bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐155: Utilizing Varian TrueBeam Developer Mode for the Quantification of Mechanical Limits and the Simulation of 4D Respiratory Motion
Authors: Moseley D , Dave M 
Published: July 2014

Purpose:Use Varian TrueBeam Developer mode to quantify the mechanical limits of the couch and to simulate 4D respiratory motion.Methods:An in‐house MATLAB based GUI was created to make the BEAM XML files. The couch was moved in a triangular wave in the S/I direction with varying amplitudes (1mm, 5mm, 10mm, and 50mm) and periods (3s, 6s, and 9s). The periods were determined by specifying the speed. The theoretical positions were compared to the values recorded by the machine at 50 Hz. HD videos were taken for certain tests as external validation. 4D Respiratory motion was simulated by an A/P MV beam being delivered while the couch moved in an elliptical manner. The ellipse had a major axis of 2 cm (S/I) and a minor axis of 1 cm (A/P).Results:The path planned by the TrueBeam deviated from the theoretical triangular form as the speed increased. Deviations were noticed starting at a speed of 3.33 cm/s (50mm amplitude, 6s period). The greatest deviation occurred in the 50mm‐ 3s sequence with a correlation value of −0.13 and a 27% time increase; the plan essentially became out of phase. Excluding these two, the plans had correlation values of 0.99. The elliptical sequence effectively simulated a respiratory pattern with a period of 6s. The period could be controlled by changing the speeds or the dose rate.Conclusion:The work first shows the quantification of the mechanical limits of the couch and the speeds at which the proposed plans begin to deviate. These limits must be kept in mind when programming other couch sequences. The methodology can be used to quantify the limits of other axes. Furthermore, the work shows the possibility of creating 4D respiratory simulations without using specialized phantoms or motion‐platforms. This can be further developed to program patient‐specific breathing patterns.
SU‐E‐J‐157: Improving the Quality of T2‐Weighted 4D Magnetic Resonance Imaging for Clinical Evaluation
Authors: Du D , Caruthers S , Glide‐Hurst C , Low D , Mutic S , Hu Y 
Published: July 2014

Purpose:To develop an imaging technique that enables us to acquire T2‐ weighted 4D Magnetic Resonance Imaging (4DMRI) with sufficient spatial coverage, temporal resolution and spatial resolution for clinical evaluation.Methods:T2‐weighed 4DMRI images were acquired from a healthy volunteer using a respiratory amplitude triggered T2‐weighted Turbo Spin Echo sequence. 10 respiratory states were used to equally sample the respiratory range based on amplitude (0%, 20%i, 40%i, 60%i, 80%i, 100%, 80%e, 60%e, 40%e and 20%e). To avoid frequent scanning halts, a methodology was devised that split 10 respiratory states into two packages in an interleaved manner and packages were acquired separately. Sixty 3mm sagittal slices at 1.5mm in‐plane spatial resolution were acquired to offer good spatial coverage and reasonable spatial resolution. The in‐plane field of view was 375mm × 260mm with nominal scan time of 3 minutes 42 seconds. Acquired 2D images at the same respiratory state were combined to form the 3D image set corresponding to that respiratory state and reconstructed in the coronal view to evaluate whether all slices were at the same respiratory state. 3D image sets of 10 respiratory states represented a complete 4D MRI image set.Results:T2‐weighted 4DMRI image were acquired in 10 minutes which was within clinical acceptable range. Qualitatively, the acquired MRI images had good image quality for delineation purposes. There were no abrupt position changes in reconstructed coronal images which confirmed that all sagittal slices were in the same respiratory state.Conclusion:We demonstrated it was feasible to acquire T2‐weighted 4DMRI image set within a practical amount of time (10 minutes) that had good temporal resolution (10 respiratory states), spatial resolution (1.5mm × 1.5mm × 3.0mm) and spatial coverage (60 slices) for future clinical evaluation.
SU‐E‐J‐166: Comprehensive Evaluation of Three Deformation Image Registration Algorithms Using Digital Phantoms Created From Patients with Head and Neck Cancer
Authors: Shen Z , Bzdusek K , Shang Q , Xia P 
Published: July 2014

Purpose:To create digital phantoms using paired planning and replanning CTs from patients with H' N cancer and to comprehensively evaluate three commonly‐used deformable image registration (DIR) algorithms with known ROIs and volumetric doses from the established phantoms.Methods:We have identified five H' N patients with adaptive‐IMRT. For each patient, manually‐adjusted meshes were created for selected physicianapproved ROIs. These meshes were applied to drive the thin‐plate spline algorithm to deform the planning CT to match the replanning CT. The digital phantom consisted of the planning CT and simulated replanning CT, which were linked by a known deformation vector field (DVF). Three DIR algorithms (Fast‐Symmetric Demons, B‐Spline, and intensity‐based) were applied to these five digital phantoms. The images, ROIs, and volumetric doses were mapped from the planning CT to the simulated replanning CT using the DVFs computed by these three DIRs and compared to those using the known DVF.Results:The average normalized cross‐correlation (NCC) value between planning and replanning CTs with rigid registration was 0.924, indicating large anatomical changes. The NCC values were improved to 0.998, 0.974, and 0.996, with Demons, B‐Spline, and intensity‐based DIRs, respectively. The mean Dice coefficients for selected ROIs (e.g. PTV, brainstem, spinal cord, mandible, parotids) were in the range of 0.87‐0.95, 0.84–0.94, and 0.85–0.95 for Demons, B‐Spline, and intensity‐based DIRs, respectively. The mean slice‐wise Hausdorff distances for selected ROIs were in the range of 1.8–4.9 mm, 2.2–5.4 mm, and 2.4–6.6 mm for Demons, B‐Spline, and intensity‐based DIRs, respectively. The average percentage of voxels in the external contours that have dose errors <2Gy were 88.6%, 85.7%, and 90.7% for Demons, B‐Spline, and intensity‐based DIRs, respectively.Conclusion:All three DIR algorithms were very comparable. The deformed images, ROIs, and volumetric doses obtained by these three DIRs agreed well with those mapped from the known DVF.This work was supported by a research grant from Philips Healthcare. Karl Bzdusek is an employee of Philips Healthcare.
SU‐E‐J‐167: Improvement of Time‐Ordered Four Dimensional Cone‐Beam CT; Image Mosaicing with Real and Virtual Projections
Authors: Nakano M , Kida S , Masutani Y , Shiraki T , Yamamoto K , Shiraishi K , Nakagawa K , Haga A 
Published: July 2014

Purpose:In the previous study, we developed time‐ordered fourdimensional (4D) cone‐beam CT (CBCT) technique to visualize nonperiodic organ motion, such as peristaltic motion of gastrointestinal organs and adjacent area, using half‐scan reconstruction method. One important obstacle was that truncation of projection was caused by asymmetric location of flat‐panel detector (FPD) in order to cover whole abdomen or pelvis in one rotation. In this study, we propose image mosaicing to extend projection data to make possible to reconstruct full field‐of‐view (FOV) image using half‐scan reconstruction.Methods:The projections of prostate cancer patients were acquired using the X‐ray Volume Imaging system (XVI, version 4.5) on Synergy linear accelerator system (Elekta, UK). The XVI system has three options of FOV, S, M and L, and M FOV was chosen for pelvic CBCT acquisition, with a FPD panel 11.5 cm offset. The method to produce extended projections consists of three main steps: First, normal three‐dimensional (3D) reconstruction which contains whole pelvis was implemented using real projections. Second, virtual projections were produced by reprojection process of the reconstructed 3D image. Third, real and virtual projections in each angle were combined into one extended mosaic projection. Then, 4D CBCT images were reconstructed using our inhouse reconstruction software based on Feldkamp, Davis and Kress algorithm. The angular range of each reconstruction phase in the 4D reconstruction was 180 degrees, and the range moved as time progressed.Results:Projection data were successfully extended without discontinuous boundary between real and virtual projections. Using mosaic projections, 4D CBCT image sets were reconstructed without artifacts caused by the truncation, and thus, whole pelvis was clearly visible.Conclusion:The present method provides extended projections which contain whole pelvis. The presented reconstruction method also enables time‐ordered 4D CBCT reconstruction of organs with non‐periodic motion with full FOV without projection‐truncation artifacts.This work was partly supported by the JSPS Core‐to‐Core Program(No. 23003). This work was partly supported by JSPS KAKENHI 24234567.
SU‐E‐J‐169: Process for QA of Normal Tissue Delineation and Reported Doses in Clinical Trials
Authors: Williamson R , Yang J , Timmerman R , Court L 
Published: July 2014

Purpose:To create and evaluate a process of using auto‐segmentation for quality assurance of doses reported to normal structures in clinical trials.Methods:Multiple atlases for normal tissue segmentation were created for the esophagus, trachea/large bronchus, and brachial plexus. These atlases were used to independently delineate 21 patients who were enrolled in a phase III study of accelerated hypofractionated IGRT for patients with stage II‐III NSCLC. The results of the multi‐atlas segmentation were visually evaluated for acceptability. The dose volume limits and the maximum point doses specified by the protocol were compared for the originally delineated and auto‐segmented contours. It was noted whether these differences affected whether plans met or failed the protocol constraints.Results:On visual inspection, the auto‐segmented contour was acceptable with the exception of 8 cases (38%) of the esophagus. In these cases, the anatomy of the esophagus was notably different from that of atlases so that the autosegmentation failed. On the other hand, the process using auto‐segmentation identified two cases where not all contours of the structure had been delineated in the original plan (one trachea/large bronchus case and one brachial plexus case). The average difference in maximum dose to the esophagus, trachea, and brachial plexus were 0.2±4.4Gy (range: – 13.6:4.7Gy), 0.2±1.1Gy (−3.9:0.8Gy), and 3.6±10.7Gy (−1.2:34.1Gy), respectively. In one esophagus case and one trachea case, the plan became unacceptable when calculated using the auto‐segmented contour, but in both cases the dosimetric difference was very small.Conclusion:Two cases (10%) of contouring with insufficient coverage (trachea/large bronchus and brachial plexus) in the original plan were identified using the proposed process. However, patient‐to‐patient variations in the position of the esophagus meant that our current auto‐segmentation is inadequate to evaluate this organ, and more work is needed to optimize the process.Work funded by Cancer Prevention Research Institute of Texas (CPRIT)
SU‐E‐J‐170: Beyond Single‐Cycle 4DCT: Maximum a Posteriori (MAP) Reconstruction‐Based Binning‐Free Multicycle 4DCT for Lung Radiotherapy
Authors: Cheung Y , Hinkle J , Joshi S , Sawant A 
Published: July 2014

Purpose:Thoracic motion changes from cycle‐to‐cycle and day‐to‐day. Conventional 4DCT does not capture these cycle to cycle variations. We present initial results of a novel 4DCT reconstruction technique based on maximum a posteriori (MAP) reconstruction. The technique uses the same acquisition process (and therefore dose) as a conventional 4DCT in order to create a high spatiotemporal resolution cine CT that captures several breathing cycles.Methods:Raw 4DCT data were acquired from a lung cancer patient. The continuous 4DCT was reconstructed using MAP algorithm which uses the raw, time‐stamped CT data to reconstruct images while simultaneously estimating deformation in the subject's anatomy. This framework incorporates physical effects such as hysteresis and is robust to detector noise and irregular breathing patterns. The 4D image is described in terms of a 3D reference image defined at one end of the hysteresis loop, and two deformation vector fields (DVFs) corresponding to inhale motion and exhale motion respectively. The MAP method uses all of the CT projection data and maximizes the log posterior in order to iteratively estimate a timevariant deformation vector field that describes the entire moving and deforming volume.Results:The MAP 4DCT yielded CT‐quality images for multiple cycles corresponding to the entire duration of CT acquisition, unlike the conventional 4DCT, which only yielded a single cycle. Variations such as amplitude and frequency changes and baseline shifts were clearly captured by the MAP 4DCConclusion:We have developed a novel, binning‐free, parameterized 4DCT reconstruction technique that can capture cycle‐to‐cycle variations of respiratory motion. This technique provides an invaluable tool for respiratory motion management research. This work was supported by funding from the National Institutes of Health and VisionRT Ltd.Amit Sawant receives research funding from Varian Medical Systems, Vision RT and Elekta
SU‐E‐J‐172: A Quantitative Assessment of Lung Tumor Motion Using 4DCT Imaging Under Conditions of Controlled Breathing in the Management of Non‐Small Cell Lung Cancer (NSCLC) Using Stereotactic Body Radiation Therapy (SBRT)
Authors: Mohatt D , Gomez J , Singh A , Malhotra H 
Published: July 2014

Purpose:To study breathing related tumor motion amplitudes by lung lobe location under controlled breathing conditions used in Stereotactic Body Radiation Therapy (SBRT) for NSCLC.Methods:Sixty‐five NSCLC SBRT patients since 2009 were investigated. Patients were categorized based on tumor anatomic location (RUL‐17, RML‐7, RLL‐18, LUL‐14, LLL‐9). A 16‐slice CT scanner [GE RT16 Pro] along with Varian Realtime Position Management (RPM) software was used to acquire the 4DCT data set using 1.25 mm slice width. Images were binned in 10 phases, T00 being at maximum inspiration ' T50 at maximum expiration phase. Tumor volume was segmented in T50 using the CT‐lung window and its displacement were measured from phase to phase in all three axes; superiorinferior, anterior‐posterior ' medial‐lateral at the centroid level of the tumor.Results:The median tumor movement in each lobe was as follows: RUL= 3.8±2.0 mm (mean ITV: 9.5 cm3), RML= 4.7±2.8 mm (mean ITV: 9.2 cm3), RLL=6.6±2.6 mm (mean ITV: 12.3 cm3), LUL=3.8±2.4 mm (mean ITV: 18.5 cm3), ' LLL=4.7±2.5 mm (mean ITV: 11.9 cm3). The median respiratory cycle for all patients was found to be 3.81 ± 1.08 seconds [minimum 2.50 seconds, maximum 7.07 seconds]. The tumor mobility incorporating breathing cycle was RUL = 0.95±0.49 mm/s, RML = 1.35±0.62 mm/s, RLL = 1.83±0.71 mm/s, LUL = 0.98 ±0.50 mm/s, and LLL = 1.15 ±0.53 mm/s.Conclusion:Our results show that tumor displacement is location dependent. The range of motion and mobility increases as the location of the tumor nears the diaphragm. Under abdominal compression, the magnitude of tumor motion is reduced by as much as a factor of 2 in comparison to reported tumor magnitudes under conventional free breathing conditions. This study demonstrates the utility of abdominal compression in reducing the tumor motion leading to reduced ITV and planning tumor volumes (PTV).
SU‐E‐J‐173: Evaluation of Deformable Registration for Correcting Respiratory Motion in 4DCT Lung Images
Authors: Larrue A , van Elmpt W , Kaster F , Kadir T , Gooding M 
Published: July 2014

Purpose:Deformable Image Registration (DIR) is gaining wider clinical acceptance in radiation oncology. The aim of this work is to characterise a DIR algorithm on publically available 4DCT lung images, such that comparison can be performed against other algorithms. We propose an evaluation method of registration accuracy that takes into account the initial misregistration of the datasets.Methods:The “DIR Validation dataset” (http://www.creatis.insa‐lyon.fr/rio/dir_validation_data) provides benchmark data for evaluating 3D CT registration algorithms. It consists of six 4DCT lung datasets (1×1×2mm resolution) with 100 landmarks identified on the end‐exhalation and end‐inhalation phases. Images were registered to end‐inhalation using proprietary form of optical flow in commercial software (Mirada RTx, Mirada Medical, UK). Target registration error was measured before and after DIR, referred to as Initial Registration Error (IRE) and Final Registration Error (FRE).Results:The mean FRE over all landmarks was 1.37±1.81mm. FRE increased with IRE. Mean FRE of 0.86, 0.86, 1.53, 3.38, 4.45, 7.58mm was observed for IRE in the ranges 0–5, 5–10, 10–15, 15–20, 20–25, >25 mm. Higher FRE was observed at the inferior lung, where IRE was greater. Out‐of‐plane motion contributed more to IRE, and therefore to FRE. Maximum FRE of 20.6mm was observed for IRE of 32.1mm, located at the posterior of the middle lobe for dataset 2. Sub‐voxel registration accuracy was achieved for up to 10mm IRE, and increased linearly at 0.3mm FRE/mm IRE thereafter.Conclusion:Publicly available clinical datasets enable algorithms to be compared objectively between publications. However, only reporting average TRE after registration can be misleading as the ability of an algorithm to correct for displacements varies with the IRE or position within the patient. Consequently, algorithms should be characterized using the entire range of initial displacements. For the algorithm assessed, clinically acceptable error within one voxel was achieved for IRE of up to 15mm.TK, AL, and MG are employees of Mirada Medical
SU‐E‐J‐184: Stereo Time‐Of‐Flight System for Patient Positioning in Radiotherapy
Authors: Wentz T , Gilles M , Le Fur E , Pradier O , Visvikis D 
Published: July 2014

Purpose:The objective of this work is to test the advantage of using the surface acquired by two stereo Time‐of‐Flight (ToF) cameras in comparison of the use of one camera only for patient positioning in radiotherapy.Methods:A first step consisted on validating the use of a stereo ToFcamera system for positioning management of a phantom mounted on a linear actuator producing very accurate and repeatable displacements. The displacements between two positions were computed from the surface point cloud acquired by either one or two cameras thanks to an iterative closest point algorithm. A second step consisted on determining the displacements on patient datasets, with two cameras fixed on the ceiling of the radiotherapy room. Measurements were done first on voluntary subject with fixed translations, then on patients during the normal clinical radiotherapy routine.Results:The phantom tests showed a major improvement in lateral and depth axis for motions above 10 mm when using the stereo‐system instead of a unique camera (Fig1). Patient measurements validate these results with a mean real and measured displacement differences in the depth direction of 1.5 mm when using one camera and 0.9 mm when using two cameras (Fig2). In the lateral direction, a mean difference of 1 mm was obtained by the stereo‐system instead of 3.2 mm. Along the longitudinal axis mean differences of 5.4 and 3.4 mm with one and two cameras respectively were noticed but these measurements were still inaccurate and globally underestimated in this direction as in the literature. Similar results were also found for patient subjects with a mean difference reduction of 35%, 7%, and 25% for the lateral, depth, and longitudinal displacement with the stereo‐system.Conclusion:The addition of a second ToF‐camera to determine patient displacement strongly improved patient repositioning results and therefore insures better radiation delivery.
SU‐E‐J‐185: Gated CBCT Imaging for Positioning Moving Lung Tumor in Lung SBRT Treatment
Authors: Li X , Li T , Zhang Y , Burton S , Karlovits B , Clump D , Heron D , Huq M 
Published: July 2014

Purpose:Lung stereo‐tactic body radiotherapy(SBRT) treatment requires high accuracy of lung tumor positioning during treatment, which is usually accomplished by free breathing Cone‐Beam computerized tomography (CBCT) scan. However, respiratory motion induced image artifacts in free breathing CBCT may degrade such positioning accuracy. The purpose of this study is to investigate the feasibility of gated CBCT imaging for lung SBRT treatment.Methods:Six Lung SBRT patients were selected for this study. The respiratory motion of the tumors ranged from 1.2cm to 3.5cm, and the gating windows for all patients were set between 35% and 65% of the respiratory phases. Each Lung SBRT patient underwent free‐breathing CBCT scan using half‐fan scan technique. The acquired projection images were transferred out for off‐line analyses. An In‐house semi‐automatic algorithm was developed to trace the diaphragm movement from those projection images to acquire a patient's specific respiratory motion curve, which was used to correlate respiratory phases with each projection image. Afterwards, a filtered back‐projection algorithm was utilized to reconstruct the gated CBCT images based on the projection images only within the gating window.Results:Target volumes determined by free breathing CBCT images were 71.9%±72% bigger than the volume shown in gated CBCT image. On the contrary, the target volume differences between gated CBCT and planning CT images at exhale stage were 5.8%±2.4%. The center to center distance of the targets shown in free breathing CBCT and gated CBCT images were 9.2±8.1mm. For one particular case, the superior boundary of the target was shifted 15mm between free breathing CBCT and gated CBCT.Conclusion:Gated CBCT imaging provides better representation of the moving lung tumor with less motion artifacts, and has the potential to improve the positioning accuracy in lung SBRT treatment.
SU‐E‐J‐187: Individually Optimized Contrast‐Enhancement 4D‐CT for Pancreatic Adenocarcinoma in Radiotherapy Simulation
Authors: Xue M , Patel K , Regine W , Lane B , D' Souza W , Klahr P , Lu W 
Published: July 2014

Purpose:To study the feasibility of individually optimized contrastenhancement (CE) 4D‐CT for pancreatic adenocarcinoma (PDA) in radiotherapy simulation. To evaluate the image quality and contrast enhancement of tumor in the CE 4D‐CT, compared to the clinical standard of CE 3D‐CT and 4D‐CT.Methods:In this IRB‐approved study, each of the 7 PDA patients enrolled underwent 3 CT scans: a free‐breathing 3D‐CT with contrast (CE 3D‐CT) followed by a 4D‐CT without contrast (4D‐CT) in the first study session, and a 4D‐CT with individually synchronized contrast injection (CE 4D‐CT) in the second study session. In CE 4D‐CT, the time of full contrast injection was determined based on the time of peak enhancement for the test injection, injection rate, table speed, and longitudinal location and span of the pancreatic region. Physicians contoured both the tumor (T) and the normal pancreatic parenchyma (P) on the three CTs (end‐of‐exhalation for 4D‐CT). The contrast between the tumor and normal pancreatic tissue was computed as the difference of the mean enhancement level of three 1 cm3 regions of interests in T and P, respectively. Wilcoxon rank sum test was used to statistically compare the scores and contrasts.Results:In qualitative evaluations, both CE 3D‐CT and CE 4D‐CT scored significantly better than 4D‐CT (4.0 and 3.6 vs. 2.6). There was no significant difference between CE 3D‐CT and CE 4D‐CT. In quantitative evaluations, the contrasts between the tumor and the normal pancreatic parenchyma were 0.6±23.4, −2.1±8.0, and −19.6±28.8 HU, in CE 3D‐CT, 4D‐CT, and CE 4D‐CT, respectively. Although not statistically significant, CE 4D‐CT achieved better contrast enhancement between the tumor and the normal pancreatic parenchyma than both CE 3D‐CT and 4DCT.Conclusion:CE 4D‐CT achieved equivalent image quality and better contrast enhancement between tumor and normal pancreatic parenchyma than the clinical standard of CE 3D‐CT and 4D‐CT.This study was supported in part by Philips Healthcare.