cope with drifts, we introduced a novel correlation model with an explicit time dependence, and we proposed to replace the currently applied linear-motion tracking (LMT) by mixed-model tracking (MMT). In MMT, the linear correlation model is extended with an explicit time dependence in case of a detected baseline drift. MMT prediction accuracies were then established for the same >120.000 computer-generated patients as used for LMT.Main results.For 150 s update intervals, MMT outperformed LMT in internal target position prediction accuracy for 93.7 ∣ 97.2% of patients with 0.25 ∣ 0.5 mm min^-1linear respiratory motion baseline drifts with similar numbers of X-ray images and similar treatment times. For the upper 25% of patients, mean 3D internal target position prediction errors reduced by 0.7 ∣ 1.8 mm, while near maximum reductions (upper 10% of patients) were 0.9 ∣ 2.0 mm.Significance.For equal numbers of acquired X-ray images, MMT greatly improved tracking accuracy compared to LMT, especially in the presence of baseline drifts. Even with almost 50% less acquired X-ray images, MMT still outperformed LMT in internal target position prediction accuracy.

Experience With Normal Breathhold Planning Scans for Radiosurgery of Moving Targets With Live Tracking

PURPOSE

Utilization of breathhold scans with live tracking has a long track record of good published outcomes for stereotactic body radiation therapy (SBRT) and is recommended by the manufacturer of the Synchrony tracking system. However, the popularity of four-dimensional computed tomography (4DCT) scans challenges the validity of the breathhold scan with live tracking technique. Although this study is not intended to prove the superiority of either method, we demonstrate the feasibility of using the breathhold scans with a phantom test and clinical examples.

METHODS

A 4DCT of a perfect sphere was scanned at 20 breaths per minute and compared to a 4DCT of a small lung tumor in one patient and a 4DCT of a larger renal tumor in another patient, as well as to fiducial matching in a patient with pancreatic cancer. Normal exhale and normal inhale breathhold CT scans were performed for the pancreatic cancer patient, combined with Synchrony tracking on CyberKnife (Sunnyvale, CA: Accuray) for treatment.

RESULTS

The 4DCT scan of the phantom exhibited considerable apparent deformation, which must be entirely due to imaging artifact since the perfect sphere in the phantom is known to be completely rigid. The 4DCT of the lung and renal tumors in patients had similar apparent deformation. Usually in patients, from 4DCT alone, it is difficult to determine how much was due to deformation and how much was due to artifact. Fiducial positions in the final normal exhale and normal inhale breathhold scans for Synchrony matched each other within 1mm for the pancreatic cancer patient.

CONCLUSION

We demonstrated the feasibility of breathhold scans with Synchrony live tracking, as recommended by the manufacturer. More studies will be needed to determine whether this method is better than using a 4DCT.

Tracking target/chest relationship changes during motion‐synchronized tomotherapy treatments

Background

Radixact Synchrony® is an intrafraction motion tracking system for helical tomotherapy treatments that uses kV radiographs of the target and LEDs on the patient's chest to synchronize the movement of the radiation beam with the respiratory motion of the target. Several works have demonstrated Synchrony's ability to track target motion when the chest and target motions are perfectly correlated.

Purpose

The purpose of this work was to determine Synchrony's ability to accurately adapt to scenarios with a changing target/chest correlation.

Methods

A custom ion chamber mimicking plug with embedded fiducials was placed inside a Delta4 Phantom+ and used as the tracking object. A separate motion stage was programmed to mimic chest motion. The target and chest surrogate phantom were programmed to move sinusoidally and two types of target/chest relationship changes were introduced: rigid shifts and linear drifts of the target position but not surrogate position. Tracking analysis was performed by comparing programmed phantom motion to log files of the Synchrony‐modeled motion. No dosimetry was performed in this work.

Results

At the fastest imaging rate of 2 s/img, Synchrony accurately adapted for gradual drifts in the target location (up to 5 mm/min) with minor increases in tracking errors and adapted for an abrupt 5 mm shift after about 30 s (with an auto‐pause threshold at 60 s). When the imaging period was longer (> 4 s/img), larger tracking errors (> 5 mm) were observed, and the treatment would be paused. The measured delta (MD) parameter (2D target localization error on the most recent image) was found to be a more responsive indicator of tracking errors than the potential difference (PD) parameter (3D estimator of tracking error based on all images in the model). Lastly, the effect of a recent update to the tracking algorithm was found to improve the ability of Synchrony to track target/chest relationship changes.

Conclusions

This work demonstrated that Synchrony can adapt to gradual changes (drifts) in the target/chest relationship, but it takes a finite amount of time to adapt to abrupt shifts. Ability to adapt to these changes increases with increasing imaging frequency. Larger tracking errors were observed in this work than others have reported in the literature due to the introduction of target/chest correlation changes in this work. Future work needs to be performed investigating what type and magnitude of target/chest miscorrelations occur in patients. Lastly, users should ensure they are using the most recent software (3.0.1 or newer) to improve the ability of Synchrony to track these movements.

Target margin design through analyzing a large cohort of clinical log data in the cyberknife system

Purpose

Calculating the adequate target margin for real‐time tumor tracking using the Cyberknife system is a challenging issue since different sources of error exist. In this study, the clinical log data of the Cyberknife system were analyzed to adequately quantify the planned target volume (PTV) margins of tumors located in the lung and abdomen regions.

Methods

In this study, 45 patients treated with the Cyberknife module were examined. In this context, adequate PTV margins were estimated based on the Van Herk formulation and the uncertainty estimation method by considering the impact of errors and uncertainties. To investigate the impact of errors and uncertainties on the estimated PTV margins, a statistical analysis was also performed.

Results

Our study demonstrates five different sources of errors, including segmentation, deformation, correlation, prediction, and targeting errors, which were identified as the main sources of error in the Cyberknife system. Furthermore, the clinical evaluation of the current study reveals that the two different formalisms provided almost identical PTV margin estimates. Additionally, 4–5 mm and 5 mm margins on average could provide adequate PTV margins at lung and abdomen tumors in all three directions, respectively. Overall, it was found that concerning the PTV margins, the impact of correlation and prediction errors is very high, while the impact of robotics error is low.

Conclusions

The current study can address two limitations in previous researches, namely insufficient sample sites and a smaller number of patients. A comparison of the present results concerning the lung and abdomen areas with other studies reveals that the proposed strategy could provide a better reference in selection the PTV margins. To our knowledge, this study is one of the first attempts to estimate the PTV margins in the lung and abdomen regions for a large cohort of patients treated using the Cyberknife system.