Dual kV Research Articles

Iodine maps derived from sparse-view kV-switching dual-energy CT equipped with a deep learning reconstruction for diagnosis of hepatocellular carcinoma

Deep learning-based spectral CT imaging (DL-SCTI) is a novel type of fast kilovolt-switching dual-energy CT equipped with a cascaded deep-learning reconstruction which completes the views missing in the sinogram space and improves the image quality in the image space because it uses deep convolutional neural networks trained on fully sampled dual-energy data acquired via dual kV rotations. We investigated the clinical utility of iodine maps generated from DL-SCTI scans for assessing hepatocellular carcinoma (HCC). In the clinical study, dynamic DL-SCTI scans (tube voltage 135 and 80 kV) were acquired in 52 patients with hypervascular HCCs whose vascularity was confirmed by CT during hepatic arteriography. Virtual monochromatic 70 keV images served as the reference images. Iodine maps were reconstructed using three-material decomposition (fat, healthy liver tissue, iodine). A radiologist calculated the contrast-to-noise ratio (CNR) during the hepatic arterial phase (CNRa) and the equilibrium phase (CNRe). In the phantom study, DL-SCTI scans (tube voltage 135 and 80 kV) were acquired to assess the accuracy of iodine maps; the iodine concentration was known. The CNRa was significantly higher on the iodine maps than on 70 keV images (p < 0.01). The CNRe was significantly higher on 70 keV images than on iodine maps (p < 0.01). The estimated iodine concentration derived from DL-SCTI scans in the phantom study was highly correlated with the known iodine concentration. It was underestimated in small-diameter modules and in large-diameter modules with an iodine concentration of less than 2.0 mgI/ml. Iodine maps generated from DL-SCTI scans can improve the CNR for HCCs during hepatic arterial phase but not during equilibrium phase in comparison with virtual monochromatic 70 keV images. Also, when the lesion is small or the iodine concentration is low, iodine quantification may result in underestimation.

SU‐C‐103‐04: 3D Tumor Tracking On Vero

Purpose: The unique gimbal system of the BrainLAB Vero allows the treatment head to pivot in two dimensions for tumor tracking. In order to utilize this feature, it is crucial to directly monitor tumor motion during treatment. We present a 3D tumor motion monitoring method incorporating the orthogonal kV imaging subsystems on Vero. Methods: An anthropomorphic phantom was used in this study. A lung tumor and two BBs were driven in a regular 3D sine motion pattern using a programmable 4D motion platform. 4D CT scans were performed and the tumor was contoured at the end of inhale phase. Stereoscopic kV images were acquired at a rate of 5 fps. A spherical template was created to match the projections of BBs. Two sets of DRRs were created: one DRR set containing the tumor only and the other set containing the full anatomy without the tumor. They were combined to produce composite DRRs and their individual positions were optimized by comparing of the composite DRRs with acquired kV images. 3D tumor and BB positions were then determined from the results of stereo kV x‐rays. Results: Dual orthogonal kV images were acquired with the MV beam at gantry angles of 0 and 45 degrees. This produced approximately 640 images with corresponding kV imaging angles of ‐ 315, 45, 0, and 90 degrees. The tumor and the BBs were identified on every kV image. Both 2D and 3D positions were compared with the programmed positions. The maximum differences were 1 mm. Conclusion: The dual kV imaging systems on Vero, used in conjunction with our tumor tracking algorithm, are capable of marker or marker‐less lung tumor tracking. This technique may be applied to track tumors in real‐time to provide direct tumor motion information for compensation of tumor motion throughout the course of radiotherapy.

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.

Initial application of a geometric QA tool for integrated MV and kV imaging systems on three image guided radiotherapy systems

Several linacs with integrated kilovoltage (kV) imaging have been developed for delivery of image guided radiation therapy (IGRT). High geometric accuracy and coincidence of kV imaging systems and megavoltage (MV) beam delivery are essential for successful image guidance. A geometric QA tool has been adapted for routine QA for evaluating and characterizing the geometric accuracy of kV and MV cone-beam imaging systems. The purpose of this work is to demonstrate the application of methodology to routine QA across three IGRT-dedicated linac platforms. It has been applied to a Varian Trilogy (Varian Medical Systems, Palo Alto, CA), an Elekta SynergyS (Elekta, Stockholm, Sweden), and a Brainlab Vero (Brainlab AG, Feldkirchen, Germany). Both the Trilogy and SynergyS linacs are equipped with a retractable kV x-ray tube and a flat panel detector. The Vero utilizes a rotating, rigid ring structure integrating a MV x-ray head mounted on orthogonal gimbals, an electronic portal imaging device (EPID), two kV x-ray tubes, and two fixed flat panel detectors. This dual kV imaging system provides orthogonal radiographs, CBCT images, and real-time fluoroscopic monitoring. Two QA phantoms were built to suit different field sizes. Projection images of a QA phantom were acquired using MV and kV imaging systems at a series of gantry angles. Software developed for this study was used to analyze the projection images and calculate nine geometric parameters for each projection. The Trilogy was characterized five times over one year, while the SynergyS was characterized four times and the Vero once. Over 6500 individual projections were acquired and analyzed. Quantitative geometric parameters of both MV and kV imaging systems, as well as the isocenter consistency of the imaging systems, were successfully evaluated. A geometric tool has been successfully implemented for calibration and QA of integrated kV and MV across a variety of radiotherapy platforms. X-ray source angle deviations up to 0.8 degrees, and detector center offsets up to 3 mm, were observed for three linacs, with the exception of the Vero, for which a significant center offset of one kV detector (prior to machine commissioning) was observed. In contrast, the gimbal-based MV source positioning of the Vero demonstrated differences between observed and expected source positions of less than 0.2 mm, both with and without gimbal rotation. This initial application of this geometric QA tool shows promise as a universal, independent tool for quantitative evaluation of geometric accuracies of both MV and integrated kV imaging systems across a range of platforms. It provides nine geometric parameters of any imaging system at every gantry angle as well as the isocenter coincidence of the MV and kV image systems.

TH-D-303A-02: Correction Strategy to Overcome Non-Random Target Motions for Hypofractionated Spine Body Radiotherapy

Purpose: Non‐random target motions have been reported for hypofractionated spine stereotactic body radiotherapy(SBRT), largely due to prolonged treatment delivery as compared to conventional radiotherapy. In this study, we aim to develop an adaptive correction strategy to overcome such non‐random target motions. Method and Materials: Intra‐fraction target motions of more than 200 treatment sessions were analyzed. These target motions were detected using an in‐room dual kV x‐ray imagingsystem. Non‐random target motions was characterized in six degree of freedom (DOF) that included translations (x‐, y‐, z‐ shifts) and rotations (roll, yaw, pitch). Based on the observed incidence and motion characteristics, a correction strategy based on periodic interventions (e.g., via realigning the patient or the beams) was developed in order to correct the effects of such motions to an acceptable level. The population averaged time intervals for implementing the strategy were calculated for different treatment sites that included cervical, thoracic, and lumbar‐sacral lesions. Results: Non‐random target motions were found to be present for every case studied regardless of target locations. Cervical spine targets were found to possess the highest incidences of non‐random target motions as compared to other sites (p<0.0001). The correction strategy employing periodic intervention was found to be effective in compensating the observed target motions. The average time intervals required to maintain the target motions to within 1 mm in translation or 1 degree in rotation were 5.5 min, 5.9 min, and 7.1 min for cervical, thoracic, and lumbar‐sacral lesions, respectively. Conclusion: Interventions of approximately every 5–8 minutes or less are warranted in overcoming non‐random target motions in protracted spine SBRT treatments.

SU‐FF‐J‐75: High Performance Dual KV &amp; MV Imaging with One Detector

Purpose: Recent developments in Adaptive Radiation Therapy (ART) leverage MV and kV X‐ray imaging to acquire patient images in treatment position. We have developed a kV X‐ray imaging system, in line with the MV treatment beam, which enables us to acquire: (i) 2D kV X‐ray images (single acquisitions and fluoroscopy) simultaneously with the MV treatment, (ii) 3D tomographic kV X‐ray images, and (iii) MV beam pattern and profile (for entrance dosimetry). Our imaging system utilizes a detector with wide dynamic range allowing us to achieve these technically challenging objectives. Methods and Materials: In the in‐line imaging system, the kV source is opposite to the linear accelerator target with its focal point 100cm from the isocenter. During kV imaging, the kV detector is deployed close to the exit window of the MV beam, which adds to the intensity of the MV beam seen by the detector. Providing all the possible modes of imaging requires a large dynamic range for the flat panel imager. Two multiple gain detectors from Perkin Elmer Optoelectronics were evaluated (XRD1640AN &amp; XRD1621AN), their acquisition and interface parameters were defined. Results: kV CBCT imaging allows for 1% contrast in 4mm object to be visible with a dose of 3.4cGy (120kV) using 1mm slice thickness. Cross sectional images of a bar resolution phantom with a 5123 reconstruction allow for 0.9 lp/mm bars to be resolvable. Both detectors were evaluated for saturation at multiple MV energies. Conclusion: We have developed an imaging system that provides a challenging combination of high quality 2D KV imaging simultaneous with the MV treatment beam, 3D kV CBCT volumetric images, and the acquisition of the MV beam shape and profile (for entrance dosimetry). Conflict of Interest: Sponsored by Siemens.