bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐D‐204‐03: Comparison of Patient Positioning Methods Through Modeling of Acute Rectal Toxicity in Intensity Modulated Radiation Therapy for Prostate Cancer. Does Quality of Data Matter More Than the Quantity?
Authors: Liu X , Fatyga M , Herman M , Vora S , Wong W , Schild S , Schild M , Li J , Wu T 
Published: July 2016

Purpose:To determine if differences in patient positioning methods have an impact on the incidence and modeling of grade >=2 acute rectal toxicity in prostate cancer patients who were treated with Intensity Modulated Radiation Therapy (IMRT).Methods:We compared two databases of patients treated with radiation therapy for prostate cancer: a database of 79 patients who were treated with 7 field IMRT and daily image guided positioning based on implanted gold markers (IGRTdb), and a database of 302 patients who were treated with 5 field IMRT and daily positioning using a trans‐abdominal ultrasound system (USdb). Complete planning dosimetry was available for IGRTdb patients while limited planning dosimetry, recorded at the time of planning, was available for USdb patients. We fit Lyman‐Kutcher‐Burman (LKB) model to IGRTdb only, and Univariate Logistic Regression (ULR) NTCP model to both databases. We perform Receiver Operating Characteristics analysis to determine the predictive power of NTCP models.Results:The incidence of grade >= 2 acute rectal toxicity in IGRTdb was 20%, while the incidence in USdb was 54%. Fits of both LKB and ULR models yielded predictive NTCP models for IGRTdb patients with Area Under the Curve (AUC) in the 0.63 – 0.67 range. Extrapolation of the ULR model from IGRTdb to planning dosimetry in USdb predicts that the incidence of acute rectal toxicity in USdb should not exceed 40%. Fits of the ULR model to the USdb do not yield predictive NTCP models and their AUC is consistent with AUC = 0.5.Conclusion:Accuracy of a patient positioning system affects clinically observed toxicity rates and the quality of NTCP models that can be derived from toxicity data. Poor correlation between planned and clinically delivered dosimetry may lead to erroneous or poorly performing NTCP models, even if the number of patients in a database is large.
SU‐D‐BRC‐01: An Automatic Beam Model Commissioning Method for Monte Carlo Simulations in Pencil‐Beam Scanning Proton Therapy
Authors: Qin N , Shen C , Tian Z , Jiang S , Jia X 
Published: July 2016

Purpose:Monte Carlo (MC) simulation is typically regarded as the most accurate dose calculation method for proton therapy. Yet for real clinical cases, the overall accuracy also depends on that of the MC beam model. Commissioning a beam model to faithfully represent a real beam requires finely tuning a set of model parameters, which could be tedious given the large number of pencil beams to commmission. This abstract reports an automatic beam‐model commissioning method for pencil‐beam scanning proton therapy via an optimization approach.Methods:We modeled a real pencil beam with energy and spatial spread following Gaussian distributions. Mean energy, and energy and spatial spread are model parameters. To commission against a real beam, we first performed MC simulations to calculate dose distributions of a set of ideal (monoenergetic, zero‐size) pencil beams. Dose distribution for a real pencil beam is hence linear superposition of doses for those ideal pencil beams with weights in the Gaussian form. We formulated the commissioning task as an optimization problem, such that the calculated central axis depth dose and lateral profiles at several depths match corresponding measurements. An iterative algorithm combining conjugate gradient method and parameter fitting was employed to solve the optimization problem. We validated our method in simulation studies.Results:We calculated dose distributions for three real pencil beams with nominal energies 83, 147 and 199 MeV using realistic beam parameters. These data were regarded as measurements and used for commission. After commissioning, average difference in energy and beam spread between determined values and ground truth were 4.6% and 0.2%. With the commissioned model, we recomputed dose. Mean dose differences from measurements were 0.64%, 0.20% and 0.25%.Conclusion:The developed automatic MC beam‐model commissioning method for pencil‐beam scanning proton therapy can determine beam model parameters with satisfactory accuracy.
SU‐D‐BRC‐06: Experimental and Monte Carlo Studies of Fluence Corrections for Graphite Calorimetry in Proton Therapy
Authors: Lourenco A , Thomas R , Bouchard H , Kacperek A , Vondracek V , Royle G , Palmans H 
Published: July 2016

Purpose:For photon and electron beams, the standard device used to measure absorbed dose is a calorimeter. Standards laboratories are currently working on the establishment of graphite calorimeters as a primary standard for proton beams. To provide a practical method for graphite calorimetry, it is necessary to convert dose to graphite to dose to water, requiring knowledge of the water‐to‐graphite stopping‐power ratio and the fluence correction factor. This study aims to present a novel method to determine fluence corrections experimentally, and to apply this methodology to low‐ and high‐energy proton beams.Methods:Measurements were performed in 60 MeV and 180 MeV proton beams. Experimental information was obtained from depth‐dose ionization chamber measurements performed in a water phantom. This was repeated with different thicknesses of graphite plates in front of the water phantom. One distinct advantage of this method is that only ionization chamber perturbation factors for water are required. Fluence corrections were also obtained through Monte Carlo simulations for comparison with the experiments.Results:The experimental observations made in this study confirm the Monte Carlo results. Overall, fluence corrections between water and graphite increased with depth, with a maximum correction of 1% for the low‐energy beam and 4% for the high‐energy beam. The results also showed that a fraction of the secondary particles generated in proton therapy beams do not have enough energy to cross the ionization chamber wall; thus, their contribution is not accounted for in the measured fluence corrections. This effect shows up as a discrepancy in fluence corrections of 1% and has been confirmed by simulations of the experimental setup.Conclusion:Fluence corrections derived by experiment do not account for low‐energy secondary particles that are stopped in the ion chamber wall. This work will contribute to a practical graphite calorimetry technique for determining absolute dose to water in proton beams.
SU‐D‐BRB‐03: Full Pre‐Clinical Validation of Comprehensive Knowledge‐Based Planning for Stereotactic Radiosurgery
Authors: Ziemer B , Shiraishi S , Hattangadi‐Gluth J , Sanghvi P , Moore K 
Published: July 2016

Purpose:As knowledge‐based planning (KBP) would augment and potentially supplant manual human‐driven treatment planning, it is imperative to ensure that the KBP system maintains or improves overall plan quality in the aggregate. The purpose of this study was to: (I) demonstrate non‐inferiority of KBP‐driven automated stereotactic radiosurgery (SRS) planning with blinded physician review and (II) determine what factors, if any, contributed to the preference of manual plans over KBP in the blinded review.Methods:Automated KBP routines in non‐coplanar VMAT were developed for three clinical SRS scenarios: isolated brain lesions (ISOLATED), lesions closely abutting (<3cm) non‐brain OARs (INVOLVED), and single‐isocenter multiple metastases (MULTIMET). Two SRS‐specializing physicians were given the patient's history/diagnosis/prescription and then presented with the candidate plans with the identities (manual or KBP) obscured. The preferred plan was then selected by the physician reviewer. If two plans were judged to be clinically indistinguishable, this was scored as a KBP selection as the automated plan had thus achieved the same quality as the manual plan. Multiple parameters were explored as possible correlates to manual preference (i.e. KBP failure): planning date, planner, attending physician, reviewing physicist, PTV volume, nearest OAR‐to‐PTV distance and prescription dose. Correlation coefficients were calculated using the Kendall‐Tau statistical test with significance threshold p<0.05.Results:For the ISOLATED, INVOLVED and MULTIMET scenarios, the KBP plans were chosen 86% (90/105), 77% (20/26) and 76% (13/17) of the time, respectively. Across the groups, no factors proved to be even moderately correlated or predictive. The only correlation coefficient approaching significance was 0.126 (p=0.052) for PTV volume, implying that KBP plans were selected at a slightly lower rate in the case of smaller PTVs.Conclusion:The clinically‐deliverable KBP automated SRS plans were equivalent or superior to manual SRS plans for a clear majority of the cases in all three clinical scenarios.J.A. Hattangadi: Research Grant; Varian Medical Systems; K.L. Moore: Research Grant; Varian Medical Systems
SU‐D‐BRB‐04: Nomogram for Prediction, Comparison, and Evaluation of Dose to Normal Tissue in SRS Planning
Authors: Templeton A , Liao Y , Diaz A , Turian J 
Published: July 2016

Purpose:Radiosurgery of brain metastases is a unique treatment planning subset in which the treatment approach, high conformality and steep dose gradients are relatively invariant with varying location, size and shape of the target. Prescription doses are generally limited by the size of tumor or amount of surrounding normal brain receiving intermediate doses. We tabulated our treatment plans to establish a nomogram which provides planning expectations, useful for patient scheduling, planning efficiency, and training purposes.Methods:The clinical treatment plans of 247 individual metastases (0.3–100cc, 1–5 fractions) were processed, after exclusion of targets qualitatively close to a sensitive brain structure. Plans were designed with 3–5 dynamic conformal arcs using BrainLab‐Iplan or 1–2 VMAT arcs using Eclipse. The effective prescription (D95) was calculated for each plan, and the total volumes of tissue receiving 10%, 20%, 30%, etc. of that dose were calculated (V10, V20, V30 etc.). These data were fitted against the target equivalent diameter with a 3rd degree polynomial minimizing the least‐squares difference, from which the upper and lower quartile fits were generated. Plans were then separated by qualitative concavity of the target, and by MLC type; 0.5cm central leaves versus 0.25cm for Millenium and HD MLCs, respectively.Results:The polynomial fitting all data predicted the treated V50 with an r2 value of 0.97 and a mean error of 3.0 cc. The lower‐to‐upper‐quartile V50 range in cc was 12.2–16.2, 14.6–18.1, and 17.2–20.8 for convex, intermediate, and concave targets. The 0.5cm leaves exhibited 1.5cc higher V50 for the smallest targets over 0.25cm leaves.Conclusion:Planning performance based on institutional knowledge data offers insights into the attainable results before the planning process begins, and provides support during plan evaluation. Our compiled database will be used to compare treatment approaches and to triage patients.
SU‐D‐BRB‐06: Toward Big‐Data Driven Treatment Planning: VMAT/IMRT Inverse Planning Autopiloted by Population‐Based Prior Data
Authors: Wang H , Xing L 
Published: July 2016

Purpose:Current treatment planning remains a costly and labor intensive procedure and requires multiple trial‐and‐error adjustments of system parameters such as weighting factors and prescriptions. The purpose of this work is to develop an autonomous treatment planning technique with effective use of population‐based prior knowledge.Methods:Our autopiloted planning tool consists of three major components: (i) a commercial treatment planning system (TPS) (EclipseTM, Varian Medical Systems, CA); (ii) a statistical formulation of prior knowledge, which takes an assemble of prior treatment plans similar to the patient under planning and provides a priori variation range of final solution with an assigned preference level; and (iii) a decision‐making or outer‐loop optimization that assesses plan generated by Eclipse and drives the search toward a solution consistent with population‐based prior knowledge. To query and interact with TPS, Microsoft (MS) Visual Studio Coded UI is applied to record some common planner‐TPS interactions as subroutines. These subroutines are called back in the autopilot program written in C# to navigate through the solution space with an iterative algorithm. The utility of the approach is demonstrated by using a prostate IMRT case and three head and neck VMAT case.Results:An autonomous inverse planning formalism of using population‐based prior knowledge for autopiloting the VMAT/IMRT treatment planning process is implemented successfully in platform of a commercial TPS. The process mimics the decision‐making process of autopiloted automobile and provides a clinically sensible treatment plan automatically, thus effectively eliminating the tedious manual trial‐and‐errors process of treatment planning. It is found that the prostate and head and neck treatment plans compare favorably with that used for patients’ actual treatments.Conclusion:Clinical inverse treatment planning process can be autopiloted effectively with the use of population‐based prior knowledge. The strategy lays foundation for future development of big data‐driven inverse planning of various disease sites.Research grant and speak honoraria from Varian Medical Systems
SU‐D‐BRA‐01: Feasibility Study for Swallowing Prediction Using Pressure Sensors
Authors: Cho M , Kim S , Kim T , Kim D , Kang S , Kim K , Shin D , Noh Y , Suh T 
Published: July 2016

Purpose:To develop a swallowing prediction system (SPS) using force sensing sensors and evaluate its feasibility.Methods:The SPS developed consists of force sensing sensor units, a thermoplastic mask, a signal transport device and a control PC installed with an in‐house software. The SPS is designed to predict the pharyngeal stage of swallowing because it is known that internal organ movement occurs in pharyngeal stage. To detect prediction signal in the SPS, the force sensing sensor units were attached on both the submental muscle region and thyroid cartilage region of the thermoplastic mask. While the signal from the thyroid cartilage region informs the action of swallowing, the signal from the submental muscle region is utilized as a precursor for swallowing. Since the duration of swallowing is relatively short, using such precursor (or warning) signals for machine control is considered more beneficial. A volunteer study was conducted to evaluate the feasibility of the system. In this volunteer study, we intended to verify that the system could predict the pharyngeal stage of the swallowing. We measured time gaps between obtaining the warning signals in the SPS and starting points of the pharyngeal stage of swallowing.Results:The measured data was examined whether the time gaps were in reasonable order to be easily utilized. The mean and standard deviation values of these time gaps were 0.550 s ± 0.183 s. in 8 volunteers.Conclusion:The proposed method was able to predict the on‐set of swallowing of human subjects inside the thermoplastic mask, which has never been possible with other monitoring systems such as camera‐based monitoring system. With the prediction ability of swallowing incorporated into the machine control mechanism (in the future), beam delivery can be controlled to skip swallowing periods and significant dosimetric gain is expected in head & neck cancer treatments.This work was supported by the Radiation Technology R&D program (No. 2015M2A2A7038291) and by the Mid‐career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.
SU‐D‐BRA‐04: Computerized Framework for Marker‐Less Localization of Anatomical Feature Points in Range Images Based On Differential Geometry Features for Image‐Guided Radiation Therapy
Authors: Soufi M , Arimura H , Nakamura K , Hirose T , Umezu Y , Shioyama Y , Toyofuku F 
Published: July 2016

Purpose:To propose a computerized framework for localization of anatomical feature points on the patient surface in infrared‐ray based range images by using differential geometry (curvature) features.Methods:The general concept was to reconstruct the patient surface by using a mathematical modeling technique for the computation of differential geometry features that characterize the local shapes of the patient surfaces. A region of interest (ROI) was firstly extracted based on a template matching technique applied on amplitude (grayscale) images. The extracted ROI was preprocessed for reducing temporal and spatial noises by using Kalman and bilateral filters, respectively. Next, a smooth patient surface was reconstructed by using a non‐uniform rational basis spline (NURBS) model. Finally, differential geometry features, i.e. the shape index and curvedness features were computed for localizing the anatomical feature points. The proposed framework was trained for optimizing shape index and curvedness thresholds and tested on range images of an anthropomorphic head phantom. The range images were acquired by an infrared ray‐based time‐of‐flight (TOF) camera. The localization accuracy was evaluated by measuring the mean of minimum Euclidean distances (MMED) between reference (ground truth) points and the feature points localized by the proposed framework. The evaluation was performed for points localized on convex regions (e.g. apex of nose) and concave regions (e.g. nasofacial sulcus).Results:The proposed framework has localized anatomical feature points on convex and concave anatomical landmarks with MMEDs of 1.91±0.50 mm and 3.70±0.92 mm, respectively. A statistically significant difference was obtained between the feature points on the convex and concave regions (P<0.001).Conclusion:Our study has shown the feasibility of differential geometry features for localization of anatomical feature points on the patient surface in range images. The proposed framework might be useful for tasks involving feature‐based image registration in range‐image guided radiation therapy.
SU‐D‐BRA‐07: Applications of Combined KV/MV CBCT Imaging with a High‐DQE MV Detector
Authors: Bazalova‐Carter M , Wang A , Wu M , Newson M , Xing L , Ansbacher W , Fahrig R , Star‐Lack J 
Published: July 2016

Purpose:To investigate whether a high detection quantum efficiency (DQE) MV detector makes combined kV/MV CBCT clinically practical.Methods:Combined kV/MV CBCT was studied for scan time reduction (STR) and metal artifact reduction (MAR). 6MV CBCT data (dose rate = 0.017 MU/degree) were collected using 1) a novel focused pixelated cadmium tungstate (CWO) scintillator (15mm thickness, DQE(0) = 22%, 0.784mm pixel pitch) coupled to a flat panel imager, and 2) a commercial portal imager with a 133mg/cm2 gadolinium oxysulfide (GOS) screen (DQE(0) = 1.2%). The 100kVp data were acquired using a commercial imager employing a columnar cesium iodide scintillator (DQE(0) = 70%) with a dose rate of 0.0016 cGy/degree. For STR, MV and kV projections spanning 105° were combined to constitute a complete CBCT scan. Total dose was ∼2cGy and acquisition time was 18s. For MAR, only the metalcorrupted pixels in the kV projections were replaced with MV data resulting in a total dose of less than 1cGy for a 360° scan. Image quality was assessed using an 18‐cm diameter electron density phantom with nine tissue inserts, some of which were replaced with steel rods for MAR studies.Results:The CWO contrast‐to‐noise ratio (CNR) was ∼4.0x higher than the GOS CNR and was ∼4.8x lower than the kV CNR when normalized for dose. When CWO MV data were combined with kV data for STR, all contrast inserts were visible, but only two were detectable in the composite kV/GOS image. Metal artifacts were greatly reduced using the kV/MV MAR technique with all contrast inserts clearly visible in the composite kV/CWO image but only two inserts visible in the composite kV/GOS image.Conclusion:We have demonstrated that a high DQE MV detector significantly improves kV/MV CBCT image quality thus enabling scan time reduction and metal artifact reduction without a severe dose penalty.AW and JS‐L are employees of Varian, RF is an employee of Siemens.
SU‐D‐202‐01: Functional Lung Avoidance and Response‐Adaptive Escalation (FLARE) RT: Feasibility of a Precision Radiation Oncology Strategy
Authors: Bowen S , Lee E , Miyaoka R , Saini J , Kinahan P , Sandison G , Wong T , Vesselle H , Rengan R , Zeng J 
Published: July 2016

Purpose:NSCLC patient RT is planned without consideration of spatial heterogeneity in lung function or tumor response, which may have contributed to failed uniform dose escalation in a randomized trial. The feasibility of functional lung avoidance and response‐adaptive escalation (FLARE) RT to reduce dose to [9 9mTc]MAA‐SPECT/CT perfused lung while redistributing 74Gy within [1 8F]FDG‐PET/CT biological target volumes was assessed.Methods:Eight Stage IIB–IIIB NSCLC patients underwent FDG‐PET/CT and MAA‐SPECT/CT treatment planning scans. Perfused lung objectives were derived from scatter/collimator/attenuation‐corrected MAA‐SPECT uptake relative to ITV‐subtracted lung to maintain <20Gy mean lung dose (MLD). Prescriptions included 60Gy to PTV and concomitant boost of 74Gy mean to biological target volumes (BTV=GTV+PET margin) scaled to each BTV voxel by relative FDG‐PET SUV. Dose‐painting‐by‐numbers prescriptions were integrated into commercial TPS via previously reported ROI discretization. Dose constraints for lung, heart, cord, and esophagus were defined. FLARE RT plans were optimized with VMAT, proton pencil beam scanning (PBS) with 3%‐3mm robust optimization, and combination PBS (avoidance) plus VMAT (escalation). Dosimetric differences were evaluated by Friedman non‐parametric paired test with multiple sampling correction.Results:PTV and normal tissue objectives were not violated in 24 FLARE RT plans. Population median of mean BTV dose was 73.7Gy (68.5–75.5Gy), mean FDG‐PET peak dose was 89.7Gy (73.5–103Gy), MLD was 12.3Gy (7.5–19.6Gy), and perfused MLD was 4.8Gy (0.9–12.1Gy). VMAT achieved higher dose to the FDG‐PET peak subvolume (p=0.01), while PBS delivered lower dose to lung (p<0.001). Voxelwise linear correlation between BTV dose and FDG‐PET uptake was higher for VMAT (R=0.93) and PBS+VMAT (R=0.94) compared to PBS alone (R=0.89).Conclusion:FLARE RT is feasible with VMAT and PBS. A combination of PBS for functional lung avoidance and VMAT for FDG‐PET dose escalation balances target/normal tissue objective tradeoffs. These results support future testing of FLARE RT safety and efficacy within a precision radiation oncology trial. This work was supported by a Research Scholar grant from the Radiological Society of North American Research & Education Foundation.