bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐AB‐BRC‐11: Moving a GPU‐OpenCL‐Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling
Authors: Tian Z , Li Y , Folkerts M , Jiang S , Jia X 
Published: July 2016

Purpose:We have previously developed a GPU‐OpenCL‐based MC dose engine named goMC with built‐in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam‐commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans.Methods:Our commissioning method is to automatically adjust the relative weights among the sub‐sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf‐sequencing into source sampling. Specifically, instead of sampling source particles control‐point by control‐point and rejecting the particles blocked by MLC, we assigned a control‐point index to each sampled source particle, according to MLC leaf‐open duration of each control‐point at the pixel where the particle intersects the iso‐center plane.Results:Our auto‐commissioning method decreased distance‐to‐agreement (DTA) of depth dose at build‐up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root‐mean‐square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed‐up factor.Conclusion:Our studies have demonstrated the feasibility and effectiveness of our auto‐commissioning approach and new efficient source sampling strategy, implying the potential of our GPU‐based MC dose engine goMC for routine clinical use.
TU‐AB‐BRA‐02: An Efficient Atlas‐Based Synthetic CT Generation Method
Authors: Han X 
Published: July 2016

Purpose:A major obstacle for MR‐only radiotherapy is the need to generate an accurate synthetic CT (sCT) from MR image(s) of a patient for the purposes of dose calculation and DRR generation. We propose here an accurate and efficient atlas‐based sCT generation method, which has a computation speed largely independent of the number of atlases used.Methods:Atlas‐based sCT generation requires a set of atlases with co‐registered CT and MR images. Unlike existing methods that align each atlas to the new patient independently, we first create an average atlas and pre‐align every atlas to the average atlas space. When a new patient arrives, we compute only one deformable image registration to align the patient MR image to the average atlas, which indirectly aligns the patient to all pre‐aligned atlases. A patch‐based non‐local weighted fusion is performed in the average atlas space to generate the sCT for the patient, which is then warped back to the original patient space. We further adapt a PatchMatch algorithm that can quickly find top matches between patches of the patient image and all atlas images, which makes the patch fusion step also independent of the number of atlases used.Results:Nineteen brain tumour patients with both CT and T1‐weighted MR images are used as testing data and a leave‐one‐out validation is performed. Each sCT generated is compared against the original CT image of the same patient on a voxel‐by‐voxel basis. The proposed method produces a mean absolute error (MAE) of 98.6±26.9 HU overall. The accuracy is comparable with a conventional implementation scheme, but the computation time is reduced from over an hour to four minutes.Conclusion:An average atlas space patch fusion approach can produce highly accurate sCT estimations very efficiently. Further validation on dose computation accuracy and using a larger patient cohort is warranted. The author is a full time employee of Elekta, Inc.
TU‐AB‐BRA‐10: Treatment of Gastric MALT Lymphoma Utilizing a Magnetic Resonance Image‐Guided Radiation Therapy (MR‐IGRT) System: Evaluation of Gating Feasibility
Authors: Mazur T , Gach H , Chundury A , Fischer‐Valuck B , Huang J , Thomas M , Green O 
Published: July 2016

Purpose:To evaluate the feasibility of real‐time, real‐anatomy tracking and gating for gastric lymphoma patients treated with magnetic resonance image‐guided radiation therapy (MR‐IGRT)Methods:Over the last 2 years, 8 patients with gastric lymphoma were treated with 0.3‐T, Co‐60 MR‐IGRT. Post‐treatment analysis of real‐time cine imaging in the sagittal plane during each patient's treatment revealed significant motion of the stomach. While this motion was accounted for with generous PTV margins, the system's capability for real‐time, real‐anatomy tracking could be used to reduce treatment margins by gating. However, analysis was needed for the feasibility of gating using only the single available sagittal imaging plane. While any plane may be chosen, if the stomach moves differently where it is not being observed, there may potentially be a mistreatment. To that end, imaging with healthy volunteers was done to ascertain stomach motion over 2–4 min by analyzing multiple parallel sagittal and coronal planes 0.75 cm apart. The stomach was contoured on every slice, and the mean displacement between pairs of contour centroids was used to determine the amount of overall motion.Results:The mean displacement of the centroid in the image plane was 4.3 ± 0.7 mm. The greatest observed motion was more medial with respect to the patient, and less motion laterally, which implies that gating on a plane located closer to MRI isocenter will provide the more conservative scenario as it will turn the radiation delivery off when the stomach is observed to move outside a predetermined boundary.Conclusion:The stomach was observed to move relatively uniformly throughout, with maximum extent of motion closer to where most MRI systems have the best spatial integrity (near isocenter). Analysis of possible PTV margins from the healthy volunteer study (coupled with previous patient data on interfraction volumetric stomach deformation) is pending.
TU‐AB‐BRA‐12: Quality Assurance of An Integrated Magnetic Resonance Image Guided Adaptive Radiotherapy Machine Using Cherenkov Imaging
Authors: Andreozzi J , Mooney K , Bruza P , Curcuru A , Saunders S , Gladstone D , Pogue B , Green O 
Published: July 2016

Purpose:To investigate the viability of using Cherenkov imaging as a fast and robust method for quality assurance tests in the presence of a magnetic field, where other instruments can be limited.Methods:Water tank measurements were acquired from a clinically utilized adaptive magnetic resonance image guided radiation therapy (MR‐IGRT) machine with three multileaf‐collimator equipped 60Co sources. Cherenkov imaging used an intensified charge coupled device (ICCD) camera placed 3.5m from the treatment isocenter, looking down the bore of the 0.35T MRI into a water tank. Images were post‐processed to make quantitative comparison between Cherenkov light intensity with both film and treatment planning system predictions, in terms of percent depth dose curves as well as lateral beam profile measurements. A TG‐119 commissioning test plan (C4: C‐Shape) was imaged in real‐time at 6.33 frames per second to investigate the temporal and spatial resolution of the Cherenkov imaging technique.Results:A .33mm/pixel Cherenkov image resolution was achieved across 1024×1024 pixels in this setup. Analysis of the Cherenkov image of a 10.5×10.5cm treatment beam in the water tank successfully measured the beam width at the depth of maximum dose within 1.2% of the film measurement at the same point. The percent depth dose curve for the same beam was on average within 2% of ionization chamber measurements for corresponding depths between 3–100mm. Cherenkov video of the TG‐119 test plan provided qualitative agreement with the treatment planning system dose predictions, and a novel temporal verification of the treatment.Conclusions:Cherenkov imaging was successfully used to make QA measurements of percent depth dose curves and cross beam profiles of MRI‐IGRT radiotherapy machines after only several seconds of beam‐on time and data capture; both curves were extracted from the same data set. Video‐rate imaging of a dynamic treatment plan provided new information regarding temporal dose deposition.This study has been funded by NIH grants R21EB17559 and R01CA109558, as well as Norris Cotton Cancer Center Pilot funding.
TU‐AB‐202‐02: Deformable Image Registration Accuracy Between External Beam Radiotherapy and HDR Brachytherapy CT Images for Cervical Cancer Using a 3D‐Printed Deformable Pelvis Phantom
Authors: Miyasaka Y , Kadoya N , Kuroda Y , Ito K , Chiba M , Nakajima Y , Sato K , Dobashi S , Takeda K , Jingu K 
Published: July 2016

Purpose:Accurate deformable image registration (DIR) between external beam radiotherapy (EBRT) and HDR brachytherapy (BT) CT images in cervical cancer is challenging. DSC has been evaluated only on the basis of the consistency of the structure, and its use does not guarantee an anatomically reasonable deformation. We evaluate the DIR accuracy for cervical cancer with DSC and anatomical landmarks using a 3D‐printed pelvis phantom.Methods:A 3D‐printed, deformable female pelvis phantom was created on the basis of the patient's CT image. Urethane and silicon were used as materials for creating the uterus and bladder, respectively, in the phantom. We performed DIR in two cases: case‐A with a full bladder (170 ml) in both the EBRT and BT images and case‐B with a full bladder in the BT image and a half bladder (100 ml) in the EBRT image. DIR was evaluated using DSCs and 70 uterus and bladder landmarks. A Hybrid intensity and structure DIR algorithm with two settings (RayStation) was used.Results:In the case‐A, DSCs of the intensity‐based DIR were 0.93 and 0.85 for the bladder and uterus, respectively, whereas those of hybrid‐DIR were 0.98 and 0.96, respectively. The mean landmark error values of intensity‐based DIR were 0.73±0.29 and 1.70±0.19 cm for the bladder and uterus, respectively, whereas those of Hybrid‐DIR were 0.43±0.33 and 1.23±0.25 cm, respectively. In both cases, the Hybrid‐DIR accuracy was better than the intensity‐based DIR accuracy for both evaluation methods. However, for several bladder landmarks, the Hybrid‐DIR landmark errors were larger than the corresponding intensity‐based DIR errors (e.g., 2.26 vs 1.25 cm).Conclusion:Our results demonstrate that Hybrid‐DIR can perform with a better accuracy than the intensity‐based DIR for both DSC and landmark errors; however, Hybrid‐DIR shows a larger landmark error for some landmarks because the technique focuses on both the structure and intensity.
TU‐AB‐202‐04: Development of a DeformableImage Registration (DIR) Error Correction Method Employing Kolmogorov‐Zurbenko(KZ) Filter
Authors: Liang X , Wang C , Chang Z , Yin F , Cai J 
Published: July 2016

Purpose:This study aims to develop a DIR error correction method capable of utilizing sparse ground‐truth motion information and recovering missing data with the Kolmogorov‐Zurbenko (KZ) filter.Methods:The error correction method employs a two‐step approach. First, sparse ground‐truth displacement vectors are integrated into a pre‐correction deformable vector field (DVF) to estimate a post‐correction DVF with coarse resolution. Second, the coarse post‐correction DVF is boosted to a full‐resolution DVF through convolution with the KZ filter. To validate the use of the KZ filter for missing data recovery, recovery errors were determined by comparing a DVF recovered from down‐sampling with the original full‐resolution DVF. The entire error correction method was tested on an in‐house developed digital lung motion phantom consisting of a primary volume, a DVF, and a secondary volume synthesized by applying the DVF on the primary volume. Five pre‐correction DVFs were obtained by performing DIR between the two volumes using Velocity, MIM, ILK and OHS algorithms in DIRART toolbox, and Elastix, and then corrected. Primary volumes were synthesized with pre‐ and post‐correction DVFs, respectively. The error correction method was evaluated with pre‐ and post‐correction registration errors, and intensity errors in synthesized primary volumes.Results:Our test results for sparsely down‐sampled (<0.4%) DVFs showed that the KZ filter outperformed the cubic polynomial interpolation method for whole lung DVF map recovery in terms of median error (0.60mm vs 0.73mm) and mean error (1.18mm vs 1.29mm). Pre‐ and post‐correction 3D registration errors per voxel for Velocity, MIM, ILK, OHS, and Elastix are reduced by 2.39 mm on average. Pre‐ and post‐correction intensity errors are reduced by 0.37 in unit of image intensity on average.Conclusion:We have implemented a two‐step method capable of utilizing sparse ground‐truth displacement vectors for DIR error reduction, allowing DIR accuracy improvement utilizing clinically available motion data.This study is supported by NIH grant 1R21CA165384.
TU‐AB‐202‐09: Performance of Cross‐Modality DIR Algorithms Using Images Computed from a Novel, Tissue‐Like Phantom Capable of Reproducible Degrees of Deformation
Authors: Ionascu D , Castillo E , Qin A , Solis D , Lack D , Sandhu R , Yee S , Guerrero T 
Published: July 2016

Purpose:Develop a framework for the spatial accuracy assessment of multi‐modality deformable image registration (DIR) based on precise and reproducible deformations of a novel prostate phantom.Methods:An existing, tissue‐like prostate phantom has been adapted to allow quantifiable, reproducible, and variable degrees of volumetric deformation. This phantom is sequentially deformed into 11 stationary deformation states that can be individually imaged using CT, MRI, US and CBCT. The deformation is induced programmatically by changing the water volume of a balloon using a precise syringe pusher (5ml increments), effectively displacing and deforming the prostate and surrounding tissue. To demonstrate the phantom's utility as a DIR assessment tool, selected DIR algorithms (CT<‐>MR: Normalized Mutual Information, MR‐MR: Mutual Information, CT‐CT: Local Cross‐Correlation+Mutual Information) were applied to intra and cross‐imaging modalities depicting varying degrees of deformation. DIR accuracy was assessed via the DICE overlap score, calculated between the deformed prostate contour (computed by warping the manually delineated contour on the initial deformation state) and the manually delineated contour on the target deformation state.Results:DICE coefficients show excellent agreement of individual deformation states for MR and CT, hence validating the reproducibility of the induced deformation (< 1.0 + 0.1 %). Intra‐modality DIR (MR‐MR, CT‐CT) shows good performance (0.93–0.98). CT‐to‐MR performance is acceptable only for the closest 5–6 deformation states (> 0.94), while the DIR solutions for farthest 6 deformation states (0.78–0.92) are erroneous or artifactual. MR‐to‐CT DIR performance is demonstrably weaker (0.0–0.96) yielding asymmetrical errors w.r.t. the initial deformation state (no‐deformation vs. maxdeformation). Moreover, the first 3 deformed contours show zero overlap with the manual contours.Conclusion:We have developed a novel prostate phantom capable of gradual and reproducible deformation, and demonstrated its ability to assess multi‐modality (CT<‐>MR) DIR algorithm performance and range. Due to the phantom multi‐imaging capabilities, other cross‐imaging DIR algorithms can now be explored.
TU‐AB‐202‐10: How Effective Are Current Atlas Selection Methods for Atlas‐Based Auto‐Contouring in Radiotherapy Planning?
Authors: Peressutti D , Schipaanboord B , van Soest J , Lustberg T , van Elmpt W , Kadir T , Dekker A , Gooding M 
Published: July 2016

Purpose:To investigate the effectiveness of atlas selection methods for improving atlas‐based auto‐contouring in radiotherapy planning.Methods:275 H&N clinically delineated cases were employed as an atlas database from which atlases would be selected. A further 40 previously contoured cases were used as test patients against which atlas selection could be performed and evaluated. 26 variations of selection methods proposed in the literature and used in commercial systems were investigated. Atlas selection methods comprised either global or local image similarity measures, computed after rigid or deformable registration, combined with direct atlas search or with an intermediate template image. Workflow Box (Mirada‐Medical, Oxford, UK) was used for all auto‐contouring. Results on brain, brainstem, parotids and spinal cord were compared to random selection, a fixed set of 10 “good” atlases, and optimal selection by an “oracle” with knowledge of the ground truth. The Dice score and the average ranking with respect to the “oracle” were employed to assess the performance of the top 10 atlases selected by each method.Results:The fixed set of “good” atlases outperformed all of the atlas‐patient image similarity‐based selection methods (mean Dice 0.715 c.f. 0.603 to 0.677). In general, methods based on exhaustive comparison of local similarity measures showed better average Dice scores (0.658 to 0.677) compared to the use of either template image (0.655 to 0.672) or global similarity measures (0.603 to 0.666). The performance of image‐based selection methods was found to be only slightly better than a random (0.645). Dice scores given relate to the left parotid, but similar results patterns were observed for all organs.Conclusion:Intuitively, atlas selection based on the patient CT is expected to improve auto‐contouring performance. However, it was found that published approaches performed marginally better than random and use of a fixed set of representative atlases showed favourable performance.This research was funded via InnovateUK Grant 600277 as part of Eurostars Grant E!9297.DP,BS,MG,TK are employees of Mirada Medical Ltd.
TU‐B‐201‐03: Accounting for MV Imaging Dose and the Future of MV Imaging
Authors: Flynn R. 
Published: July 2016

Radiotherapy is in the era of image guided radiation therapy (IGRT) in which imaging procedures are routinely performed for patient positioning, and target localization. The additional imaging dose delivered may increase risk to the patient and therefore needs to be managed. This lecture provides an overview of the AAPM TG‐180 which is charged with: providing an overview on imaging dose including megavoltage electronic portal imaging (MV EPI), kilovoltage digital radiography (kV DR), Tomotherapy MV‐CT, megavoltage cone‐beam CT (MV‐CBCT) and kilovoltage cone‐beam CT (kV‐CBCT) as well as providing general guidelines for commissioning and managing imaging dose calculations. The dose to radiotherapy (RT) patients resulting from different image guidance procedures is reviewed and recommendations for managing the imaging dose are provided. Different techniques for reducing the image guidance dose are summarized. A recommended threshold beyond which imaging dose should be considered in the treatment planning process is discussed. This lecture also discusses kilovoltage imaging dose determination by calculation and estimation, and inclusion in treatment planning as well as accounting for MV imaging dose and the future of MV imaging.

Learning Objectives:
Learn the different image guidance modalities, typical organ doses resulting from different image procedures, and techniques to reduce the imaging dose;
Understand the imaging dose threshold and rationale for accounting for the imaging dose;
Learn how to account for kV imaging dose
Learn how to account for MV imaging dose and understand the future of MV imaging
TU‐D‐204‐00: The Gadget: Making of the Atomic Bomb
Authors: Reiser Ingrid 
Published: July 2016

Making of the Atomic Bomb2015 is the 70th anniversary of the detonation of the first atomic bomb. Since then, few scientific issues have aroused so much public controversy as the effects of radiation. This lecture will present the extraordinary historical genesis and the thoughts of great men and women in the development of the atomic bomb. In addition, the difficult military and political decisions will be covered such as: target selection, the debate over whether to give the Japanese government a demonstration of its power and whether to use it at all. Also, were the German and Japanese scientists developing there own bomb? Declassified top secret documents now help in answering some of these questions.
TU‐D‐204‐01: Making of the Atomic Bomb
Authors: Strubler K. 
Published: July 2016

Making of the Atomic Bomb2015 is the 70th anniversary of the detonation of the first atomic bomb. Since then, few scientific issues have aroused so much public controversy as the effects of radiation. This lecture will present the extraordinary historical genesis and the thoughts of great men and women in the development of the atomic bomb. In addition, the difficult military and political decisions will be covered such as: target selection, the debate over whether to give the Japanese government a demonstration of its power and whether to use it at all. Also, were the German and Japanese scientists developing there own bomb? Declassified top secret documents now help in answering some of these questions.
TU‐D‐201‐04: Veracity of Data Elements in Radiation Oncology Incident Learning Systems
Authors: Kapur A , Evans S , Brown D , Ezzell G , Hoopes D , Dieterich S , Kapetanovic K , Tomlinson C 
Published: July 2016

Purpose:Incident learning systems encompass volumes, varieties, values, and velocities of underlying data elements consistent with the V's of big data. Veracity, the 5th V however exists only if there is high inter‐rater reliability (IRR) within the data elements. The purpose of this work was to assess IRR in the nationally deployed RO‐ILS: Radiation Oncology‐Incident Learning System (R) sponsored by the American Society for Radiation Oncology (ASTRO) and the American Association of Physicists in Medicine (AAPM).Methods:Ten incident reports covering a wide range of scenarios were created in standardized narrative and video formats and disseminated to 67 volunteers of multiple disciplines from 26 institutions along with two published narratives from the International Commission of Radiological Protection to assess IRR on a nationally representative level. The volunteers were instructed to independently enter the associated data elements in a test version of RO‐ILS over a 3‐week period. All responses were aggregated into a spreadsheet to assess IRR using free‐marginal kappa metrics.Results:48 volunteers from 21 institutions completed all reports in the study period. The average kappa score for all raters across all critical data elements was 0.659 [range 0.326–1.000]. Statistically significant differences (p <0.05) were noted between reporters of different disciplines and raters with varying levels of experience. Kappa scores were high for event classification (0.781) and contributory factors (0.777) and low for likelihood‐of‐harm (0.326). IRR was highest among AAPM‐ASTRO members (0.672) and lowest among trainees (0.463).Conclusion:A moderate‐to‐substantial level of IRR in RO‐ILS was noted in this study. Although the number of events reviewed in this study was small, opportunities for improving the taxonomy for the lower scoring data elements as well as specific educational targets for training were identified by assessing data veracity quantitatively. This is expected to improve the quality of the data garnered from RO‐ILS.