Joerg Rottmann

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery.

PURPOSE 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. METHODS 2D radiographs from the therapy beams-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. RESULTS 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. CONCLUSIONS 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.

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

PURPOSE The authors combine the registration of 2D beams 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.

A novel EPID design for enhanced contrast and detective quantum efficiency

Beams-eye-view imaging applications such as real-time soft-tissue motion estimation are hindered by the inherently low image contrast of electronic portal imaging devices (EPID) currently available for clinical use. We introduce and characterize a novel EPID design that provides substantially increased detective quantum efficiency (DQE), contrast-to-noise ratio (CNR) and sensitivity without degradation in spatial resolution. The prototype design features a stack of four conventional EPID layers combined with low noise integrated readout electronics. Each layer consists of a copper plate, a scintillator ([Formula: see text]) and a photodiode/TFT-switch (aSi:H). We characterize the prototypes signal response to a 6 MV photon beam in terms of modulation transfer function (MTF), DQE and CNR. The presampled MTF is estimated using a slanted slit technique, the DQE is calculated from measured normalized noise power spectra (nNPS) and the MTF and CNR is estimated using a Las Vegas contrast phantom. The prototype has been designed and built to be interchangeable with the current clinical EPID on the Varian TrueBeam platform (AS-1200) in terms of size and data output specifications. Performance evaluation is conducted in absolute values as well as in relative terms using the Varian AS-1200 EPID as a reference detector. A fivefold increase of DQE(0) to about 6.7% was observed by using the four-layered design versus the AS-1200 reference detector. No substantial differences are observed between each layers individual MTF and the one for all four layers operating combined indicating that defocusing due to beam divergence is negligible. Also, using four layers instead of one increases the signal to noise ratio by a factor of 1.7.

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

PURPOSE In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. METHODS The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. RESULTS The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. CONCLUSIONS The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model. This is the first method to estimate volumetric time-varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient.

The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

PURPOSE Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated. METHODS Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R). RESULTS For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R -0.58 and -0.19 for both studies, respectively. CONCLUSIONS Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.

3-D fiducial motion tracking using limited MV projections in arc therapy

PURPOSE In-treatment fiducial tracking has recently received attention as a method for improving treatment accuracy, dose conformity, and sparing of healthy tissue. 3-D fiducial localization in arc-radiotherapy remains challenging due to the motion of targets and the complexity of arc deliveries. We propose a novel statistical method for estimating 3-D fiducial motion using limited 2-D megavoltage (MV) projections. METHODS 3-D fiducial motion was estimated by a maximum a posteriori (MAP) approach to integrating information of fiducial projections with prior knowledge of target motion. To obtain the imaging geometries, short sequences of MV projections were selected in which fiducials were continuously visible. The MAP algorithm estimated the 3-D motion by maximizing the probability of displacement of fiducials in the sequences. Prior knowledge of target motion from a large statistical sample was built into the model to enhance the accuracy of estimation. In the case that a motion prior was unavailable, the algorithm can be simplified to the maximum likelihood (ML) approach. To compare tracking performance, a multiprojection geometric method was also presented by extending the typical two-project ion geometric estimation approach. The algorithms were evaluated using clinical prostate motion traces, and the performance was measured in quality indices and statistical evaluation. RESULTS The results showed that the MAP method significantly outperforms the geometric method in all measures. In our simulations, the MAP method achieved an accuracy of less than 1 mm RMS error using only five continuous projections, whereas the geometric method required 15 projections to achieve a similar result. CONCLUSIONS The approach presented can accurately estimate tumor motion using a limited number of continuous projections. The MAP motion estimation is superior to both the ML and geometric estimation methods.

Cine EPID evaluation of two non-commercial techniques for DIBH

PURPOSE To evaluate the efficacy of two noncommercial techniques for deep inspiration breathhold (DIBH) treatment of left-sided breast cancer (LSBC) using cine electronic portal imaging device (EPID) images. METHODS 23,875 EPID images of 65 patients treated for LSBC at two different cancer treatment centers were retrieved. At the Milford Regional Cancer Center, DIBH stability was maintained by visual alignment of inroom lasers and patient skin tattoos (TAT). At the South Shore Hospital, a distance-measuring laser device (RTSSD) was implemented. For both centers,cine EPID images were acquired at least once per week during beam-on. Chest wall position relative to image boundary was measured and tracked over the course of treatment for every patient and treatment fraction for which data were acquired. RESULTS Median intrabeam chest motion was 0.31 mm for the TAT method and 0.37 mm for the RTSSD method. The maximum excursions exceeded our treatment protocol threshold of 3 mm in 0.3% of cases (TAT) and 1.2% of cases (RTSSD). The authors did not observe a clinically significant difference between the two datasets. CONCLUSIONS Both noncommercial techniques for monitoring the DIBH location provided DIBH stability within the predetermined treatment protocol parameters (<3 mm). The intreatment imaging offered by the EPID operating in cine mode facilitates retrospective analysis and validation of both techniques.

3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based and 4DCT-based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery.

MO‐FG‐BRA‐07: Theranostic Gadolinium‐Based AGuIX Nanoparticles for MRI‐Guided Radiation Therapy

Purpose: AGuIX are gadolinium-based nanoparticles, initially developed for MRI, that have a potential role in radiation therapy as a radiosensitizer. Our goal is to demonstrate that these nanoparticles can both be used as an MRI contrast agent, as well as to obtain local dose enhancement in a pancreatic tumor when delivered in combination with an external beam irradiation. Methods: We performed in vitro cell uptake and radiosensitization studies of a pancreatic cancer cell line in a low energy (220kVp) beam, a standard clinical 6MV beam (STD) and a flattening filter free clinical 6MV beam (FFF). After injection of 40mM of nanoparticles, a biodistribution study was performed in vivo on mice with subcutaneous xenograft pancreatic tumors. In vivo radiation therapy studies were performed at the time point of maximum tumor uptake. Results: The concentration of AGuIX nanoparticles in Panc-1 pancreatic cancer cells, determined in vitro by MRI and ICPMS, peaks after 30 minutes with 0.3% of the initial concentration (5mg/g). Clonogenic assays show a significant effect (p<0.05) when the AGuIX are coupled with MV photon irradiation (DEF20%=1.31). Similar AGuIX tumor uptake is found in vivo by both MRI and ICPMS 30 minutes after intravenous injection. For long term survival studies, the choice of the radiation dose is determined with 5 control groups (3mice/group) irradiated with 0, 5, 10, 15, and 20Gy. Afterwards, 4 groups (8mice/group) are used to evaluate the effect of the nanoparticles. A Logrank test is performed as a statistical test to evaluate the effect of the nanoparticles. Conclusion: The combination of the MRI contrast and radiosensitization properties of gadolinium nanoparticles reveals a strong potential for usage with MRI-guided radiation therapy.

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

PURPOSE Beams-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.