J Lu

Four‐dimensional cone beam CT with adaptive gantry rotation and adaptive data sampling

We have developed a new four-dimensional cone beam CT (4D-CBCT) on a Varian image-guided radiation therapy system, which has radiation therapy treatment and cone beam CT imaging capabilities. We adapted the speed of gantry rotation time of the CBCT to the average breath cycle of the patient to maintain the same level of image quality and adjusted the data sampling frequency to keep a similar level of radiation exposure to the patient. Our design utilized the real-time positioning and monitoring system to record the respiratory signal of the patient during the acquisition of the CBCT data. We used the full-fan bowtie filter during data acquisition, acquired the projection data over 200 deg of gantry rotation, and reconstructed the images with a half-scan cone beam reconstruction. The scan time for a 200-deg gantry rotation per patient ranged from 3.3 to 6.6 min for the average breath cycle of 3-6 s. The radiation dose of the 4D-CBCT was about 1-2 times the radiation dose of the 4D-CT on a multislice CT scanner. We evaluated the 4D-CBCT in scanning, data processing and image quality with phantom studies. We demonstrated the clinical applicability of the 4D-CBCT and compared the 4D-CBCT and the 4D-CT scans in four patient studies. The contrast-to-noise ratio of the 4D-CT was 2.8-3.5 times of the contrast-to-noise ratio of the 4D-CBCT in the four patient studies.

TH‐D‐351‐04: Cone Beam CT Beam Hardening and Scatter Preprocessing for Improved Image Quality in Image‐Guided Adaptive Radiation Therapy

Purpose: To improve cone beam CT(CBCT)image quality in terms of CT number uniformity and accuracy to better support key image‐guidedadaptive radiation therapy tasks such as intensity‐driven deformable image registration and adaptive treatment planning.Method and Materials: Subtractive scatter corrections to Varian on‐board imager (OBI) CBCT projections utilized Monte Carlo simulated scatter profiles based upon the known phantom geometry. A first‐order water linearization correction was developed based upon the measured x‐ray beam central ray spectrum with mathematical spectral correction for the bowtie filter thickness associated with each detector pixel. Projections corrected for scatter and beam hardening and further corrected using Varians scatter normalization phantom, were reconstructed with an in‐house FDK reconstruction engine. The preprocessing algorithm was applied to both half‐fan and full‐fan projection sets with and without the bowtie filter. Results:CBCTimages corrected with the described preprocessing method showed improved CT number uniformity and reduction of the notorious CBCT cupping artifact. For a 20 cm diameter water phantom, the cupping artifact was reduced from about 15% to within 2%. Conclusion: Model‐based scatter and beam‐hardening preprocessing procedures improve the on‐board CBCTimage quality, improving its utility for image‐guidedadaptive radiation therapy.Conflict of Interest: This work was supported by NIH P01 CA116602 and a grant from Varian Medical Systems.

TH-D-351-06: Comparison Between 2D Monte Carlo Modeled and Experimental Cone-Beam CT X-Ray Projections

Purpose: Fast and accurate modeling of cone‐beam CT(CBCT) x‐ray projection data can improve cone‐beam CT(CBCT)image quality either by conditioning projection data prior to image reconstruction or by supporting rigorous comparative simulation studies of competing image reconstruction and processing algorithms. In this study, we compare Monte Carlo‐ computed x‐ray projections with projections experimentally acquired from our Varian Trilogy CBCTimaging system for phantoms of known design. Method and Materials: Our recently developed Monte Carlo photon‐transport code, PTRAN, was used to compute primary and scatter projections for cylindrical phantoms of known diameter (CatPhan and NA model 76‐410) with and without bow‐tie filter and antiscatter grid for both full‐ and half‐fan geometries. The simulations were based upon measured 120 kVp spectra, beam profiles, and flat‐panel detector (4030CB) point‐spread functions. The beam‐stop array method was used to acquire scatter and SPR distributions from the OBI images. The biasing of scatter measurements due to the long detector PSF tails was corrected either by a lead mask or by deconvolution. Computed projections were compared to flat‐ and dark‐field corrected 4030CB images.Results: The simulated primary profiles agree with experiment within 3%, while the simulated scatter profiles agree within 8–10%. Both PSF measurements and mask measurements indicate that scatter radiation values can be biased by as much as 7% detector PSF tails. Conclusion: In agreement with the literature, the difference between simulated and measured projection data is of the order of 6–8%. Higher accuracy can be achieved mainly by improving the beam modeling and correcting the non linearities induced by the detector PSF. This project was supported in part by grants from Varian Medical Systems and NCI (R01 CA 75371).

Optimization of 4D cone-beam CT: evaluation of streaking artifacts and noise with various simulated gantry rotation speeds

We have investigated the relationship between scan parameters and image quality in fourdimensional cone-beam computed tomography (4D-CBCT) performed with a flat panel imager in image-guided radiotherapy. We have determined upper bounds on scan time while achieving objective thresholds of image quality, namely in noise performance and minimization of view aliasing artifacts. A slow-gantry design for 4D-CBCT was used, in which we slow down clinical linear accelerator gantry speed from the typical 1.0 rpm speed to 0.1 - 0.125 rpm, to ensure the projection angle spacing between two consecutive respiratory cycles is less than 3 degrees. A respiratory monitoring device was used to record the respiratory signal for temporal correlation of the projection data for 4D-CBCT image reconstruction. Four patient data sets were acquired. Reference images were reconstructed with all projection data and were compared with images reconstructed with 50%, 33% and 20% of the projection data. These three partial data reconstructions are simulations of scans with shorter acquisition times. The main image degradations in the short scan simulation image sets are streaking artifacts and poor signal to noise ratio, both caused by sparse projection sampling. The amount of streaking artifacts and SNR in each image set is quantified. By allowing some streaking artifacts and not compromising the assessment of tumor motion, we produce images that suggest that a reduction in scan time from 3 to 6 min to approximately 2 min may be possible, making 4D-CBCT feasible in a clinical setting.

TH‐D‐BRC‐06: The Investigation and Correction of a Bowtie‐Related Cone‐Beam CT Circular Band Artifact

Purpose: In the course of developing projection‐space preprocessing algorithms for improving on‐board CBCTCT number accuracy and uniformity, a persistent, prominent circular band artifact (CBA) with asymmetric illumination shadows was discovered. The CBA remain unchanged even after applying beam‐hardening, scatter subtraction, and veiling glare corrections to Varian OBI full‐fan projection data but only when a bow‐tie filter is used. This study investigates the causes and correction strategies of the CBA. Method and Materials:CBCTimages were acquired, preprocessed, and reconstructed with an in‐house FDK engine for phantoms of different diameters and locations relative to isocenter, on several OBI systems, to characterize CBA behavior and to form hypotheses as to its origin. Numerical simulations were used to evaluate all hypothesized contributing factors, as assessed by the necessary experimental measurements. A custom calibration was performed to identify the dependence of kV source location and flat‐panel detector pose as a function of gantry angle. Different correction approaches were tried on both synthetic and measured datasets, including gantry‐angle‐dependent normalization, full‐ and partial kV beam geometry calibrations, and empirical cancellation. The interplay between the CBA corrections and scatter and beam hardening corrections was also studied. Results: The CBA had a diameter of about 15 cm, was centered at the isocenter, and had similar asymmetric illumination, for all phantom dimensions, locations, and machines, and was reproducible over time. It appeared only when the bowtie filter was used. Simulations and experimental studies identified that a combination of geometric wobble and the bowtie filter slope caused the artifact. Gantry‐angle dependent calibrations of normalization were sufficient for about 80% CBA mitigation, but that complete elimination required gantry‐angle dependent beam‐hardening corrections. Conclusion:CBCT geometric wobble with the presence of bowtie filter could cause a circular band artifact. Supported by NIH P01 CA116602 and a grant from Varian Medical Systems.

SU‐GG‐J‐137: New Prospective Gated CBCT

Purpose: Design and feasibility of a new prospective gated CBCT for gated treatment IGRT and body SRT treatments. Method and Materials: 4D cone beam CT (4D CBCT) can be used to assess tumor motion for IGRT and body SRT treatments. However, acquisition time for 4D CBCT is normally longer than 3 minutes. For gated treatments, it is sufficient to measure the tumor motion in the range of the gate. We propose using prospective gated CBCT for assessing the tumor motion for the gated treatment to save time in CBCTdata acquisition. The same monitoring system (RPM, Varian Medical Systems, Palo Alto, CA) is used to gate the radiotherapy treatment and the CBCT acquisition. Both x‐ray and gantry rotation start when the condition of gating is met such as the breathing amplitude falls in the threshold setting for therapy. The patient can be coached with audio prompting during data acquisition and treatment. The acquisition time is between 1 to 2 min and can be accelerated with a faster gantry rotation. Only one CBCT reconstruction is needed. We applied this approach on a dynamic phantom with 30% duty cycle of beam on time. Results: The gated acquisition was feasible and the image acquired with the gated acquisition of the phantom demonstrated the gated image of the phantom with the specified duty cycle. Conclusion: We have designed a new prospective CBCT and demonstrated its feasibility with a dynamic phantom. This system uses the same thresholds for imaging and treatment demonstrating position and residual motion within the gate on each day. The prospective CBCT is shorter in acquisition time than 4D CBCT. This system can be applied for improving the quality of gated treatment IGRT and body SRT treatments.

MO‐F‐BRA‐02: Evaluation of 4D CT to 4D Cone‐Beam CT Deformable Image Registration for Lung Cancer Adaptive Radiation Therapy

PURPOSE To evaluate two deformable image registration (DIR) algorithms for the purpose of contour mapping to support image guided adaptive radiotherapy (IGART) with 4D cone beam CT (4DCBCT). METHODS Eleven locally advanced non-small cell lung cancer (NSCLC) patients underwent one planning 4D fan- beam CT (4DFBCT) and seven weekly 4DCBCT scans. Gross tumor volume (GTV) and carina were delineated by a physician in all 4D images. For day to day registration, the end of inspiration 4DFBCT phase was deformably registered to the corresponding phase in each 4DCBCT image. For phase to phase registration, the end of inspiration phase from each 4D image was registered to end of expiration phase. The delineated contours were warped using the resulting transforms and compared to the manual contours through Dice similarity coefficient (DSC), false positive and false negative indices, and, for carina, target registration error (TRE). Two DIR algorithms were tested: 1) small deformation, inverse consistent linear elastic (SICLE) algorithm and 2) Insight Toolkit diffeomorphic demons (DEMONS). RESULTS For day to day registrations, the mean DSC was 0.59 ± 0.16 after rigid registration, 0.72 ± 0.13 with SICLE and to 0.66 ± 0.18 with DEMONS. SICLE and DEMONS reduced TRE to 4.1 ± 2.1 mm and 5.8 ± 3.7 mm respectively, from 6.2 ± 3.5 mm; and reduced false positive index to 0.27 and 0.26 respectively from 0.46. Registration with the cone beam as the fixed image resulted in higher DSC than with the fan beam as fixed (p < 0.001). SICLE and DEMONS increased the DSC on average by 10.0% and 8.0% and reduced TRE by 2.8 mm and 2.9 mm respectively for phase to phase DIR. CONCLUSIONS DIR achieved more congruent mapping of target structures to delineations than rigid registration alone, although DIR performance varied with algorithm and patient. This work was supported by National Cancer Institute Grant No. P01 CA 116602.

SU‐E‐J‐159: Correlation of Respiration‐Induced Motion of an External Surrogate and Implanted Internal Markers

Purpose: To investigate the correlation between the respiratory motion of implanted internal markers (IM) and external RPM traces for lungcancer patients in dynamic imaging. Methods: Under an IRB‐approved research protocol, 3 patients with VISICOIL marker (10 mm long) implants near/in their lungtumor were scanned with a daily single‐slow gantry rotation arc 4D‐CBCT acquisition. The Varian Real‐time Position Management system (RPM) was used as an external respiratory motion surrogate, with the marker block placed on the patient abdominal surface near the diaphragm. The IM motion was segmented in all 2D projections with an in‐house built Matlab program. The positions in the 3D spatial domain of the markers were extracted to (LR: left‐right, CC: cranial‐caudal, AP: anterior‐posterior). A Pearson‐type auto‐correlation function of the RPM AP trace and cross‐ correlation functions between RPM AP motion and the IM motions in three orthogonal directions was used to analyze the time series. Results: Our data shows that there is a strong positive correlation between the RPM AP motion and the IM motion in the CC direction. The correlation between the external motion and the IM motions in LR and AP directions varied from fraction to fraction. In addition, phase shift is observed in LR and AP directions. Different implanted markers in the same patient presented the very similar correlations, especially in the CC direction. This result suggests that multiple implanted markers can be used to provide supplementary information of the tumor motion. When the patient coughs during their respiratory cycle, internal motion and external motion may become uncorrelated. Conclusions: The RPM respiratory trace provides a good surrogate of the internal respiratory motion in the CC direction when the patient maintains a normal breathing pattern. Supported by NIH grant P01 CA 116602.

SU‐GG‐J‐31: Simultaneous Estimation of Beam Geometry and Radiation/Imaging Isocenter Coincidence in Cone‐Beam CT‐Guided Radiation Therapy

Purpose: To simultaneously characterize the geometric pose of an on‐board CBCTimaging system and measure the relative positions of the imaging and treatment machine radiation isocenters. Method and Materials: The method is based on an existing technique (Cho, et al, Med Phys 32(4), 968), which utilizes CBCT projections of a fiducial phantom to calculate the source and detector positions and orientations as a function of gantry angle. The algorithm was modified to localize the phantom pose relative to the kV source trajectory, and to transform beam geometry parameters from the phantom to imaging isocenter coordinate system. The method was applied to both CBCT and MV EPID projections acquired during the same imaging session without moving the phantom. The calculated positions of the phantom relative to the CBCT and EPID projection isocenters provide the relative displacement of the imaging and treatment isocenters. Two additional CBCTimaging experiments were then performed with the phantom displaced known distances. Results: Calculated CBCT geometric parameters were consistent over the three experiments, even with the phantom displaced from the machine isocenter by 10mm or misaligned with the gantry rotation axis by 1°. The CBCT beam parameters were close to nominal with small variations with gantry angle, with the exception of a 1 mm detector offset parallel to the gantry axis. Displacement of the CBCTimaging isocenter from the treatment isocenter was found to be (0.07, 1.24, 0.05 mm) in the (L‐R, A‐P, S‐I) direction. Conclusion: The methods output can assist in mitigation of geometric distortion‐related CBCTimage artifacts and simultaneously provides the imaging‐to‐treatment isocenter offset. Supported by NCI Grant P01 CA 116602

WE‐D‐204B‐09: Interfraction Variability of Tumor Motion Trajectory from Serial 4D Cone‐Beam CT Imaging during Audio‐Visual Biofeedback

Purpose: To quantify interfraction variations in position, volume, and intrafraction breathing motion trajectory of lungtumors and critical structures with 4DCT and 4D cone beam CT (4D CBCT)images, for patients undergoing audiovisual biofeedback.Method and Materials: A pretreatment 4D fan beam CT (4DCT) and 35–40 daily 4D CBCTs were acquired daily throughout the treatment for 7 non‐small cell lungcancer patients. The tumor, esophagus, and trachea were contoured for all 10 phases of each CT. Each phase‐specific image was registered manually on bony anatomy to the end‐inhalation phase image from the 4DCT. The centroid and volume of each structure were calculated for each phase, and used to quantify the variability of the tumor and critical structure locations during each fraction. The tumor volume, relative to its end‐inhalation volume on 4DCT, was calculated for end‐inhalation and end‐exhalation phases for each fraction. The mean position of each organ, relative to the 4DCT, was calculated for each 4D CBCT scan. Results: Analysis has been completed for one patient to date consisting of 27 fractions, consisting of 7 4D CBCTs. Over the course of treatment, the tumor volume at end‐inhalation decreased by 31%. The systematic (random) error in mean tumor position was found to be 0.12cm (0.14 cm), 0.29cm (0.12 cm), and 0.31cm (0.62 cm) in the mediolateral, anterior‐posterior, and superior inferior directions respectively. These were large in comparison to the average range of tumor motion, which was 0.09cm, 0.21cm, 0.25cm in the corresponding axes. The corresponding ranges of motion over the treatment course, were 0.06–0.13cm, 0.14–0.26cm, and 0.12–0.42cm. Conclusion: For this patient, the interfractional variation in mean tumor position was the dominant variation with fraction‐to‐fraction changes as large as 2 cm. Audiovisual biofeedback did not adequately control these baseline variations. Supported by Grant P01 CA 116602