bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐H‐209‐01: Acceptance Procedures for Savi, Contura and ML Mammosite
Authors: Kyriacou A. 
Published: July 2016

Learnings Objectives:
Although brachytherapy is the oldest form of radiation therapy, the rapid advancement of the methods of dose calculation, treatment planning and treatment delivery pushes us to keep updating our knowledge and experience to new procedures all the time. Our purpose is to present the newest applicators used in Accelerated Partial Breast Irradiation (APBI) and the techniques of using them for a maximum effective treatment. Our objective will be to get the user familiar with the Savi, Contura and ML Mammosite from the detailed description and measurements to cavity eval and choice or size, to acceptance tests and use of each.
At the end of the session the attendants will be able to assist at the scanning of the patient for the first treatment, decide on the proper localization and immobilization devices, import the scans in the treatment planning system, perform the structure segmentation, reconstruct the catheters and develop a treatment plan using inverse planning (IPSA) or volume optimization. The attendant should be able to evaluate the quality of a treatment plan according to the ABS protocols and B39 after this session.
Our goal is that all the attendants to gain knowledge of all the quality assurance procedures required to be performed prior to a treatment, at the beginning of a treatment day, weekly, monthly and annualy on the remote afterloader, the treatment planning system and the secondary check system. We will provide tips for a consistent treatment delivery of the 10 fractions in a BID (twice daily) regimen.
TU‐H‐207B‐03: Radiomics & Regulatory Issues
Authors: Myers K. 
Published: July 2016

Research and development in radiomics for precision medicine have been advancing at a rapid pace, and can be extended to eventually be mature enough for integration into clinical practice. To facilitate advances in this field, investigators need updated information on research funding, regulatory matters, and clinical translation efforts. In this special radiomics symposium, the attendee will learn of various novel funding mechanisms – both past and present – that have been used to support a number of quantitative imaging and radiomics research and resource infrastructures. In addition, a regulatory presentation will be given to provide the attendee with an understanding of when a radiomics tool might require FDA clearance or approval, and with what supporting performance data. We will end with insights from a clinical radiologist who is greatly involved in quantitative imaging in order to enable the attendee to appreciate the needs and subtleties involved in moving radiomics into the clinical workflow.J. Boone, This is a memorial and not a funded event.
TU‐H‐207B‐04: Clinical Translation of Radiomics
Authors: Schwartz L. 
Published: July 2016

Research and development in radiomics for precision medicine have been advancing at a rapid pace, and can be extended to eventually be mature enough for integration into clinical practice. To facilitate advances in this field, investigators need updated information on research funding, regulatory matters, and clinical translation efforts. In this special radiomics symposium, the attendee will learn of various novel funding mechanisms – both past and present – that have been used to support a number of quantitative imaging and radiomics research and resource infrastructures. In addition, a regulatory presentation will be given to provide the attendee with an understanding of when a radiomics tool might require FDA clearance or approval, and with what supporting performance data. We will end with insights from a clinical radiologist who is greatly involved in quantitative imaging in order to enable the attendee to appreciate the needs and subtleties involved in moving radiomics into the clinical workflow.J. Boone, This is a memorial and not a funded event.
TU‐H‐CAMPUS‐IeP1‐02: Validation of a CT Monte Carlo Software
Authors: Schmidt R , Wulff J , Penchev P , Zink K 
Published: July 2016

Purpose:To validate the in‐house developed CT Monte Carlo calculation tool GMctdospp against reference simulation sets provided by the AAPM in the new report 195.Methods:Deposited energy was calculated in four segments (test 1) and two 10 cm long cylinders (test 2) inside a CTDI phantom (following case #4 of the AAPM report 195). The x‐ray point source of a given 120 kVp spectrum was collimated to a fan beam with two thicknesses (10 mm, 80 mm) for a static and a rotational setup. In addition, a given chest geometry was used to calculate deposited energy in several organs for a 0° static and a rotational beam (following case #5 of the AAPM report 195). The results of GMctdospp were compared against the particular mean value of the four quoted Monte Carlo codes (EGSnrc, Geant 4, MCNP and Penelope).Results:Calculated values showed no outliers in any of the cases. Differences between GMctdospp and the particular meanResults:Calculated values showed no outliers in any of the cases. Differences between GMctdospp and the particular mean value were always at similar magnitude compared to the quoted codes. For case #4 (CTDI phantom) the relative differences were within 1.5 %, on average 0.4 % and for case #5 (chest phantom) within 2.5 % and on average 0.85 %.Conclusion:The results confirmed an overall uncertainty of the Monte‐Carlo calculation chain in GMctdospp being <2.5 %, for most cases even better. This can be considered small compared to other sources of uncertainties, e.g. virtual source and patient models. The photon transport implemented in GMctdospp inside a voxel‐based patient geometry was successfully verified.
TU‐H‐CAMPUS‐IeP1‐05: A Framework for the Analytic Calculation of Patient‐Specific Dose Distribution Due to CBCT Scan for IGRT
Authors: Youn H , Kim J , Jeon H , Kim H , Cho M , Yun S , Nam J , Lee J , Lee J , Park D , Kim W , Ki Y , Kim D 
Published: July 2016

Purpose:To investigate the feasibility of an analytic framework to estimate patients’ absorbed dose distribution owing to daily cone‐beam CT scan for image‐guided radiation treatment.Methods:To compute total absorbed dose distribution, we separated the framework into primary and scattered dose calculations. Using the source parameters such as voltage, current, and bowtie filtration, for the primary dose calculation, we simulated the forward projection from the source to each voxel of an imaging object including some inhomogeneous inserts. Then we calculated the primary absorbed dose at each voxel based on the absorption probability deduced from the HU values and Beer's law. In sequence, all voxels constructing the phantom were regarded as secondary sources to radiate scattered photons for scattered dose calculation. Details of forward projection were identical to that of the previous step. The secondary source intensities were given by using scatter‐to‐ primary ratios provided by NIST. In addition, we compared the analytically calculated dose distribution with their Monte Carlo simulation results.Results:The suggested framework for absorbed dose estimation successfully provided the primary and secondary dose distributions of the phantom. Moreover, our analytic dose calculations and Monte Carlo calculations were well agreed each other even near the inhomogeneous inserts.Conclusion:This work indicated that our framework can be an effective monitor to estimate a patient's exposure owing to cone‐beam CT scan for image‐guided radiation treatment. Therefore, we expected that the patient's over‐exposure during IGRT might be prevented by our framework.
TU‐H‐CAMPUS‐JeP1‐04: Deformable Image Registration Performances in Pelvis Patients: Impact of CBCT Image Quality
Authors: Fusella M , Loi G , Fiandra C , Lanzi E 
Published: July 2016

Purpose:To investigate the accuracy and robustness, against image noise and artifacts (typical of CBCT images), of a commercial algorithm for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on real prostate patient images.Methods:The Anaconda DIR algorithm, implemented in RayStation was tested. Two specific Deformation Vector Fields (DVFs) were applied to the reference data set (CTref) using the ImSimQA software, obtaining two deformed CTs. For each dataset twenty‐four different level of noise and/or capping artifacts were applied to simulate CBCT images. DIR was performed between CTref and each deformed CTs and CBCTs. In order to investigate the relationship between image quality parameters and the DIR results (expressed by a logit transform of the Dice Index) a bilinear regression was defined.Results:More than 550 DIR‐mapped ROIs were analyzed. The Statistical analysis states that deformation strenght and artifacts were significant prognostic factors of DIR performances, while noise appeared to have a minor role in DIR process as implemented in RayStation as expected by the image similarity metric built in the registration algorithm. Capping artifacts reveals a determinant role for the accuracy of DIR results. Two optimal values for capping artifacts were found to obtain acceptable DIR results (DICE> 075/ 0.85). Various clinical CBCT acquisition protocol were reported to evaluate the significance of the study.Conclusion:This work illustrates the impact of image quality on DIR performance. Clinical issues like Adaptive Radiation Therapy (ART) and Dose Accumulation need accurate and robust DIR software. The RayStation DIR algorithm resulted robust against noise, but sensitive to image artifacts. This result highlights the need of robustness quality assurance against image noise and artifacts in the commissioning of a DIR commercial system and underlines the importance to adopt optimized protocols for CBCT image acquisitions in ART clinical implementation.
TU‐H‐CAMPUS‐IeP2‐04: Efficient Binary Tree Description of High Resolution Breast Models for in Silico Imaging
Authors: Badal A , Graff C , Zeng R , Samuelson F , Badano A 
Published: July 2016

Purpose:We introduce a new geometric model for Monte Carlo (MC) simulation of breast tomosynthesis and mammography images with very high resolution digital breast phantoms voxelized at resolutions down to 50 microns or less. This fine sampling of the anatomy is required to reproduce the spiculated lesions and microcalcifications visible in clinical mammograms with pixel sizes under 100 microns. Phantoms voxelized at this resolution require such a large amount of computer memory that it might not be possible to execute the simulation in regular computers or in Graphics Processing Units (GPU), limiting the realism that can be achieved in virtual clinical trials.Methods:The standard voxel‐based geometry model used in MC codes is inefficient in terms of memory use, because uniform regions are described with a large number of identical voxels. We have developed a new geometric model based on a binary tree partition of space. The binary tree recursively divides the object in two equal halves, alternating the x, y, and z dimensions, until a uniform volume or a final voxel are found. A top‐down search of the tree structure is used to determine the exact composition of a particular voxel during the ray‐tracing process.Results:The binary tree geometry was implemented in PENELOPE and its GPU‐accelerated version MC‐GPU. An example tomosynthesis scan was simulated using a computational breast phantom voxelized at 50 micron. This phantom was too large to fit in the GPU memory directly, but its binary tree version required 10 times less memory. The time spend searching the binary tree reduced the simulation speed in half approximately.Conclusion:We have introduced a new geometry model for in silico imaging of very high resolution phantoms. The binary tree model increases the computation time but, more importantly, enables the simulation of more detailed phantoms than previously possible.
TU‐H‐CAMPUS‐TeP2‐03: High Sensitivity and High Resolution Fiber Based Micro‐Detector for Sub‐Millimeter Preclinical Dosimetry
Authors: Izaguirre E , Pokhrel S , Hedrick S , Knewtson T 
Published: July 2016

Purpose:Current precision of small animal and cell micro‐irradiators has continuously increased during the past years. Currently, preclinical irradiators can deliver sub‐millimeter fields with micrometric precision but there are no water equivalent dosimeters to determine small field profiles and dose in the orthovoltage range of energies with micrometric resolution and precision. We have developed a fiber based micro‐dosimeter with the resolution and dosimetric accuracy required for radiobiological research.Methods:We constructed two prototypes of micro‐dosimeters based on different compositions of fiber scintillators to study the spatial resolution and dosimetric precision of small animal and cell micro‐irradiators. The first has green output and the second has blue output. The blue output dosimeter has the highest sensitivity because it matches the spectral sensitivity of silicon photomultipliers. A blue detector with 500um cross section was built and tested respect to a CC01 ion chamber, film, and the 1500um green output detector. Orthovoltage fields from 1×1mm2 to 5×5mm2 were used for detector characteristics comparison.Results:The blue fiber dosimeter shows great agreement with films and matches dose measurements with the gold‐standard ion chamber for 5×5mm2 fields. The detector has the appropriate sensitivity to measure fields from 1×1mm2 to larger sizes with a 1% dosimetric accuracy. The spatial resolution is in the sub‐millimeter range and the spectral matching with the photomultiplier allows reducing the sensor cross section even further than the presented prototype. These results suggest that scintillating fibers combined with silicon photomultipliers is the appropriate technology to pursue micro‐dosimetry for small animals and disperse cell samples.Conclusion:The constructed detectors establish a new landmark for the resolution and sensitivity of fiber based microdetectors. The validation of the detector in our small animal and cell irradiator shows that they are appropriate for preclinical and micro single cell irradiation quality assurance and dosimetry.
TU‐H‐CAMPUS‐TeP3‐02: In‐Situ Dose Painting Using Gold Nanoparticles Released From Cylindrically Shaped Fiducials During External Beam Radiation Therapy
Authors: Mueller R , Hao Y , Hesser J , Ngwa W 
Published: July 2016

Purpose:Recent studies have shown that the presence of Gold Nanoparticles (GNPs) in tumor tissue can lead to significant dose enhancement (DE) during External Beam Radiation Therapy (EBRT). In this in‐silico study we investigate EBRT with in‐situ dose painting using GNPs released from cylindrically shaped GNP‐loaded fiducials.Methods:Reported Biologically Target/Tumor Volumes (BTVs) for 12 prostate carcinoma patients were employed in this study. Distribution of the GNPs after burst release from the fiducial (1.5mm diameter and 5mm length) located in the center of the spherically assumed BTV were modeled by isotropic and free diffusion without boundary condition and under the assumption of superposition. An experimentally determined diffusion coefficient for 10nm nanoparticles was adapted for investigating other GNP sizes (2, 5, 15, and 20nm) using the Stokes‐Einstein equation. The maximum size of GNPs to achieve a minimal DE Factor (DEF) of 1.1 for 6MV EBRT using a fiducial‐load of 30mg/g was calculated for typical periods of 14 and 21 days after implantation. Further, the minimal fiducial‐load needed to achieve a clinically significant DEF of 1.2 was computed for 2nm GNPs.Results:Results showed that a minimal DEF of 1.1 could be reached for the smallest patient BTV using a maximal GNP size of 10nm and 20nm after 14 and 21 days, respectively. With increasing BTV smaller GNPs are required to ensure the same DEF. In particular, the largest BTV requires 2nm GNPs for periods of 14 and 21 days. Meanwhile, the required fiducial‐load to reach a minimal DEF of 1.2 after 14 days was found in the range of 17mg/g and 59mg/g for all reported BTVs.Conclusion:This preliminary study indicates a strong dependence on GNP size and fiducial‐load to realize a significant DE. The findings avail further research towards development of GNP‐loaded fiducials for significantly enhancing radiotherapy for cancer patients.
TU‐H‐CAMPUS‐TeP3‐03: Dose Enhancement by Gold Nanoparticles Around the Bragg Peak of Proton Beams
Authors: Kwon J , Sutherland K , Hashimoto T , Peng H , Xing L , Shirato H , Date H 
Published: July 2016

Purpose:To make clear the spatial distribution of dose enhancement around gold nanoparticles (GNPs) located near the proton Bragg peak, and to evaluate the potential of GNPs as a radio sensitizer.Methods:The dose enhancement by electrons emitted from GNPs under proton irradiation was estimated by Geant4 Monte Carlo simulation toolkit in two steps. In an initial macroscopic step, 100 and 195 MeV proton beams were incident on a water cube, 30 cm on a side. Energy distributions of protons were calculated at four depths, 50% and 75% proximal to the Bragg peak, 100% peak, and 75% distal to the peak (P50, P75, Peak, and D75, respectively). In a subsequent microscopic step, protons with the energy distribution calculated above were incident on a 20 nm diameter GNP in a nanometer‐size water box and the spatial distribution of dose around the GNP was determined for each energy distribution. The dose enhancement factor (DEF) was also deduced.Results:The dose enhancement effect was spread to several tens of nanometers in the both depth and radial directions. The enhancement area increased in the order of P50, P75, Peak, and D75 for both cases with 100 and 195 MeV protons. In every position around the Bragg peak, the 100 MeV beam resulted in a higher dose enhancement than the 195 MeV beam. At P75, the average and maximum DEF were 3.9 and 17.0 for 100 MeV, and 3.5 and 16.2 for 195 MeV, respectively. These results indicate that lower energy protons caused higher dose enhancement in this incident proton energy range.Conclusion:The dose enhancement around GNPs spread as the position in the Bragg peak region becomes deeper and depends on proton energy. It is expected that GNPs can be used as a radio sensitizer with consideration of the location and proton beam energy.
WE‐A‐BRC‐01: Introduction to the Certificate Course
Authors: Palta J. 
Published: July 2016

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments.

Learning Objectives:
Understand the impact of clinical and technical quality on outcomes
Understand the importance of quality care in radiation oncology
Learn to assess the impact of quality on clinical outcomesD. Followill, NIH Grant CA180803
WE‐AB‐BRB‐03: Real‐Time Volumetric Scintillation Dosimetry for Radiation Therapy
Authors: Beddar S. 
Published: July 2016

Despite widespread IMRT treatments at modern radiation therapy clinics, precise dosimetric commissioning of an IMRT system remains a challenge. In the most recent report from the Radiological Physics Center (RPC), nearly 20% of institutions failed an end‐to‐end test with an anthropomorphic head and neck phantom, a test that has rather lenient dose difference and distance‐to‐agreement criteria of 7% and 4 mm. The RPC report provides strong evidence that IMRT implementation is prone to error and that improved quality assurance tools are required. At the heart of radiation therapy dosimetry is the multidimensional dosimeter. However, due to the limited availability of water‐equivalent dosimetry materials, research and development in this important field is challenging. In this session, we will review a few dosimeter developments that are either in the laboratory phase or in the pre‐commercialization phase. 1) Radiochromic plastic. Novel formulations exhibit light absorbing optical contrast with very little scatter, enabling faster, broad beam optical CT design. 2) Storage phosphor. After irradiation, the dosimetry panels will be read out using a dedicated 2D scanning apparatus in a non‐invasive, electro‐optic manner and immediately restored for further use. 3) Liquid scintillator. Scintillators convert the energy from x‐rays and proton beams into visible light, which can be recorded with a scientific camera (CCD or CMOS) from multiple angles. The 3D shape of the dose distribution can then be reconstructed. 4) Cherenkov emission imaging. Gated intensified imaging allows video‐rate passive detection of Cherenkov emission during radiation therapy with the room lights on.

Learning Objectives:
To understand the physics of a variety of dosimetry techniques based upon optical imaging
To investigate the strategies to overcome respective challenges and limitations
To explore novel ideas of dosimeter designSupported in part by NIH Grants R01CA148853, R01CA182450, R01CA109558. Brian Pogue is founder and president of the company DoseOptics LLC, dedicated to developing and commercializing the first dedicated Cerenkov imaging camera and system for radiation dose imaging. Work reported in this talk does not involve the use of DoseOptics technology.; H. Li, this work was supported in part by NIH Grant No. R01CA148853; S. Beddar, NIH funding R01‐CA182450