FLEX: FLexible Transducer With External Tracking for Ultrasound Imaging With Patient-Specific Geometry Estimation

Flexible array transducers can adapt to patient-specific geometries during real-time ultrasound (US) image-guided therapy monitoring. This makes the system radiation-free and less user-dependency. Precise estimation of the flexible transducer's geometry is crucial for the delay-and-sum (DAS) beamforming algorithm to reconstruct B-mode US images. The primary innovation of this research is to build a system named FLexible transducer with EXternal tracking (FLEX) to estimate the position of each element of the flexible transducer and reconstruct precise US images. FLEX utilizes customized optical markers and a tracker to monitor the probe's geometry, employing a polygon fitting algorithm to estimate the position and azimuth angle of each transducer element. Subsequently, the traditional DAS algorithm processes the delay estimation from the tracked element position, reconstructing US images from radio-frequency (RF) channel data. The proposed method underwent evaluation on phantoms and cadaveric specimens, demonstrating its clinical feasibility. Deviations in tracked probe geometry compared to ground truth were minimal, measuring 0.50 ± 0.29 mm for the CIRS phantom, 0.54 ± 0.35 mm for the deformable phantom, and 0.36 ± 0.24 mm on the cadaveric specimen. Reconstructing the US image using tracked probe geometry significantly outperformed the untracked geometry, as indicated by a Dice score of 95.1 ± 3.3% versus 62.3 ± 9.2% for the CIRS phantom. The proposed method achieved high accuracy (<0.5 mm error) in tracking the element position for various random curvatures applicable for clinical deployment. The evaluation results show that the radiation-free proposed method can effectively reconstruct US images and assist in monitoring image-guided therapy with minimal user dependency.

Scatter imaging during lung stereotactic body radiation therapy characterized with phantom studies

By collecting photons scattered out of the therapy beam, scatter imaging creates images of the treated volume. Two phantoms were used to assess the possible application of scatter imaging for markerless tracking of lung tumors during stereotactic body radiation therapy (SBRT) treatment. A scatter-imaging camera was assembled with a CsI flat-panel detector and a 5 mm diameter pinhole collimator. Scatter images were collected during the irradiation of phantoms with megavoltage photons. To assess scatter image quality, spherical phantom lung tumors of 2.1-2.8 cm diameters were placed inside a static, anthropomorphic phantom. To show the efficacy of the technique with a moving target (3 cm diameter), the position of a simulated tumor was tracked in scatter images during sinusoidal motion (15 mm amplitude, 0.25 Hz frequency) in a dynamic lung phantom in open-field, dynamic conformal arc (DCA), and volumetric modulated arc therapy (VMAT) deliveries. Anatomical features are identifiable on static phantom scatter images collected with 10 MU of delivered dose (2.1 cm diameter lung tumor contrast-to-noise ratio of 4.4). The contrast-to-noise ratio increases with tumor size and delivered dose. During dynamic motion, the position of the 3.0 cm diameter lung tumor was identified with a root-mean-square error of 0.8, 1.2, and 2.9 mm for open field (0.3 s frame integration), DCA (0.5 s), and VMAT (0.5 s), respectively. Based on phantom studies, scatter imaging is a potential technique for markerless lung tumor tracking during SBRT without additional imaging dose. Quality scatter images may be collected at low, clinically relevant doses (10 MU). Scatter images are capable of sub-millimeter tracking precision, but modulation decreases accuracy.

4D Monte Carlo dose calculations for pre-treatment quality assurance of VMAT SBRT: a phantom-based feasibility study

Volumetric arc therapy (VMAT) for lung stereotactic body radiotherapy (SBRT) is challenging due to both breathing-induced motion and the dynamic components of the linear accelerator. In this study, a 4D Monte Carlo (4DMC) dose calculation method for VMAT SBRT is proposed and the feasibility of the method is evaluated. A rigidly-moving lung phantom was imaged using four dimensional computed tomography (4DCT). VMAT SBRT plans were generated on the average intensity projection dataset using the internal target volume (ITV) strategy (ITV-plan) and a single phase to simulate a dynamic treatment-couch tracking technique (TRACKING-plan). 4DMC simulations were performed and compared to 3D Monte Carlo (3DMC) and 3D- and 4D- calculations in the treatment planning system using the adaptive convolution (AC) algorithm. Dose metrics calculated for the ITV-plan showed an overestimation with 3D adaptive convolution (3DAC) for D[Formula: see text] (GTV) by 3.5% and by 2.0% for 3DMC, both compared to 4DMC. The TRACKING-plan D[Formula: see text] (GTV) calculated with the 3DAC method overestimated by 2.0% compared with 4DMC. Deviations between the calculation methods for D _mean (Lung) and D[Formula: see text] (PTV) were minimal. For both plans, measurements were taken with EBT3 film inside the phantom tumour. EBT3 film profiles showed good agreement with 4DMC for the TRACKING-plan giving a gamma pass rate of 97.2% for 3%/3 mm global and for 3DAC compared with measured, 95.8%. Whereas for the ITV-plan, the 3D profiles varied from film in the ITV periphery region with a pass rates of 50% and 48.6% for 3DAC and 3DMC, respectively. 4DMC agreed more closely to measurements for this plan with a pass rate of 95.8%. We have proposed an accurate method to perform 4D dose calculations for pre-treatment quality assurance of VMAT SBRT. The method was compared to experimental measurements and for both plans, 4DMC dose agreed with measurements more closely than other evaluated dose calculation methods. This study has demonstrated the feasibility of this 4DMC method.

The ideal couch tracking system-Requirements and evaluation of current systems

INTRODUCTION

Intrafractional motion can cause substantial uncertainty in precision radiotherapy. Traditionally, the target volume is defined to be sufficiently large to cover the tumor in every position. With the robotic treatment couch, a real-time motion compensation can improve tumor coverage and organ at risk sparing. However, this approach poses additional requirements, which are systematically developed and which allow the ideal robotic couch to be specified.

METHODS AND MATERIALS

Data of intrafractional tumor motion were collected and analyzed regarding motion range, frequency, speed, and acceleration. Using this data, ideal couch requirements were formulated. The four robotic couches Protura, Perfect Pitch, RoboCouch, and RPSbase were tested with respect to these requirements.

RESULTS

The data collected resulted in maximum speed requirements of 60 mm/s in all directions and maximum accelerations of 80 mm/s² in the longitudinal, 60 mm/s² in the lateral, and 30 mm/s² in the vertical direction. While the two robotic couches RoboCouch and RPSbase completely met the requirements, even these two showed a substantial residual motion (40% of input amplitude), arguably due to their time delays.

CONCLUSION

The requirements for the motion compensation by an ideal couch are formulated and found to be feasible for currently available robotic couches. However, the performance these couches can be improved further regarding the position control if the demanded speed and acceleration are taken into account as well.

Optimization based trajectory planning for real-time 6DoF robotic patient motion compensation systems

Purpose

Robotic stabilization of a therapeutic radiation beam with respect to a dynamically moving tumor target can be accomplished either by moving the radiation source, the patient, or both. As the treatment beam is on during this process, the primary goal is to minimize exposure of normal tissue to radiation as much as possible when moving the target back to the desired position. Due to the complex mechanical structure of 6 degree-of-freedom (6DoF) robots, it is not intuitive as to what 6 dimensional (6D) correction trajectory is optimal in achieving such a goal. With proportional-integrative-derivative (PID) and other controls, the potential exists that the controller may generate a trajectory that is highly curved, slow, or suboptimal in that it leads to unnecessary exposure of healthy tissue to radiation. This work investigates a novel feedback planning method that takes into account a robot’s mechanical joint structure, patient safety tolerances, and other system constraints, and performs real-time optimization to search the entire 6D trajectory space in each time cycle so it can respond with an optimal 6D correction trajectory.

Methods

Computer simulations were created for two 6DoF robotic patient support systems: a Stewart-Gough platform for moving a patient’s head in frameless maskless stereotactic radiosurgery, and a linear accelerator treatment table for moving a patient in prostate cancer radiation therapy. Motion planning was formulated as an optimization problem and solved at real-time speeds using the L-BFGS algorithm. Three planning methods were investigated, moving the platform as fast as possible (platform-D), moving the target along a straight-line (target-S), and moving the target based on the fastest descent of position error (target-D). Both synthetic motion and prior recorded human motion were used as input data and output results were analyzed.

Results

For randomly generated 6D step-like and sinusoidal synthetic input motion, target-D planning demonstrated the smallest net trajectory error in all cases. On average, optimal planning was found to have a 45% smaller target trajectory error than platform-D control, and a 44% smaller target trajectory error than target-S planning. For patient head motion compensation, only target-D planning was able to maintain a ≤0.5mm and ≤0.5deg clinical tolerance objective for 100% of the treatment time. For prostate motion, both target-S planning and target-D planning outperformed platform-D control.

Conclusions

A general 6D target trajectory optimization framework for robotic patient motion compensation systems was investigated. The method was found to be flexible as it allows control over various performance requirements such as mechanical limits, velocities, acceleration, or other system control objectives.

MRI-guided lung SBRT: Present and future developments

Stereotactic body radiotherapy (SBRT) is rapidly becoming an alternative to surgery for the treatment of early-stage non-small cell lung cancer patients. Lung SBRT is administered in a hypo-fractionated, conformal manner, delivering high doses to the target. To avoid normal-tissue toxicity, it is crucial to limit the exposure of nearby healthy organs-at-risk (OAR). Current image-guided radiotherapy strategies for lung SBRT are mostly based on X-ray imaging modalities. Although still in its infancy, magnetic resonance imaging (MRI) guidance for lung SBRT is not exposure-limited and MRI promises to improve crucial soft-tissue contrast. Looking beyond anatomical imaging, functional MRI is expected to inform treatment decisions and adaptations in the future. This review summarises and discusses how MRI could be advantageous to the different links of the radiotherapy treatment chain for lung SBRT: diagnosis and staging, tumour and OAR delineation, treatment planning, and inter- or intrafractional motion management. Special emphasis is placed on a new generation of hybrid MRI treatment devices and their potential for real-time adaptive radiotherapy.

An infrared interactive patient position guidance and acquisition control system for use during radiotherapy treatment

Background

The control of patient position, posture and respiratory movements during radiotherapy is important for effective and specific treatment of malignancy. We have developed an infrared (IR) interactive patient position guidance and acquisition control system for clinical use, comprising IR cameras, IR markers and dedicated software.

Materials and methods

We evaluated the system with ten healthy volunteers and ten experienced operators. IR markers were placed on the body surface. Their positions were calculated using vectors of three translational and three rotational parameters, and the intrafractional error for each marker was acquired with and without respiratory motion. The inclusion of multiple positioning markers allowed for real-time visualisation of the patient posture, with feedback on misalignment and required postural adjustments.

Results

The positioning time was 73 seconds (with a minimum period of 39 seconds), which was significantly shorter than for conventional line alignment. A comparison of positioning reproducibility between conventional line alignment and this system was <3·5 mm and was not patient dependent or operator dependent. An intrafractional error of displacement of up to 10·0 mm was found in the right iliac crest.

Conclusions

This IR interactive system was shown to be high utility and suitable for monitoring patient position, posture and respiratory movements during radiotherapy.

Magnitude, Impact, and Management of Respiration-induced Target Motion in Radiotherapy Treatment: A Comprehensive Review

Tumors in thoracic and upper abdomen regions such as lungs, liver, pancreas, esophagus, and breast move due to respiration. Respiration-induced motion introduces uncertainties in radiotherapy treatments of these sites and is regarded as a significant bottleneck in achieving highly conformal dose distributions. Recent developments in radiation therapy have resulted in (i) motion-encompassing, (ii) respiratory gating, and (iii) tracking methods for adapting the radiation beam aperture to account for the respiration-induced target motion. The purpose of this review is to discuss the magnitude, impact, and management of respiration-induced tumor motion.

ITV, mid-ventilation, gating or couch tracking - A comparison of respiratory motion-management techniques based on 4D dose calculations

PURPOSE

Respiratory motion-management techniques (MMT) aim to ensure tumor dose coverage while sparing lung tissue. Dynamic treatment-couch tracking of the moving tumor is a promising new MMT and was compared to the internal-target-volume (ITV) concept, the mid-ventilation (MidV) principle and the gating approach in a planning study based on 4D dose calculations.

METHODS

For twenty patients with lung lesions, planning target volumes (PTV) were adapted to the MMT and stereotactic body radiotherapy treatments were prepared with the 65%-isodose enclosing the PTV. For tracking, three concepts for target volume definition were considered: Including the gross tumor volume of one phase (single-phase tracking), including deformations between phases (multi-phase tracking) and additionally including tracking latencies of a couch tracking system (reliable couch tracking). The accumulated tumor and lung doses were estimated with 4D dose calculations based on 4D-CT datasets and deformable image registration.

RESULTS

Single-phase tracking showed the lowest ipsilateral lung Dmean (median: 3.3Gy), followed by multi-phase tracking, gating, reliable couch tracking, MidV and ITV concepts (3.6, 3.8, 4.1, 4.3 and 4.8Gy). The 4D dose calculations showed the MidV and single-phase tracking overestimated the target mean dose (-2.3% and -1.3%), while it was slightly underestimated by the other MMT (<+1%).

CONCLUSION

The ITV concept ensures tumor coverage, but exposes the lung tissue to a higher dose. The MidV, gating and tracking concepts were shown to reduce the lung dose. Neglecting non-translational changes of the tumor in the target volume definition for tracking results in a slightly reduced target coverage. The slightly inferior dose coverage for MidV should be considered when applying this technique clinically.

Validation of dynamic treatment-couch tracking for prostate SBRT

PURPOSE

In stereotactic body radiation therapy (SBRT) of prostatic cancer, a high dose per fraction is applied to the target with steep dose gradients. Intrafractional prostate motion can occur unpredictably during the treatment and lead to target miss. This work investigated the dosimetric benefit of motion compensation with dynamic treatment-couch tracking for prostate SBRT treatments in the presence of prostatic motion.

METHODS

Ten SBRT treatment plans for prostate cancer patients with integrated boosts to their index lesion were prepared. The treatment plans were applied with a TrueBeam linear accelerator to a phantom in (a) static reference position, (b) moved with five prostate motion trajectories without any motion compensation, and (c) with real-time compensation using transponder-guided couch tracking. The geometrical position of the electromagnetic transponder was evaluated in the tracked and untracked situation. The dosimetric performance of couch tracking was evaluated, using Gamma agreement indices (GAI) and other dose parameters. These were evaluated within the phantoms biplanar diode array, as well as target- and organ-specific.

RESULTS

The root-mean-square error of the motion traces (range: 0.8-4.4 mm) was drastically reduced with couch tracking (0.2-0.4 mm). Residual motion was mainly observed at abrupt direction changes with steep motion gradients. The phantom measurements showed significantly better GAI_1%/1mm with tracked (range: 83.4%-100.0%) than with untracked motion (28.9%-99.7%). Also GAI_2%/2mm was significantly superior for the tracked (98.4%-100.0%) than the untracked motion (52.3%-100.0%). The organ-specific evaluation showed significantly better target coverage with tracking. The dose to the rectum and bladder showed a dependency on the anterior-posterior motion direction.

CONCLUSIONS

Couch tracking clearly improved the dosimetric accuracy of prostate SBRT treatments. The treatment couch was able to compensate the prostatic motion with only some minor residual motion. Therefore, couch tracking combined with electromagnetic position monitoring for prostate SBRT is feasible and improves the accuracy in treatment delivery when prostate motion is present.

Multimodal chest surface motion data for respiratory and cardiovascular monitoring applications

Chest surface motion is of significant importance as it contains information of respiratory and cardiac systems together with the complex coupling between these two systems. Chest surface motion is not only critical in radiotherapy, but also useful in personalized systems for continuous cardiorespiratory monitoring. In this dataset, a multimodal setup is employed to simultaneously acquire cardiorespiratory signals. These signals include high-density trunk surface motion (from 16 distinct locations) with VICON motion capture system, nasal breathing from a thermal sensor, respiratory effort from a strain belt and electrocardiogram in lead-II configuration. This dataset contains 72 trials recorded from 11 participants with a cumulative duration of approximately 215 min under various conditions such as normal breathing, breath-hold, irregular breathing and post-exercise recovery. The presented dataset is not only useful for evaluating prediction algorithms for radiotherapy applications, but can also be employed for the development of techniques to evaluate the cardio-mechanics and hemodynamic parameters of chest surface motion.

Simulating intrafraction prostate motion with a random walk model

Purpose

Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model.

Methods and materials

Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively.

Results

A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm²/min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion.

Conclusions

Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during delivery of radiation therapy.

Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%); (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable prediction performance. The ability to predict a baseline shift with a sufficient look-ahead window will enable clinical systems or even human users to hold the treatment beam in such situations, thereby reducing the probability of serious geometric and dosimetric errors.

Lung stereotactic body radiotherapy with an MR-linac - Quantifying the impact of the magnetic field and real-time tumor tracking

BACKGROUND AND PURPOSE

There are concerns that radiotherapy doses delivered in a magnetic field might be distorted due to the Lorentz force deflecting secondary electrons. This study investigates this effect on lung stereotactic body radiotherapy (SBRT) treatments, conducted either with or without multileaf collimator (MLC) tumor tracking.

MATERIAL AND METHODS

Lung SBRT treatments with an MR-linac were simulated for nine patients. Two different treatment techniques were compared: conventional, non-tracked deliveries and deliveries with real-time MLC tumor tracking, each conducted either with or without a 1.5T magnetic field.

RESULTS

Slight dose distortions at air-tissue-interfaces were observed in the presence of the magnetic field. Most prominently, the dose to 2% of the skin increased by 1.4Gy on average. Regardless of the presence of the magnetic field, MLC tracking was able to spare healthy tissue, for example by decreasing the mean lung dose by 0.3Gy on average, while maintaining the target dose.

CONCLUSIONS

Accounting for the magnetic field during treatment plan optimization allowed for design and delivery of clinically acceptable lung SBRT treatments with an MR-linac. Furthermore, the ability of MLC tumor tracking to decrease dose exposure of healthy tissue, was not inhibited by the magnetic field.

Ensemble framework based real-time respiratory motion prediction for adaptive radiotherapy applications

Successful treatment of tumors with motion-adaptive radiotherapy requires accurate prediction of respiratory motion, ideally with a prediction horizon larger than the latency in radiotherapy system. Accurate prediction of respiratory motion is however a non-trivial task due to the presence of irregularities and intra-trace variabilities, such as baseline drift and temporal changes in fundamental frequency pattern. In this paper, to enhance the accuracy of the respiratory motion prediction, we propose a stacked regression ensemble framework that integrates heterogeneous respiratory motion prediction algorithms. We further address two crucial issues for developing a successful ensemble framework: (1) selection of appropriate prediction methods to ensemble (level-0 methods) among the best existing prediction methods; and (2) finding a suitable generalization approach that can successfully exploit the relative advantages of the chosen level-0 methods. The efficacy of the developed ensemble framework is assessed with real respiratory motion traces acquired from 31 patients undergoing treatment. Results show that the developed ensemble framework improves the prediction performance significantly compared to the best existing methods.

Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy

PURPOSE

Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy.

METHODS

kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated.

RESULTS

Regular dual-energy imaging was able to increase tracking accuracy in left-right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size.

CONCLUSIONS

This study has highlighted the influence of patient anatomy on the success rate of real-time markerless tumor tracking using dual-energy imaging. Additionally, the importance of the spectral separation of the imaging beams used to generate the dual-energy images has been shown.

Real-time prediction of respiratory motion traces for radiotherapy with ensemble learning

In this paper, we introduce a hybrid method for prediction of respiratory motion to overcome the inherent delay in robotic radiosurgery while treating lung tumors. The hybrid method adopts least squares support vector machine (LS-SVM) based ensemble learning approach to exploit the relative advantages of the individual methods local circular motion (LCM) with extended Kalman filter (EKF) and autoregressive moving average (ARMA) model with fading memory Kalman filter (FMKF). The efficiency the proposed hybrid approach was assessed with the real respiratory motion traces of 31 patients while treating with CyberKnife(TM). Results show that the proposed hybrid method improves the prediction accuracy by approximately 10% for prediction horizons of 460 ms compared to the existing methods.

Dynamic tumor tracking using the Elekta Agility MLC

PURPOSE

To evaluate the performance of the Elekta Agility multileaf collimator (MLC) for dynamic real-time tumor tracking.

METHODS

The authors have developed a new control software which interfaces to the Agility MLC to dynamically program the movement of individual leaves, the dynamic leaf guides (DLGs), and the Y collimators ("jaws") based on the actual target trajectory. A motion platform was used to perform dynamic tracking experiments with sinusoidal trajectories. The actual target positions reported by the motion platform at 20, 30, or 40 Hz were used as shift vectors for the MLC in beams-eye-view. The system latency of the MLC (i.e., the average latency comprising target device reporting latencies and MLC adjustment latency) and the geometric tracking accuracy were extracted from a sequence of MV portal images acquired during irradiation for the following treatment scenarios: leaf-only motion, jaw + leaf motion, and DLG + leaf motion.

RESULTS

The portal imager measurements indicated a clear dependence of the system latency on the target position reporting frequency. Deducting the effect of the target frequency, the leaf adjustment latency was measured to be 38 ± 3 ms for a maximum target speed v of 13 mm/s. The jaw + leaf adjustment latency was 53 ± 3 at a similar speed. The system latency at a target position frequency of 30 Hz was in the range of 56-61 ms for the leaves (v ≤ 31 mm/s), 71-78 ms for the jaw + leaf motion (v ≤ 25 mm/s), and 58-72 ms for the DLG + leaf motion (v ≤ 59 mm/s). The tracking accuracy showed a similar dependency on the target position frequency and the maximum target speed. For the leaves, the root-mean-squared error (RMSE) was between 0.6-1.5 mm depending on the maximum target speed. For the jaw + leaf (DLG + leaf) motion, the RMSE was between 0.7-1.5 mm (1.9-3.4 mm).

CONCLUSIONS

The authors have measured the latency and geometric accuracy of the Agility MLC, facilitating its future use for clinical tracking applications.

Motion management during IMAT treatment of mobile lung tumors--a comparison of MLC tracking and gated delivery

PURPOSE

To compare real-time dynamic multileaf collimator (MLC) tracking, respiratory amplitude and phase gating, and no compensation for intrafraction motion management during intensity modulated arc therapy (IMAT).

METHODS

Motion management with MLC tracking and gating was evaluated for four lung cancer patients. The IMAT plans were delivered to a dosimetric phantom mounted onto a 3D motion phantom performing patient-specific lung tumor motion. The MLC tracking system was guided by an optical system that used stereoscopic infrared (IR) cameras and five spherical reflecting markers attached to the dosimetric phantom. The gated delivery used a duty cycle of 35% and collected position data using an IR camera and two reflecting markers attached to a marker block.

RESULTS

The average gamma index failure rate (2% and 2 mm criteria) was <0.01% with amplitude gating for all patients, and <0.1% with phase gating and <3.7% with MLC tracking for three of the four patients. One of the patients had an average failure rate of 15.1% with phase gating and 18.3% with MLC tracking. With no motion compensation, the average gamma index failure rate ranged from 7.1% to 46.9% for the different patients. Evaluation of the dosimetric error contributions showed that the gated delivery mainly had errors in target localization, while MLC tracking also had contributions from MLC leaf fitting and leaf adjustment. The average treatment time was about three times longer with gating compared to delivery with MLC tracking (that did not prolong the treatment time) or no motion compensation. For two of the patients, the different motion compensation techniques allowed for approximately the same margin reduction but for two of the patients, gating enabled a larger reduction of the margins than MLC tracking.

CONCLUSIONS

Both gating and MLC tracking reduced the effects of the target movements, although the gated delivery showed a better dosimetric accuracy and enabled a larger reduction of the margins in some cases. MLC tracking did not prolong the treatment time compared to delivery with no motion compensation while gating had a considerably longer delivery time. In a clinical setting, the optical monitoring of the patients breathing would have to be correlated to the internal movements of the tumor.

Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [(18)F]FDG. The lung lesion insert was driven by six different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses, and 2%-2 mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10-20%, treatment planning errors were 5-10%, and treatment delivery errors were 5-30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5-10% in PET/CT imaging, <5% in treatment planning, and <2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT delivery under a dose painting paradigm is feasible within an integrated respiratory motion phantom workflow. For a limited set of cases, the magnitude of errors was comparable during PET/CT imaging and treatment delivery without motion compensation. Errors were moderately mitigated during PET/CT imaging and significantly mitigated during RT delivery with motion compensation. This dynamic motion phantom end-to-end workflow provides a method for quality assurance of 4D PET/CT-guided radiotherapy, including evaluation of respiratory motion compensation methods during imaging and treatment delivery.

Suitability of markerless EPID tracking for tumor position verification in gated radiotherapy

PURPOSE

To maximize the benefits of respiratory gated radiotherapy (RGRT) of lung tumors real-time verification of the tumor position is required. This work investigates the feasibility of markerless tracking of lung tumors during beam-on time in electronic portal imaging device (EPID) images of the MV therapeutic beam.

METHODS

EPID movies were acquired at ∼2 fps for seven lung cancer patients with tumor peak-to-peak motion ranges between 7.8 and 17.9 mm (mean: 13.7 mm) undergoing stereotactic body radiotherapy. The external breathing motion of the abdomen was synchronously measured. Both datasets were retrospectively analyzed in PortalTrack, an in-house developed tracking software. The authors define a three-step procedure to run the simulations: (1) gating window definition, (2) gated-beam delivery simulation, and (3) tumor tracking. First, an amplitude threshold level was set on the external signal, defining the onset of beam-on/-off signals. This information was then mapped onto a sequence of EPID images to generate stamps of beam-on/-hold periods throughout the EPID movies in PortalTrack, by obscuring the frames corresponding to beam-off times. Last, tumor motion in the superior-inferior direction was determined on portal images by the tracking algorithm during beam-on time. The residual motion inside the gating window as well as target coverage (TC) and the marginal target displacement (MTD) were used as measures to quantify tumor position variability.

RESULTS

Tumor position monitoring and estimation from beam's-eye-view images during RGRT was possible in 67% of the analyzed beams. For a reference gating window of 5 mm, deviations ranging from 2% to 86% (35% on average) were recorded between the reference and measured residual motion. TC (range: 62%-93%; mean: 77%) losses were correlated with false positives incidence rates resulting mostly from intra-/inter-beam baseline drifts, as well as sudden cycle-to-cycle fluctuations in exhale positions. Both phenomena can lead to considerable deviations (with MTD values up to a maximum of 7.8 mm) from the intended tumor position, and in turn may result in a marginal miss. The difference between tumor traces determined within the gating window against ground truth trajectory maps was 1.1 ± 0.7 mm on average (range: 0.4-2.3 mm).

CONCLUSIONS

In this retrospective analysis of motion data, it is demonstrated that the system is capable of determining tumor positions in the plane perpendicular to the beam direction without the aid of fiducial markers, and may hence be suitable as an online verification tool in RGRT. It may be possible to use the tracking information to enable on-the-fly corrections to intra-/inter-beam variations by adapting the gating window by means of a robotic couch.

Joint surface reconstruction and 4D deformation estimation from sparse data and prior knowledge for marker-less Respiratory motion tracking

PURPOSE

The intraprocedural tracking of respiratory motion has the potential to substantially improve image-guided diagnosis and interventions. The authors have developed a sparse-to-dense registration approach that is capable of recovering the patient's external 3D body surface and estimating a 4D (3D + time) surface motion field from sparse sampling data and patient-specific prior shape knowledge.

METHODS

The system utilizes an emerging marker-less and laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3D measurements in real-time. These sparse position measurements are registered with a dense reference surface extracted from planning data. Thereby a dense displacement field is recovered, which describes the spatio-temporal 4D deformation of the complete patient body surface, depending on the type and state of respiration. It yields both a reconstruction of the instantaneous patient shape and a high-dimensional respiratory surrogate for respiratory motion tracking. The method is validated on a 4D CT respiration phantom and evaluated on both real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured-light scanner.

RESULTS

In the experiments, the authors estimated surface motion fields with the proposed algorithm on 256 datasets from 16 subjects and in different respiration states, achieving a mean surface reconstruction accuracy of ± 0.23 mm with respect to ground truth data-down from a mean initial surface mismatch of 5.66 mm. The 95th percentile of the local residual mesh-to-mesh distance after registration did not exceed 1.17 mm for any subject. On average, the total runtime of our proof of concept CPU implementation is 2.3 s per frame, outperforming related work substantially.

CONCLUSIONS

In external beam radiation therapy, the approach holds potential for patient monitoring during treatment using the reconstructed surface, and for motion-compensated dose delivery using the estimated 4D surface motion field in combination with external-internal correlation models.

The first clinical implementation of electromagnetic transponder-guided MLC tracking

PURPOSE

We report on the clinical process, quality assurance, and geometric and dosimetric results of the first clinical implementation of electromagnetic transponder-guided MLC tracking which occurred on 28 November 2013 at the Northern Sydney Cancer Centre.

METHODS

An electromagnetic transponder-based positioning system (Calypso) was modified to send the target position output to in-house-developed MLC tracking code, which adjusts the leaf positions to optimally align the treatment beam with the real-time target position. Clinical process and quality assurance procedures were developed and performed. The first clinical implementation of electromagnetic transponder-guided MLC tracking was for a prostate cancer patient being treated with dual-arc VMAT (RapidArc). For the first fraction of the first patient treatment of electromagnetic transponder-guided MLC tracking we recorded the in-room time and transponder positions, and performed dose reconstruction to estimate the delivered dose and also the dose received had MLC tracking not been used.

RESULTS

The total in-room time was 21 min with 2 min of beam delivery. No additional time was needed for MLC tracking and there were no beam holds. The average prostate position from the initial setup was 1.2 mm, mostly an anterior shift. Dose reconstruction analysis of the delivered dose with MLC tracking showed similar isodose and target dose volume histograms to the planned treatment and a 4.6% increase in the fractional rectal V60. Dose reconstruction without motion compensation showed a 30% increase in the fractional rectal V60 from that planned, even for the small motion.

CONCLUSIONS

The real-time beam-target correction method, electromagnetic transponder-guided MLC tracking, has been translated to the clinic. This achievement represents a milestone in improving geometric and dosimetric accuracy, and by inference treatment outcomes, in cancer radiotherapy.

Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity

We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fluoroscopic intensity is the superimposition of intensity components of all the structures passed through by the X-ray. The tumor can then be extracted by decomposing the fluoroscopic intensity into the tumor intensity component and the others. The decomposition problem for more than two structures is ill posed, but it can be transformed into a well-posed one by temporally accumulating constraints that must be satisfied by the decomposed moving tumor component and the rest of the intensity components. The extracted tumor image can then be used to achieve accurate tumor motion tracking without implanted markers that are widely used in the current tracking techniques. The performance evaluation showed that the extraction error was sufficiently small and the extracted tumor tracking achieved a high and sufficient accuracy less than 1 mm for clinical datasets. These results clearly demonstrate the usefulness of the proposed method for markerless tumor motion tracking.

Toward correcting drift in target position during radiotherapy via computer-controlled couch adjustments on a programmable Linac

PURPOSE

Real-time tracking of respiratory target motion during radiation therapy is technically challenging, owing to rapid and possibly irregular breathing variations. The authors report on a method to predict and correct respiration-averaged drift in target position by means of couch adjustments on an accelerator equipped with such capability.

METHODS

Dose delivery is broken up into a sequence of 10 s field segments, each followed by a couch adjustment based on analysis of breathing motion from an external monitor as a surrogate of internal target motion. Signal averaging over three respiratory cycles yields a baseline representing target drift. A Kalman filter predicts the baseline position 5 s in advance, for determination of the couch correction. The method's feasibility is tested with a motion phantom programmed according to previously recorded patient signals. Computed couch corrections are preprogrammed into a research mode of an accelerator capable of computer-controlled couch translations synchronized with the motion phantom. The method's performance is evaluated with five cases recorded during hypofractionated treatment and five from respiration-correlated CT simulation, using a root-mean-squared deviation (RMSD) of the baseline from the treatment planned position.

RESULTS

RMSD is reduced in all 10 cases, from a mean of 4.9 mm (range 2.7-9.4 mm) before correction to 1.7 mm (range 0.7-2.3 mm) after correction. Treatment time is increased ∼5% relative to that for no corrections.

CONCLUSIONS

This work illustrates the potential for reduction in baseline respiratory drift with periodic adjustments in couch position during treatment. Future treatment machine capabilities will enable the use of "on-the-fly" couch adjustments during treatment.

The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery

PURPOSE

Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced by using a leaf position constraint (LPC) that reduces the difference in the position of adjacent MLC leaves in the plan. The purpose of this study was to investigate the impact of the LPC on the quality of inversely optimized arc radiotherapy plans and the effect of the MLC motion pattern on the dosimetric accuracy of MLC tracking delivery. Specifically, the possibility of predicting the accuracy of MLC tracking delivery based on the plan modulation was investigated.

METHODS

Inversely optimized arc radiotherapy plans were created on CT-data of three lung cancer patients. For each case, five plans with a single 358° arc were generated with LPC priorities of 0 (no LPC), 0.25, 0.5, 0.75, and 1 (highest possible LPC), respectively. All the plans had a prescribed dose of 2 Gy × 30, used 6 MV, a maximum dose rate of 600 MU/min and a collimator angle of 45° or 315°. To quantify the plan modulation, an average adjacent leaf distance (ALD) was calculated by averaging the mean adjacent leaf distance for each control point. The linear relationship between the plan quality [i.e., the calculated dose distributions and the number of monitor units (MU)] and the LPC was investigated, and the linear regression coefficient as well as a two tailed confidence level of 95% was used in the evaluation. The effect of the plan modulation on the performance of MLC tracking was tested by delivering the plans to a cylindrical diode array phantom moving with sinusoidal motion in the superior-inferior direction with a peak-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system. The dosimetric results were evaluated using gamma index evaluation with static target measurements as reference.

RESULTS

The plan quality parameters did not depend significantly on the LPC (p ≥ 0.066), whereas the ALD depended significantly on the LPC (p < 0.001). The gamma index failure rate depended significantly on the ALD, weighted to the percentage of the beam delivered in each control point of the plan (ALD(w)) when MLC tracking was used (p < 0.001), but not for delivery without MLC tracking (p ≥ 0.342). The gamma index failure rate with the criteria of 2% and 2 mm was decreased from > 33.9% without MLC tracking to <31.4% (LPC 0) and <2.2% (LPC 1) with MLC tracking.

CONCLUSIONS

The results indicate that the dosimetric robustness of MLC tracking delivery of an inversely optimized arc radiotherapy plan can be improved by incorporating leaf position constraints in the objective function without otherwise affecting the plan quality. The dosimetric robustness may be estimated prior to delivery by evaluating the ALD(w) of the plan.

Optimized order estimation for autoregressive models to predict respiratory motion

PURPOSE

To successfully ablate moving tumors in robotic radio-surgery, it is necessary to compensate for motion of inner organs caused by respiration. This can be achieved by tracking the body surface and correlating the external movement with the tumor position as it is implemented in the CyberKnife[Formula: see text] Synchrony system. Tracking errors, originating from system immanent time delays, are typically reduced by time series prediction. Many prediction algorithms exploit autoregressive (AR) properties of the signal. Estimating the optimal model order [Formula: see text] for these algorithms constitutes a challenge often solved via grid search or prior knowledge about the signal.

METHODS

Aiming at a more efficient approach instead, this study evaluates the Akaike information criterion (AIC), the corrected AIC, and the Bayesian information criterion (BIC) on the first minute of the respiratory signal. Exemplarily, we evaluated the approach for a least mean square (LMS) and a wavelet-based LMS (wLMS) predictor.

RESULTS

Analyzing 12 motion traces, orders estimated by AIC had the highest prediction accuracy for both prediction algorithms. Extending the investigations to 304 real motion traces, the prediction error of wLMS using AIC was found to decrease significantly by 85.1 % of the data compared to the original implementation

CONCLUSIONS

The overall results suggest that using AIC to estimate the model order [Formula: see text] for prediction algorithms based on AR properties is a valid method which avoids intensive grid search and leads to high prediction accuracy.

Dosimetric benefit of DMLC tracking for conventional and sub-volume boosted prostate intensity-modulated arc radiotherapy

This study investigated the dosimetric impact of uncompensated motion and motion compensation with dynamic multileaf collimator (DMLC) tracking for prostate intensity modulated arc therapy. Two treatment approaches were investigated; a conventional approach with a uniform radiation dose to the target volume and an intraprostatic lesion (IPL) boosted approach with an increased dose to a subvolume of the prostate. The impact on plan quality of optimizations with a leaf position constraint, which limited the distance between neighbouring adjacent MLC leaves, was also investigated. Deliveries were done with and without DMLC tracking on a linear acceleration with a high-resolution MLC. A cylindrical phantom containing two orthogonal diode arrays was used for dosimetry. A motion platform reproduced six patient-derived prostate motion traces, with the average displacement ranging from 1.0 to 8.9 mm during the first 75 s. A research DMLC tracking system was used for real-time motion compensation with optical monitoring for position input. The gamma index was used for evaluation, with measurements with a static phantom or the planned dose as reference, using 2% and 2 mm gamma criteria. The average pass rate with DMLC tracking was 99.9% (range 98.7-100%, measurement as reference), whereas the pass rate for untracked deliveries decreased distinctly as the average displacement increased, with an average pass rate of 61.3% (range 32.7-99.3%). Dose-volume histograms showed that DMLC tracking maintained the planned dose distributions in the presence of motion whereas traces with >3 mm average displacement caused clear plan degradation for untracked deliveries. The dose to the rectum and bladder had an evident dependence on the motion direction and amplitude for untracked deliveries, and the dose to the rectum was slightly increased for IPL boosted plans compared to conventional plans for anterior motion with large amplitude. In conclusion, optimization using a leaf position constraint had minimal dosimetric effect, DMLC tracking improved the target and normal tissue dose distributions compared to no tracking for target motion >3 mm, with the DMLC tracking distributions showing generally good agreement between the planned and delivered doses.

Evaluation of the potential of multi-modal sensors for respiratory motion prediction and correlation

In modern robotic radiotherapy, precise radiation of moving tumors is possible by tracking external optical surrogates. The surrogates are used to compensate for time delays and to predict internal landmarks using a correlation model. The correlation depends significantly on the surrogate position and breathing characteristics of the patient. In this context, we aim to increase the accuracy and robustness of prediction and correlation models by using a multi-modal sensor setup. Here, we evaluate the correlation coefficient of a strain belt, an acceleration and temperature sensor (air flow) with respect to external optical sensors and one internal landmark in the liver, measured by 3D ultrasound. The focus of this study is the influence of breathing artefacts, like coughing and harrumphing. Evaluating seven subjects, we found a strong decrease of the correlation for all modalities in case of artefacts. The results indicate that no precise motion compensation during these times is possible. Overall, we found that apart from the optical markers, the strain belt and temperature sensor data show the best correlation to external and internal motion.

Challenges and opportunities in patient-specific, motion-managed and PET/CT-guided radiation therapy of lung cancer: review and perspective

The increasing interest in combined positron emission tomography (PET) and computed tomography (CT) to guide lung cancer radiation therapy planning has been well documented. Motion management strategies during treatment simulation PET/CT imaging and treatment delivery have been proposed to improve the precision and accuracy of radiotherapy. In light of these research advances, why has translation of motion-managed PET/CT to clinical radiotherapy been slow and infrequent? Solutions to this problem are as complex as they are numerous, driven by large inter-patient variability in tumor motion trajectories across a highly heterogeneous population. Such variation dictates a comprehensive and patient-specific incorporation of motion management strategies into PET/CT-guided radiotherapy rather than a one-size-fits-all tactic. This review summarizes challenges and opportunities for clinical translation of advances in PET/CT-guided radiotherapy, as well as in respiratory motion-managed radiotherapy of lung cancer. These two concepts are then integrated into proposed patient-specific workflows that span classification schemes, PET/CT image formation, treatment planning, and adaptive image-guided radiotherapy delivery techniques.

[Image-guided radiation therapy]

Radiotherapy technology has improved rapidly over the past two decades. New imaging modalities, such as positron emission (computed) tomography (PET, PET-CT) and high-resolution morphological and functional magnetic resonance imaging (MRI) have been introduced into the treatment planning process. Image-guided radiation therapy (IGRT) with 3D soft tissue depiction directly imaging target and normal structures, is currently replacing patient positioning based on patient surface markers, frame-based intracranial and extracranial stereotactic treatment and partially also 2D field verification methods. On-line 3D soft tissue-based position correction unlocked the full potential of new delivery techniques, such as intensity-modulated radiotherapy, by safely delivering highly conformal dose distributions that facilitate dose escalation and hypofractionation. These strategies have already resulted in better clinical outcomes, e.g. in prostate and lung cancer and are expected to further improve radiotherapy results.

Accuracy of real-time couch tracking during 3-dimensional conformal radiation therapy, intensity modulated radiation therapy, and volumetric modulated arc therapy for prostate cancer

PURPOSE

To evaluate the accuracy of real-time couch tracking for prostate cancer.

METHODS AND MATERIALS

Intrafractional motion trajectories of 15 prostate cancer patients were the basis for this phantom study; prostate motion had been monitored with the Calypso System. An industrial robot moved a phantom along these trajectories, motion was detected via an infrared camera system, and the robotic HexaPOD couch was used for real-time counter-steering. Residual phantom motion during real-time tracking was measured with the infrared camera system. Film dosimetry was performed during delivery of 3-dimensional conformal radiation therapy (3D-CRT), step-and-shoot intensity modulated radiation therapy (IMRT), and volumetric modulated arc therapy (VMAT).

RESULTS

Motion of the prostate was largest in the anterior-posterior direction, with systematic (∑) and random (σ) errors of 2.3 mm and 2.9 mm, respectively; the prostate was outside a threshold of 5 mm (3D vector) for 25.0%±19.8% of treatment time. Real-time tracking reduced prostate motion to ∑=0.01 mm and σ = 0.55 mm in the anterior-posterior direction; the prostate remained within a 1-mm and 5-mm threshold for 93.9%±4.6% and 99.7%±0.4% of the time, respectively. Without real-time tracking, pass rates based on a γ index of 2%/2 mm in film dosimetry ranged between 66% and 72% for 3D-CRT, IMRT, and VMAT, on average. Real-time tracking increased pass rates to minimum 98% on average for 3D-CRT, IMRT, and VMAT.

CONCLUSIONS

Real-time couch tracking resulted in submillimeter accuracy for prostate cancer, which transferred into high dosimetric accuracy independently of whether 3D-CRT, IMRT, or VMAT was used.

Experimental investigation of a moving averaging algorithm for motion perpendicular to the leaf travel direction in dynamic MLC target tracking

PURPOSE

In dynamic multileaf collimator (MLC) motion tracking with complex intensity-modulated radiation therapy (IMRT) fields, target motion perpendicular to the MLC leaf travel direction can cause beam holds, which increase beam delivery time by up to a factor of 4. As a means to balance delivery efficiency and accuracy, a moving average algorithm was incorporated into a dynamic MLC motion tracking system (i.e., moving average tracking) to account for target motion perpendicular to the MLC leaf travel direction. The experimental investigation of the moving average algorithm compared with real-time tracking and no compensation beam delivery is described.

METHODS

The properties of the moving average algorithm were measured and compared with those of real-time tracking (dynamic MLC motion tracking accounting for both target motion parallel and perpendicular to the leaf travel direction) and no compensation beam delivery. The algorithm was investigated using a synthetic motion trace with a baseline drift and four patient-measured 3D tumor motion traces representing regular and irregular motions with varying baseline drifts. Each motion trace was reproduced by a moving platform. The delivery efficiency, geometric accuracy, and dosimetric accuracy were evaluated for conformal, step-and-shoot IMRT, and dynamic sliding window IMRT treatment plans using the synthetic and patient motion traces. The dosimetric accuracy was quantified via a tgamma-test with a 3%/3 mm criterion.

RESULTS

The delivery efficiency ranged from 89 to 100% for moving average tracking, 26%-100% for real-time tracking, and 100% (by definition) for no compensation. The root-mean-square geometric error ranged from 3.2 to 4.0 mm for moving average tracking, 0.7-1.1 mm for real-time tracking, and 3.7-7.2 mm for no compensation. The percentage of dosimetric points failing the gamma-test ranged from 4 to 30% for moving average tracking, 0%-23% for real-time tracking, and 10%-47% for no compensation.

CONCLUSIONS

The delivery efficiency of moving average tracking was up to four times higher than that of real-time tracking and approached the efficiency of no compensation for all cases. The geometric accuracy and dosimetric accuracy of the moving average algorithm was between real-time tracking and no compensation, approximately half the percentage of dosimetric points failing the gamma-test compared with no compensation.