bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐D‐202‐05: Evaluation of Four‐Dimensional Dose Reconstruction Under Breathing Irregularity
Authors: Yoon J , Yeo I , Jung J , Yi B 
Published: July 2016

Purpose:A method of four dimensional dose reconstruction (4D‐DR) using a cine mode of an EPID to determine the delivered 4D dose distribution has been suggested. This method, however, has not been tested under irregular breathing. This study investigated their effects on 4D‐DR.Methods:The 4D‐DR attempts to find the patient's breathing phase associated with each EPID image by comparing it to pre‐generated‐EPID‐quality DRRs of every breathing phases. A lung phantom with a tumor object (3cm diameter cylinder) on a moving platform was used for this test under conditions of amplitude reduction by 1/2 during (1) the entire delivery and (2) the duration when MLC blocked the tumor (hindering the phase determination). The dose delivered to the phantom was inversely reconstructed in the associated phase image of the phantom from each EPID image based on our documented inverse method of the 4D‐DR; the phase‐specific dose was integrated, generating the 4D reconstructed dose. Forward 4D Monte Carlo calculations were used as the 4D dose of a ground truth.Results:The reconstructed dose showed 98.1% gamma pass rate for 3%/3mm under regular breathing (i.e. no amplitude reduction) when compared with the forward 4D dose. When the irregular condition (#1) was adopted for treatment, the pass rate became 94.2%. The irregularity under the MLC block (#2) showed the pass rate of 91.3%. The two conditions did not affect the reconstruction noticeably in DVH plots of the tumor and lung‐tumor.Conclusion:As long as the extent of on‐treatment motion is smaller than that of the planning CT, the 4D‐DR can be done accurately. Otherwise, ontreatment 4D CT images are necessary.
SU‐D‐202‐06: Prospective Free‐Breathing CT Scan Selection for 5DCT
Authors: O'Connell D , Thomas D , Dou T , Yang L , Lamb J , Lewis J , Ruan D , Lee P , Low D 
Published: July 2016

Purpose:5DCT employs 25 fast helical scans and breathing surrogate monitoring to sample the respiratory cycle. Deformable image registration is used to fit a correspondence model between tissue motion and breathing amplitude and rate. The number of scans was chosen to ensure a high probability that tissues were imaged at sufficiently distinct breathing phases for accurate modeling of the entire breathing cycle. This work describes a method to prospectively select scan start times and reduce the protocol's number of scans from 25 to 6.Methods:Breathing traces from 7 patients imaged with 5DCT were used to simulate acquisition of 6 scans. Breathing phase was estimated using only observations from previous time points. Cross‐correlation between the representative breath and the most recent half period was continuously computed. If phase and cross‐correlation criteria were met, scans were triggered with a 2 second delay before acquisition. Blind acquisition, 6 scans separated by a fixed delay, was modeled at staggered start times. The spread of prospectively and blindly sampled breathing waveforms was characterized using a previously published objective function.Results:Prospectively selected scans ranked on average in the 84th percentile of objective function values obtained by blind acquisition at staggered start times for 7 patient breathing traces.Conclusion:A method to prospectively determine scan start times for 5DCT was developed and tested by simulating acquisition on patient breathing traces. The method is computationally inexpensive enough for real‐time implementation and would result in an imaging dose of less than one quarter of the current 5DCT protocol.
SU‐D‐202‐07: Clinical Applicability of An Optical‐Surface‐Imaging‐Based Technique for Spirometric Measurement, Breathing Pattern Monitoring and Body Drift Correction
Authors: Zhang S , Huang H , Wei J , Li G 
Published: July 2016

Purpose:To explore the capabilities of optical surface imaging (OSI) as a comprehensive tumor motion surrogate to provide dynamic spirometric measurements, breathing pattern monitoring and body positioning correction.Methods:OSI captures the moving surface of the torso with all respiration‐induced external motions in real time. Tidal volume (TV) and its time derivative (TV’, airflow) were measured based on the volume conservation rule within the pseudo‐closed torso system: torso volume change equals TV in reference to full exhalation. In addition, breathing pattern (BP=ΔVchest/TV), indicating TV distribution within the torso, was quantified using this OSI‐based technique. Moreover, slow body position changes were detected by OSI via surface image registration in every breathing cycle at full‐exhalation phases, which are most reproducible phases unless voluntary body shift occurs. Volume changes due to body shift out of the volume of interest (VOI) were calculated to correct TV baseline drifts. Real‐time OSI images captured in both high‐resolution and low‐resolution was applied for TV, TV’ and BP measurements and baseline drift correction. Eleven volunteers participated in the IRB‐approved protocol study and performed free‐breathing, belly‐breathing and chest‐breathing exercises during OSI image acquisition.Results:Small TV baseline shifts are often observed in OSI‐based spirometry measurement with an average rate of ∼0.4cc/s. Using surface registration among fullexhalation phases and volume calculation from the body shifts relative to the fixed VOI, 80–90% baseline drift on average is corrected in three breathing exercises. The baseline drift is a useful indication of patient body shift and can be effectively corrected. When reducing OSI resolution from high to low, image capture rate increases from 5Hz to 10Hz, while the TV measurement accuracy is retained.Conclusion:The OSI‐based spirometric technique provides multiple parameters for monitoring patient respirations and body shift. The spirometric measurements, BP monitoring, and body‐shift detection are useful for tumor motion surrogating.This study is in part supported by the NIH (U54CA137788/U54CA132378).
SU‐D‐207A‐03: Potential Role of BOLD MRI in Discrimination of Aggressive Tumor Habitat in Prostate Cancer
Authors: Ford J , Lopez C , Tschudi Y , Breto A , Padgett K , Pollack A , Stoyanova R 
Published: July 2016

Purpose:To determine whether blood oxygenation level dependent (BOLD) MRI signal measured in prostate cancer patients, in addition to quantitative diffusion and perfusion parameters from multiparametric (mp)MRI exams, can help discriminate aggressive and/or radioresistant lesions.Methods:Several ongoing clinical trials in our institution require mpMRI exam to determine eligibility (presence of identifiable tumor lesion on mpMRI) and prostate volumes for dose escalation. Upon consent, patients undergo fiducial markers placement and a T2*‐weighted imaging at the time of CT sim to facilitate the fusion. In a retrospective analysis eleven clinical trial patients were identified who had undergone mpMRI on GE 3T magnet, followed by T2*‐weighted imaging (time‐period mean±SD = 48±20 days) using a consistent protocol (gradient echo, TR/TE=30/11.8ms, flip angle=12, matrix=256×256×75, voxel size=1.25×1.25×2.5mm). ROIs for prostate tumor lesions were automatically determined using ADC threshold ≤1200 µm2/s. Although the MR protocol was not intended for BOLD analysis, we utilized the T2*‐weighted signal normalized to that in nearby muscle; likewise, T2‐weighted lesion signal was normalized to muscle, following rigid registration of the T2 to T2* images. The ratio of these normalized signals, T2*/T2, is a measure of BOLD effect in the prostate tumors. Perfusion parameters (Ktrans, ve, kep) were also calculated.Results:T2*/T2 (mean±SE) was found to be substantially lower for Gleason score (GS) 8&9 (0.82±0.04) compared to GS 7 (1.08±0.07). A k‐means cluster analysis of T2*/T2 versus kep = Ktrans/ve revealed two distinct clusters, one with higher T2*/T2 and lower kep, containing only GS 7 lesions, and another with lower T2*/T2 and higher kep, associated with tumor aggressiveness. This latter cluster contained all GS 8&9 lesions, as well as some GS 7.Conclusion:BOLD MRI, in addition to ADC and kep, may play a role (perhaps orthogonal to Gleason score) in identifying prostate lesions that would benefit from more aggressive radiotherapy.
SU‐D‐207A‐05: Investigating Sparse‐Sampled MRI for Motion Management in Thoracic Radiotherapy
Authors: Sabouri P , Arai T , Sawant A 
Published: July 2016

Purpose:Sparse sampling and reconstruction‐based MRI techniques represent an attractive strategy to achieve sufficiently high image acquisition speed while maintaining image quality for the task of radiotherapy guidance. In this study, we examine rapid dynamic MRI using a sparse sampling sequence k‐t BLAST in capturing motion‐induced, cycle‐to‐cycle variations in tumor position. We investigate the utility of long‐term MRI‐based motion monitoring as a means of better characterizing respiration‐induced tumor motion compared to a single‐cycle 4DCT.Methods:An MRI‐compatible, programmable, deformable lung motion phantom with eleven 1.5 ml water marker tubes was placed inside a 3.0 T whole‐body MR scanner (Philips Ingenia). The phantom was programmed with 10 lung tumor motion traces previously recorded using the Synchrony system. 2D+t image sequences of a coronal slice were acquired using a balanced‐SSFP sequence combined with k‐t BLAST (accn=3, resolution=0.66×0.66×5 mm3; acquisition time = 110 ms/slice). kV fluoroscopic (ground truth) and 4DCT imaging was performed with the same phantom setup and motion trajectories. Marker positions in all three modalities were segmented and tracked using an opensource deformable image registration package, NiftyReg.Results:Marker trajectories obtained from rapid MRI exhibited <1 mm error compared to kv Fluoro trajectories in the presence of complex motion including baseline shifts and changes in respiratory amplitude, indicating the ability of MRI to monitor motion with adequate geometric fidelity for the purpose of radiotherapy guidance. In contrast, the trajectory derived from 4DCT exhibited significant errors up to 6 mm due to cycle‐to‐cycle variations and baseline shifts. Consequently, 4DCT was found to underestimate the range of marker motion by as much as 50%.Conclusion:Dynamic MRI is a promising tool for radiotherapy motion management as it permits for longterm, dose‐free, soft‐tissue‐based monitoring of motion, yielding richer and more accurate information about tumor position and motion range compared to the current state‐of‐the‐art, 4DCT.This work was partially supported through research funding from National Institutes of Health (R01CA169102).
SU‐D‐207A‐06: Pediatric Abdominal Organ Motion Quantified Via a Novel 4D MRI Method
Authors: Uh J , Krasin MJ , Lucas JT , Tinkle C , Merchant TE , Hua C 
Published: July 2016

Purpose:To develop a 4D MRI method for assessing respiration‐induced abdominal organ motion in children receiving radiation therapy.Methods:A 4D MRI using internal image‐based respiratory surrogate has been developed and implemented on a clinical scanner (1.5T Siemens Avanto). Ten patients (younger group: N=6, 2–5 years, anesthetized; older group: N=4, 11–15 years) with neuroblastoma, Wilm's tumor rhabdomyosarcoma, or desmoplastic small round cell tumor received free breathing 4D MRI scans for treatment planning. Coronal image slices of the entire abdomen were retrospectively constructed in 10 respiratory phases. A B‐spline deformable registration (Metz et al. 2011) was performed on 4D datasets to automatically derive motion trajectories of selected anatomical landmarks, including the dome and the center of the liver, and the superior edges of kidneys and spleen. The extents of the motion in three dimensions (anteroposterior, AP; mediolateral, ML; superoinferior, SI) and the correlations between organ motion trajectories were quantified.Results:The 4D MRI scans were successfully performed in <20 minutes for all patients without the use of any external device. Organ motion extents were larger in adolescents (kidneys: 3–13 mm SI, liver and spleen: 6–18 mm SI) than in younger children (kidneys:<3mm in all directions; liver and spleen: 1–8 mm SI, 1–5 mm ML and AP). The magnitude of respiratory motion in some adolescents may warrant special motion management. Motion trajectories were not synchronized across selected anatomical landmarks, particularly in the ML and AP directions, indicating inter‐ and intra‐organ variations of the respiratory‐induced motion.Conclusion:The developed 4D MRI acquisition and motion analysis methods provide a non‐ionizing, non‐invasive approach to automatically measure the organ motion trajectory in the pediatric abdomen. It is useful for defining ITV and PRV, monitoring changes in target motion patterns during the treatment course, and studying interplay effects in proton scanning.
SU‐D‐206‐01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi‐GPU Platform
Authors: Li B , Tian Z , Zhou L , Jiang S , Jia X 
Published: July 2016

Purpose:While compressed sensing‐based cone‐beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high‐quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi‐GPU platform for improved computational efficiency.Methods:Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subject to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom.Result:Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi‐GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction.Conclusion:We have developed a consensus ADMM‐based CBCT reconstruction method which enabled performing reconstruction on a multi‐GPU platform. The achieved efficiency made this method clinically attractive.
SU‐D‐206‐02: Evaluation of Partial Storage of the System Matrix for Cone Beam Computed Tomography Using a GPU Platform
Authors: Matenine D , Cote G , Mascolo‐Fortin J , Goussard Y , Despres P 
Published: July 2016

Purpose:Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersections between the photons’ trajectories and the object, also called ray‐tracing or system matrix computation. This work evaluates different ways to store the system matrix, aiming to reconstruct dense image grids in reasonable time.Methods:We propose an optimized implementation of the Siddon's algorithm using graphics processing units (GPUs) with a novel data storage scheme. The algorithm computes a part of the system matrix on demand, typically, for one projection angle. The proposed method was enhanced with accelerating options: storage of larger subsets of the system matrix, systematic reuse of data via geometric symmetries, an arithmetic‐rich parallel code and code configuration via machine learning. It was tested on geometries mimicking a cone beam CT acquisition of a human head. To realistically assess the execution time, the ray‐tracing routines were integrated into a regularized Poisson‐based reconstruction algorithm. The proposed scheme was also compared to a different approach, where the system matrix is fully pre‐computed and loaded at reconstruction time.Results:Fast ray‐tracing of realistic acquisition geometries, which often lack spatial symmetry properties, was enabled via the proposed method. Ray‐tracing interleaved with projection and backprojection operations required significant additional time. In most cases, ray‐tracing was shown to use about 66 % of the total reconstruction time. In absolute terms, tracing times varied from 3.6 s to 7.5 min, depending on the problem size. The presence of geometrical symmetries allowed for non‐negligible ray‐tracing and reconstruction time reduction. Arithmetic‐rich parallel code and machine learning permitted a modest reconstruction time reduction, in the order of 1 %.Conclusion:Partial system matrix storage permitted the reconstruction of higher 3D image grid sizes and larger projection datasets at the cost of additional time, when compared to the fully pre‐computed approach.This work was supported in part by the Fonds de recherche du Quebec ‐ Nature et technologies (FRQ‐NT). The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council of Canada (Grant No. 432290).
SU‐D‐206‐04: Iterative CBCT Scatter Shading Correction Without Prior Information
Authors: Bai Y , Wu P , Mao T , Gong S , Wang J , Sheng K , Xie Y , Niu T 
Published: July 2016

Purpose:To estimate and remove the scatter contamination in the acquired projection of cone‐beam CT (CBCT), to suppress the shading artifacts and improve the image quality without prior information.Methods:The uncorrected CBCT images containing shading artifacts are reconstructed by applying the standard FDK algorithm on CBCT raw projections. The uncorrected image is then segmented to generate an initial template image. To estimate scatter signal, the differences are calculated by subtracting the simulated projections of the template image from the raw projections. Since scatter signals are dominantly continuous and low‐frequency in the projection domain, they are estimated by low‐pass filtering the difference signals and subtracted from the raw CBCT projections to achieve the scatter correction. Finally, the corrected CBCT image is reconstructed from the corrected projection data. Since an accurate template image is not readily segmented from the uncorrected CBCT image, the proposed scheme is iterated until the produced template is not altered.Results:The proposed scheme is evaluated on the Catphan©600 phantom data and CBCT images acquired from a pelvis patient. The result shows that shading artifacts have been effectively suppressed by the proposed method. Using multi‐detector CT (MDCT) images as reference, quantitative analysis is operated to measure the quality of corrected images. Compared to images without correction, the method proposed reduces the overall CT number error from over 200 HU to be less than 50 HU and can increase the spatial uniformity.Conclusion:An iterative strategy without relying on the prior information is proposed in this work to remove the shading artifacts due to scatter contamination in the projection domain. The method is evaluated in phantom and patient studies and the result shows that the image quality is remarkably improved. The proposed method is efficient and practical to address the poor image quality issue of CBCT images.This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High‐tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).
SU‐D‐206‐05: A Critical Look at CBCT‐Based Dose Calculation Accuracy as It Is Applied to Adaptive Radiotherapy
Authors: Bejarano Buele A , Sperling N , Parsai E 
Published: July 2016

Purpose:Cone‐beam CTs (CBCT) obtained from On‐Board Imaging Devices (OBI) are increasingly being used for dose calculation purposes in adaptive radiotherapy. Patient and target morphology are monitored and the treatment plan is updated using CBCT. Due to the difference in image acquisition parameters, dose calculated in a CBCT can differ from planned dose. We evaluate the difference between dose calculation in kV CBCT and simulation CT, and the effect of HU‐density tables in dose discrepanciesMethods:HU values for various materials were obtained using a Catphan 504 phantom for a simulator CT (CTSIM) and two different OBI systems using three imaging protocols: Head, Thorax and Pelvis. HU‐density tables were created in the TPS for each OBI image protocol. Treatment plans were made on each Catphan 504 dataset and on the head, thorax and pelvis sections of an anthropomorphic phantom, with and without the respective HU‐density table. DVH information was compared among OBI systems and planning CT.Results:Dose calculations carried on the Catphan 504 CBCTs, with and without the respective CT‐density table, had a maximum difference of −0.65% from the values on the planning CT. The use of the respective HU‐density table decreased the percent differences from planned values by half in most of the protocols. For the anthropomorphic phantom datasets, the use of the correct HU‐density table reduced differences by 0.89% on OBI1 and 0.59% on OBI2 for the head, 0.49% on OBI1 for the thorax, and 0.25% on OBI2 for the pelvis. Differences from planned values without HU‐density correction ranged from 3.13% (OBI1, thorax) to 0.30% (OBI2, thorax).Conclusion:CT‐density tables in the TPS yield acceptable differences when used in partly homogeneous medium. Further corrections are needed when the medium contains pronounced density differences for accurate CBCT calculation. Current difference range (1–3%) can be clinically acceptable.