M.A. Hoggarth

Prospective Evaluation of Dual-Energy Imaging in Patients Undergoing Image Guided Radiation Therapy for Lung Cancer: Initial Clinical Results

PURPOSE A prospective feasibility study was conducted to investigate the utility of dual-energy (DE) imaging compared to conventional x-ray imaging for patients undergoing kV-based image guided radiation therapy (IGRT) for lung cancer. METHODS AND MATERIALS An institutional review board-approved feasibility study enrolled patients with lung cancer undergoing IGRT and was initiated in September 2011. During daily setup, 2 sequential respiration-gated x-ray images were obtained using an on-board imager. Imaging was composed of 1 standard x-ray image at 120 kVp (1 mAs) and a second image obtained at 60 kVp (4 mAs). Weighted logarithmic subtraction of the 2 images was performed offline to create a soft tissue-selective DE image. Conventional and DE images were evaluated by measuring relative contrast and contrast-to-noise ratios (CNR) and also by comparing spatial localization, using both approaches. Imaging dose was assessed using a calibrated ion chamber. RESULTS To date, 10 patients with stage IA to IIIA lung cancer were enrolled and 57 DE images were analyzed. DE subtraction resulted in complete suppression of overlying bone in all 57 DE images, with an average improvement in relative contrast of 4.7 ± 3.3 over that of 120 kVp x-ray images (P<.0002). The improvement in relative contrast with DE imaging was seen for both smaller (gross tumor volume [GTV] ≤5 cc) and larger tumors (GTV >5 cc), with average relative contrast improvement ratios of 3.4 ± 4.1 and 5.4 ± 3.6, respectively. Moreover, the GTV was reliably localized in 95% of the DE images versus 74% of the single energy (SE images, (P=.004). Mean skin dose per DE image set was 0.44 ± 0.03 mGy versus 0.43 ± 0.03 mGy, using conventional kV imaging parameters. CONCLUSIONS Initial results of this feasibility study suggest that DE thoracic imaging may enhance tumor localization in lung cancer patients receiving kV-based IGRT without increasing imaging dose.

SU‐E‐J‐44: Dual Energy Subtraction Imaging to Improve Tumor Visibility at Oblique Angles

PURPOSE To characterize the contrast improvement of simulated tumors in an anthropomorphic phantom using Dual Energy (DE) subtraction with a clinical on-board imager (OBI) at oblique angles. METHODS An Alderson lung/chest anthropomorphic phantom with simulated tumors in the thoracic cavity was imaged using a sequential DE imaging methodology. High (120kVp) and low (60kVp) planar images were obtained in pairs every 100 in a full (3600) rotation using the OBI (Varian Medical Systems, Palo Alto, CA). Optimal mAs settings for DE component images were determined byvarying the x-ray exposure time, while maintaining a constant tube current. DE images were created to best suppress the bone overlaying the simulated tumors. Tumor visibility in DE images was quantified using the Contrast-to-Noise Ratio (CNR). The ratio of the CNR from the DE image relative to a single image (standard protocol) was evaluated as a function of gantry angle. RESULTS CNR was improved with DE imaging by an average ratio of 1.66 over all gantry angles. The greatest improvement occurred at gantry angles where the tumor was obstructed by the ribs alone. More modest improvements were observed where the tumor overlapped other soft tissue structures (such as the heart) or the dense spine, on a given projection. CONCLUSIONS This study illustrates the feasibility of performing DE imaging at oblique gantry angles using a clinical on-board imaging system. Incorporating DE imaging into clinical practice may allow for verification of tumor position at oblique gantry angles, and may facilitate the development of markerless motion tracking techniques. Supported by a grant from Varian Medical Systems.

SU‐E‐J‐91: FFT Based Medical Image Registration Using a Graphics Processing Unit (GPU)

PURPOSE To evaluate the efficiency gains obtained from using a Graphics Processing Unit (GPU) to perform a Fourier Transform (FT) based image registration. METHODS Fourier-based image registration involves obtaining the FT of the component images, and analyzing them in Fourier space to determine the translations and rotations of one image set relative to another. An important property of FT registration is that by enlarging the images (adding additional pixels), one can obtain translations and rotations with sub-pixel resolution. The expense, however, is an increased computational time. GPUs may decrease the computational time associated with FT image registration by taking advantage of their parallel architecture to perform matrix computations much more efficiently than a Central Processor Unit (CPU). In order to evaluate the computational gains produced by a GPU, images with known translational shifts were utilized. A program was written in the Interactive Data Language (IDL; Exelis, Boulder, CO) to performCPU-based calculations. Subsequently, the program was modified using GPU bindings (Tech-X, Boulder, CO) to perform GPU-based computation on the same system. Multiple image sizes were used, ranging from 256×256 to 2304×2304. The time required to complete the full algorithm by the CPU and GPU were benchmarked and the speed increase was defined as the ratio of the CPU-to-GPU computational time. RESULTS The ratio of the CPU-to- GPU time was greater than 1.0 for all images, which indicates the GPU is performing the algorithm faster than the CPU. The smallest improvement, a 1.21 ratio, was found with the smallest image size of 256×256, and the largest speedup, a 4.25 ratio, was observed with the largest image size of 2304×2304. CONCLUSIONS GPU programming resulted in a significant decrease in computational time associated with a FT image registration algorithm. The inclusion of the GPU may provide near real-time, sub-pixel registration capability.

TH‐E‐218‐02: Deformable Registration Techniques for Dual Energy Imaging in Clinical Radiotherapy

Purpose: To demonstrate a deformable registration algorithm to reduce cardiac and respiratory motion artifacts in planar dual energy (DE) subtraction images obtained using a clinical on‐board imaging (OBI) system. Methods: A Demons‐based deformable registration algorithm was developed to reduce motion artifacts between sequential planar x‐ray images obtained on the OBI. The algorithm was applied to paired (120 kVp and 60 kVp) chest x‐rays, deforming the low energy image to the high energy image. To test the algorithm, a total of 20‐paired scans were obtained from 6 lungcancer patients. All images were obtained using respiratory gating (RPM, Varian Medical Systems, Palo Alto, CA). In order to quantify the reduction in image artifacts, homologous landmarks were chosen using soft‐tissue features on both sets of images. Landmarks were placed throughout the images to examine both cardiac and respiratory motion. The root‐mean‐square (RMS) difference between the individual points was calculated both before and after application of deformable registration. Results: A total of 160 landmarks were evaluated. Measurement of the RMS distances between the landmarks in the high and low energy deformed images showed improvement in all sectors. For points with 2 mm RMS difference, the corresponding reduction was 64%. Qualitatively, DE images produced using Demons deformation showed fewer artifacts, and more defined tumor edges. Conclusions: The Demons algorithm reduced motion artifacts across all DE planar images. The greatest improvements were observed in regions near the diaphragm and the heart. In particular, artifacts due to cardiac motion showed the most improvement as these are not taken into account when performing respiratory gating. The iterative, matrix‐based algorithm would greatly benefit from integration of GPU parallel‐processing and will be implemented in future investigations. Supported by a grant from Varian Medical Systems.

SU‐E‐J‐93: Fourier Transform‐Based Medical Image Registration

PURPOSE To evaluate the use of a Fast Fourier Transform (FFT) based pattern-matching algorithm for two-dimensional translational and rotational medical image registration. METHODS The FFT pattern matching algorithm is based on the Fourier shift theorem. Briefly, image registration is accomplished by obtaining the Fourier Transform (FT) of two images, taking the normalized cross-correlation of the two FT, and performing an inverse FT on this correlation matrix. This results in a Dirchlet delta function that has a maximum value at a location corresponding to the translational shift between the two images. Rotational registration can also be achieved by performing this algorithm on the polar transformation of the FT images. The FT registration method was evaluated through the use of clinical images with induced translational and rotational shifts. RESULTS Over a range of induced shifts of +/-10 mm in both the x and y directions, and induced rotations of +/-10 degrees, all recovered rotations were within 0.1 degree of the induced rotation, and all recovered translations were within 0.5 mm of the induced translation. The computational time of the FT registration on a 1024×1024 image was approximately 2.23 sec. CONCLUSIONS An FFT based image registration algorithm is computationally efficient and provides a high degree of accuracy for two dimensional image registrations. The FFT registration approach provides a distinct analytical solution and does not rely on iterative methods to converge on a solution. In addition, the discrete nature of the FFT means that the accuracy of the solution is directly related to the size of the pixels in the images. The equivalent of sub-pixel registration can be achieved by simply resizing the image to a larger matrix (i.e. 512×512 to 1024×1024).

Dose-volume factors to select patient-specific image-guidance action thresholds in prostate cancer.

For radiation delivery tracking systems that monitor intrafraction prostate motion, generalized departmental threshold protocols may be used. The purpose of this study is to determine whether predefined action thresholds can be generally applied or if patient-specific action thresholds may be required. Software algorithms were developed in the MatLab (The Mathworks Inc., Natick, MA) software environment to simulate shifts of the patient structure set consisting of prostate, bladder, and rectum. These structures were shifted by +/- 10 mm in each direction in 1 mm increments to simulate displacements during treatment, without taking into consideration organ deformity. Dose-volume data at each shift were plotted and analyzed. A linear relationship was observed between planning dose-volume parameters and shifted dose-volume parameters. For a 5 mm anterior shift, it was observed that individual rectal V70 values increased by absolute magnitudes of 6–15%, dependent on the planning rectal V70 of each patient. Likewise, for a 5 mm inferior shift, individual bladder V70 values increased by 1–14%, dependent on planning bladder V70. This linear relationship was observed for all levels of shifts up to 10 mm. Since rectum and bladder dose-volume changes due to patient shifts are dependent on dose-volume parameters, this study suggests that patient-specific action thresholds may be necessary.