Geometric uncertainty of 2D projection imaging in monitoring 3D tumor motion

Investigation of uncertainty in internal target volume definition for lung stereotactic body radiotherapy

This study evaluated the validity of internal target volumes (ITVs) defined by three- (3DCT) and four-dimensional computed tomography (4DCT), and subsequently compared them with actual movements during treatment. Five patients with upper lobe lung tumors were treated with stereotactic body radiotherapy (SBRT) at 48 Gy in four fractions. Planning 3DCT images were acquired with peak-exhale and peak-inhale breath-holds, and 4DCT images were acquired in the cine mode under free breathing. Cine images were acquired using an electronic portal imaging device during irradiation. Tumor coverage was evaluated based on the manner in which the peak-to-peak breathing amplitude on the planning CT covered the range of tumor motion (± 3 SD) during irradiation in the left-right, anteroposterior, and cranio-caudal (CC) directions. The mean tumor coverage of the 4DCT-based ITV was better than that of the 3DCT-based ITV in the CC direction. The internal margin should be considered when setting the irradiation field for 4DCT. The proposed 4DCT-based ITV can be used as an efficient approach in free-breathing SBRT for upper-lobe tumors of the lung because its coverage is superior to that of 3DCT.

Dense feature-based motion estimation in MV fluoroscopy during dynamic tumor tracking treatment: preliminary study on reduced aperture and partial occlusion handling

Quality assurance solutions to complement available motion compensation technologies are central for their safe routine implementation and success of treatment. This work presents a dense feature-based method for soft-tissue tumor motion estimation in megavoltage (MV) beam's-eye-view (BEV) projections for potential intra-treatment monitoring during dynamic tumor tracking (DTT). Dense sampling and matching principles were employed to track a gridded set of features landmarks (FLs) in MV-BEV projections and estimate tumor motion, capable to overcome reduced field aperture and partial occlusion challenges. The algorithm's performance was evaluated by retrospectively applying it to fluoroscopic sequences acquired at ∼2 frames s^-1 (fps) for a dynamic phantom and two lung stereotactic body radiation therapy (SBRT) patients treated with DTT on the Vero SBRT system. First, a field-specific train image is initialized by sampling the tumor region at, S, pixel intervals on a grid using a representative frame from a stream of query frames. Sampled FLs are locally characterized in the form of descriptor vectors and geometric attributes representing the target. For motion tracking, subsequent query frames are likewise sampled, corresponding feature descriptors determined, and then patch-wise matched to the training set based on their descriptors and geometric relationships. FLs with high correspondence are pruned and used to estimate tumor displacement. In scenarios of partial occlusions, position is estimated from the set of correctly (visible) FLs on past observations. Reconstructed trajectories were benchmarked against ground-truth manual tracking using the root-mean-square (RMS) as a metric of positional accuracy. A total of 19 fluoroscopy sequences were analyzed. This included scenarios of field aperture obstruction during three-dimensional conformal, as well as step-and-shoot intensity modulated radiotherapy (IMRT) delivery assisted with DTT. The algorithm resolved target motion satisfactorily. The RMS was <1.2 mm and <1.8 mm for the phantom and the clinical dataset, respectively. Dense tracking showed promising results to overcome localization challenges at the field penumbra and partial obstruction by multi-leaf collimator (MLC). Motion retrieval was possible in ∼66% of the control points studied. In addition to MLC obstruction, changes in the external/internal breathing dynamics and baseline drifts were a major source of estimation bias. Dense feature-based tracking is a viable alternative. The algorithm is rotation-/scale-invariant and robust to photometric changes. Tracking multiple features may help overcome partial occlusion challenges by the MLC. This in turn opens up new possibilities for motion detection and intra-treatment monitoring during IMRT and potentially VMAT.

On the total system error of a robotic radiosurgery system: phantom measurements, clinical evaluation and long-term analysis

The total system error (TSE) of a CyberKnife^® system was measured using two phantom-based methods and one patient-based method. The standard radiochromic film (RCF) end-to-end (E2E) test using an anthropomorphic head and neck phantom and isocentric treatment delivery was used with the 6Dskull, Fiducial and Xsight^® spine (XST) tracking methods. More than 200 RCF-based E2E results covering the period from installation in 2006 until 2017 were analyzed with respect to tracking method, system hardware and software versions, secondary collimation system, and years since installation. An independent polymer gel E2E method was also applied, involving a 3D printed head phantom and multiple spherical target volumes widely distributed within the brain. Finally, the TSE was assessed by comparing the delineated target in the planning computed tomography images of a patient treated for a thalamic functional target with the radiation-induced lesion defined on the six-month follow-up magnetic resonance (MR) images. Statistical analysis of the RCF-based TSE results showed mean  ±  standard deviation values of 0.40  ±  0.18 mm, 0.40  ±  0.19 mm, and 0.55  ±  0.20 mm for the 6Dskull, Fiducial, and XST tracking methods, respectively. Polymer gel TSE values smaller than 0.66 mm were found for seven targets distributed within the brain, showing that the targeting accuracy of the system is sustained even for targets situated up to 80 mm away from the center of the skull. An average clinical TSE value of 0.87  ±  0.25 mm was also measured using the FSE T2 and FLAIR post-treatment MR image data. Analysis of the long-term RCF-based E2E tests showed no changes of TSE over time. This study is the first to report long-term (>10 years) analysis of TSE, TSE measurement for targets positioned at large distances from the virtual machine isocenter, or a clinical assessment of TSE for the CyberKnife system. All of these measurements demonstrate TSE consistently  <  1 mm.

Comparison of 2D and 3D modeled tumor motion estimation/prediction for dynamic tumor tracking during arc radiotherapy

Many real-time imaging techniques have been developed to localize a target in 3D space or in a 2D beam's eye view (BEV) plane for intrafraction motion tracking in radiation therapy. With tracking system latency, the 3D-modeled method is expected to be more accurate even in terms of 2D BEV tracking error. No quantitative analysis, however, has been reported. In this study, we simulated co-planar arc deliveries using respiratory motion data acquired from 42 patients to quantitatively compare the accuracy between 2D BEV and 3D-modeled tracking in arc therapy and to determine whether 3D information is needed for motion tracking. We used our previously developed low kV dose adaptive MV-kV imaging and motion compensation framework as a representative of 3D-modeled methods. It optimizes the balance between additional kV imaging dose and 3D tracking accuracy and solves the MLC blockage issue. With simulated Gaussian marker detection errors (zero mean and 0.39 mm standard deviation) and ~155/310/460 ms tracking system latencies, the mean percentage of time that the target moved  >2 mm from the predicted 2D BEV position are 1.1%/4.0%/7.8% and 1.3%/5.8%/11.6% for the 3D-modeled and 2D-only tracking, respectively. The corresponding average BEV RMS errors are 0.67/0.90/1.13 mm and 0.79/1.10/1.37 mm. Compared to the 2D method, the 3D method reduced the average RMS unresolved motion along the beam direction from ~3 mm to ~1 mm, resulting in on average only  <1% dosimetric advantage in the depth direction. Only for a small fraction of the patients, when tracking latency is long, the 3D-modeled method showed significant improvement of BEV tracking accuracy, indicating potential dosimetric advantage. However, if the tracking latency is short (~150 ms or less), those improvements are limited. Therefore, 2D BEV tracking has sufficient targeting accuracy for most clinical cases. The 3D technique is, however, still important in solving the MLC blockage problem during 2D BEV tracking.

Continuous monitoring of prostate position using stereoscopic and monoscopic kV image guidance

PURPOSE

To demonstrate continuous kV x-ray monitoring of prostate motion using both stereoscopic and monoscopic localizations, assess the spatial accuracy of these techniques, and evaluate the dose delivered from the added image guidance.

METHODS

The authors implemented both stereoscopic and monoscopic fiducial localizations using a room-mounted dual oblique x-ray system. Recently developed monoscopic 3D position estimation techniques potentially overcome the issue of treatment head interference with stereoscopic imaging at certain gantry angles. To demonstrate continuous position monitoring, a gold fiducial marker was placed in an anthropomorphic phantom and placed on the Linac couch. The couch was used as a programmable translation stage. The couch was programmed with a series of patient prostate motion trajectories exemplifying five distinct categories: stable prostate, slow drift, persistent excursion, transient excursion, and high frequency excursions. The phantom and fiducial were imaged using 140 kVp, 0.63 mAs per image at 1 Hz for a 60 s monitoring period. Both stereoscopic and monoscopic 3D localization accuracies were assessed by comparison to the ground-truth obtained from the Linac log file. Imaging dose was also assessed, using optically stimulated luminescence dosimeter inserts in the phantom.

RESULTS

Stereoscopic localization accuracy varied between 0.13 ± 0.05 and 0.33 ± 0.30 mm, depending on the motion trajectory. Monoscopic localization accuracy varied from 0.2 ± 0.1 to 1.1 ± 0.7 mm. The largest localization errors were typically observed in the left-right direction. There were significant differences in accuracy between the two monoscopic views, but which view was better varied from trajectory to trajectory. The imaging dose was measured to be between 2 and 15 μGy/mAs, depending on location in the phantom.

CONCLUSIONS

The authors have demonstrated the first use of monoscopic localization for a room-mounted dual x-ray system. Three-dimensional position estimation from monoscopic imaging permits continuous, uninterrupted intrafraction motion monitoring even in the presence of gantry rotation, which may block kV sources or imagers. This potentially allows for more accurate treatment delivery, by ensuring that the prostate does not deviate substantially from the initial setup position.

Beam's-eye-view imaging during non-coplanar lung SBRT

PURPOSE

Beam's-eye-view (BEV) imaging with an electronic portal imaging device (EPID) can be performed during lung stereotactic body radiation therapy (SBRT) to monitor the tumor location in real-time. Image quality for each patient and treatment field depends on several factors including the patient anatomy and the gantry and couch angles. The authors investigated the angular dependence of automatic tumor localization during non-coplanar lung SBRT delivery.

METHODS

All images were acquired at a frame rate of 12 Hz with an amorphous silicon EPID. A previously validated markerless lung tumor localization algorithm was employed with manual localization as the reference. From ten SBRT patients, 12 987 image frames of 123 image sequences acquired at 48 different gantry-couch rotations were analyzed. δ was defined by the position difference of the automatic and manual localization.

RESULTS

Regardless of the couch angle, the best tracking performance was found in image sequences with a gantry angle within 20° of 250° (δ = 1.40 mm). Image sequences acquired with gantry angles of 150°, 210°, and 350° also led to good tracking performances with δ = 1.77-2.00 mm. Overall, the couch angle was not correlated with the tracking results. Among all the gantry-couch combinations, image sequences acquired at (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) led to the best tracking results with δ = 1.19-1.82 mm. The worst performing combinations were (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) with δ > 3.5 mm. However, 35% (17/48) of the gantry-couch rotations demonstrated substantial variability in tracking performances between patients. For example, the field angle (θ = 70°, ϕ = 10°) was acquired for five patients. While the tracking errors were ≤1.98 mm for three patients, poor performance was found for the other two patients with δ ≥ 2.18 mm, leading to average tracking error of 2.70 mm. Only one image sequence was acquired for all other gantry-couch rotations (δ = 1.18-10.29 mm).

CONCLUSIONS

Non-coplanar beams with gantry-couch rotation of (θ = 30°, ϕ = 330°), (θ = 210°, ϕ = 10°), and (θ = 250°, ϕ = 30°) have the highest accuracy for BEV lung tumor localization. Additionally, gantry angles of 150°, 210°, 250°, and 350° also offer good tracking performance. The beam geometries (θ = 90° and 230°, ϕ = 10°) and (θ = 270°, ϕ = 30°) are associated with substantial automatic localization errors. Overall, lung tumor visibility and tracking performance were patient dependent for a substantial number of the gantry-couch angle combinations studied.

Registration of clinical volumes to beams-eye-view images for real-time tracking

PURPOSE

The authors combine the registration of 2D beam's eye view (BEV) images and 3D planning computed tomography (CT) images, with relative, markerless tumor tracking to provide automatic absolute tracking of physician defined volumes such as the gross tumor volume (GTV).

METHODS

During treatment of lung SBRT cases, BEV images were continuously acquired with an electronic portal imaging device (EPID) operating in cine mode. For absolute registration of physician-defined volumes, an intensity based 2D/3D registration to the planning CT was performed using the end-of-exhale (EoE) phase of the four dimensional computed tomography (4DCT). The volume was converted from Hounsfield units into electron density by a calibration curve and digitally reconstructed radiographs (DRRs) were generated for each beam geometry. Using normalized cross correlation between the DRR and an EoE BEV image, the best in-plane rigid transformation was found. The transformation was applied to physician-defined contours in the planning CT, mapping them into the EPID image domain. A robust multiregion method of relative markerless lung tumor tracking quantified deviations from the EoE position.

RESULTS

The success of 2D/3D registration was demonstrated at the EoE breathing phase. By registering at this phase and then employing a separate technique for relative tracking, the authors are able to successfully track target volumes in the BEV images throughout the entire treatment delivery.

CONCLUSIONS

Through the combination of EPID/4DCT registration and relative tracking, a necessary step toward the clinical implementation of BEV tracking has been completed. The knowledge of tumor volumes relative to the treatment field is important for future applications like real-time motion management, adaptive radiotherapy, and delivered dose calculations.

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.

Real-time 2D/3D registration using kV-MV image pairs for tumor motion tracking in image guided radiotherapy

Intra-fractional respiratory motion during radiotherapy leads to a larger planning target volume (PTV). Real-time tumor motion tracking by two-dimensional (2D)/3D registration using on-board kilo-voltage (kV) imaging can allow for a reduction of the PTV though motion along the imaging beam axis cannot be resolved using only one projection image. We present a retrospective patient study investigating the impact of paired portal mega-voltage (MV) and kV images on registration accuracy. Material and methods. We used data from 10 patients suffering from non-small cell lung cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) lung treatment. For each patient we acquired a planning computed tomography (CT) and sequences of kV and MV images during treatment. We compared the accuracy of motion tracking in six degrees-of-freedom (DOF) using the anterior-posterior (AP) kV sequence or the sequence of kV-MV image pairs. Results. Motion along cranial-caudal direction could accurately be extracted when using only the kV sequence but in AP direction we obtained large errors. When using kV-MV pairs, the average error was reduced from 2.9 mm to 1.5 mm and the motion along AP was successfully extracted. Mean registration time was 188 ms. Conclusion. Our evaluation shows that using kV-MV image pairs leads to improved motion extraction in six DOF and is suitable for real-time tumor motion tracking with a conventional LINAC.

Monitoring tumor motion by real time 2D/3D registration during radiotherapy

Background and purpose

In this paper, we investigate the possibility to use X-ray based real time 2D/3D registration for non-invasive tumor motion monitoring during radiotherapy.

Materials and methods

The 2D/3D registration scheme is implemented using general purpose computation on graphics hardware (GPGPU) programming techniques and several algorithmic refinements in the registration process. Validation is conducted off-line using a phantom and five clinical patient data sets. The registration is performed on a region of interest (ROI) centered around the planned target volume (PTV).

Results

The phantom motion is measured with an rms error of 2.56 mm. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is shown. Videos show a good match between X-ray and digitally reconstructed radiographs (DRR) displacement. Mean registration time is 0.5 s.

Conclusions

We have demonstrated that real-time organ motion monitoring using image based markerless registration is feasible.

Active Tracking and Dynamic Dose Delivery for robotic couch in radiation therapy

Precise and accurate dose delivery is critically important in external beam radiation therapy. In many cases target-volumes are stationary, but the problem arises when the tumors move significantly due to cardiac and respiratory motions. This is a case for tumors in lung, esophagus, pancreas, liver, prostate, breast, and other organs in thoracic and abdominal regions. In the article we have described the Active Tracking and Dynamic Dose Delivery (ATDD) technique for real-time tumor motion compensation. In this approach, the robotic treatment table moves while delivering the radiation beam and compensates for breathing-induced tumor motion. Many parameters of the control system, such as patient mass or breathing pattern, are initially uncertain and may vary during the treatment. To solve these problems, feedforward adaptive control was adopted to minimize irradiation to healthy tissue and spare critical organs while ensuring prescribed radiation dose coverage to the target-volume.

Interfractional reproducibility of lung tumor location using various methods of respiratory motion mitigation

PURPOSE

To determine interfractional reproducibility of the location of lung tumors using respiratory motion mitigation.

METHODS AND MATERIALS

Free-breathing four-dimensional computed tomography (CT) data sets and CT data sets during breath hold were acquired weekly for 17 patients undergoing treatment for non-small-cell lung cancer. Distances between the center of the gross tumor volume (GTV) and a reproducible bony reference point under conditions of breath hold on end inspiration (EI) and end expiration (EE) and during free breathing on the 0% phase (corresponding to EI) and 50% phase (corresponding to EE) were analyzed for interfractional reproducibility. Systematic uncertainties in tumor location were determined as the difference in distance between the GTV center on the first CT data set and the mean location of GTV centers on the subsequent data sets. Random uncertainties in tumor location were determined as the standard deviation of the distances between the GTV centers and the bony reference points. Margins to account for systematic and random interfractional variations were estimated based on these uncertainties.

RESULTS

Mean values of interfractional setup uncertainties were as follows: systematic uncertainties--EI, 0.3 cm; EE, 0.2 cm; 0% phase, 0.3 cm; and 50% phase, 0.3 cm; and random uncertainties--EI, 0.3 cm; EE, 0.3 cm; 0% phase, 0.3 cm; and 50% phase, 0.3 cm. There does not appear to be any correlation between uncertainties and GTV size, but there appears to be a weak positive correlation between uncertainties and the magnitude of GTV excursion.

CONCLUSIONS

Voluntary breath hold and gating on either EI or EE appear to be equally reliable methods of ensuring the reproducibility of lung tumor position. We recommend setup margins of 0.3 cm if using cone-beam CT or kilovoltage X-ray with fiducials and aligning directly to the tumor and 0.8 cm when aligning to a nearby bony surrogate using cone-beam CT or kilovoltage X-ray.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Accuracy in the localization of thoracic and abdominal tumors using respiratory displacement, velocity, and phase

Current four dimensional (4D) computed tomography (CT) reconstruction techniques are retrospectively created based on either the phase or displacement of the respiratory signal. Both techniques have known limitations which cause clinically significant motion artifacts in 4D CT images. These artifacts, which appear as undefined or irregular boundaries in the 4D CT images, cause systematic errors in patient contouring and dose calculations. The aim of this work was to evaluate the reproducibility of tumor position as a function of displacement, phase, and velocity of the respiratory signal, respectively, in order to determine the optimum parameter or combination of parameters to use in order to minimize artifacts in 4D CT images or to accurately deliver radiation to relevant structures during treatment.

METHOD AND MATERIALS

Estimated tumor centroid position and respiratory signal data were acquired with the Cyberknife Synchrony system for 26 thoracic radiotherapy patients (52 fractions). A reference respiratory cycle was calculated for each patient. Displacement, phase, and velocity of ten data points were calculated from this reference respiratory cycle, where each point represents an image bin. The corresponding tumor position was then sorted into these image bins if the phase, displacement, simultaneous displacement and phase, or simultaneous displacement and velocity of the respiratory signal were within tolerances of 0.5 mm for displacement and 0.5 mm/s for velocity, respectively, from the corresponding data of the reference cycle for each image bin.

RESULTS

The mean of the standard deviations of tumor positions over all bins and all fractions for the superior-inferior direction were 2.13 +/- 1.01 mm for phase sorting, 1.20 +/- 0.76 mm for displacement sorting, 1.20 +/- 0.71 mm for simultaneous displacement and phase sorting, and 1.10 +/- 0.71 mm for simultaneous displacement and velocity sorting, with maximum deviations of 43.0, 16.1, 15.5, and 14.1 mm for each scenario, respectively. The same trend was observed for the anterior-posterior and left-right directions. A linear dependence was observed between the mean of the standard deviations of tumor positions over all fractions as a function of the velocity of the respiratory signal at each bin for all the sorting scenarios. A substantially larger gradient for the phase sorting scenario, compared to the other scenarios, suggests that tumor localization will become increasingly less accurate as the velocity of the tumor increases during a breathing cycle, e.g., if the amplitude of motion increases while the period of the respiratory cycle stays constant or during mid inhale or exhale phases of the respiratory cycle.

CONCLUSION

This study illustrates that position of a tumor can be determined more accurately if displacement and velocity are used simultaneously as sorting parameters for 4D CT images or during treatment. A real-time displacement and velocity based 4D CT image sorting method may therefore produce fewer and smaller artifacts in 4D CT images than current retrospective sorting methods.

On the accuracy of a moving average algorithm for target tracking during radiation therapy treatment delivery

Real-time tumor targeting involves the continuous realignment of the radiation beam with the tumor. Real-time tumor targeting offers several advantages such as improved accuracy of tumor treatment and reduced dose to surrounding tissue. Current limitations to this technique include mechanical motion constraints. The purpose of this study was to investigate an alternative treatment scenario using a moving average algorithm. The algorithm, using a suitable averaging period, accounts for variations in the average tumor position, but respiratory induced target position variations about this average are ignored during delivery and can be treated as a random error during planning. In order to test the method a comparison between five different treatment techniques was performed: (1) moving average algorithm, (2) real-time motion tracking, (3) respiration motion gating (at both inhale and exhale), (4) moving average gating (at both inhale and exhale) and (5) static beam delivery. Two data sets were used for the purpose of this analysis: (a) external respiratory-motion traces using different coaching techniques included 331 respiration motion traces from 24 lung-cancer patients acquired using three different breathing types [free breathing (FB), audio coaching (A) and audio-visual biofeedback (AV)]; (b) 3D tumor motion included implanted fiducial motion data for over 160 treatment fractions for 46 thoracic and abdominal cancer patients obtained from the Cyberknife Synchrony. The metrics used for comparison were the group systematic error (M), the standard deviation (SD) of the systematic error (sigma) and the root mean square of the random error (sigma). Margins were calculated using the formula by Stroom et al. [Int. J. Radiat. Oncol., Biol., Phys. 43(4), 905-919 (1999)]: 2sigma + 0.7sigma. The resultant calculations for implanted fiducial motion traces (all values in cm) show that M and sigma are negligible for moving average algorithm, moving average gating, and real-time tracking (i.e., M and sigma = 0 cm) compared to static beam (M = 0.02 cm and sigma = 0.16 cm) or gated beam delivery (M = -0.05 and 0.16 cm at both exhale and inhale, respectively, and sigma = 0.17 and 0.26 cm at both exhale and inhale, respectively). Moving average algorithm sigma = 0.22 cm has a slightly lower random error than static beam delivery sigma = 0.24 cm, though gating, moving average gating, and real-time tracking have much lower random error values for implanted fiducial motion. Similar trends were also observed for the results using the external respiratory motion data. Moving average algorithm delivery significantly reduces M and sigma compared with static beam delivery. The moving average algorithm removes the nonstationary part of the respiration motion which is also achieved by AV, and thus the addition of the moving average algorithm shows little improvement with AV. Overall, a moving average algorithm shows margin reduction compared with gating and static beam delivery, and may have some mechanical advantages over real-time tracking when the beam is aligned with the target and patient compliance advantages over real-time tracking when the target is aligned to the beam.

A deliverable four-dimensional intensity-modulated radiation therapy-planning method for dynamic multileaf collimator tumor tracking delivery

PURPOSE

To develop a deliverable four-dimensional (4D) intensity-modulated radiation therapy (IMRT) planning method for dynamic multileaf collimator (MLC) tumor tracking delivery.

METHODS AND MATERIALS

The deliverable 4D IMRT planning method involves aligning MLC leaf motion parallel to the major axis of target motion and translating MLC leaf positions by the difference in the target centroid position between respiratory phases of the 4D CT scan. This method ignores nonlinear respiratory motion and deformation. A three-dimensional (3D) optimal method whereby an IMRT plan on each respiratory phase of the 4D CT scan was independently optimized was used for comparison. For 12 lung cancer patient 4D CT scans, individual phase plans and deformable dose-summed 4D plans using the two methods were created and compared.

RESULTS

For each of the individual phase plans, the deliverable method yielded similar isodose distributions and dose-volume histograms. The deliverable and 3D optimal methods yielded statistically equivalent dose-volume metrics for both individual phase plans and 4D plans (p > 0.05 for all metrics compared). The deliverable method was affected by 4D CT artifacts in one case. Both methods were affected by high vector field variations from deformable registration.

CONCLUSIONS

The deliverable method yielded similar dose distributions for each of the individual phase plans and statistically equivalent dosimetric values compared with the 3D optimal method, indicating that the deliverable method is dosimetrically robust to the variations of fractional time spent in respiratory phases on a given 4D CT scan. Nonlinear target motion and deformation did not cause significant dose discrepancies.