bluuebunny/crossref_metadata_2025 huggingface dataset:
TH‐AB‐BRA‐01: A Novel Doubly‐Focused Multileaf Collimator Design for MR‐Guided Radiation Therapy
Authors: Li H , Mutic S , Low D , Green O , Fought G , Kawrakow I , Sharma A , Shvartsman S , Dempsey J
Published: July 2016

Purpose:

To describe the physical and dosimetric properties of a novel double‐stack multileaf collimator (MLC).

Methods:

One of the compromises made in the MLC design has been to employ linear‐motion singly‐divergent shapes. Because the MLC leading edge moves linearly, it is rounded to provide a consistent, albeit compromised penumbra. The MLC employed in the new linac‐based MR‐IGRT unit is designed to be doubly focused in that each leaf moves in an arc centered at the source, and the sides of the leaves are machined such that they lie parallel to a line between the leaf edge and the source. The curvature of the MLC keeps motors and encoders in lower magnetic field. However, high spatial‐resolution leaves are difficult to manufacture to sufficiently tight tolerances and difficult to move due to restricted space on the gantry. Wider leaves alleviate this problem with less moving parts but the coarse resolution disallows treating very small lesions. This compromise has been overcome by splitting the MLC leaf bank into two sets, stacked one upon the other and offset half of a leaf width. The dosimetry has been simulated using Monte‐Carlo and a 6 MV linac in a 0.35 T magnetic field.

Results:

The combined MLC leaf set has a spatial resolution of effectively half of the leaf width, 4mm here. The dosimetry resolution and conformality are consistent with 4mm wide MLC assisted by inverse fluence modulation. Also, because each leaf junction is backed up by the stacked leaf that lies over the junction, the problem of tongue‐and‐groove dosimetry has been greatly reduced. The novel MLC design allows the use of more powerful leaf motors than would be otherwise possible if a single MLC bank is employed.

Conclusions:

The stacked MLC will provide highly conformal dose distributions suitable for stereotactic radiation therapy of small lesions.

The research was funded by ViewRay, Inc.
TH‐AB‐BRA‐02: Automated Triplet Beam Orientation Optimization for MRI‐Guided Co‐60 Radiotherapy
Authors: Nguyen D , Thomas D , Cao M , O'Connor D , Lamb J , Sheng K
Published: July 2016

Purpose:

MRI guided Co‐60 provides daily and intrafractional MRI soft tissue imaging for improved target tracking and adaptive radiotherapy. To remedy the low output limitation, the system uses three Co‐60 sources at 120° apart, but using all three sources in planning is considerably unintuitive. We automate the beam orientation optimization using column generation, and then solve a novel fluence map optimization (FMO) problem while regularizing the number of MLC segments.

Methods:

Three patients—1 prostate (PRT), 1 lung (LNG), and 1 head‐and‐neck boost plan (H&NBoost)—were evaluated. The beamlet dose for 180 equally spaced coplanar beams under 0.35 T magnetic field was calculated using Monte Carlo. The 60 triplets were selected utilizing the column generation algorithm. The FMO problem was formulated using an L2‐norm minimization with anisotropic total variation (TV) regularization term, which allows for control over the number of MLC segments. Our Fluence Regularized and Optimized Selection of Triplets (FROST) plans were compared against the clinical treatment plans (CLN) produced by an experienced dosimetrist.

Results:

The mean PTV D95, D98, and D99 differ by −0.02%, +0.12%, and +0.44% of the prescription dose between planning methods, showing same PTV dose coverage. The mean PTV homogeneity (D95/D5) was at 0.9360 (FROST) and 0.9356 (CLN). R50 decreased by 0.07 with FROST. On average, FROST reduced Dmax and Dmean of OARs by 6.56% and 5.86% of the prescription dose. The manual CLN planning required iterative trial and error runs which is very time consuming, while FROST required minimal human intervention.

Conclusions:

MRI guided Co‐60 therapy needs the output of all sources yet suffers from unintuitive and laborious manual beam selection processes. Automated triplet orientation optimization is shown essential to overcome the difficulty and improves the dosimetry. A novel FMO with regularization provides additional controls over the number of MLC segments and treatment time.

Varian Medical Systems; NIH grant R01CA188300; NIH grant R43CA183390.
TH‐CD‐206‐01: Expectation‐Maximization Algorithm‐Based Tissue Mixture Quantification for Perfusion MRI
Authors: Han H , Liang Z , Li L , Xing L
Published: July 2016

Purpose:

To investigate the feasibility of estimating the tissue mixture perfusions and quantifying cerebral blood flow change in arterial spin labeled (ASL) perfusion MR images.

Methods:

The proposed perfusion MR image analysis framework consists of 5 steps: (1) Inhomogeneity correction was performed on the T1‐ and T2‐weighted images, which are available for each studied perfusion MR dataset. (2) We used the publicly available FSL toolbox to strip off the non‐brain structures from the T1‐ and T2‐weighted MR images. (3) We applied a multi‐spectral tissue‐mixture segmentation algorithm on both T1‐ and T2‐structural MR images to roughly estimate the fraction of each tissue type ‐ white matter, grey matter and cerebral spinal fluid inside each image voxel. (4) The distributions of the three tissue types or tissue mixture across the structural image array are down‐sampled and mapped onto the ASL voxel array via a co‐registration operation. (5) The presented 4‐dimensional expectation‐maximization (4D‐EM) algorithm takes the down‐sampled three tissue type distributions on perfusion image data to generate the perfusion mean, variance and percentage images for each tissue type of interest.

Results:

Experimental results on three volunteer datasets demonstrated that the multi‐spectral tissue‐mixture segmentation algorithm was effective to initialize tissue mixtures from T1‐ and T2‐weighted MR images. Compared with the conventional ASL image processing toolbox, the proposed 4D‐EM algorithm not only generated comparable perfusion mean images, but also produced perfusion variance and percentage images, which the ASL toolbox cannot obtain. It is observed that the perfusion contribution percentages may not be the same as the corresponding tissue mixture volume fractions estimated in the structural images.

Conclusion:

A specific application to brain ASL images showed that the presented perfusion image analysis method is promising for detecting subtle changes in tissue perfusions, which is valuable for the early diagnosis of certain brain diseases, e.g. multiple sclerosis.
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 environment

R. 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 environment

R. 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‐E‐201‐01: Diagnostic Radiology Residents Physics Curriculum and Updates
Authors: Sensakovic W.
Published: July 2016

The ABR Core Examination stresses integrating physics into real‐world clinical practice and, accordingly, has shifted its focus from passive recall of facts to active application of physics principles. Physics education of radiology residents poses a challenge. The traditional method of didactic lectures alone is insufficient, yet it is difficult to incorporate physics teaching consistently into clinical rotations due to time constraints.

Faced with this challenge, diagnostic medical physicists who teach radiology residents, have been thinking about how to adapt their teaching to the new paradigm, what to teach and meet expectation of the radiology resident and the radiology residency program. The proposed lecture attempts to discuss above questions. Newly developed diagnostic radiology residents physics curriculum by the AAPM Imaging Physics Curricula Subcommittee will be reviewed. Initial experience on hands‐on physics teaching will be discussed. Radiology resident who will have taken the BAR Core Examination will share the expectation of physics teaching from a resident perspective.

The lecture will help develop robust educational approaches to prepare radiology residents for safer and more effective lifelong practice.

Learning Objectives:

Learn updated physics requirements for radiology residents

Pursue effective approaches to teach physics to radiology residents

Learn expectation of physics teaching from resident perspective

J. Zhang, This topic is partially supported by RSNA Education Scholar Grant
TH‐E‐201‐03: A Radiology Resident's Perspectives of Physics Teaching
Authors: Key A.
Published: July 2016

The ABR Core Examination stresses integrating physics into real‐world clinical practice and, accordingly, has shifted its focus from passive recall of facts to active application of physics principles. Physics education of radiology residents poses a challenge. The traditional method of didactic lectures alone is insufficient, yet it is difficult to incorporate physics teaching consistently into clinical rotations due to time constraints.

Faced with this challenge, diagnostic medical physicists who teach radiology residents, have been thinking about how to adapt their teaching to the new paradigm, what to teach and meet expectation of the radiology resident and the radiology residency program. The proposed lecture attempts to discuss above questions. Newly developed diagnostic radiology residents physics curriculum by the AAPM Imaging Physics Curricula Subcommittee will be reviewed. Initial experience on hands‐on physics teaching will be discussed. Radiology resident who will have taken the BAR Core Examination will share the expectation of physics teaching from a resident perspective.

The lecture will help develop robust educational approaches to prepare radiology residents for safer and more effective lifelong practice.

Learning Objectives:

Learn updated physics requirements for radiology residents

Pursue effective approaches to teach physics to radiology residents

Learn expectation of physics teaching from resident perspective

J. Zhang, This topic is partially supported by RSNA Education Scholar Grant
TH‐EF‐204‐01: Introduction
Authors: Cygler J.
Published: July 2016

Joanna E. Cygler, Jan Seuntjens, J. Daniel Bourland, M. Saiful Huq, Josep Puxeu Vaque, Daniel Zucca Aparicio, Tatiana Krylova, Yuri Kirpichev, Eric Ford, Caridad Borras

Stereotactic Radiation Therapy (SRT) utilizes small static and dynamic (IMRT) fields, to successfully treat malignant and benign diseases using techniques such as Stereotactic Radiosurgery (SRS) and Stereotactic Body Radiation Therapy (SBRT). SRT is characterized by sharp dose gradients for individual fields and their resultant dose distributions. For appropriate targets, small field radiotherapy offers improved treatment quality by allowing better sparing of organs at risk while delivering the prescribed target dose. Specialized small field treatment delivery systems, such as robotic‐controlled linear accelerators, gamma radiosurgery units, and dynamic arc linear accelerators may utilize rigid fixation, image guidance, and tumor tracking, to insure precise dose delivery to static or moving targets. However, in addition to great advantages, small field delivery techniques present special technical challenges for dose calibration due to unique geometries and small field sizes not covered by existing reference dosimetry protocols such as AAPM TG‐51 or IAEA TRS 398. In recent years extensive research has been performed to understand small field dosimetry and measurement instrumentation. AAPM, IAEA and ICRU task groups are expected to provide soon recommendations on the dosimetry of small radiation fields. In this symposium we will: 1] discuss the physics, instrumentation, methodologies and challenges for small field radiation dose measurements; 2] review IAEA and ICRU recommendations on prescribing, recording and reporting of small field radiation therapy; 3] discuss selected clinical applications and technical aspects for specialized image‐guided, small field, linear accelerator based treatment techniques such as IMRT and SBRT.

Learning Objectives:

To learn the physics of small fields in contrast to dosimetry of conventional fields

To learn about detectors suitable for small fields

To learn about the role of Monte Carlo simulations in determination of small field output factors

To provide an overview of the IAEA small field dosimetry recommendations

To provide an overview of the content of the ICRU report on Prescribing, Reporting and Recording of Small Field Radiation Therapy.

To learn about special technical considerations in delivering IMRT and SBRT treatments

To appreciate specific challenges of IMRT implementation

J. Seuntjens, Natural Sciences and Engineering Research Council; Canadian Institutes of Health Research
TH‐EF‐BRB‐05: 4pi Non‐Coplanar IMRT Beam Angle Selection by Convex Optimization with Group Sparsity Penalty
Authors: O'Connor D , Voronenko Y , Nguyen D , Yin W , Sheng K
Published: July 2016

Purpose:

Integrated beam orientation and fluence map optimization is expected to be the foundation of robust automated planning but existing heuristic methods do not promise global optimality. We aim to develop a new method for beam angle selection in 4π non‐coplanar IMRT systems based on solving (globally) a single convex optimization problem, and to demonstrate the effectiveness of the method by comparison with a state of the art column generation method for 4π beam angle selection.

Methods:

The beam angle selection problem is formulated as a large scale convex fluence map optimization problem with an additional group sparsity term that encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated first‐order method, the Fast Iterative Shrinkage‐Thresholding Algorithm (FISTA). The beam angle selection and fluence map optimization algorithm is used to create non‐coplanar 4π treatment plans for several cases (including head and neck, lung, and prostate cases) and the resulting treatment plans are compared with 4π treatment plans created using the column generation algorithm.

Results:

In our experiments the treatment plans created using the group sparsity method meet or exceed the dosimetric quality of plans created using the column generation algorithm, which was shown superior to clinical plans. Moreover, the group sparsity approach converges in about 3 minutes in these cases, as compared with runtimes of a few hours for the column generation method.

Conclusion:

This work demonstrates the first non‐greedy approach to non‐coplanar beam angle selection, based on convex optimization, for 4π IMRT systems. The method given here improves both treatment plan quality and runtime as compared with a state of the art column generation algorithm. When the group sparsity term is set to zero, we obtain an excellent method for fluence map optimization, useful when beam angles have already been selected.

NIH R43CA183390, NIH R01CA188300, Varian Medical Systems; Part of this research took place while D. O'Connor was a summer intern at RefleXion Medical.
TH‐EF‐BRB‐06: Implementation of a Modulated‐Arc Total Body Irradiation (TBI) Technique Using the RayStation Treatment Planning System
Authors: Phillips J , Cheung J , Held M , Han D , Morin O
Published: July 2016

Purpose:

To develop a clinical workflow for delivering a modulated‐arc total body irradiation (TBI) with RayStation scripting. This technique uses arc fields with the patient lying at floor level on a padded table and is validated through measurements taken on a custom‐made TBI phantom.

Methods:

Treatment planning was performed for a retrospective cohort of eight patients with a diverse range of heights and body types. Each was replanned using an open‐field dual arc method, with the patient in supine and prone positions on the floor of the vault. All plans were optimized using Raystation Planning 4.7.2.5 (RaySearch Laboratories, Stockholm, Sweden), with 200 cGy prescribed to the 95% of the body contour − 5mm. This results in an open‐field beam that sweeps craniocaudally across the length of the patient. The technique is validated with measurements at 10 cm intervals in a custom‐milled, 5 cm thick acrylic phantom. A centrally located CC13 ion chamber and a Mobile MOSFET (Best Medical Canada, Ottawa, ON) detector array were used to measure dose. Supine and prone arcs for each patient were consecutively delivered, and the aggregate dose at each point was compared to the planned dose calculated in the phantom.

Results:

The ion chamber measurements differed from the planned dose by an average of .5%, with a standard deviation of 2.1%. All measured data for the MOSFETS were within 10% of the corresponding planned dose except for two outlying points. The standard deviation of dose differences across the entire cohort was 4.0%. Most significant discrepancies occurred either in inhomogeneous regions with large gradients, or at inferior points where beam angle was steepest.

Conclusion:

We have confirmed that the planned dose is well matched to our measurements within 10% for this method of planning and delivery. We are currently incorporating this technique into our clinical workflow.

This work is supported by RaySearch.
TH‐EF‐BRA‐02: A Novel Markerless 4D CBCT Projection Phase Sorting Technique Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study
Authors: Zhang L , Zhang Y , Yin F , Harris W , Cai J , Ren L
Published: July 2016

Purpose:

To investigate the feasibility of a novel marker‐less motion‐modeling based method for automatic 4D‐CBCT projection phase sorting.

Methods:

Patient on‐board image volume at any instant is considered as a deformation of one phase of the prior planning 4D‐CT. The deformation field map(DFM) is represented as a linear combination of three major deformation patterns extracted from the planning 4D‐CT using principle‐component‐analysis(PCA). The PCA coefficients are solved for each single projection based on data fidelity constraint, and are used as motion information for phase sorting. Projections at the valleys of the Z direction coefficient are sorted as phase 0/100% and projection phases in between are linearly interpolated. 4D‐digital‐extended‐cardiac‐torso(XCAT) phantoms and 3 patient cases were used for evaluation. XCAT phantoms simulated different patient respiratory and anatomical changes from prior 4D‐CT to on‐board image volume, including changes of tumor size, locations, motion amplitudes and motion directions. Three patient cases include 2 full‐fan slow‐rotation and one half‐fan normal‐rotation case. Manual phase sorting based on visual inspection was used as the gold standard. The average absolute phase difference, and the pass rate (percentage of projections sorted within 10% phase error) were used to evaluate sorting accuracy.

Results:

The amplitude of PCA coefficient motion curve correlated with the actual motion amplitude. The algorithm was robust against respiratory and anatomical changes from prior to on‐board imaging. For all XCAT cases, the average phase errors were lower than 1.43%, and the pass rate was 100%. The patient data set showed average phase error of 2.47%, 1.90% for full fan slow rotation case and 2.78% for half fan normal rotation case, respectively. The corresponding pass rates were 99.4%, 98.5% and 99.5%, respectively.

Conclusion:

Preliminary results demonstrated the robustness and high accuracy of the marker‐less PCA based phase sorting algorithm for different patient scenarios and 4D‐CBCT scanning protocols.
TH‐EF‐BRA‐03: Assessment of Data‐Driven Respiratory Motion‐Compensation Methods for 4D‐CBCT Image Registration and Reconstruction Using Clinical Datasets
Authors: Riblett MJ , Weiss E , Christensen GE , Hugo GD
Published: July 2016

Purpose:

To evaluate the performance of a 4D‐CBCT registration and reconstruction method that corrects for respiratory motion and enhances image quality under clinically relevant conditions.

Methods:

Building on previous work, which tested feasibility of a motion‐compensation workflow using image datasets superior to clinical acquisitions, this study assesses workflow performance under clinical conditions in terms of image quality improvement. Evaluated workflows utilized a combination of groupwise deformable image registration (DIR) and image reconstruction. Four‐dimensional cone beam CT (4D‐CBCT) FDK reconstructions were registered to either mean or respiratory phase reference frame images to model respiratory motion. The resulting 4D transformation was used to deform projection data during the FDK backprojection operation to create a motion‐compensated reconstruction. To simulate clinically realistic conditions, superior quality projection datasets were sampled using a phase‐binned striding method. Tissue interface sharpness (TIS) was defined as the slope of a sigmoid curve fit to the lung‐diaphragm boundary or to the carina tissue‐airway boundary when no diaphragm was discernable. Image quality improvement was assessed in 19 clinical cases by evaluating mitigation of view‐aliasing artifacts, tissue interface sharpness recovery, and noise reduction.

Results:

For clinical datasets, evaluated average TIS recovery relative to base 4D‐CBCT reconstructions was observed to be 87% using fixed‐frame registration alone; 87% using fixed‐frame with motion‐compensated reconstruction; 92% using mean‐frame registration alone; and 90% using mean‐frame with motion‐compensated reconstruction. Soft tissue noise was reduced on average by 43% and 44% for the fixed‐frame registration and registration with motion‐compensation methods, respectively, and by 40% and 42% for the corresponding mean‐frame methods. Considerable reductions in view aliasing artifacts were observed for each method.

Conclusion:

Data‐driven groupwise registration and motion‐compensated reconstruction have the potential to improve the quality of 4D‐CBCT images acquired under clinical conditions. For clinical image datasets, the addition of motion compensation after groupwise registration visibly reduced artifact impact.

This work was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA166119. Hugo and Weiss hold a research agreement with Philips Healthcare and license agreement with Varian Medical Systems. Weiss receives royalties from UpToDate. Christensen receives funds from Roger Koch to support research.
TH‐E‐202‐01: Pitfalls and Remedies in PET/CT Imaging for RT Planning
Authors: Pan T.
Published: July 2016

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss:

Pitfalls and remedies in PET/CT imaging for RT planning

The use of hypoxia PET imaging for radiotherapy

PET for tumor response evaluation

The first presentation will address the issue of mis‐registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image‐guidance in radiation therapy. The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de‐escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi‐quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non‐FDG PET tracers for response assessment.

Learning Objectives:

Identify the causes of mis‐registration of CT and PET images in PET/CT, and review the strategies to remedy the issue.

Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo‐radiation therapy).

Understand the basics of dynamic PET imaging, compartmental modeling and parametric images.

Understand the basics of using FDG PET/CT for tumor response evaluation.

Learn about recent advancement in PET/CT radiomics and non‐FDG PET tracers for response assessment.

This work was supported in part by the National Cancer Institute Grants R01CA172638.; W. Lu, This work was supported in part by the National Cancer Institute Grants R01CA172638.