bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐158: Audiovisual Biofeedback Reduces Image Artefacts in 4DCT: A Digital Phantom Study
Authors: Pollock S , Kipritidis J , Lee D , Bernatowicz K , Keall P 
Published: June 2015

Purpose:Irregular breathing motion has a deleterious impact on 4DCT image quality. The breathing guidance system: audiovisual biofeedback (AVB) is designed to improve breathing regularity, however, its impact on 4DCT image quality has yet to be quantified. The purpose of this study was to quantify the impact of AVB on thoracic 4DCT image quality by utilizing the digital eXtended Cardiac Torso (XCAT) phantom driven by lung tumor motion patterns.Methods:2D tumor motion obtained from 4 lung cancer patients under two breathing conditions (i) without breathing guidance (free breathing), and (ii) with guidance (AVB). There were two breathing sessions, yielding 8 tumor motion traces. This tumor motion was synchronized with the XCAT phantom to simulate 4DCT acquisitions under two acquisition modes: (1) cine mode, and (2) prospective respiratory‐gated mode. Motion regularity was quantified by the root mean square error (RMSE) of displacement. The number of artefacts was visually assessed for each 4DCT and summed up for each breathing condition. Inter‐session anatomic reproducibility was quantified by the mean absolute difference (MAD) between the Session 1 4DCT and Session 2 4DCT.Results:AVB improved tumor motion regularity by 30%. In cine mode, the number of artefacts was reduced from 61 in free breathing to 40 with AVB, in addition to AVB reducing the MAD by 34%. In gated mode, the number of artefacts was reduced from 63 in free breathing to 51 with AVB, in addition to AVB reducing the MAD by 23%.Conclusion:This was the first study to compare the impact of breathing guidance on 4DCT image quality compared to free breathing, with AVB reducing the amount of artefacts present in 4DCT images in addition to improving inter‐session anatomic reproducibility. Results thus far suggest that breathing guidance interventions could have implications for improving radiotherapy treatment planning and interfraction reproducibility.
SU‐E‐J‐160: Motion Analysis and 3D Plane Fit Through the Tumor Center of Mass Positions in the 4DCT Data Set
Authors: Jurkovic I , Stathakis S , Li Y , Patel A , Vincent J , Papanikolaou N , Mavroidis P 
Published: June 2015

Purpose:To model GTV's center of mass (COM) motion planes based on 4DCT lung data sets and establish possible correlation with the GTV's size and/or location as an aid in defining adequate GTV margins based on the most prominent motion amplitude in the 3D space.Methods:For the modeling of the COM motion throughout the respiratory phases, eleven lung cancer patients were used and the least square fitting was applied. The least square fitting generally involves either data smoothening or apparent trend identification. Quadratic minimization, singular value decomposition, orthogonal projections (orthogonal regression), are ways to find a least square solution. The linear least squares method was initially used for the planar fitting of the 3D point data. Evaluation of the goodness of fit was performed through the root mean square deviations (root mean square error, RMSE) and normalized RMSE (NRMSE) values.Results:The summed square of residuals of the fit method varied from 0.02 to 0.26 cm and the coefficient of determination from 0.04 to 0.89, while RMSE ranged from 0.05 to 0.13 and NRMSE from 0.11 to 0.29. The most prominent motion was in the transverse and sagittal planes. A correlation was found between the best fit motion plane and the GTV size and/or location. In the lower GTVs, when maximum SI was 1.5, AP and RL motions were 0.87 and 1.0 cm, respectively. This Result confirms the need for margins larger than 0.5 cm for these GTVs.Conclusion:The lower RMSE and NRMSE values showed that for each patient a good planar fit can be achieved for the COM motion path. Knowing the GTV size and location, a good estimate of the motion plane in the 3D space can be made. The required dosimetric margins can be easily calculated knowing only one motion extent and motion plane angle.
SU‐E‐J‐164: Estimation of DVH Variation for PTV Due to Interfraction Organ Motion in Prostate VMAT Using Gaussian Error Function
Authors: Lewis C , Jiang R , Chow J 
Published: June 2015

Purpose:We developed a method to predict the change of DVH for PTV due to interfraction organ motion in prostate VMAT without repeating the CT scan and treatment planning. The method is based on a pre‐calculated patient database with DVH curves of PTV modelled by the Gaussian error function (GEF).Methods:For a group of 30 patients with different prostate sizes, their VMAT plans were recalculated by shifting their PTVs 1 cm with 10 increments in the anterior‐posterior, left‐right and superior‐inferior directions. The DVH curve of PTV in each replan was then fitted by the GEF to determine parameters describing the shape of curve. Information of parameters, varying with the DVH change due to prostate motion for different prostate sizes, was analyzed and stored in a database of a program written by MATLAB.Results:To predict a new DVH for PTV due to prostate interfraction motion, prostate size and shift distance with direction were input to the program. Parameters modelling the DVH for PTV were determined based on the pre‐calculated patient dataset. From the new parameters, DVH curves of PTVs with and without considering the prostate motion were plotted for comparison. The program was verified with different prostate cases involving interfraction prostate shifts and replans.Conclusion:Variation of DVH for PTV in prostate VMAT can be predicted using a pre‐calculated patient database with DVH curve fitting. The computing time is fast because CT rescan and replan are not required. This quick DVH estimation can help radiation staff to determine if the changed PTV coverage due to prostate shift is tolerable in the treatment. However, it should be noted that the program can only consider prostate interfraction motions along three axes, and is restricted to prostate VMAT plan using the same plan script in the treatment planning system.
SU‐E‐J‐167: Dosimetric Consequences From Minimal Displacements in APBI with SAVI Applicators
Authors: Chandrasekara S , Dumitru N , Hyvarinen M , Pella S 
Published: June 2015

Purpose:To determine the importance of providing proper solid immobilization in every fraction of treatment in APBI with brachytherapy.Methods:125 patients treated with APBI brachytherapy with SAVI applicators at SFRO Boca Raton, from 2013–2015 were considered for this retrospective study. The CT scans of each patient, which were taken before each treatment, were imported in to the Oncentra treatment planning system. Then they were compared with the initial CT scan which was used for the initial plan. Deviation in displacements in reference to ribs and skin surface was measured and dosimetric evaluations respective to the initial image were performed.Results:Small deviations in displacements were observed from the SAVI applicator to the ribs and the skin surface. Dosimetric evaluations revealed, very small changes in the inter‐fractionation position make significant differences in the maximum dose to critical organs. Additionally, the volume of the cavity also changed between fractions. As a Result, the maximum dose manifested variance between 10% and 32% in ribs and skin surface respectively.Conclusion:It appears that taking a CT scan before each treatment is necessary to minimize the risk of delivering undesired high doses to the critical organs. This study indicates, in 30% of the cases re‐planning was necessary between treatments. We conclude that, treatment planning teams should evaluate the placement of the device by analyzing the CT images before each treatment and they must be prepared for re‐planning if needed. This study also reveals the urgent need of improving the immobilization methods with APBI when treating with the SAVI applicator.
SU‐E‐J‐168: Investigation of the Effect of Modulation Factor and Treatment Delivery Time for Liver VMAT SBRT
Authors: Hubley E , Pierce G , Ecclestone G 
Published: June 2015

Purpose:To investigate the effect on PTV target coverage of liver VMAT SBRT treatment plans by varying the IMRT modulation factor (MF) and length of delivery time in the presence of induced respiratory motion.Methods:Four different VMAT SBRT plans (MFs 2.1 to 3.5) were created for a liver phantom within the treatment planning system (Eclipse, Varian Oncology Systems). For each plan, the dose prescription was set to 5 different values (1000cGy to 5000cGy in 5 fractions); these variations force a change in the treatment delivery time due to reduce gantry speed required to deliver higher doses. To simulate respiratory motion, an in‐house program was developed that shifts the positions of the MLC leaves at each control point according to population‐based respiratory curves. This was done for 4 respiratory traces of comparable peak‐to‐peak amplitudes and breathing cycle lengths, with one trace exhibiting a baseline drift. A PTV margin of 5mm was used for all treatment plans.Results:A two‐way repeatedmeasures ANOVA looked at changes in PTV V95 and GTV V95 coverage, based on IMRT factor and treatment time. The GTV V95 coverage and mean liver dose showed no significant difference (p values >0.05). The PTV V95 coverage showed a significant decrease with increasing IMRT factor and decreasing treatment time (p values < 0.01 for both). The patient curve with baseline drift exhibited a decrease in PTV coverage with increasing delivery time.Conclusion:Decreased PTV coverage was seen with increasing modulation factor and decreasing treatment times for patients with regular breathing curves. With the advent of faster treatment times it is recommended that lower modulation factors for SBRT treatment plans be utilized to mitigate the possibility of interplay. Additionally, longer treatment times could be advantageous to blur out the interplay effect for SBRT treatments. Further investigation is required in patient plans.
SU‐E‐J‐170: Dosimetric Consequences of Uncorrected Rotational Setup Errors During Stereotactic Body Radiation Therapy (SBRT) Treatment of Pancreatic Cancers
Authors: Di Maso L , Forbang R Teboh , Zhang Y , Herman J , Lee J 
Published: June 2015

Purpose:To explore the dosimetric consequences of uncorrected rotational setup errors during SBRT for pancreatic cancer patients.Methods:This was a retrospective study utilizing data from ten (n=10) previously treated SBRT pancreas patients. For each original planning CT, we applied rotational transformations to derive additional CT images representative of possible rotational setup errors. This resulted in 6 different sets of rotational combinations, creating a total of 60 CT planning images. The patients’ clinical dosimetric plans were then applied to their corresponding rotated CT images. The 6 rotation sets encompassed a 3, 2 and 1‐degree rotation in each rotational direction and a 3‐degree in just the pitch, a 3‐degree in just the yaw and a 3‐degree in just the roll. After the dosimetric plan was applied to the rotated CT images, the resulting plan was then evaluated and compared with the clinical plan for tumor coverage and normal tissue sparing.Results:PTV coverage, defined here by V33 throughout all of the patients’ clinical plans, ranged from 92–98%. After an n degree rotation in each rotational direction that range decreased to 68–87%, 85–92%, and 88– 94% for n=3, 2 and 1 respectively. Normal tissue sparing defined here by the proximal stomach V15 throughout all of the patients’ clinical plans ranged from 0–8.9 cc. After an n degree rotation in each rotational direction that range increased to 0–17 cc, 0–12 cc, and 0–10 cc for n=3, 2, and 1 respectively.Conclusion:For pancreatic SBRT, small rotational setup errors in the pitch, yaw and roll direction on average caused under dosage to PTV and over dosage to proximal normal tissue. The 1‐degree rotation was on average the least detrimental to the normal tissue and the coverage of the PTV. The 3‐degree yaw created on average the lowest increase in volume coverage to normal tissue.This research was sponsored by the AAPM Education Council through the AAPM Education and Research Fund for the AAPM Summer Undergraduate Fellowship Program.
SU‐E‐J‐177: A Computational Approach for Determination of Anisotropic PTV Margins Based On Statistical Shape Analysis for Prostate Cancer Radiotherapy
Authors: Shibayama Y , Arimura H , Hirose T , Nakamura K , Umezu Y , Nakamura Y , Honda H , Toyofuku F 
Published: June 2015

Purpose:Our aim of this study was to propose a computational approach for determination of anisotropic planning target volume (PTV) margins based on statistical shape analysis with taking into account time variations of clinical target volume (CTV) shapes for the prostate cancer radiation treatment planning (RTP).Methods:Systematic and random setup errors were measured using orthogonal projection and cone beam computed tomography (CBCT) images for data of 20 patients, who underwent the intensity modulated radiation therapy for prostate cancer. The low‐risk, intermediate‐risk, and high‐risk CTVs were defined as only a prostate, a prostate plus proximal 1‐cm seminal vesicles, and a prostate plus proximal 2‐cm seminal vesicles, respectively. All CTV regions were registered with a reference CTV region with a median volume to remove the effect of the setup errors, and converted to a point distribution models. The systematic and random errors for translations of CTV regions were automatically evaluated by analyzing the movements of centroids of CTV regions. The random and systematic errors for shape variations of CTV regions were obtained from covariance matrices based on point distributions for the CTV contours on CBCT images of 72 fractions of 10 patients. Anisotropic PTV margins for 6 directions (right, left, anterior, posterior, superior and inferior) were derived by using Yoda's PTV margin model.Results:PTV margins with and without shape variations were 5.75 to 8.03 mm and 5.23 to 7.67 mm for low‐risk group, 5.87 to 8.33 mm and 5.23 to 7.67 mm for intermediate‐risk group, and 5.88 to 8.25 mm and 5.29 to 7.82 mm for highrisk group, respectively.Conclusion:The proposed computational approach could be feasible for determination of the anisotropic PTV margins with taking into account CTV shape variations for the RTP.
SU‐E‐J‐178: Towards ART ‐ Bootstrap Based Estimation of Cumulated Dose Distribution
Authors: Gizynska M , Blatkiewicz D , Cichonski A , Czyzew B , Galecki M , Gil‐Ulkowska M , Kaminski M , Lukomska S , Piziorska M , Zaleska A , Ziemek M , Zygierewicz J , Kukolowicz P 
Published: June 2015

Purpose:A lot of effort is put into diminishing the CTV‐PTV margin and providing Adaptive RT in order to spare normal structures adjacent to the PTV. The purpose of this work was to test the hypothesis that bootstrap method can be used to estimate cumulated dose distribution, representing the whole treatment and that the quality of this estimation is independent on the CTV‐PTV margin.Methods:For 25 prostate patients treated in our clinic daily set‐up errors were recorded. For each patient treatment plans for three techniques were prepared: 3D‐CRT, IMRT and VMAT. We prepared plans for different CTV‐PTV margins, for asymmetric margin (0.4, 0.7, and 0.7 cm for lateral, cranial‐caudal, and AP respectively) and than for several symmetric ones of 0.0, 0.2, 0.4, 0.6, 0.8, 1.0 cm. For each treatment plan and each fraction the dose distribution was calculated with the isocenter corrected for the set‐up error. Cumulated Dose Distribution (CDDall) was calculated as the sum of all dose distributions for each single fraction. Estimated Dose Distribution (EDDn) was calculated with bootstrap methodology. The EDDn and CDDall were compared using the 3D gamma concept (2mm and 2%) for each pair of dose distributions. The Result was treated as acceptable if at least 95% of voxels with gamma index ≤ 1 were obtained.Results:For 3D and IMRT EDDn calculated from at least 8 (3D) and 7 (IMRT) first fractions (EDDn>7 and EDDn>6), for all patients, but one, acceptable results were obtained. For VMAT our requirement was fulfilled for all patients and EDDn>2. Statistical tests show no significant difference between gamma results for different CTV‐PTV margins.Conclusion:The cumulated dose distribution CDDall can be estimated from at least 8 fractions regardless of the technique and CTV‐PTV margin. For VMAT technique the cumulated dose distribution may be estimated with 3 fractions.
SU‐E‐J‐185: A Systematic Review of Breathing Guidance in Radiation Oncology and Radiology
Authors: Pollock S , Keall R , Keall P 
Published: June 2015

Purpose:The advent of image‐guided radiation therapy (IGRT) has led to dramatic improvements in the accuracy of treatment delivery in radiotherapy. Such advancements have highlighted the deleterious impact tumor motion can have on both image quality and radiation treatment delivery. One approach to reducing tumor motion is the use of breathing guidance systems during imaging and treatment. A review of such research had not yet been performed, it was therefore our aim to perform a systematic review of breathing guidance interventions within the fields of radiation oncology and radiology.Methods:Results of online database searches were filtered in accordance to a set of eligibility criteria. The search, filtration, and analysis of articles were conducted in accordance with the PRISMAStatement reporting standard (Preferred Reporting Items for Systematic reviews and Meta‐Analyses) utilizing the PICOS approach (Participants, Intervention, Comparison, Outcome, Study design).Participants:Cancer patients, healthy volunteers.Intervention:Biofeedback breathing guidance systems.Comparison:No breathing guidance of the same breathing type.Outcome:Regularity of breathing signal and anatomic/tumor motion, medical image quality, radiation treatment margins and coverage, medical imaging and radiation treatment times.Study design:Quantitative and controlled prospective or retrospective trials.Results:The systematic search yielded a total of 479 articles, which were filtered down to 27 relevant articles in accordance to the eligibility criteria. The vast majority of investigated outcomes were significantly positively impacted by the use of breathing guidance; however, this was dependent upon the nature of the breathing guidance system and study design. In 25/27 studies significant improvements from the use of breathing guidance were observed.Conclusion:The results found here indicate that further clinical studies are warranted which quantify more comprehensively the clinical impact of The results found here indicate that further clinical studies are warranted which quantify more comprehensively the clinical impact of breathing guidance interventions.
SU‐E‐J‐196: Implementation of An In‐House Visual Feedback System for Motion Management During Radiation Therapy
Authors: Nguyen V , Ellerbusch D , James J , Wang B 
Published: June 2015

Purpose:To describe an in‐house video goggle feedback system for motion management during simulation and treatment of radiation therapy patients.Methods:This video goggle system works by splitting and amplifying the video output signal directly from the Varian Real‐Time Position Management (RPM) workstation or TrueBeam imaging workstation into two signals using a Distribution Amplifier. The first signal S[1] gets reconnected back to the monitor. The second signal S[2] gets connected to the input of a Video Scaler. The S[2] signal can be scaled, cropped and panned in real time to display only the relevant information to the patient. The output signal from the Video Scaler gets connected to an HDMI Extender Transmitter via a DVI‐D to HDMI converter cable. The S[2] signal can be transported from the HDMI Extender Transmitter to the HDMI Extender Receiver located inside the treatment room via a Cat5e/6 cable. Inside the treatment room, the HDMI Extender Receiver is permanently mounted on the wall near the conduit where the Cat5e/6 cable is located. An HDMI cable is used to connect from the output of the HDMI Receiver to the video goggles.Results:This video goggle feedback system is currently being used at two institutions. At one institution, the system was just recently implemented for simulation and treatments on two breath‐hold gated patients with 8+ total fractions over a two month period. At the other institution, the system was used to treat 100+ breath‐hold gated patients on three Varian TrueBeam linacs and has been operational for twelve months. The average time to prepare the video goggle system for treatment is less than 1 minute.Conclusion:The video goggle system provides an efficient and reliable method to set up a video feedback signal for radiotherapy patients with motion management.
SU‐E‐J‐197: Investigation of Microsoft Kinect 2.0 Depth Resolution for Patient Motion Tracking
Authors: Silverstein E , Snyder M 
Published: June 2015

Purpose:Investigate the use of the Kinect 2.0 for patient motion tracking during radiotherapy by studying spatial and depth resolution capabilities.Methods:Using code written in C#, depth map data was abstracted from the Kinect to create an initial depth map template indicative of the initial position of an object to be compared to the depth map of the object over time. To test this process, simple setup was created in which two objects were imaged: a 40 cm × 40 cm board covered in non reflective material and a 15 cm × 26 cm textbook with a slightly reflective, glossy cover. Each object, imaged and measured separately, was placed on a movable platform with object to camera distance measured. The object was then moved a specified amount to ascertain whether the Kinect's depth camera would visualize the difference in position of the object.Results:Initial investigations have shown the Kinect depth resolution is dependent on the object to camera distance. Measurements indicate that movements as small as 1 mm can be visualized for objects as close as 50 cm away. This depth resolution decreases linearly with object to camera distance. At 4 m, the depth resolution had decreased to observe a minimum movement of 1 cm.Conclusion:The improved resolution and advanced hardware of the Kinect 2.0 allows for increase of depth resolution over the Kinect 1.0. Although obvious that the depth resolution should decrease with increasing distance from an object given the decrease in number of pixels representing said object, the depth resolution at large distances indicates its usefulness in a clinical setting.