bluuebunny/crossref_metadata_2025_split huggingface dataset:
TH‐AB‐BRD‐01: Basic Physics and Quality Assurance of Proton Therapy
Authors: Arjomandy B. 
Published: June 2015

The goal of this session is to introduce the audience to the physics, dosimetry, treatment planning techniques, and quality assurances (QA) procedures used in proton therapy. The course material covers the physics of proton interaction with matter and physical characteristics of clinical proton beams. It will provide information on proton delivery systems and beam delivery techniques for double scattering (DS), uniform scanning (US), and pencil beam scanning (PBS). The session covers the treatment planning strategies used in DS, US, and PBS for various anatomical sites, methods to address uncertainties in proton therapy and uncertainty mitigation to generate robust treatment plans. Challenges involved in the motion management in proton therapy will also be discussed. It will also include the methodology for proton beam dosimetry for clinical commissioning, beam calibration, and quality assurance checks.Learning Objectives:

Gain knowledge on physics, dosimetry, and treatment planning for proton therapy including intensity modulated proton therapy.
Be acquainted with the procedures involved in machine and patient treatment field specific QA.
Understand the uncertainties associated with proton therapy and currently used strategies for their mitigation in treatment planning.
TH‐AB‐BRB‐01: Solving Larger IMRT Problems by Enhanced Reduced‐Order Constrained Optimization
Authors: Nourzadeh H , Radke R , Jackson A , Bakr S , Tuomaala S 
Published: June 2015

Purpose:To report the latest improvements in the pipeline of the reduced‐order constrained optimization (ROCO) method for fast IMRT planning.Methods:The ROCO method involves the characterization of the solution space of the underlying fluence map IMRT optimization problem in a compact form, which enables forming a clinically tractable constrained optimization problem. The offline part of the method consists of three stages: sampling, learning the effective mode space, and mode‐dose calculation. In the sampling stage, a set of unconstrained optimization problems is solved, each corresponding to a different choice of weights and dose‐volume limits. As opposed to previous implementations, we preprocess the samples, identify the effective beamlets with non‐zero variances, and use them to attain a compact representation of the fluence space using Principal Component Analysis (PCA). In the mode‐dose calculation stage, the dose corresponding to each mode is computed based on the underlying full dose‐calculation technique. We offer a new formulation for handling possible negative mode elements, exploiting linearity of the mode‐dose map. In the online phase, a constrained optimization problem with a minimal number of constraints is solved over the basis coefficients spanning the reduced‐size space.Results:The results suggest that for a typical prostate case, the PCA stage can be performed about 5 times faster. Moreover, the mode dose calculation performance is accelerated by a factor of 2. Apart from computational efficiency, we also observed significantly lower memory demand for ROCO model compared to optimization models relying on pre‐calculation of dose deposition coefficients (DDCs). The proposed method has been integrated into the Varian Eclipse version 13.5 treatment planning system as a stand‐alone application.Conclusion:The new implementation has led a substantial savings in memory requirements and computational effort, allowing larger IMRT problems with finer beamlet resolution to be addressed with the available memory resources in less time.
TH‐AB‐BRB‐08: Optimizing Global Liver Function in Liver SBRT Treatment Planning
Authors: Wu V , Epelman M , Romeijn E , Feng M , Cao Y , Wang H , Ten Haken R , Matuszak M 
Published: June 2015

Purpose:Liver SBRT patients have variable pre‐treatment liver function, which strongly influences liver toxicity risk. Previous studies include a “perfusion‐weighted” mean dose model as a surrogate for liver function in plan optimization. This work investigates the benefit of using a more sophisticated dose‐response model that incorporates two important dose thresholds: (i) based on pre‐treatment function, a significant low‐dose may need to be exceeded before noticeable damage is done, and (ii) a high‐dose saturation point, beyond which no additional damage is done.Methods:Voxel‐based liver perfusion from DCE‐MRI was obtained. Two optimization models subject to the same linear dose constraints (e.g., minimum target EUD, maximum critical structure dose) were compared: the original linear model, which use pre‐treatment perfusion‐weighted mean liver dose only, and a new model designed to directly optimize the predicted post‐treatment global liver function. The latter, a highly non‐linear non‐convex problem, was approximately solved by optimizing a piece‐wise linear approximation of the objective function with a customized mixed‐integer linear programming (MILP) based algorithm. 2D synthetic and 3D clinical cases were studied to assess the potential benefit of the new model.Results:Compared to those of the original model, dose distributions for the functional dose response model take advantage of voxels with saturated damage to deliver the required dose to the target instead of inflicting additional damage on other well‐functioning voxels. This leads to an improvement in predicted post‐treatment global liver function. The customized solution method also improves optimization efficiency compared to solving the MILP conventionally.Conclusion:Functional imaging such as DCE‐MRI can be used during treatment planning to maximize potential post‐treatment function. However, simple approximations such as minimization of perfusion‐weighted mean dose may not be sufficient. Alternatively, a dose‐response model that reflects response threshold and saturation effects was shown to improve the prediction of post‐treatment function in liver SBRT.Supported by P01 CA 059827
TH‐AB‐BRA‐02: Generation of 3D Dosimetric Reference Datasets for Commissioning and Validation of 192Ir Brachytherapy Model‐Based Dose Calculation Software
Authors: Ma Y , Vijande J , Ballester F , Tedgren Asa Carlsson , Granero D , Haworth A , Mourtada F , Fonseca G , Zourari K , Papagiannis P , Rivard M , Siebert F , Sloboda R , Smith R , Thomson R , Verhaegen F , Beaulieu L 
Published: June 2015

Purpose:Previously, generic HDR 192Ir source and shielded applicator were designed by WG‐ MBDCA, the AAPM‐ESTRO‐ABG Working Group on model‐based dose calculation algorithms. TPS vendors have incorporated both into their TPS. A charge of WG‐MBDCA is to develop a limited number of well‐defined test cases and perform MBDCA dose calculations and comparisons. Here, we describe the test cases proposed, the 3D dosimetric data generation process and the 3D gamma analysis performed.Methods:A voxelized phantom of 512×512×512 voxels (HU=‐1024,Air), with each voxel being 1×1×1 mm3, containing a concentric cubic contour structure (HU=0,Water) of dimension 201×201×201 voxels, was created in the DICOM‐ RT format. Three configurations were tested: i) source located at the center with surrounding structure assigned to water to mimic TG‐43 conditions, ii) source displaced +7 cm along the × axis, iii) source located at the center with the shielded applicator in place. Advanced Collapsed‐cone Engine (ACE, Elekta) and AcurosBV (Varian) were benchmarked. Reference datasets were independently produced by different groups using BrachyDose (1010 photons), GEANT4(4×1010), Penelope (2×1010), MCNP5(2 x1010), MCNP6(1011), and ALGEBRA(4×1010) Monte Carlo (MC) dose calculation platforms.Results:For the three configurations, MC agreed within 1% for the volume bounded by the 1% isodose surface; MCNP6 data sets were designated as reference (statistical error < 0.2% across the phantom). A 2%/1mm 3D γ‐ index criteria was used, within the volume bounded by 5% isodose surface, to account for both dose difference and source placement errors in TPS. Voxel pass rates were 95.2%, 99.5% and 90% for ACE and 98%, 98.4% and 95.9% for AcurosBV, respectively.Conclusion:The evaluated test cases are suitable for MBDCA QA. DICOM‐RT files are being integrated into the joint AAPM/IROC Houston registry to support end‐user TPS software commissioning.
TH‐AB‐BRA‐06: Independent Automatic Catheter Digitization Algorithm for High Dose Rate (HDR) Brachytherapy Quality Improvement (QI) and Quality Assurance (QA)
Authors: Dong P , Cunha J 
Published: June 2015

Purpose:Individual‐user and inter‐user variability during manual catheter digitization for interstitial HDR brachytherapy can be significant since the process can time consuming and error prone. We present an algorithm and workflow for catheter digitization that can be used for independent verification of manual digitization (QA) or automatic digitization (QI).Methods:After DICOM CT images are imported into the TPS, this proximal end of each catheter is located and numbered on a single slice near the needle template. The DICOM RP and CT files are then exported for digitization. Each transverse CT slice is smoothed with a Gaussian filter, then a convolution kernel finds the Laplacian of the CT image. This process highlights regions of rapid density change. A sliding window filter is applied to the image afterwards to locate each catheter center. The catheter is traced and geometry digitized from the needle template to the tip slice by slice, similar to the manual procedure. All the contour points are written into the original DICOM RP file and imported back into the TPS for planning. The difference between the manual digitization and the automatic digitization was quantified with a RMS calculation of the deviation between the manual and automatic catheter geometries for 11 clinical cases.Results:The RMS difference between the automatic and manual digitization was 0.50±0.04mm. Execution time for automatic digitization is ∼3 minutes (analysis ∼2 min; DICOM export/import ∼1 minute).Conclusion:This automatic catheter digitization method can be used as both a QA and QI tool. As a QI it is executed instead of manual catheter digitization. The algorithmic nature ensures reduced individual‐ and intra‐user variability and reduces digitization time. As a QA tool, the algorithm can be used to validate the manually generated catheter pattern to ensure digitization integrity.
TH‐AB‐BRA‐08: Impact of Approximating the Differential Photon Fluence On the Accuracy of the Spectroscopic Dose‐Rate Constant
Authors: Malin M , Bartol L , DeWerd L 
Published: June 2015

Purpose:To investigate why dose‐rate constants computed using the spectroscopic technique do not agree with those computed using standard Monte Carlo (MC) techniques. Published work shows that the disagreement between the two techniques is not attributable to any currently characterized source of uncertainty. This work examined if approximations to the differential photon fluence made by the spectroscopic technique are the cause of the disagreement. Specifically, approximations of the spatial, angular and energy distributions of photons leaving the source were studied.Methods:Phase spaces of the fluence leaving the encapsulation of 14 125‐I and 6 103‐Pd models were modified to reflect one of the approximated distributions while the other distributions were left unaltered. The dose‐rate constant was computed from the modified phase space using MC and compared to that computed using standard MC techniques. This process was repeated for each assumption with each source model.Results:Approximations to the differential photon fluence used in the spectroscopic technique cause offsets in the dose‐rate constant of up to 5.3% relative to standard MC techniques. The largest offsets were introduced by the approximated angular fluence distribution. Approximations of the spatial distribution leaving the encapsulation caused smaller discrepancies with an average discrepancy of −0.4% relative to standard MC techniques. Approximations to the energy distribution introduced an average discrepancy of 0.1% relative to standard MC techniques, which is within the uncertainty of the computations.Conclusion:Current approximations of the differential photon fluence used in the spectroscopic technique reduce the accuracy of the technique and are a source of uncertainty not currently considered with the technique. Either more accurate fluence distributions need to be used when computing the dose‐rate constant with the spectroscopic technique, or the additional uncertainties arising from the approximated distributions need to be included when using the current calculation technique.
TH‐AB‐BRA‐09: Radiation and Thermal Dosimetric Considerations of a Combination of Hyperthermia and Thermo‐Brachytherapy Seeds
Authors: Warrell G. , Shvydka D. , Parsai E.I. 
Published: June 2015

Purpose:A novel dual‐modality thermo‐brachytherapy (TB) seed invented by our group offers a potential means of adding hyperthermia to brachytherapy of prostate tumors, either simultaneously for dose enhancement or as a salvage therapy. To improve the minimum target temperature and temperature uniformity with this implant, we propose use of adjuvant hyperthermia‐only (HT‐only) seeds in unused spots within the needles used to implant the TB seeds. The impact on temperatures reached within the target, temperature uniformity, and the radiation interseed effect due to HT‐only seeds were studied.Methods:Previous patient plans were reproduced in a Monte Carlo (MCNP5) model to generate dose distributions of TB seeds, with and without additional HT‐ only seeds. Temperature distributions for these simulated implants were obtained with the finite element analysis solver COMSOL Multiphysics. In‐house software calculated dose‐volume and temperature‐volume histograms from these distributions.Results:Use of additional hyperthermia‐only seeds substantially improves the temperature uniformity of the implant. The power generation required of the seeds for adequate temperature coverage (90% of the PTV heated to 42 °C) increases exponentially with the blood perfusion rate (BPR) of the implanted tissue, but decreases with an increase in the seeds’ Curie temperature. Large blood vessels within the target decrease the volume of the PTV reaching 42 °C by ≤7%. The temperature heterogeneity coefficient was found to vary linearly with the BPR. The interseed and scatter effect on radiation dose (beyond that of a standard LDR implant) due to non‐radioactive HT‐only seeds in the target was found to reduce D90 by <10% and D50 by <7%.Conclusion:Additional HT‐ only seeds are useful in improving the quality of hyperthermia delivered by TB seeds. For future application of these seeds in the clinic, addition of HT‐only seeds is recommended, provided the planned D90 is adjusted to compensate for the incresed interseed effect.This research is partially supported with NRC grant No. NRC‐HQ‐12‐G‐38‐0042.
TH‐CD‐201‐00: Clinical Networks: IT for Radiation Oncology
Authors: Siochi Ramon Alfredo 
Published: June 2015

Radiation Oncology is a data intensive discipline. Data moves among various systems (imaging, treatment planning, image guidance and delivery) and the development of troubleshooting methods and appropriate QA and QC measures strongly depends on the medical physicists’ understanding of fundamental information technology concepts. This session will cover the concepts involved in networking, data transfer, DICOM and HL7 connectivity, database operations and QA for IT. Databases are at the heart of all modern radiotherapy clinics and are used for planning as well as treatment delivery, and they also drive the observed state of the data at various clients. Querying and reporting from the database is an important skill that medical physicists need to learn. Interactions between clients and databases need to be well understood to ensure that correct, synchronized, and up‐to‐date information is properly communicated amongst all stakeholders involved in the treatment management process. Entrance into the database via DICOM, HL7 and other proprietary transfer mechanisms must also be tested for accuracy of information storage and presentation. Issues with inter‐operability between systems must also be well understood during acceptance testing and commissioning activities. The ongoing efforts of IHE‐RO will be explained in the context of the need for increased engagement on the part of medical physicists.Learning Objectives:

Understand the basic IT infrastructure required to run a radiotherapy department
Become familiar with database concepts to improve troubleshooting skills
Learn the principles of designing a QA program tailored to one's specific clinical IT environment.
Curan: Funding from AAPM for travel and expenses DICOM and Funding from ASTRO for travel and expenses IHE RO
TH‐CD‐201‐01: Radiation Therapy Databases
Authors: Balter P. 
Published: June 2015

Radiation Oncology is a data intensive discipline. Data moves among various systems (imaging, treatment planning, image guidance and delivery) and the development of troubleshooting methods and appropriate QA and QC measures strongly depends on the medical physicists’ understanding of fundamental information technology concepts. This session will cover the concepts involved in networking, data transfer, DICOM and HL7 connectivity, database operations and QA for IT. Databases are at the heart of all modern radiotherapy clinics and are used for planning as well as treatment delivery, and they also drive the observed state of the data at various clients. Querying and reporting from the database is an important skill that medical physicists need to learn. Interactions between clients and databases need to be well understood to ensure that correct, synchronized, and up‐to‐date information is properly communicated amongst all stakeholders involved in the treatment management process. Entrance into the database via DICOM, HL7 and other proprietary transfer mechanisms must also be tested for accuracy of information storage and presentation. Issues with inter‐operability between systems must also be well understood during acceptance testing and commissioning activities. The ongoing efforts of IHE‐RO will be explained in the context of the need for increased engagement on the part of medical physicists.Learning Objectives:

Understand the basic IT infrastructure required to run a radiotherapy department
Become familiar with database concepts to improve troubleshooting skills
Learn the principles of designing a QA program tailored to one's specific clinical IT environment.
Curan: Funding from AAPM for travel and expenses DICOM and Funding from ASTRO for travel and expenses IHE RO
TH‐CD‐201‐03: QA for Radiotherapy IT
Authors: Siochi R. 
Published: June 2015

Radiation Oncology is a data intensive discipline. Data moves among various systems (imaging, treatment planning, image guidance and delivery) and the development of troubleshooting methods and appropriate QA and QC measures strongly depends on the medical physicists’ understanding of fundamental information technology concepts. This session will cover the concepts involved in networking, data transfer, DICOM and HL7 connectivity, database operations and QA for IT. Databases are at the heart of all modern radiotherapy clinics and are used for planning as well as treatment delivery, and they also drive the observed state of the data at various clients. Querying and reporting from the database is an important skill that medical physicists need to learn. Interactions between clients and databases need to be well understood to ensure that correct, synchronized, and up‐to‐date information is properly communicated amongst all stakeholders involved in the treatment management process. Entrance into the database via DICOM, HL7 and other proprietary transfer mechanisms must also be tested for accuracy of information storage and presentation. Issues with inter‐operability between systems must also be well understood during acceptance testing and commissioning activities. The ongoing efforts of IHE‐RO will be explained in the context of the need for increased engagement on the part of medical physicists.Learning Objectives:

Understand the basic IT infrastructure required to run a radiotherapy department
Become familiar with database concepts to improve troubleshooting skills
Learn the principles of designing a QA program tailored to one's specific clinical IT environment.
Curan: Funding from AAPM for travel and expenses DICOM and Funding from ASTRO for travel and expenses IHE RO
TH‐E‐304‐03: Absorbed Dose Standards for Brachytherapy
Authors: Sarfehnia A. 
Published: June 2015

It is fair to say that the clinical determination of absorbed dose in a high‐energy photon beam is the only situation where there is currently a direct chain of traceability from the standards laboratory to the end‐user and the protocol requires only ‘simple’ conversion/ correction factors. For all other modalities the primary standard is in a different quantity (e.g., air kerma) or in the right quantity but a different radiation beam (e.g., for proton dosimetry) from what is required for the clinical dose delivery. Complex conversion factors are often then required in applying protocols to give the desired final quantity. Such conversion factors can be from kerma to dose (in the case of kilovoltage x‐rays or brachytherapy) or from one type of radiation beam to another (in the case of electron or proton beams). Even non‐standard MV photon beams (e.g. non‐standard geometry, presence of a magnetic field) can have a significant impact on the procedure that must be followed compared to what is found in TG‐51. While national and international bodies, such as the AAPM and the IAEA, primarily address the end‐user's needs with protocols and guidelines, calibration laboratories are developing new measurement standards and approaches that should simplify the calibration chain and therefore lead to simpler, more robust procedures to yield absorbed dose in the beam of interest in the radiation therapy clinic.This session will provide a broad overview of the worldwide developments currently in progress, and also planned for the near future, of absorbed dose standards for a range of beam modalities including: Proton beamsHDR and LDR brachytherapyNon‐standard photon fields (small fields, impact of magnetic fields, etc)Learning Objectives:

Understand the present traceability chain for all beam modalities in regular use in the radiation therapy clinic.
Understand the current and planned development of absorbed dose standards for modalities other than linac photon beams.
Understand the physical basis of these standards and the potential impact on end‐user dosimetry.
Understand the likely impact of these standards developments on dosimetry protocols in the coming 5–10 years.