Beam's Eye-view Images Research Articles

TH-AB-202-01: Daily Lung Tumor Motion Characterization On EPIDs Using a Markerless Tiling Model

Purpose: Tracking lung tumor motion in real time allows for target dose escalation while simultaneously reducing dose to sensitive structures, thus increasing local control without increasing toxicity. We present a novel intra-fractional markerless lung tumor tracking algorithm using MV treatment beam images acquired during treatment delivery. Strong signals superimposed on the tumor significantly reduced the soft tissue resolution; while different imaging modalities involved introduce global imaging discrepancies. This reduced the comparison accuracies. A simple yet elegant Tiling algorithm is reported to overcome the aforementioned issues. Methods: MV treatment beam images were acquired continuously in beam's eye view (BEV) by an electronic portal imaging device (EPID) during treatment and analyzed to obtain tumor positions on every frame. Every frame of the MV image was simulated by a composite of two components with separate digitally reconstructed radiographs (DRRs): all non-moving structures and the tumor. This Titling algorithm divides the global composite DRR and the corresponding MV projection into sub-images called tiles. Rigid registration is performed independently on tile-pairs in order to improve local soft tissue resolution. This enables the composite DRR to be transformed accurately to match the MV projection and attain a high correlation value through a pixel-based linear transformation. The highest cumulative correlation for all tile-pairs achieved over a user-defined search range indicates the 2-D coordinates of the tumor location on the MV projection. Results: This algorithm was successfully applied to cine-mode BEV images acquired during two SBRT plans delivered five times with different motion patterns to each of two phantoms. Approximately 15000 beam's eye view images were analyzed and tumor locations were successfully identified on every projection with a maximum/average error of 1.8 mm / 1.0 mm. Conclusion: Despite the presence of strong anatomical signal overlapping with tumor images, this markerless detection algorithm accurately tracks intrafractional lung tumor motions. This project is partially supported by an Elekta research grant

Development of system using beam's eye view images to measure respiratory motion tracking errors in image-guided robotic radiosurgery system.

The accuracy of the CyberKnife Synchrony Respiratory Tracking System (SRTS) is considered to be patient‐dependent because the SRTS relies on an individual correlation between the internal tumor position (ITP) and the external marker position (EMP), as well as a prediction method to compensate for the delay incurred to adjust the position of the linear accelerator (linac). We aimed to develop a system for obtaining pretreatment statistical measurements of the SRTS tracking error by using beam's eye view (BEV) images, to enable the prediction of the patient‐specific accuracy. The respiratory motion data for the ITP and the EMP were derived from cine MR images obtained from 23 patients. The dynamic motion phantom was used to reproduce both the ITP and EMP motions. The CyberKnife was subsequently operated with the SRTS, with a CCD camera mounted on the head of the linac. BEV images from the CCD camera were recorded during the tracking of a ball target by the linac. The tracking error was measured at 15 Hz using in‐house software. To assess the precision of the position detection using an MR image, the positions of test tubes (determined from MR images) were compared with their actual positions. To assess the precision of the position detection of the ball, ball positions measured from BEV images were compared with values measured using a Vernier caliper. The SRTS accuracy was evaluated by determining the tracking error that could be identified with a probability of more than 95% (Ep95). The detection precision of the tumor position (determined from cine MR images) was <0.2 mm. The detection precision of the tracking error when using the BEV images was <0.2 mm. These two detection precisions were derived from our measurement system and were not obtained from the SRTS. The median of Ep95 was found to be 1.5 (range, 1.0–3.5) mm. The difference between the minimum and maximum Ep95 was 2.5 mm, indicating that this provides a better means of evaluating patient‐specific SRTS accuracy. A suitable margin, based on the predicted patient‐specific SRTS accuracy, can be added to the clinical target volume.PACS number: 87.53.Ly

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

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). 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. 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. 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

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. 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. 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). 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 soft tissue motion estimation for lung tumors during radiotherapy delivery

To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm. The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.

SU-E-T-584: The Accuracy of the Respiratory Motion Tracking with Robotic Radiosurgery System

Purpose: To evaluate the accuracy of the respiratory motion tracking system of the CyberKnife by Beam's eye view images from CCDcamera. Methods: The ball, 20.1 mm in diameter, in which gold marker was placed was used as a target. Using a dynamic motion phantom, it moved based on motion either of data sets from a sine curve or irregular patterns of respiration that came from two patients, both of which had 1 cm amplitude. Treatment planning was based on a static CT scan using standard parameters for CyberKnife treatment, and all of the beams in the plan aimed center of the ball. Beam's eye view images were recorded with a CCDcamera mounted on a linac head which was tracking the ball. The errors from displacement between the CCDcamera's central axis and center of the ball were measured by fifteen times per second, with self‐developed software. Results: In the case of the motion by the sine curve, errors were 2mm or less at 99% of the tracking time. In the case of the respiratory irregular motion, errors were 3mm or less in 99% of the tracking time. However, more than 5 mm errors were momentarily detected. Conclusions: We developed a method to measure statistically the error of the respiratory motion tracking. In this experiment, it was very small; however, larger errors were observed in irregular motion, comparing with regular motion with the same amplitude. The reason is the respiratory motion tracking system uses the algorithm based on prediction of the future target position using past pattern of motion. Thus, PTV margin may be set for each patient individually.

SU-E-T-499: Assessment of Patient Setup Accuracy at a Treatment Position after the Patient Has Been Registered at Another Location Using Robotic Positioner and a Dual KV Imaging System

Purpose: We use cardinal angle and beam eye view images with DRRs to register a patient at every treatment position. This process is time consuming; moreover, every treatment position is not amenable to imaging. This study is to assess the combined robotic positioner and gantry movement accuracy at a treatment position relative to zero yaw image registration so that additional imaging at the new location can be avoided. Methods: A Styrofoam phantom 30 cm × 30 cm × 30 cm with beekleys embedded in such a way that they could easily be distinguished on a DRR. The phantom was CT scanned with a 2.5 mm slice thickness and a 50 cm field of view. Treatment planningDRRs were created at numerous table and gantry angles. The phantom was subsequently set up in the treatment room with both table yaw and gantry at zero. The table was loaded with 200 lb weight in order to replicate a typical patient. Image registration was carried out using cardinal angle images and the DRRs. The robotic positioner and gantry were then moved to a new treatment position. The accuracy of the move was evaluated using the beam eye view image, the orthogonal images at the new position and the DRRs for this location. The process was repeated for numerous table and gantry positions as predetermined during treatment planning. Results: The accuracy was found better than a 1.0 mm for all moves except near treatment position with table yaw 90° and Gantry angle between 180° to 270°, where the accuracy was still better than 1.7 mm. Conclusions: As such, the system can be clinically used for patient registration, but we are in the process of further improving the setup accuracy for all clinically relevant robotic positioner and gantry movements without additional imaging.

SU-GG-T-131: A Linear Metric of Knowledge-Based IMRT Treatment Plan Quality for the Prostate

Purpose: In prostate IMRTtreatment planning, the variation in patient anatomy makes it difficult to a priori estimate the maximum extent of dose reduction possible to rectum and bladder. Such an estimation would greatly aid treatment planning by letting clinicians adjust PTV margins to satisfy their dose sparing requirements. This work provides a Mutual Information‐based framework for estimating rectal and bladder sparing, developed using an existing database of treatment plans. Method and Materials: The database consists of 100 prostate patients, previously planned with IMRT. Beam's Eye View images were created for seven standard gantry angles, with each projection showing bladder, rectum, PTV and all possible overlaps. The summed mutual information between patients in the database for the seven gantry angles were correlated against the DVH results (at specific constraint cutpoints) from the IMRT plans. A linear relationship between the Mutual Information and DVH reductions was established. Results: Initial results of 13 patients, compared against a total of 74 known plans, show a strong linear correlation of a set of DVH‐cutpoints to a weighted MI, that is fit using individual weights for every possible region of overlap. The initial unweighted R2 correlation of DVH quality to MI was 0.46, and after fitting the correlation was 0.84. Conclusion: This study shows the potential to extract from a large enough data bank, information about the structural importance of the various critical structures of the prostate region and the PTV. The increase of the R2 correlation indicates that the fit is good, and that the value of this weighted MI better indicates treatment plan quality.

Poster - Thurs Eve-16: Just-in-time tomography (JiTT).

Soft-tissue target motion is one of the main concerns in high-precision radiation therapy. Cone beam computed tomography (CBCT) has been developed recently to image soft-tissue targets in the treatment room for image-guided radiation therapy. However, due to its relatively long image acquisition time the CBCT approach cannot provide images of the target at the instant of the treatment and thus is not adequate for imaging targets with intrafraction motion. In this work, a new concept for image-guided radiation therapy- just-in-time tomography (JiTT) - is introduced. Differing from CBCT, JiTT takes much less time to generate the needed tomographical, beam's-eye-view images of the treatment target at the right moment to guide the radiation therapy treatment. A system to achieve JiTT is proposed and its feasibility is investigated. Research supported by Siemens.

A novel method for estimating SBRT delivered dose with beam's-eye-view images

Stereotactic body radiation therapy is predicated on a high degree of targeting accuracy. However, inaccurate patient setup as well as intra-fractional motion can hinder the delivery of high doses preferentially to the target. To ensure that the coverage delivered to the patient is as planned, an image-guided verification system has been created to estimate the delivered dose retrospectively. This will not only aid the assessment of treatment techniques, but will also allow for more accurate dose response analysis. Patients with limited hepatic metastases from solid tumors were treated with SBRT. Implanted gold markers were used as target surrogates and a body frame and compression plate provided stereotactic localization and target immobilization, respectively. During treatment, an electronic portal imaging device (EPID), operating in cine mode, collected the exit dose. The sequences of images for each field were processed off-line using in-house software for registration and seed localization. The beam's-eye-view seed positions in the treatment images were compared to those in the DRR's to determine the target shifts in the imaging plane. These target shifts were then imported into the treatment planning software. Each original field was multiplied by the number of images taken during treatment. The calculated shift from each image was then applied to each of the new subfields. Summing all of these subfields together gives the dose distribution that was actually delivered to the patient. The dose-volume histograms for the planned and delivered distributions for four patients' complete treatments are shown. For two of the patients, underdosing due to a setup error or intra-fractional drift was not wholly resolved by subsequent fractions. For one of these patients two alternative corrective strategies have been applied, retrospectively, and the prescribed target coverage recovered for both. The delivered dose can be estimated using the information contained in cine EPID images acquired during irradiation. Calculating the dose actually delivered to the target will allow us to assess treatment procedures as well as more accurately report clinical results.

SU‐GG‐J‐66: Delivered Dose Assessment with Beam's‐Eye‐View Imaging During Radiotherapy

Purpose: During conventional radiotherapy the location of the patients' anatomy, particularly the tumor, while the treatment beam is on is of primary importance. This becomes especially relevant in treatment sites where large intra‐fraction motion has been observed (upper abdomen and thorax). We have already demonstrated a method for monitoring the target during irradiation with beam's‐eye‐view (BEV) imaging. In this work we use the intra‐fraction data to retrospectively calculate the delivered dose. This can be done in between each fraction and the cumulative treatment dose updated daily. If discrepancies are seen between planned and delivered, the treatment may be altered such that the delivered distribution converges with the plan. Method and Materials: The radiotherapy target is visualized daily during radiotherapy by collecting the exit radiation with an electronic portal‐imaging device (EPID). In between each fraction, the location of the target in the treatment images is compared with the reference position from simulation. The in‐treatment target positions are introduced in the treatment planning software as sub‐fields representing equal fractions of the original fields' monitor units. The dose distributions from each of the sub‐fields are summed to calculate the dose delivered each day. This distribution is updated daily to provide the cumulative delivered dose distribution. Results: The dose‐volume histograms (DVH) for the planned and delivered distributions have been calculated for several patients. Delivered doses to target and critical structures are generated for each fraction and cumulatively. Conclusion: The delivered dose can be calculated using the information contained in BEV images acquired during irradiation. By calculating the dose actually delivered to the target, we can assess our treatment procedures as well as more accurately report clinical results. Conflict of Interest: This work was partially supported by Varian Medical Systems, Inc.

Just-in-time tomography (JiTT): a new concept for image-guided radiation therapy

Soft-tissue target motion is one of the main concerns in high-precision radiation therapy. Cone beam computed tomography (CBCT) has been developed recently to image soft-tissue targets in the treatment room and guide the radiation therapy treatment. However, due to its relatively long image acquisition time the CBCT approach cannot provide images of the target at the instant of the treatment and thus it is not adequate for imaging targets with intrafraction motion. In this note, a new approach for image-guided radiation therapy—just-in-time tomography (JiTT)—is proposed. Differing from CBCT, JiTT takes much less time to generate the needed tomographical, beam's-eye-view images of the treatment target at the right moment to guide the radiation therapy treatment.

Beam's eye view based prostate treatment planning: Is it useful?

Prostate cancer is a common malignancy often treated with radiation therapy. Treatment optimization may improve local control while reducing acute and long-term complications. We routinely obtained CT scans on prostate cancer patients in treatment position after simulation. We analyzed the impact and implications of using our 3-D Beam's Eye View (BEV) capability on field definition and blocking for 12 consecutive patients. Conclusions include: (a) it is necessary to use multiple bony landmarks to align BEV images with simulator films; (b) it is difficult to enter volumes precisely, that is, the exact inferior extent of prostate; (c) Beam's Eye View-based plans show more individual variability in field size and position than are allowed for by recommendations in the literature; and (d) in this small series we found no significant correlation between prostate volume and clinical staging. In addition, computerized Beam's Eye View capability enables us to do normal tissue dosimetry. We have used Dose Volume Histograms (DVH) to study the impact of Beam's Eye View on optimization of dose to the bladder and rectum while adequately treating the prostate, with or without the seminal vesicles. Dose Volume Histograms using Beam's Eye View are compared with Dose Volume Histograms using target volumes from the literature. The results will be discussed, as well as the relative advantages of using Beam's Eye View for prostate cancer on a routine basis.