Evaluation of the need for simultaneous orthogonal gated setup imaging

Image‐guided patient setup for respiratory‐gated radiotherapy often relies on a pair of respiratory‐gated orthogonal radiographs, acquired one after the other. This study quantifies the error due to changes in the internal/external correlation which may affect asynchronous (non‐simultaneous) imaging. The dataset from eight patients includes internal and external coordinates acquired at 30Hz during multi‐fraction SBRT treatments using the Mitsubishi RTRT system coupled with an external surrogate gating device. We performed a computational simulation of the position of an implanted fiducial marker in an asynchronous orthogonal image set. A comparison is made to the reference position, the actual 3D fiducial location at the initial time point, as would be obtainable by simultaneous orthogonal setup imaging at that time point. The time interval between the two simulated radiographic acquisitions was set to a minimum of 30, 60 or 90 seconds, based on our clinical experience. The setup position is derived from a combination of both the initial (AP) and the final (LR) simulated 2D images in the following way: LRsetup=LRinitial,SIsetup=SIinitial+(SIfinal−SIinitial)/2,APsetup=APfinal. The 3D error is then the magnitude of the vector from the initial (reference) position to the setup position. The calculation was done for every exhale phase in the data for which there was another one at least 30, 60 or 90 seconds later, at an amplitude within 0.5 mm from the first. A correlation between the time interval and the 3D error was also sought. The mean 3D error is found to be roughly equivalent for time intervals (tinterval) of 30, 60 and 90 seconds between the orthogonal simulated images (0.8 mm, 0.8 mm, 0.6 mm, respectively). The 3D error is less than 1, 2 and 3 mm for 77%, 89% and 98% of the data points, respectively. The actual time between simulated images turned out to be very close to tinterval, with 90% of the second simulated image acquisitions being completed within 38, 68 and 95 seconds of the first simulated image for tinterval of 30, 60 and 90 seconds, respectively. No correlation was found between the length of the time interval and the 3D error. When acquiring respiratory‐gated radiographs for patient setup, only small errors should be expected if those images are not taken simultaneously. PACS number: 87.55.n

Evaluation of 3D fluoroscopic image generation from a single planar treatment image on patient data with a modified XCAT phantom

Accurate understanding and modeling of respiration-induced uncertainties is essential in image-guided radiotherapy. Explicit modeling of overall lung motion and interaction among different organs promises to be a useful approach. Recently, preliminary studies on 3D fluoroscopic treatment imaging and tumor localization based on Principal Component Analysis (PCA) motion models and cost function optimization have shown encouraging results. However, the performance of this technique for varying breathing parameters and under realistic conditions remains unclear and thus warrants further investigation. In this work, we present a systematic evaluation of a 3D fluoroscopic image generation algorithm via two different approaches. In the first approach the model’s accuracy is tested for changing parameters for sinusoidal breathing. These parameters included changing respiratory motion amplitude, period, and baseline shift. The effects of setup error, imaging noise and different tumor sizes are also examined. In the second approach, we test the model for anthropomorphic images obtained from a modified XCAT phantom. This set of experiments is important as all the underlying breathing parameters are simultaneously tested, as in realistic clinical conditions. Based on our simulation results for more than 250 seconds of breathing data for 8 different lung patients, the overall tumor localization accuracy of the model in left-right (LR), anterior-posterior (AP) and superior-inferior (SI) directions are 0.1 ± 0.1 mm, 0.5 ± 0.5 mm and 0.8 ± 0.8 mm respectively. 3D tumor centroid localization accuracy is 1.0 ± 0.9 mm

An Expanded Multi-scale Monte Carlo Simulation Method for Personalized Radiobiological Effect Estimation in Radiotherapy: a feasibility study

A novel and versatile “bottom-up� approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy

Nanoparticle Mediated Tumor Vascular Disruption: A Novel Strategy in Radiation Therapy

More than 50% of all cancer patients receive radiation therapy. The clinical delivery of curative radiation dose is strictly restricted by the proximal healthy tissues. We propose a dual-targeting strategy using vessel-targeted-radiosensitizing gold nanoparticles and conformal-image guided radiation therapy to specifically amplify damage in the tumor neoendothelium. The resulting tumor vascular disruption substantially improved the therapeutic outcome and subsidized the radiation/nanoparticle toxicity, extending its utility to intransigent or nonresectable tumors that barely respond to standard therapies

Measurement of the interplay effect in lung IMRT treatment using EDR2 films

Intrafraction organ motion during the dynamic delivery of intensity‐modulated radiation therapy (IMRT) treatment of lung tumors may cause unexpected hot/cold spots within the target volume, due to the interplay effect between tumor motion and multileaf collimator (MLC) leaf motion. In the past, this has been investigated through theoretical analysis, computer simulation, and experimental measurement using an ionization chamber dosimeter. In the work presented here, the interplay effect was studied experimentally in 2D, using Kodak EDR2 films. A five‐field lung IMRT plan was delivered to a solid water phantom with embedded film. The phantom was placed on a motor‐driven platform with a sinusoidal motion to simulate the respiration‐induced tumor motion. The delivery of each field began at one of eight equally spaced initial breathing phases. The dose distribution for each treatment fraction was estimated by combining the dose distributions for all fields with randomly sampled initial breathing phases. The dose variation caused by the interplay effect was estimated by looking at the dose values from 1000 trials of 30 fractions. It was found that, on a day‐to‐day basis, the standard deviation of the dose to a given pixel in the high‐dose region could be as high as 2% to 4% due to the motion interplay effect. After 30 fractions, the standard deviation in the dose to each pixel is reduced to 0.4% to 0.7%. However, compared to the static delivery, the dose distribution from a 30‐fraction case in the presence of motion shows some underdosing in the region of interest. We found that the maximum dose in the target remains within 1% of the maximum dose in the static case, but the minimum dose in the target is most likely to be about 6% lower than the static case. Our results indicate that there can be some underdosing of the tumor due to the interplay effect in lung IMRT delivery over the entire course of a 30‐fraction treatment. PACS number: 87.53.M