bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐F‐T‐91: Development of Real Time Abdominal Compression Force (ACF) Monitoring System
Authors: Kim T , Kim S , Kim D , Kang S , Cho M , Kim K , Shin D , Noh Y , Suh T 
Published: July 2016

Purpose:Hard‐plate based abdominal compression is known to be effective, but no explicit method exists to quantify abdominal compression force (ACF) and maintain the proper ACF through the whole procedure. In addition, even with compression, it is necessary to do 4D CT to manage residual motion but, 4D CT is often not possible due to reduced surrogating sensitivity. In this study, we developed and evaluated a system that both monitors ACF in real time and provides surrogating signal even under compression. The system can also provide visual‐biofeedback.Methods:The system developed consists of a compression plate, an ACF monitoring unit and a visual‐biofeedback device. The ACF monitoring unit contains a thin air balloon in the size of compression plate and a gas pressure sensor. The unit is attached to the bottom of the plate thus, placed between the plate and the patient when compression is applied, and detects compression pressure. For reliability test, 3 volunteers were directed to take several different breathing patterns and the ACF variation was compared with the respiratory flow and external respiratory signal to assure that the system provides corresponding behavior. In addition, guiding waveform were generated based on free breathing, and then applied for evaluating the effectiveness of visual‐biofeedback.Results:We could monitor ACF variation in real time and confirmed that the data was correlated with both respiratory flow data and external respiratory signal. Even under abdominal compression, in addition, it was possible to make the subjects successfully follow the guide patterns using the visual biofeedback system.Conclusion:The developed real time ACF monitoring system was found to be functional as intended and consistent. With the capability of both providing real time surrogating signal under compression and enabling visual‐biofeedback, it is considered that the system would improve the quality of respiratory motion management in radiation therapy.This research was supported by the Mid‐career Researcher Program through NRF funded by the Ministry of Science, ICT & Future Planning of Korea (NRF‐2014R1A2A1A10050270) and by the Radiation Technology R&D program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (No. 2013M2A2A7038291)
SU‐F‐T‐101: Insight into Dosimetry Workload and Planning Timelines: A 6 Year Review at One Institution
Authors: Cardan R , Popple R , Smith H , Fiveash J 
Published: July 2016

Purpose:To elucidate realistic clinical treatment planning workload and timelines to improve understanding for patients, payers, and other institutions involved in radiotherapy processes.Methods:A web based tool was developed using Oracle Express (Oracle Corp, Redwood City, CA) which allowed communication between the physicians and staff about the current state of the patient plan. For 6 years, all patient courses were logged and time‐stamped in 22 discreet steps which detailed start and stop times for simulation, contouring, and treatment planning tasks. This data was combined with the treatment planning database (TPDB) using the Eclipse Scripting API (Varian Medical Systems, Palo Alto, CA) to cross‐identify plans between the two systems. This time data was analyzed across our dosimetry staff and treatment modality.Results:In 6 years, 110,477 patient statuses were time‐logged for 9683 courses of treatment using our internal software. The courses contained 8305 unique patients who were binned into one of 11 diagnosis site categories. 8253 courses could be reconciled against the TPDB using timestamp data from patient statuses. The average planning volume per dosimetrist was 375.8 ± 142.4 plans per year with the average number of planning revisions per dosimetrist of 71.0 ± 27.1 plans per year. The median treatment planning times by modality ranged from to 48.3 hours for IMRT plans 5 fields or less to 119.6 hours for IMRT with 8 or more fields. Two arc VMAT, three arc VMAT, and 3D plans median times were 89.1 hours, 113.8 hours, and 50.9 hours respectively.Conclusion:Using our web based tool, we have demonstrated the ability to quantify treatment planning timelines and workloads which could help in setting appropriate expectations for patients, payers, and hospital administration.COI: Author received monies from Varian Medical Systems for research and teaching honorarium.
SU‐F‐T‐104: Determining the NTCP Parameters of Pharyngeal Constrictors and Proximal Esophagus for Radiation Induced Swallowing Problems Recorded Six Months After Radiation Therapy for Head and Neck Tumors
Authors: Mavroidis P , Price A , Kostich M , Amdur R , Mendenhall W , Sheets N , Green R , Das S , Marks L , Chera B 
Published: July 2016

Purpose:To estimate the radiobiological parameters of four NTCP models that describe the dose‐response relations of pharyngeal constrictors and proximal esophagus regarding the severity of patient reported swallowing problems 6 months post chemo‐radiotherapy. To identify the section/structure that best correlates with the manifestation of the clinical endpoints. Finally, to compare the goodness‐of‐fit of those models.Methods:Forty‐three patients were treated on a prospective multi‐institutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data of superior, medium and inferior sections of pharyngeal constrictors (SPC, MPC and IPC), superior and inferior sections of esophagus (SES and IES) as separate structures as well as combinations. The Lyman‐Kutcher‐Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patient data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods.Results:The AUC values were highest for the SPC for Grade ≥ 2 (0.719 for the RS and RL models, and 0.716 for LKB and Logit). For Grade ≥ 1, the respective values were 0.699 for RS, LKB and Logit and 0.676 for RL. For MPC the AUC values varied between 0.463–0.477, for IPC between 0.396–0.458, for SES between 0.556–0.613 and for IES between 0.410–0.519. The Odds Ratio for the SPC was 15.6 (1.7–146.4) for RS, LKB and Logit for NTCP of 55%.Conclusion:All the examined NTCP models could fit the clinical data with similar accuracy. The SPC appear to correlate best with the clinical endpoints of swallowing problems. A prospective study could establish the use of NTCP values of SPC as a constraint in treatment planning.
SU‐F‐T‐108: Texture Analysis for Toxicity Prediction From Dose Surface Maps
Authors: Witztum A , Warren S , Partridge M , Hawkins M 
Published: July 2016

Purpose:To find spatial features that best predict acute duodenal related toxicity grade ≥ 3 from 2D dose surface maps in pancreatic chemoradiotherapy.Methods:Nineteen patients from the ARCII trial (EudraCT 2008‐006302‐42) treating locally‐advanced pancreatic cancer (LAPC) with chemoradiotherapy were analysed. Previous work considering traditional dose‐volume and dose‐surface metrics as predictors had little power. We investigate the use of texture analysis to improve predictive capabilities. 2D duodenal dose surface maps (DSMs) were converted to 4, 8, and 16 gray (dose) levels. A gray‐level co‐occurrence matrix (GLCM) was produced and statistics (contrast, correlation, energy and homogeneity) were extracted. ROC curves were produced for each statistic for three different gray level maps (4, 8, and 16). The area under curve (AUC) was recorded and used to find the best predictor for acute duodenal related toxicity grade ≥ 3.Results:For all GLCM statistics there were only small differences in AUC between 4, 8 and 16 gray levels. Homogeneity had an AUC of 0.87, 0.88 and 0.85 for 4, 8 and 16 gray levels respectively. Using cut point analysis on homogeneity using 8 gray levels it was found that a value of 0.945 correctly predicted toxicity for 17/19 patients (4/6 patients with, 13/13 patients without toxicity). The two incorrectly predicted patients had a mean dose of 59 Gy and 28 Gy. The AUC for traditional dose‐volume (V45 = 0.57, V50 = 0.60, V55 = 0.47) and dose‐surface metrics (S45 (surface area receiving at least 45 Gy) = 0.50, S50 = 0.57, S55 = 0.49) were much lower.Conclusion:Use of texture analysis improves our ability to predict grade ≥ 3 GI toxicity in pancreatic chemoradiotherapy. The additional spatial information may give better predictors than traditional dose‐volume and dose‐surface metrics. The mechanism behind this predicted toxicity will be studied on a larger patient set.Alon Witztum is supported by an MRC/Gray Institute DPhil Studentship. Sam Warren and Mike Partridge are supported by CRUK grant C5255/A15935. Maria Hawkins received an MRC Fellowship MC_PC_12001/2.
SU‐F‐T‐111: Investigation of the Attila Deterministic Solver as a Supplement to Monte Carlo for Calculating Out‐Of‐Field Radiotherapy Dose
Authors: Mille M , Lee C , Failla G 
Published: July 2016

Purpose:To use the Attila deterministic solver as a supplement to Monte Carlo for calculating out‐of‐field organ dose in support of epidemiological studies looking at the risks of second cancers. Supplemental dosimetry tools are needed to speed up dose calculations for studies involving large‐scale patient cohorts.Methods:Attila is a multi‐group discrete ordinates code which can solve the 3D photon‐electron coupled linear Boltzmann radiation transport equation on a finite‐element mesh. Dose is computed by multiplying the calculated particle flux in each mesh element by a medium‐specific energy deposition cross‐section. The out‐of‐field dosimetry capability of Attila is investigated by comparing average organ dose to that which is calculated by Monte Carlo simulation. The test scenario consists of a 6 MV external beam treatment of a female patient with a tumor in the left breast. The patient is simulated by a whole‐body adult reference female computational phantom. Monte Carlo simulations were performed using MCNP6 and XVMC. Attila can export a tetrahedral mesh for MCNP6, allowing for a direct comparison between the two codes. The Attila and Monte Carlo methods were also compared in terms of calculation speed and complexity of simulation setup. A key perquisite for this work was the modeling of a Varian Clinac 2100 linear accelerator.Results:The solid mesh of the torso part of the adult female phantom for the Attila calculation was prepared using the CAD software SpaceClaim. Preliminary calculations suggest that Attila is a user‐friendly software which shows great promise for our intended application. Computational performance is related to the number of tetrahedral elements included in the Attila calculation.Conclusion:Attila is being explored as a supplement to the conventional Monte Carlo radiation transport approach for performing retrospective patient dosimetry. The goal is for the dosimetry to be sufficiently accurate for use in retrospective epidemiological investigations.
SU‐F‐T‐113: Inherent Functional Dependence of Spinal Cord Doses of Variable Irradiated Volumes in Spine SBRT
Authors: Ma L , Braunstein S , Chiu J , Sahgal A 
Published: July 2016

Purpose:Spinal cord tolerance for SBRT has been recommended for the maximum point dose level or at irradiated volumes such as 0.35 mL or 10% of contoured volumes. In this study, we investigated an inherent functional relationship that associates these dose surrogates for irradiated spinal cord volumes of up to 3.0 mL.Methods:A hidden variable termed as Effective Dose Radius (EDR) was formulated based on a dose fall‐off model to correlate dose at irradiated spinal cord volumes ranging from 0 mL (point maximum) to 3.0 mL. A cohort of 15 spine SBRT cases was randomly selected to derive an EDR‐parameterized formula. The mean prescription dose for the studied cases was 21.0±8.0 Gy (range, 10–40Gy) delivered in 3±1 fractions with target volumes of 39.1 ± 70.6 mL. Linear regression and variance analysis were performed for the fitting parameters of variable EDR values.Results:No direct correlation was found between the dose at maximum point and doses at variable spinal cord volumes. For example, Pearson R2 = 0.643 and R2= 0.491 were obtained when correlating the point maximum dose with the spinal cord dose at 1 mL and 3 mL, respectively. However, near perfect correlation (R2 ≥0.99) was obtained when corresponding parameterized EDRs. Specifically, Pearson R2= 0.996 and R2 = 0.990 were obtained when correlating EDR (maximum point dose) with EDR (dose at 1 mL) and EDR(dose at 3 mL), respectively. As a result, high confidence level look‐up tables were established to correlate spinal cord doses at the maximum point to any finite irradiated volumes.Conclusion:An inherent functional relationship was demonstrated for spine SBRT. Such a relationship unifies dose surrogates at variable cord volumes and proves that a single dose surrogate (e.g. point maximum dose) is mathematically sufficient in constraining the overall spinal cord dose tolerance for SBRT.
SU‐F‐T‐114: A Novel Anatomically Predictive Extension Model of Computational Human Phantoms for Dose Reconstruction in Retrospective Epidemiological Studies of Second Cancer Risks in Radiotherapy Patients
Authors: Kuzmin G , Lee C , Lee C , Pelletier C , Jung J 
Published: July 2016

Purpose:Recent advances in cancer treatments have greatly increased the likelihood of post‐treatment patient survival. Secondary malignancies, however, have become a growing concern. Epidemiological studies determining secondary effects in radiotherapy patients require assessment of organ‐specific dose both inside and outside the treatment field. An essential input for Monte Carlo modeling of particle transport is radiological images showing full patient anatomy. However, in retrospective studies it is typical to only have partial anatomy from CT scans used during treatment planning. In this study, we developed a multi‐step method to extend such limited patient anatomy to full body anatomy for estimating dose to normal tissues located outside the CT scan coverage.Methods:The first step identified a phantom from a library of body size‐dependent computational human phantoms by matching the height and weight of patients. Second, a Python algorithm matched the patient CT coverage location in relation to the whole body phantom. Third, an algorithm cut the whole body phantom and scaled them to match the size of the patient. Then, merged the two anatomies into one whole body. We entitled this new approach, Anatomically Predictive Extension (APE).Results:The APE method was examined by comparing the original chest‐abdomen‐pelvis CT images of the five patients with the APE phantoms developed from only the chest part of the CAP images and whole body phantoms. We achieved average percent differences of tissue volumes of 25.7%, 34.2%, 16.5%, 26.8%, and 31.6% with an average of 27% across all patients.Conclusion:Our APE method extends the limited CT patient anatomy to whole body anatomy by using image processing and computational human phantoms. Our ongoing work includes evaluating the accuracy of these APE phantoms by comparing normal tissue doses in the APE phantoms and doses calculated for the original full CAP images under generic radiotherapy simulations.This research was supported by the NIH Intramural Research Program.
SU‐F‐T‐124: Radiation Biological Equivalent Presentations OfLEM‐1 and MKM Approaches in the Carbon‐Ion Radiotherapy
Authors: Hsi W , Jiang G , Sheng Y 
Published: July 2016

Purpose:To study the correlations of the radiation biological equivalent doses (BED) along depth and lateral distance between LEM‐1 and MKM approaches.Methods:In NIRS‐MKM (Microdosimetric Kinetic Model) approach, the prescribed BED, referred as C‐Eq, doses aims to present the relative biological effectiveness (RBE) for different energies of carbon‐ions on a fixed 10% survival value of HCG cell with respect to convention X‐ray. Instead of a fixed 10% survival, the BED doses of LEM‐1 (Local Effect Model) approach, referred as X‐Eq, aims to present the RBE over the whole survival curve of chordoma‐like cell with alpha/beta ratio of 2.0. The relationship of physical doses as a function of C‐Eq and X‐Eq doses were investigated along depth and lateral distance for various sizes of cubic targets in water irradiated by carbon‐ions.Results:At the center of each cubic target, the trends between physical and C‐Eq or X‐Eq doses can be described by a linear and 2nd order polynomial functions, respectively. Using fit functions can then calculate a scaling factor between C‐Eq and X‐Eq doses to have similar physical doses. With equalized C‐Eq and X‐Eq doses at the depth of target center, over‐ and under‐estimated X‐Eq to C‐Eq are seen for depths before and after the target center, respectively. Near the distal edge along depth, sharp rising of RBE value is observed for X‐Eq, but sharp dropping of RBE value is observed for C‐Eq. For lateral locations near and just outside 50% dose level, sharp raising of RBE value is also seen for X‐Eq, while only minor increasing with fast dropping for C‐Eq.Conclusion:An analytical function to model the differences between the CEq and X‐Eq doses along depth and lateral distance need to further investigated to explain varied clinic outcome of specific cancers using two different approaches to calculated BED doses.
SU‐F‐T‐128: Dose‐Volume Constraints for Particle Therapy Treatment Planning
Authors: Stewart R , Smith W , Hendrickson K , Meyer J , Cao N , Lee E , Gopan O , Sandison G , Parvathaneni U , Laramore G 
Published: July 2016

Purpose:Determine equivalent Organ at Risk (OAR) tolerance dose (TD) constraints for MV x‐rays and particle therapy.Methods:Equivalent TD estimates for MV x‐rays are determined from an isoeffect, regression‐analysis of published and in‐house constraints for various fractionation schedules (n fractions). The analysis yields an estimate of (α/β) for an OAR. To determine equivalent particle therapy constraints, the MV x‐ray TD(n) values are divided by the RBE for DSB induction (RBEDSB) or cell survival (RBES). Estimates of (RBEDSB) are computed using the Monte Carlo Damage Simulation, and estimates of RBES are computed using the Repair‐Misrepair‐Fixation (RMF) model. A research build of the RayStation™ treatment planning system implementing the above model is used to estimate (RBEDSB) for OARs of interest in 16 proton therapy patient plans (head and neck, thorax, prostate and brain).Results:The analysis gives an (α/β) estimate of about 20 Gy for the trachea and heart and 2–4 Gy for the esophagus, spine, and brachial plexus. Extrapolation of MV x‐ray constraints (n = 1) to fast neutrons using RBEDSB = 2.7 are in excellent agreement with clinical experience (n = 10 to 20). When conventional (n > 30) x‐ray treatments are used as the reference radiation, fast neutron RBE increased to a maximum of 6. For comparison to a constant RBE of 1.1, the RayStation™ analysis gave estimates of proton RBEDSB from 1.03 to 1.33 for OARs of interest.Conclusion:The presented system of models is a convenient formalism to synthesize from multiple sources of information a set of self‐consistent plan constraints for MV x‐ray and hadron therapy treatments. Estimates of RBEDSB from the RayStation™ analysis differ substantially from 1.1 and vary among patients and treatment sites. A treatment planning system that incorporates patient and anatomy‐specific corrections in proton RBE would create opportunities to increase the therapeutic ratio.The research build of the RayStation used in the study was made available to the University of Washington free of charge. RaySearch Laboratories did not provide any monetary support for the reported studies.
SU‐F‐T‐133: Uniform Scanning Proton Therapy for Lung Cancer: Toxicity and Its Correlation with Dosimetry
Authors: Zheng Y , Rana S , Larson G 
Published: July 2016

Purpose:To analyze the toxicity of uniform scanning proton therapy for lung cancer patients and its correlation with dose distribution.Methods:In this study, we analyzed the toxicity of 128 lung cancer patients, including 18 small cell lung cancer and 110 non small cell lung cancer patients. Each patient was treated with uniform scanning proton beams at our center using typically 2–4 fields. The prescription was typically 74 Cobalt gray equivalent (CGE) at 2 CGE per fraction. 4D Computerized Tomography (CT) scans were used to evaluate the target motion and contour the internal target volume, and repeated 3 times during the course of treatment to evaluate the need for plan adaptation. Toxicity data for these patients were obtained from the proton collaborative group (PCG) database. For cases of grade 3 toxicities or toxicities of interest such as esophagitis and radiation dermatitis, dose distributions were reviewed and analyzed in attempt to correlate the toxicity with radiation dose.Results:At a median follow up time of about 21 months, none of the patients had experienced Grade 4 or 5 toxicity. The most common adverse effect was dermatitis (81%: 52%‐Grade 1, 28%‐Grade 2, and 1% Grade 3), followed by fatigue (48%), Cough (46%), and Esophagitis (45%), as shown in Figure 1. Severe toxicities, such as Grade 3 dermatitis or pain of skin, had a clear correlation with high radiation dose.Conclusion:Uniform scanning proton therapy is well tolerated by lung cancer patients. Preliminary analysis indicates there is correlation between severe toxicity and high radiation dose. Understanding of radiation resulted toxicities and careful choice of beam arrangement are critical in minimizing toxicity of skin and other organs.
SU‐F‐T‐137: Out‐Of‐Beam Dose for a Compact Double‐Scattering Proton Beam Therapy System
Authors: Islam M , Ahmad S , Jin H 
Published: July 2016

Purpose:The out‐of‐beam dose is important for understanding the peripheral dose in radiation therapy. In proton radiotherapy, the study of out‐of‐beam dose is scarce and the treatment planning system (TPS) based on pencil beam algorithm cannot accurately predict the out‐of‐beam dose. This study investigates the out‐of‐beam dose for the single‐room Mevion S250 double scattering proton therapy system using experimentally measured and treatment planning software generated data. The results are compared with those reported for conventional photon beam therapy. However, this study does not incorporate the neutron contribution in the scattered dose.Methods:A total of seven proton treatment plans were generated using Varian Eclipse TPS for three different sites (brain, lung, and pelvis) in an anthropomorphic phantom. Three field sizes of 5×5, 10×10, and 20×20 cm2 (lung only) with typical clinical range (13.3–22.8 g/cm2) and modulation widths (5.3–14.0 g/cm2) were used. A single beam was employed in each treatment plan to deliver a dose of 181.8 cGy (200.0 cGy (RBE)) to the selected target. The out‐of‐beam dose was measured at 2.0, 5.0, 10.0, and 15.0 cm from the beam edge in the phantom using a thimble chamber (PTW TN31010).Results:The out‐of‐beam dose generally increased with field size, range, and volume irradiated. For all the plans, the scattered dose sharply fell off with distance. At 2.0 cm, the out‐of‐beam dose ranged from 0.35% to 2.16% of the delivered dose; however, the dose was clinically negligible (<0.3%) at a distance of 5.0 cm and greater. In photon therapy, the slightly greater out‐of‐beam dose was reported (TG36; 4%, 2%, and 1% for 2.0, 5.0, and 10.0 cm, respectively, using 6 MV beam).Conclusion:The measured out‐of‐beam dose in proton therapy excluding neutron contribution was observed higher than the TPS calculated dose and comparable to that of photon beam therapy.