Purpose Lung stereotactic body radiation therapy (SBRT) requires delivering large radiation doses with millimeter accuracy, making image guidance essential. An approach to forming images of patient anatomy from Compton-scattered photons during lung SBRT is presented. Methods To investigate the potential of scatter imaging, a pinhole collimator and flat-panel detector are used for spatial localization and detection of photons scattered during external beam therapy using lung SBRT treatment conditions (6 MV FFF beam). MCNP Monte Carlo software is used to develop a model to simulate scatter images. This model is validated by comparing experimental and simulated phantom images. Patient scatter images are then simulated from 4DCT data. Results Experimental lung tumor phantom images have sufficient contrast-to-noise to visualize the tumor with as few as 10 MU (0.5 s temporal resolution). The relative signal intensity from objects of different composition as well as lung tumor contrast for simulated phantom images agree quantitatively with experimental images, thus validating the Monte Carlo model. Scatter images are shown to display high contrast between different materials (lung, water, bone). Simulated patient images show superior (~double) tumor contrast compared to MV transmission images. Conclusions Compton scatter imaging is a promising modality for directly imaging patient anatomy during treatment without additional radiation, and it has the potential to complement existing technologies and aid tumor tracking and lung SBRT image guidance.
By collimating the photons scattered when a megavoltage therapy beam interacts with the patient, a Compton-scatter image may be formed without the delivery of an extra dose. To characterize and assess the potential of the technique, an analytical model for simulating scatter images was developed and validated against Monte Carlo (MC). For three phantoms, the scatter images collected during irradiation with a 6 MV flattening-filter-free therapy beam were simulated. Images, profiles, and spectra were compared for different phantoms and different irradiation angles. The proposed analytical method simulates accurate scatter images up to 1000 times faster than MC. Minor differences between MC and analytical simulated images are attributed to limitations in the isotropic superposition/convolution algorithm used to analytically model multiple-order scattering. For a detector placed at 90° relative to the treatment beam, the simulated scattered photon energy spectrum peaks at 140–220 keV, and 40–50% of the photons are the result of multiple scattering. The high energy photons originate at the beam entrance. Increasing the angle between source and detector increases the average energy of the collected photons and decreases the relative contribution of multiple scattered photons. Multiple scattered photons cause blurring in the image. For an ideal 5 mm diameter pinhole collimator placed 18.5 cm from the isocenter, 10 cGy of deposited dose (2 Hz imaging rate for 1200 MU min−1 treatment delivery) is expected to generate an average 1000 photons per mm2 at the detector. For the considered lung tumor CT phantom, the contrast is high enough to clearly identify the lung tumor in the scatter image. Increasing the treatment beam size perpendicular to the detector plane decreases the contrast, although the scatter subject contrast is expected to be greater than the megavoltage transmission image contrast. With the analytical method, real-time tumor tracking may be possible through comparison of simulated and acquired patient images.
Three‐dimensional measurement arrays are an efficient means of acquiring a distribution of data for patient plan delivery QA. However, the tie between plan integrity and traditional gamma‐based analysis of these data are not clear. This study explores the sensitivity of such analysis by creating errors in Helical Tomotherapy delivery and measuring the passing rates with an ArcCHECK cylindrical diode array. Errors were introduced in each of the couch speed, leaf open time, and gantry starting position in increasing magnitude while the resulting gamma passing rates were tabulated. The error size required to degrade the gamma passing rate to 90% or below was on average a 3% change in couch speed, 5° in gantry synchronization, or a 5 ms in leaf closing speed for a 3%/3 mm Van Dyk gamma analysis. This varied with plan type, with prostate plans exhibiting less sensitivity than head and neck plans and with gamma analysis criteria, but in all cases the error magnitudes were large compared to actual machine tolerances. These findings suggest that the sensitivity of ArcCHECK‐based gamma analysis to single‐mode errors in tomotherapy plans is dependent upon plan and analysis type and at traditional passing thresholds unable to detect small defects in the plan.PACS number: 87.55.Qr
Purpose: A novel scatter imaging modality is developed and its feasibility for image‐guided radiation therapy (IGRT) during stereotactic body radiation therapy (SBRT) for lung cancer patients is assessed using analytic and Monte Carlo models as well as experimental testing. Methods: During treatment, incident radiation interacts and scatters from within the patient. The presented methodology forms an image of patient anatomy from the scattered radiation for real‐time localization of the treatment target. A radiographic flat panel‐based pinhole camera provides spatial information regarding the origin of detected scattered radiation. An analytical model is developed, which provides a mathematical formalism for describing the scatter imaging system. Experimental scatter images are acquired by irradiating an object using a Varian TrueBeam accelerator. The differentiation between tissue types is investigated by imaging simple objects of known compositions (water, lung, and cortical bone equivalent). A lung tumor phantom, simulating materials and geometry encountered during lung SBRT treatments, is fabricated and imaged to investigate image quality for various quantities of delivered radiation. Monte Carlo N‐Particle (MCNP) code is used for validation and testing by simulating scatter image formation using the experimental pinhole camera setup. Results: Analytical calculations, MCNP simulations, and experimental results when imaging the water, lung, and cortical bone equivalent objects show close agreement, thus validating the proposed models and demonstrating that scatter imaging differentiates these materials well. Lung tumor phantom images have sufficient contrast‐to‐noise ratio (CNR) to clearly distinguish tumor from surrounding lung tissue. CNR=4.1 and CNR=29.1 for 10MU and 5000MU images (equivalent to 0.5 and 250 second images), respectively. Conclusion: Lung SBRT provides favorable treatment outcomes, but depends on accurate target localization. A comprehensive approach, employing multiple simulation techniques and experiments, is taken to demonstrate the feasibility of a novel scatter imaging modality for the necessary real‐time image guidance.
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