bluuebunny/crossref_metadata_2025_split huggingface dataset:
TH‐CD‐206‐02: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in MR Images Using Patch‐Based Anatomical Signature
Authors: Yang X , Jani A , Rossi P , Mao H , Curran W , Liu T 
Published: July 2016

Purpose:MRI has shown promise in identifying prostate tumors with high sensitivity and specificity for the detection of prostate cancer. Accurate segmentation of the prostate plays a key role various tasks: to accurately localize prostate boundaries for biopsy needle placement and radiotherapy, to initialize multi‐modal registration algorithms or to obtain the region of interest for computer‐aided detection of prostate cancer. However, manual segmentation during biopsy or radiation therapy can be time consuming and subject to inter‐ and intra‐observer variation. This study's purpose it to develop an automated method to address this technical challenge.Methods:We present an automated multi‐atlas segmentation for MR prostate segmentation using patch‐based label fusion. After an initial preprocessing for all images, all the atlases are non‐rigidly registered to a target image. And then, the resulting transformation is used to propagate the anatomical structure labels of the atlas into the space of the target image. The top L similar atlases are further chosen by measuring intensity and structure difference in the region of interest around prostate. Finally, using voxel weighting based on patch‐based anatomical signature, the label that the majority of all warped labels predict for each voxel is used for the final segmentation of the target image.Results:This segmentation technique was validated with a clinical study of 13 patients. The accuracy of our approach was assessed using the manual segmentation (gold standard). The mean volume Dice Overlap Coefficient was 89.5±2.9% between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D MRI‐guided prostate intervention.Conclusion:We have developed a new prostate segmentation approach based on the optimal feature learning label fusion framework, demonstrated its clinical feasibility, and validated its accuracy. This segmentation technique could be a useful tool in image‐guided interventions for prostate‐cancer diagnosis and treatment.
TH‐CD‐206‐05: Machine‐Learning Based Segmentation of Organs at Risks for Head and Neck Radiotherapy Planning
Authors: Ibragimov B , Pernus F , Strojan P , Xing L 
Published: July 2016

Purpose:Accurate and efficient delineation of tumor target and organs‐at‐risks is essential for the success of radiotherapy. In reality, despite of decades of intense research efforts, auto‐segmentation has not yet become clinical practice. In this study, we present, for the first time, a deep learning‐based classification algorithm for autonomous segmentation in head and neck (HaN) treatment planning.Methods:Fifteen HN datasets of CT, MR and PET images with manual annotation of organs‐at‐risk (OARs) including spinal cord, brainstem, optic nerves, chiasm, eyes, mandible, tongue, parotid glands were collected and saved in a library of plans. We also have ten super‐resolution MR images of the tongue area, where the genioglossus and inferior longitudinalis tongue muscles are defined as organs of interest. We applied the concepts of random forest‐ and deep learning‐based object classification for automated image annotation with the aim of using machine learning to facilitate head and neck radiotherapy planning process. In this new paradigm of segmentation, random forests were used for landmark‐assisted segmentation of super‐resolution MR images. Alternatively to auto‐segmentation with random forest‐based landmark detection, deep convolutional neural networks were developed for voxel‐wise segmentation of OARs in single and multi‐modal images. The network consisted of three pairs of convolution and pooing layer, one RuLU layer and a softmax layer.Results:We present a comprehensive study on using machine learning concepts for auto‐segmentation of OARs and tongue muscles for the HaN radiotherapy planning. An accuracy of 81.8% in terms of Dice coefficient was achieved for segmentation of genioglossus and inferior longitudinalis tongue muscles. Preliminary results of OARs regimentation also indicate that deep‐learning afforded an unprecedented opportunities to improve the accuracy and robustness of radiotherapy planning.Conclusion:A novel machine learning framework has been developed for image annotation and structure segmentation. Our results indicate the great potential of deep learning in radiotherapy treatment planning.
TH‐CD‐209‐01: A Greedy Reassignment Algorithm for the PBS Minimum Monitor Unit Constraint
Authors: Lin Y , Kooy H , Craft D , Depauw N , Flanz J , Clasie B 
Published: July 2016

Purpose:To investigate a Greedy Reassignment algorithm in order to mitigate the effects of low weight spots in proton pencil beam scanning (PBS) treatment plans.Methods:To convert a plan from the treatment planning system's (TPS) to a deliverable plan, post processing methods can be used to adjust the spot maps to meets the minimum MU constraint. Existing methods include: deleting low weight spots (Cut method), or rounding spots with weight above/below half the limit up/down to the limit/zero (Round method). An alternative method called Greedy Reassignment was developed in this work in which the lowest weight spot in the field was removed and its weight reassigned equally among its nearest neighbors. The process was repeated with the next lowest weight spot until all spots in the field were above the MU constraint. The algorithm performance was evaluated using plans collected from 190 patients (496 fields) treated at our facility. The evaluation criteria were the γ‐index pass rate comparing the pre‐processed and post‐processed dose distributions. A planning metric was further developed to predict the impact of post‐processing on treatment plans for various treatment planning, machine, and dose tolerance parameters.Results:For fields with a gamma pass rate of 90±1%, the metric has a standard deviation equal to 18% of the centroid value. This showed that the metric and γ‐index pass rate are correlated for the Greedy Reassignment algorithm. Using a 3rd order polynomial fit to the data, the Greedy Reassignment method had 1.8 times better metric at 90% pass rate compared to other post‐processing methods.Conclusion:We showed that the Greedy Reassignment method yields deliverable plans that are closest to the optimized‐without‐MU‐constraint plan from the TPS. The metric developed in this work could help design the minimum MU threshold with the goal of keeping the γ‐index pass rate above an acceptable value.
TH‐CD‐209‐10: Scanning Proton Arc Therapy (SPArc) ‐ The First Robust and Delivery‐Efficient Spot Scanning Proton Arc Therapy
Authors: Ding X , Li X , Zhang J , Kabolizadeh P , Stevens C , Yan D 
Published: July 2016

Purpose:To develop a delivery‐efficient proton spot‐scanning arc therapy technique with robust plan quality.Methods:We developed a Scanning Proton Arc(SPArc) optimization algorithm integrated with (1)Control point re‐sampling by splitting control point into adjacent sub‐control points; (2)Energy layer re‐distribution by assigning the original energy layers to the new sub‐control points; (3)Energy layer filtration by deleting low MU weighting energy layers; (4)Energy layer re‐sampling by sampling additional layers to ensure the optimal solution. A bilateral head and neck oropharynx case and a non‐mobile lung target case were tested. Plan quality and total estimated delivery time were compared to original robust optimized multi‐field step‐and‐shoot arc plan without SPArc optimization (Arcmulti‐field) and standard robust optimized Intensity Modulated Proton Therapy(IMPT) plans. Dose‐Volume‐Histograms (DVH) of target and Organ‐at‐Risks (OARs) were analyzed along with all worst case scenarios. Total delivery time was calculated based on the assumption of a 360 degree gantry room with 1 RPM rotation speed, 2ms spot switching time, beam current 1nA, minimum spot weighting 0.01 MU, energy‐layer‐switching‐time (ELST) from 0.5 to 4s.Results:Compared to IMPT, SPArc delivered less integral dose(−14% lung and −8% oropharynx). For lung case, SPArc reduced 60% of skin max dose, 35% of rib max dose and 15% of lung mean dose. Conformity Index is improved from 7.6(IMPT) to 4.0(SPArc). Compared to Arcmulti‐field, SPArc reduced number of energy layers by 61%(276 layers in lung) and 80%(1008 layers in oropharynx) while kept the same robust plan quality. With ELST from 0.5s to 4s, it reduced 55%–60% of Arcmulti‐field delivery time for the lung case and 56%–67% for the oropharynx case.Conclusion:SPArc is the first robust and delivery‐efficient proton spot‐scanning arc therapy technique which could be implemented in routine clinic. For modern proton machine with ELST close to 0.5s, SPArc would be a popular treatment option for both single and multi‐room center.
TH‐CD‐209‐12: Spatial Mapping of Scanned Proton Biologic Effect Using the High‐Throughput Technique, Continued
Authors: Kerr M , Bronk L , Guan F , Patel D , Li Y , Wang X , Sahoo N , Peeler C , Titt U , Mirkovic D , Grosshans D , Mohan R 
Published: July 2016

Purpose:To investigate the biologic effects of scanned protons by evenly sampling dose‐averaged LET (LETd) values.Methods:Our previous high‐throughput clonogenic study demonstrated a distinct relationship between RBE and LETd. However, our initial experimental design resulted in over‐sampling the low LETd values in the plateau region of the Bragg curve while under‐sampling in the region proximal to the Bragg peak as well as the high LETd values in the distal edge of the Bragg curve. To further examine the relationship between RBE and LETd, we refined the experimental design to more evenly sample proton LETd values from 1 to 20 keV/µm by optimizing the thicknesses of the irradiation jig steps. We used the clonogenic survival as the biological endpoint for the H460 lung cancer cell line cultured in 96‐well plates (12 columns by 8 rows). In the irradiation, the 8 wells in each column received a uniform dose‐LETd pair. The dose‐LETd pairs of the 12 different columns were sampled along the Bragg curve of 81.4 MeV scanned protons. Five peak dose levels from 1.5 Gy to 7.5 Gy were delivered with an increment of 1.5 Gy in the preliminary test. Two 96‐well plates were irradiated simultaneously to decrease the statistical uncertainties.Results:In the proximal region, for LETd = 5 keV/µm and 8 keV/µm, we did not observe any distinct differential biologic effects between the survival curves. At the Bragg peak (LETd = 9.5 keV/µm) and in the distal edge, irradiation with increasing LET values resulted in decreasing cell survival.Conclusion:The survival curves from the new experimental design support our previous findings that below 10 keV/µm, the LET effect in cell kill is obscured, but above 10 keV/µm, the biologic effects increase with LETd.Funding Support: U19 CA021239‐35 and R21 CA187484‐01
TH‐CD‐207B‐01: BEST IN PHYSICS (IMAGING): Development of High Brightness Multiple‐Pixel X‐Ray Source Using Oxide Coated Cathodes
Authors: Kandlakunta P , Pham R , Zhang T 
Published: July 2016

Purpose:To develop and characterize a high brightness multiple‐pixel thermionic emission x‐ray (MPTEX) source.Methods:Multiple‐pixel x‐ray sources allow for designs of novel x‐ray imaging techniques, such as fixed gantry CT, digital tomosynthesis, tetrahedron beam computed tomography, etc. We are developing a high‐brightness multiple‐pixel thermionic emission x‐ray (MPTEX) source based on oxide coated cathodes. Oxide cathode is chosen as the electron source due to its high emission current density and low operating temperature. A MPTEX prototype has been developed which may contain up to 41 micro‐rectangular oxide cathodes in 4 mm pixel spacing. Electronics hardware was developed for source control and switching. The cathode emission current was evaluated and x‐ray measurements were performed to estimate the focal spot size.Results:The oxide cathodes were able to produce ∼110 mA cathode current in pulse mode which corresponds to an emission current density of 0.55 A/cm2. The maximum kVp of the MPTEX prototype currently is limited to 100 kV due to the rating of high voltage feedthrough. Preliminary x‐ray measurements estimated the focal spot size as 1.5 × 1.3 mm2.Conclusion:A MPTEX source was developed with thermionic oxide coated cathodes and preliminary source characterization was successfully performed. The MPTEX source is able to produce an array of high brightness x‐ray beams with a fast switching speed.
TH‐D‐204‐00: The Pursuit of Radiation Oncology Performance Excellence
Authors: Sternick Edward 
Published: July 2016

The Malcolm Baldrige National Quality Improvement Act was signed into law in 1987 to advance U.S. business competitiveness and economic growth. Administered by the National Institute of Standards and Technology NIST, the Act created the Baldrige National Quality Program, now renamed the Baldrige Performance Excellence Program. The comprehensive analytical approaches referred to as the Baldrige Healthcare Criteria, are very well suited for the evaluation and sustainable improvement of radiation oncology management and operations. A multidisciplinary self‐assessment approach is used for radiotherapy program evaluation and development in order to generate a fact based knowledge driven system for improving quality of care, increasing patient satisfaction, building employee engagement, and boosting organizational innovation. The methodology also provides a valuable framework for benchmarking an individual radiation oncology practice against guidelines defined by accreditation and professional organizations and regulatory agencies.

Learning Objectives:
To gain knowledge of the Baldrige Performance Excellence Program as it relates to Radiation Oncology.
To appreciate the value of a multidisciplinary self‐assessment approach in the pursuit of Radiation Oncology quality care, patient satisfaction, and workforce commitment.
To acquire a set of useful measurement tools with which an individual Radiation Oncology practice can benchmark its performance against guidelines defined by accreditation and professional organizations and regulatory agencies.
TH‐D‐BRB‐04: Pinnacle Scripting: Improving Efficiency While Maintaining Safety
Authors: Moore J. 
Published: July 2016

Scripting capabilities and application programming interfaces (APIs) are becoming commonly available in modern treatment planning systems. These links to the treatment planning system (TPS) allow users to read data from the TPS, and in some cases use TPS functionality and write data back to the TPS. Such tools are powerful extensions, allowing automation of routine clinical tasks and supporting research, particularly research involving repetitive tasks on large patient populations. The data and functionality exposed by scripting/API capabilities is vendor dependent, as are the languages used by script/API engines, such as the Microsoft .NET framework or Python. Scripts deployed in a clinical environment must be commissioned and validated like any other software tool. This session will provide an overview of scripting applications and a discussion of best practices, followed by a practical introduction to the scripting capabilities of three commercial treatment planning systems.

Learning Objectives:
Understand the scripting capabilities available in several treatment planning systems
Learn how to get started using scripting capabilities
Understand the best practices for safe script deployment in a clinical environmentR. Popple, Varian Medical Systems has provided research support unrelated to the topic of this session.R. Cardan, Varian Medical Systems for grant research, product evaluation, and teaching honorarium.
TH‐EF‐BRC‐01: Process Mapping
Authors: Dunscombe P. 
Published: July 2016

This Hands‐on Workshop will be focused on providing participants with experience with the principal tools of TG 100 and hence start to build both competence and confidence in the use of risk‐based quality management techniques. The three principal tools forming the basis of TG 100's risk analysis: Process mapping, Failure‐Modes and Effects Analysis and fault‐tree analysis will be introduced with a 5 minute refresher presentation and each presentation will be followed by a 30 minute small group exercise. An exercise on developing QM from the risk analysis follows. During the exercise periods, participants will apply the principles in 2 different clinical scenarios. At the conclusion of each exercise there will be ample time for participants to discuss with each other and the faculty their experience and any challenges encountered.

Learning Objectives:
To review the principles of Process Mapping, Failure Modes and Effects Analysis and Fault Tree Analysis.
To gain familiarity with these three techniques in a small group setting.
To share and discuss experiences with the three techniques with faculty and participants.Director, TreatSafely, LLC. Director, Center for the Assessment of Radiological Sciences. Occasional Consultant to the IAEA and Varian.
TH‐D‐BRC‐00: Educational Point Counter/Point: Has Photon RT Hit the Limits?
Authors: Aydogan Bulent 
Published: July 2016

Interest in proton therapy has increased dramatically in the past couple of years, especially in the United States. There certainly is an important place for proton therapy in the arsenal of cancer treatments. Its dosimetric advantage and potential for low toxicity makes it the perfect partner for photons and other cancer treatment modalities.Often there is a belief that the new technology ought to be better but many believe that they should be widely adopted in the clinic only after evidence has shown that they are at least as safe and efficacious as existing technologies, which are often less expensive. This is the case for proton radiotherapy.This session being both educational and debate will provide a good review of basics and technological advancement as well as a comprehensive clinical update for both proton and photon therapy.Future technology developments and how they will impact the potential dosimetric advantage of proton therapy will be discussed. Particularly the debate will focus on whether these developments will close or widen the gap between photon and proton therapy.

Learning Objectives:
To review challenges, limitations, and recent and future developments in proton therapy.
To review challenges, limitations, recent and future developments in photon radiotherapy.
To review current clinical trials and challenging clinical cases.C. Yu, No company or organization that my presentation mentions provided me with financial support. I am the Founder and CEO of Xcision Medical Systems, LLC. However, my presentation will not mention any product or technology developed by Xcision.
TH‐D‐BRC‐01: Panel Member
Authors: Aydogan B. 
Published: July 2016

Interest in proton therapy has increased dramatically in the past couple of years, especially in the United States. There certainly is an important place for proton therapy in the arsenal of cancer treatments. Its dosimetric advantage and potential for low toxicity makes it the perfect partner for photons and other cancer treatment modalities.Often there is a belief that the new technology ought to be better but many believe that they should be widely adopted in the clinic only after evidence has shown that they are at least as safe and efficacious as existing technologies, which are often less expensive. This is the case for proton radiotherapy.This session being both educational and debate will provide a good review of basics and technological advancement as well as a comprehensive clinical update for both proton and photon therapy.Future technology developments and how they will impact the potential dosimetric advantage of proton therapy will be discussed. Particularly the debate will focus on whether these developments will close or widen the gap between photon and proton therapy.

Learning Objectives:
To review challenges, limitations, and recent and future developments in proton therapy.
To review challenges, limitations, recent and future developments in photon radiotherapy.
To review current clinical trials and challenging clinical cases.C. Yu, No company or organization that my presentation mentions provided me with financial support. I am the Founder and CEO of Xcision Medical Systems, LLC. However, my presentation will not mention any product or technology developed by Xcision.
TH‐D‐BRC‐03: Panel Member
Authors: Paganetti H. 
Published: July 2016

Interest in proton therapy has increased dramatically in the past couple of years, especially in the United States. There certainly is an important place for proton therapy in the arsenal of cancer treatments. Its dosimetric advantage and potential for low toxicity makes it the perfect partner for photons and other cancer treatment modalities.Often there is a belief that the new technology ought to be better but many believe that they should be widely adopted in the clinic only after evidence has shown that they are at least as safe and efficacious as existing technologies, which are often less expensive. This is the case for proton radiotherapy.This session being both educational and debate will provide a good review of basics and technological advancement as well as a comprehensive clinical update for both proton and photon therapy.Future technology developments and how they will impact the potential dosimetric advantage of proton therapy will be discussed. Particularly the debate will focus on whether these developments will close or widen the gap between photon and proton therapy.

Learning Objectives:
To review challenges, limitations, and recent and future developments in proton therapy.
To review challenges, limitations, recent and future developments in photon radiotherapy.
To review current clinical trials and challenging clinical cases.C. Yu, No company or organization that my presentation mentions provided me with financial support. I am the Founder and CEO of Xcision Medical Systems, LLC. However, my presentation will not mention any product or technology developed by Xcision.
TH‐D‐BRB‐03: Introduction to Scripting in RayStation
Authors: Eley J. 
Published: July 2016

Scripting capabilities and application programming interfaces (APIs) are becoming commonly available in modern treatment planning systems. These links to the treatment planning system (TPS) allow users to read data from the TPS, and in some cases use TPS functionality and write data back to the TPS. Such tools are powerful extensions, allowing automation of routine clinical tasks and supporting research, particularly research involving repetitive tasks on large patient populations. The data and functionality exposed by scripting/API capabilities is vendor dependent, as are the languages used by script/API engines, such as the Microsoft .NET framework or Python. Scripts deployed in a clinical environment must be commissioned and validated like any other software tool. This session will provide an overview of scripting applications and a discussion of best practices, followed by a practical introduction to the scripting capabilities of three commercial treatment planning systems.

Learning Objectives:
Understand the scripting capabilities available in several treatment planning systems
Learn how to get started using scripting capabilities
Understand the best practices for safe script deployment in a clinical environmentR. Popple, Varian Medical Systems has provided research support unrelated to the topic of this session.R. Cardan, Varian Medical Systems for grant research, product evaluation, and teaching honorarium.