bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐79: Internal Tumor Volume Motion and Volume Size Assessment Using 4D CT Lung Data
Authors: Jurkovic I , Stathakis S , Li Y , Patel A , Vincent J , Papanikolaou N , Mavroidis P 
Published: July 2014

Purpose:To assess internal tumor volume change through breathing cycle and associated tumor motion using the 4DCT data.Methods:Respiration induced volume change through breathing cycle and associated motion was analyzed for nine patients that were scanned during the different respiratory phases. The examined datasets were the maximum and average intensity projections (MIP and AIP) and the 10 phases of the respiratory cycle. The internal target volume (ITV) was delineated on each of the phases and the planning target volume (PTV) was then created by adding setup margins to the ITV. Tumor motion through the phases was assessed using the acquired 4DCT dataset, which was then used to determine if the margins used for the ITV creation successfully encompassed the tumor in three dimensions.Results:Results showed that GTV motion along the superior inferior axes was the largest in all the cases independent of the tumor location and/or size or the use of abdomen compression. The extent of the tumor motion was found to be connected with the size of the GTV. The smallest GTVs exhibited largest motion vector independent of the tumor location. The motion vector size varied through the phases depending on the tumor size and location and it was smallest for phases 20 and 30. The smaller the volume of the delineated GTV, the greater its volume difference through the different respiratory phases was. The average GTV volume change was largest for the phases 60 and 70.Conclusion:Even if GTV is delineated using both AIP and MIP datasets, its motion extent will exceed the used margins especially for the very small GTV volumes. When the GTV size is less than 10 cc it is recommended to use fusion of the GTVs through all the phases to create the planning ITV.
SU‐E‐J‐84: Is There a Threshold Limit in the Accuracy of Deformable Image Registration (DIR)? A Validation Study Using Deformable Bladder Phantom with Implanted Markers
Authors: Varadhan R , Hui S , Overbeck C 
Published: July 2014

Purpose:To establish the fundamental relationship between deformation and its causative physical force using a deformable bladder phantom. To ascertain if a threshold limit exists for DIR accuracy, beyond which its applicability in deformed anatomy may be clinically inappropriate.Methods:A tissue equivalent deformable bladder phantom with 21 implanted aluminum markers was developed using a viscoelastic polymer with Youngs modulus and physical density properties comparable to human bladder. Applied force on the organ was incrementally varied from 10N to 70N which in turn deforms the organ. DIR accuracy was studied for commercially available algorithms (MIM and Velocity AI) by comparing the centroid (3D vector) of the 21 marker locations at the undeformed CT (ground truth) with synthetically derived marker positions from each target image from DIR.Results:The relationship between applied force and both 1D deformation along the axis of applied force (R2 =0.98) and 3D deformation as quantified by the 95 percentile hausdorff distance (R2 =0.96) showed a linear response. The maximum 1D deformation (compression) ranged from 3mm to 28 mm. A threshold limit at 30N (maximum 13mm 1D and 6.8mm 3D deformation) was established beyond which average registration error of 21 markers was ≥ 2mm for all algorithms studied. Utilizing the Reg Refine feature of the MIM software, the marker accuracy beyond 50N improved by 2mm while average marker error using Velocity multipass deformation was ≤3mm up to 50N.Conclusions:he accuracy of DIR was evaluated using a tissue equivalent mass and density conserving bladder phantom in the best case scenario using 21 implanted aluminum high contrast markers to improve the accuracy. The limits of applicability of DIR are strongly dependent on the magnitude of deformation. There is a threshold limit beyond which the accuracy of DIR fails for the range of mass and density conserving deformation studied.
SU‐E‐J‐97: Pretreatment Test and Post‐Treatment Evaluation for Iso‐NTCP Dose Guided Adapive Radiotherapy (DGART), Experience with Prostate Cancer Patients Treated with Rectal Balloons
Authors: Yu J , Hardcastle N , Bender E , Jeong K , Xiao Y , Ritter M , Tome' M 
Published: July 2014

Purpose:To explore the feasibility of pretreatment test for iso‐NTCP DGART and to compare the pretreatment test results with post‐treatment evaluations.Methods:NTCP here refers to late rectal wall toxicity only and is calculated with the ring rectal wall DVH. Simulation for one time iso‐ NTCP DGART starts after half of the total dose was done for 10 patients to investigate if TCP gains could be achieved. Six patients were treated using a 12‐fraction 4.3Gy technique and four using 16‐fraction 3.63Gy technique. For each of the 12‐fraction cases a VMAT plan was generated in Pinnacle3™ using the daily CT obtained prior to the 6th fraction. A pretreatment simulation was performed using only the first 6 daily CTs. The idea is to add the 6 original plan delivered doses with 6 DGART plan delivered doses by deformable dose accumulation (DDA) on each of the first 6 CTs, resulting in 6 rectal wall doses (RWDs) and NTCPs. The 95% confidence interval (95%CI) for the 6 NTCPs were computed. The posttreatment evaluation was done by: a) copy the DGART plan to 6 CTs for fraction 7–12 and calculate the 6 actual DGART delivered fractional doses; b) sum the 6 actual DGART doses with the 6 original plan delivered doses by DDA on each of the 12 CTs resulting in 12 post‐treatment RWDs and NTCPs; c) boxplot the 12 post‐treatment NTCPs.Results:Target dose gain is 0.76–1.93 Gy. The 95%CI widths of the pretreatment tests NTCPs were 1.1–2.7%. For 5 patients, the planned NTCP fell within the 95%CI. For 4 patients, the planned NTCP was lower than the 95%CI lines. Post‐treatment results show that for 7 patients, the upper quartile was within the 95%CI; for 2 patients, the upper quartile were higher than the 95%CI.Conclusion:The pretreatment test yields conservative prediction of the actual delivered NTCP.
SU‐E‐J‐98: Radiogenomics: Correspondence Between Imaging and Genetic Features Based On Clustering Analysis
Authors: Harmon S , Wendelberger B , Jeraj R 
Published: July 2014

Purpose:Radiogenomics aims to establish relationships between patient genotypes and imaging phenotypes. An open question remains on how best to integrate information from these distinct datasets. This work investigates if similarities in genetic features across patients correspond to similarities in PET‐imaging features, assessed with various clustering algorithms.Methods:[18F]FDG PET data was obtained for 26 NSCLC patients from a public database (TCIA). Tumors were contoured using an in‐house segmentation algorithm combining gradient and region‐growing techniques; resulting ROIs were used to extract 54 PET‐based features. Corresponding genetic microarray data containing 48,778 elements were also obtained for each tumor. Given mismatch in feature sizes, two dimension reduction techniques were also applied to the genetic data: principle component analysis (PCA) and selective filtering of 25 NSCLC‐associated genes‐ofinterest (GOI). Gene datasets (full, PCA, and GOI) and PET feature datasets were independently clustered using K‐means and hierarchical clustering using variable number of clusters (K). Jaccard Index (JI) was used to score similarity of cluster assignments across different datasets.Results:Patient clusters from imaging data showed poor similarity to clusters from gene datasets, regardless of clustering algorithms or number of clusters (JImean= 0.3429±0.1623). Notably, we found clustering algorithms had different sensitivities to data reduction techniques. Using hierarchical clustering, the PCA dataset showed perfect cluster agreement to the full‐gene set (JI =1) for all values of K, and the agreement between the GOI set and the full‐gene set decreased as number of clusters increased (JI=0.9231 and 0.5769 for K=2 and 5, respectively). K‐means clustering assignments were highly sensitive to data reduction and showed poor stability for different values of K (JIrange: 0.2301–1).Conclusion:Using commonly‐used clustering algorithms, we found poor agreement in patient characterization from genomic versus imaging data. Interpretation of radiogenomic associations was found to be dependent on clustering algorithms and sensitive to data reduction techniques.
SU‐E‐J‐99: Reconstruction of Cone Beam CT Image Using Volumetric Modulated Arc Therapy Exit Beams
Authors: Jeong K , Kuo H , Goddard L , Savacool M , Basavatia A , Hong L , Yaparpalvi R , Mynampati D , Godoy Scripes P , Kalnicki S , Tome' W 
Published: July 2014

Purpose:To test the possibility of obtaining an image of the treated volume during volumetric modulated arc therapy (VMAT) with exit beams.Method:Using a Varian Clinac 21EX and MVCT detector the following three sets of detector projection data were obtained for cone beam CT reconstruction with and without a Catphan 504 phantom. 1) 72 projection images from 20 × 16 cm^2 open beam with 3 MUs, 2) 72 projection images from 20 × 16 cm^2 MLC closed beam with 14 MUs. 3) 137 projection images from a test RapicArc QA plan. All projection images were obtained in ‘integrated image’ mode. We used OSCaR code to reconstruct the cone beam CT images. No attempts were made to reduce scatter or artifacts.Results:With projection set 1) we obtained a good quality MV CBCT image by optimizing the reconstruction parameters. Using projection set 2) we were not able to obtain a CBCT image of the phantom, which was determined to be due to the variation of interleaf leakage with gantry angle. From projection set 3), we were able to obtain a weak but meaningful signal in the image, especially in the target area where open beam signals were dominant. This finding suggests that one might be able to acquire CBCT images with rough body shape and some details inside the irradiated target area.Conclusion:Obtaining patient images using the VMAT exit beam is challenging but possible. We were able to determine sources of image degradation such as gantry angle dependent interleaf leakage and beams with a large scatter component. We are actively working on improving image quality.
SU‐E‐J‐100: Reconstruction of Prompt Gamma Ray Three Dimensional SPECT Image From Boron Neutron Capture Therapy(BNCT)
Authors: Yoon D , Jung J , Suh T 
Published: July 2014

Purpose:Purpose of paper is to confirm the feasibility of acquisition of three dimensional single photon emission computed tomography (SPECT) image from boron neutron capture therapy (BNCT) using Monte Carlo simulation.Methods:In case of simulation, the pixelated SPECT detector, collimator and phantom were simulated using Monte Carlo n particle extended (MCNPX) simulation tool. A thermal neutron source (<1 eV) was used to react with the boron uptake region (BUR) in the phantom. Each geometry had a spherical pattern, and three different BURs (A, B and C region, density: 2.08 g/cm3) were located in the middle of the brain phantom. The data from 128 projections for each sorting process were used to achieve image reconstruction. The ordered subset expectation maximization (OSEM) reconstruction algorithm was used to obtain a tomographic image with eight subsets and five iterations. The receiver operating characteristic (ROC) curve analysis was used to evaluate the geometric accuracy of reconstructed image.Results:The OSEM image was compared with the original phantom pattern image. The area under the curve (AUC) was calculated as the gross area under each ROC curve. The three calculated AUC values were 0.738 (A region), 0.623 (B region), and 0.817 (C region). The differences between length of centers of two boron regions and distance of maximum count points were 0.3 cm, 1.6 cm and 1.4 cm.Conclusion:The possibility of extracting a 3D BNCT SPECT image was confirmed using the Monte Carlo simulation and OSEM algorithm. The prospects for obtaining an actual BNCT SPECT image were estimated from the quality of the simulated image and the simulation conditions. When multiple tumor region should be treated using the BNCT, a reasonable model to determine how many useful images can be obtained from the SPECT could be provided to the BNCT facilities.This research was supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, Information and Communication Technologies (ICT) and Future Planning (MSIP)(Grant No.200900420) and the Radiation Technology Research and Development program (Grant No.2013043498), Republic of Korea.
SU‐E‐J‐118: Verification of Intrafractional Positional Accuracy Using Ultrasound Autoscan Tracking for Prostate Cancer Treatment
Authors: Yu S , Hristov D , Phillips T 
Published: July 2014

Purpose:Transperineal ultrasound imaging is attractive option for imageguided radiation therapy as there is no need to implant fiducials, no extra imaging dose, and real time continuous imaging is possible during treatment. The aim of this study is to verify the tracking accuracy of a commercial ultrasound system under treatment conditions with a male pelvic phantom.Methods:A CT and ultrasound scan were acquired for the male pelvic phantom. The phantom was then placed in a treatment mimicking position on a motion platform. The axial and lateral tracking accuracy of the ultrasound system were verified using an independent optical tracking system. The tracking accuracy was evaluated by tracking the phantom position detected by the ultrasound system, and comparing it to the optical tracking system under the conditions of beam on (15 MV), beam off, poor image quality with an acoustic shadow introduced, and different phantom motion cycles (10 and 20 second periods). Additionally, the time lag between the ultrasound‐detected and actual phantom motion was investigated.Results:Displacement amplitudes reported by the ultrasound system and optical system were within 0.5 mm of each other for both directions and all conditions. The ultrasound tracking performance in axial direction was better than in lateral direction. Radiation did not interfere with ultrasound tracking while image quality affected tracking accuracy. The tracking accuracy was better for periodic motion with 20 second period. The time delay between the ultrasound tracking system and the phantom motion was clinically acceptable.Conclusion:Intrafractional prostate motion is a potential source of treatment error especially in the context of emerging SBRT regimens. It is feasible to use transperineal ultrasound daily to monitor prostate motion during treatment. Our results verify the tracking accuracy of a commercial ultrasound system to be better than 1 mm under typical external beam treatment conditions.
SU‐E‐J‐130: ViewRay Real‐Time Imaging of a Motion Phantom and In‐Vivo Canine Patients
Authors: Saenz D , Bayouth J , Christensen N , Henzler M , Forrest L , Paliwal B 
Published: July 2014

Purpose:To test the sub‐second imaging achieved with ViewRay for accuracy and ability to track real‐time target motion during treatment delivery.Methods:A motion phantom incorporating MR compatibility was designed using the QUASAR Respiratory Motion Phantom. A silicon di‐electric gel poured into a cylindrical shape was used as the target, connected to the motor via a rod. The target was driven with a sinusoidal trajectory of 20 mm amplitude. The cycle length was varied from 3 to 9 seconds per cycle. Images were acquired in the sagittal plane every 0.25 seconds and processed in MATLAB. Morphological‐based automatic contouring identified the target through intensity thresholds and smoothing via erosion and dilation on each frame. The trajectory, y(n), was plotted using the centroid of each contour as an estimate of position and was fitted to a sinusoidal curve with four fitting parameters. The resultant amplitude, angular frequency, and cross‐sectional area were compared with the expected quantity. Motion tracking was also tested in canine patients. Both automatic and manual contouring on each frame was used to obtain a trajectory.Results:The average measured amplitude over each trajectory was 20.3±0.1mm, within 2% of the known amplitude. The expected angular frequency, calculated from 2 π /T, agreed with the measured value within 2% for each trajectory. The average recorded cross‐sectional area was 3.9±0.2 cm². which matches with the expected 3.9 cm². Finally, the cine images from the canine study had sufficient image quality to quantify motion and track target trajectories.Conclusion:Over the range of cycle lengths representing a wide range of breathing rates in patients, very good agreement was observed between the expected and measured target trajectory. Clinically relevant quantitative motion data can be extracted from the cine images.
SU‐E‐J‐140: Availability of Using Diaphragm Matching in Stereotactic Body Radiotherapy (SBRT) at the Time in Breath‐Holding SBRT for Liver Cancer
Authors: Kawahara D , Ozawa S , Nakashima T. , Aita M. , Tsuda S. , Ochi Y. , Okumura T. , Masuda H. , Ohno Y. , Kimura T. , Nagata Y. 
Published: July 2014

Purpose:IGRT based on the bone matching may produce a larger target positioning error in terms of the reproducibility of the expiration breath hold. Therefore, the feasibility of the 3D image matching between planning CT image and pretreatment CBCT image based on the diaphragm matching was investigated.Methods:In fifteen‐nine liver SBRT cases, Lipiodol, uptake after TACE was outlined as the marker of the tumor. The relative coordinate of the isocenter obtained by the contrast matching was defined as the reference coordinate. The target positioning difference between diaphragm matching and bone matching were evaluated by the relative coordinate of the isocenter from the reference coordinate obtained by each matching technique. In addition, we evaluated PTV margins by van Herk setup margin formula.Results:The target positioning error by the diaphragm matching and the bone matching was 1.31±0.83 and 3.10±2.80 mm in the cranial‐caudal(C‐C) direction, 1.04±0.95 and 1.62±1.02 mm in the anterior‐posterior(A‐P) direction, 0.93±1.19 and 1.12±0.94 mm in the left‐right(L‐R) direction, respectively. The positioning error by the diaphragm matching was significantly smaller than the bone matching in the C‐C direction (p<0.05). The setup margin of diaphragm matching and bone matching that we had calculated based on van Herk margin formula was 4.5mm and 6.2mm(C‐C), and 3.6mm and 6.3mm(A‐P), and 2.6mm and 4.5mm(L‐R), respectively.Conclusion:IGRT based on a diaphragm matching could be one alternative image matching technique for the positioning of the patients with liver tumor.
SU‐E‐J‐142: Performance Study of Automatic Image‐Segmentation Algorithms in Motion Tracking Via MR‐IGRT
Authors: Feng Y , Kawrakow I , Olsen J. , Parikh P. , Noel C , Wooten H , Du D , Dempsey J , Mutic S , Hu Y 
Published: July 2014

Purpose:Evaluate commonly used segmentation algorithms on a commercially available real‐time MR image guided radiotherapy (MR‐IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy.Methods:MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on‐board MR imaging system and an imaging protocol used during MR‐IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k‐means (FKM), k‐harmonic means (KHM), and reaction‐diffusion level set evolution (RD‐LSE), along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground‐truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison.Results:In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD‐LSE cannot consistently segment a liver tumor and the duodenum.Conclusion:The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR‐IGRT. Future studies include a selection of conformal segmentation methods based on image/organ‐specific information, different filtering methods and their influences on the segmentation results.Parag Parikh receives research grant from ViewRay.Sasa Mutic has consulting and research agreements with ViewRay.Yanle Hu receives travel reimbursement from ViewRay.Iwan Kawrakow and James Dempsey are ViewRay employees.
SU‐E‐J‐150: Impact of Intrafractional Prostate Motion On the Accuracy and Efficiency of Prostate SBRT Delivery: A Retrospective Analysis of Prostate Tracking Log Files
Authors: Xiang H , Qureshi M , De Armas R , Hirsch A , Katz M , Nicholas B , Keohan S , Lu H , Efstathiou J , Zietman A , Willins J , Kachnic J 
Published: July 2014

Purpose:To measure intrafractional prostate motion by time‐based stereotactic x‐ray imaging and investigate the impact on the accuracy and efficiency of prostate SBRT delivery.Methods:Prostate tracking log files with 1,892 x‐ray image registrations from 18 SBRT fractions for 6 patients were retrospectively analyzed. Patient setup and beam delivery sessions were reviewed to identify extended periods of large prostate motion that caused delays in setup or interruptions in beam delivery. The 6D prostate motions were compared to the clinically used PTV margin of 3–5 mm (3 mm posterior, 5 mm all other directions), a hypothetical PTV margin of 2–3 mm (2 mm posterior, 3 mm all other directions), and the rotation correction limits (roll ±2°, pitch ±5° and yaw ±3°) of CyberKnife to quantify beam delivery accuracy.Results:Significant incidents of treatment start delay and beam delivery interruption were observed, mostly related to large pitch rotations of ≥±5°. Optimal setup time of 5–15 minutes was recorded in 61% of the fractions, and optimal beam delivery time of 30–40 minutes in 67% of the fractions. At a default imaging interval of 15 seconds, the percentage of prostate motion beyond PTV margin of 3–5 mm varied among patients, with a mean at 12.8% (range 0.0%–31.1%); and the percentage beyond PTV margin of 2–3 mm was at a mean of 36.0% (range 3.3%–83.1%). These timely detected offsets were all corrected real‐time by the robotic manipulator or by operator intervention at the time of treatment interruptions.Conclusion:The durations of patient setup and beam delivery were directly affected by the occurrence of large prostate motion. Frequent imaging of down to 15 second interval is necessary for certain patients. Techniques for reducing prostate motion, such as using endorectal balloon, can be considered to assure consistently higher accuracy and efficiency of prostate SBRT delivery.