bluuebunny/crossref_metadata_2025 huggingface dataset:
WE‐G‐BRA‐02: SafetyNet: Automating Radiotherapy QA with An Event Driven Framework
Authors: Hadley S , Kessler M , Litzenberg D , Lee C , Irrer J , Chen X , Acosta E , Weyburne G , Keranen W , Lam K , Covington E , Younge K , Matuszak M , Moran J
Published: June 2015

Purpose:

Quality assurance is an essential task in radiotherapy that often requires many manual tasks. We investigate the use of an event driven framework in conjunction with software agents to automate QA and eliminate wait times.

Methods:

An in house developed subscription‐publication service, EventNet, was added to the Aria OIS to be a message broker for critical events occurring in the OIS and software agents. Software agents operate without user intervention and perform critical QA steps. The results of the QA are documented and the resulting event is generated and passed back to EventNet. Users can subscribe to those events and receive messages based on custom filters designed to send passing or failing results to physicists or dosimetrists. Agents were developed to expedite the following QA tasks: Plan Revision, Plan 2nd Check, SRS Winston‐Lutz isocenter, Treatment History Audit, Treatment Machine Configuration.

Results:

Plan approval in the Aria OIS was used as the event trigger for plan revision QA and Plan 2nd check agents. The agents pulled the plan data, executed the prescribed QA, stored the results and updated EventNet for publication. The Winston Lutz agent reduced QA time from 20 minutes to 4 minutes and provided a more accurate quantitative estimate of radiation isocenter. The Treatment Machine Configuration agent automatically reports any changes to the Treatment machine or HDR unit configuration. The agents are reliable, act immediately, and execute each task identically every time.

Conclusion:

An event driven framework has inverted the data chase in our radiotherapy QA process. Rather than have dosimetrists and physicists push data to QA software and pull results back into the OIS, the software agents perform these steps immediately upon receiving the sentinel events from EventNet.

Mr Keranen is an employee of Varian Medical Systems. Dr. Moran's institution receives research support for her effort for a linear accelerator QA project from Varian Medical Systems. Other quality projects involving her effort are funded by Blue Cross Blue Shield of Michigan, Breast Cancer Research Foundation, and the NIH.
WE‐G‐BRA‐05: IROC Houston On‐Site Audits and Parameters That Affect Performance
Authors: Kry S , Dromgoole L , Alvarez P , Lowenstein J , Molineu A , Taylor P , Followill D
Published: June 2015

Purpose:

To highlight the IROC Houston on‐site dosimetry audit program, and to investigate the impact of clinical conditions on the frequency of errors/recommendations noted by IROC Houston.

Methods:

The results of IROC Houston on‐site audits from 2000‐present were abstracted and compared to clinical parameters, this included 409 institutions and 1020 linacs. In particular, we investigated the frequency of recommendations versus year, and the impact of repeat visits on the number of recommendations. We also investigated the impact on the number of recommendations of several clinical parameters: the number and age of the linacs, the linac/TPS combination, and the scope of the QA program.

Results:

The number of recommendations per institution (3.1 average) has shown decline between 2000 and present, although the number of recommendations per machine (0.89) has not changed. Previous IROC Houston site visits did not Result in fewer recommendations on a repeat visit, but IROC Houston tests have changed substantially during the last 15 years as radiotherapy technology has changed. There was no impact on the number of recommendations based on the number of machines at the institution or the age of a given machine. The fewest recommendations were observed for Varian‐Eclipse combinations (0.71 recs/machine), while Elekta‐ Pinnacle combinations yielded the most (1.62 recs/machine). Finally, in the TG‐142 era (post‐2010), those institutions that had a QA recommendation (n=77) had significantly more other recommendations (1.83 per institution) than those that had no QA rec (n=12, 1.33 per institution).

Conclusion:

Establishing and maintaining a successful radiotherapy program is challenging and areas of improvement can routinely be identified. Clinical conditions such as linac‐TPS combinations and the establishment of a good QA program impact the frequency of errors/deficiencies identified by IROC Houston during their on‐site review process.
WE‐G‐BRA‐06: Application of Systems and Control Theory‐Based Hazard Analysis to Radiotherapy
Authors: Pawlicki T , Samost A , Leveson N
Published: June 2015

Purpose:

The process of delivering radiation occurs in a complex socio‐technical system heavily reliant on human operators. Furthermore, both humans and software are notoriously challenging to account for in traditional hazard analysis models. High reliability industries such as aviation have approached this problem through using hazard analysis techniques grounded in systems and control theory. The purpose of this work is to apply the Systems Theoretic Accident Model Processes (STAMP) hazard model to radiotherapy. In particular, the System‐Theoretic Process Analysis (STPA) approach is used to perform a hazard analysis of a proposed on‐line adaptive cranial radiosurgery procedure that omits the CT Simulation step and uses only CBCT for planning, localization, and treatment.

Methods:

The STPA procedure first requires the definition of high‐level accidents and hazards leading to those accidents. From there, hierarchical control structures were created followed by the identification and description of control actions for each control structure. Utilizing these control structures, unsafe states of each control action were created. Scenarios contributing to unsafe control action states were then identified and translated into system requirements to constrain process behavior within safe boundaries.

Results:

Ten control structures were created for this new CBCT‐only process which covered the areas of hospital and department management, treatment design and delivery, and vendor service. Twenty three control actions were identified that contributed to over 80 unsafe states of those control actions resulting in over 220 failure scenarios.

Conclusion:

The interaction of people, hardware, and software are highlighted through the STPA approach. STPA provides a hierarchical model for understanding the role of management decisions in impacting system safety so that a process design requirement can be traced back to the hazard and accident that it is intended to mitigate.

Varian Medical Systems, Inc.
WE‐G‐BRA‐07: Analyzing the Safety Implications of a Brachytherapy Process Improvement Project Utilizing a Novel System‐Theory‐Based Hazard‐Analysis Technique
Authors: Tang A , Samost A , Viswanathan A , Cormack R , Damato A
Published: June 2015

Purpose:

To investigate the hazards in cervical‐cancer HDR brachytherapy using a novel hazard‐analysis technique, System Theoretic Process Analysis (STPA). The applicability and benefit of STPA to the field of radiation oncology is demonstrated.

Methods:

We analyzed the tandem and ring HDR procedure through observations, discussions with physicists and physicians, and the use of a previously developed process map. Controllers and their respective control actions were identified and arranged into a hierarchical control model of the system, modeling the workflow from applicator insertion through initiating treatment delivery. We then used the STPA process to identify potentially unsafe control actions. Scenarios were then generated from the identified unsafe control actions and used to develop recommendations for system safety constraints.

Results:

10 controllers were identified and included in the final model. From these controllers 32 potentially unsafe control actions were identified, leading to more than 120 potential accident scenarios, including both clinical errors (e.g., using outdated imaging studies for planning), and managerial‐based incidents (e.g., unsafe equipment, budget, or staffing decisions). Constraints identified from those scenarios include common themes, such as the need for appropriate feedback to give the controllers an adequate mental model to maintain safe boundaries of operations. As an example, one finding was that the likelihood of the potential accident scenario of the applicator breaking during insertion might be reduced by establishing a feedback loop of equipment‐usage metrics and equipment‐failure reports to the management controller.

Conclusion:

The utility of STPA in analyzing system hazards in a clinical brachytherapy system was demonstrated. This technique, rooted in system theory, identified scenarios both technical/clinical and managerial in nature. These results suggest that STPA can be successfully used to analyze safety in brachytherapy and may prove to be an alternative to other hazard analysis techniques.
WE‐G‐BRA‐09: Microsphere Brachytherapy Failure Mode and Effects Analysis in a Dual‐Vendor Environment
Authors: Younge K C , Lee C I , Feng M , Novelli P , Moran J M , Prisciandaro J I
Published: June 2015

Purpose:

To improve the safety and quality of a dual‐vendor microsphere brachytherapy program with failure mode and effects analysis (FMEA).

Methods:

A multidisciplinary team including physicists, dosimetrists, a radiation oncologist, an interventional radiologist, and radiation safety personnel performed an FMEA for our dual‐vendor microsphere brachytherapy program employing SIR‐Spheres (Sirtex Medical Limited, Australia) and Theraspheres (BTG, England). We developed a program process tree and step‐by‐step instructions which were used to generate a comprehensive list of failure modes. These modes were then ranked according to severity, occurrence rate, and detectability. Risk priority numbers (RPNs) were calculated by multiplying these three scores together. Three different severity scales were created: one each for harmful effects to the patient, staff, or the institution. Each failure mode was ranked on one or more of these scales.

Results:

The group identified 164 failure modes for the microsphere program. 113 of these were ranked using the patient severity scale, 52 using the staff severity scale, and 50 using the institution severity scale. The highest ranked items on the patient severity scale were an error in the automated dosimetry worksheet (RPN = 297.5), and the incorrect target specified on the planning study (RPN = 135). Some failure modes ranked differently between vendors, especially those corresponding to dose vial preparation because of the different methods used. Based on our findings, we made several improvements to our QA program, including documentation to easily identify which product is being used, an additional hand calculation during planning, and reorganization of QA steps before treatment delivery. We will continue to periodically review and revise the FMEA.

Conclusion:

We have applied FMEA to our dual‐vendor microsphere brachytherapy program to identify potential key weaknesses in the treatment chain. Our FMEA results were used to improve the effectiveness of our overall microsphere program.
WE‐G‐204‐02: Utility of a Channelized Hotelling Model Observer Over a Large Range of Angiographic Exposure Levels
Authors: Fetterly K , Favazza C
Published: June 2015

Purpose:

Mathematical model observers provide a figure of merit that simultaneously considers a test object and the contrast, noise, and spatial resolution properties of an imaging system. The purpose of this work was to investigate the utility of a channelized Hotelling model observer (CHO) to assess system performance over a large range of angiographic exposure conditions.

Methods:

A 4 mm diameter disk shaped, iodine contrast test object was placed on a 20 cm thick Lucite phantom and 1204 image frames were acquired using fixed x‐ray beam quality and for several detector target dose (DTD) values in the range 6 to 240 nGy. The CHO was implemented in the spatial domain utilizing 96 Gabor functions as channels. Detectability index (DI) estimates were calculated using the “resubstitution” and “holdout” methods to train the CHO. Also, DI values calculated using discrete subsets of the data were used to estimate a minimally biased DI as might be expected from an infinitely large dataset. The relationship between DI, independently measured CNR, and changes in results expected assuming a quantum limited detector were assessed over the DTD range.

Results:

CNR measurements demonstrated that the angiography system is not quantum limited due to relatively increasing contamination from electronic noise that reduces CNR for low DTD. Direct comparison of DI versus CNR indicates that the CHO relatively overestimates DI for low DTD and/or underestimates DI values for high DTD. The relative magnitude of the apparent bias error in the DI values was ∼20% over the 40x DTD range investigated.

Conclusion:

For the angiography system investigated, the CHO can provide a minimally biased figure of merit if implemented over a restricted exposure range. However, bias leads to overestimates of DI for low exposures. This work emphasizes the need to verify CHO model performance during real‐world application.
WE‐G‐207‐01: Motion‐Compensated Iterative Reconstruction of Coronary Artery Based On 3D/2D Deformable Image Registration
Authors: Liu B , Liang B , Zhou F
Published: June 2015

Purpose:

The 3D reconstruction of coronary artery from x‐ray angiograms rotationally acquired on c‐arm is a challenging task because of the vessel motion. While ECG gated reconstruction have shown promising results, residual vessel motion exists because of imperfect gating or irregular motion, and affects the reconstruction quality. The purpose of this work is to propose and validate a new motion‐compensated reconstruction method to reduce the effect of residual vessel motion.

Methods:

The proposed method consisted of three main steps. First, a subset of angiograms were selected using nearest‐neighbor ECG gating and used to perform the initial reconstruction based on a L1 and total variation regularized iterative reconstruction method. Due to the residual vessel motion, the initial Result exhibited motion artifacts which hindered its clinical usage. Next, a novel 3D/2D registration method was proposed to estimate the vessel motion between the initial reconstruction and the vessel morphology corresponding to each angiogram. Finally, a regularized iterative reconstruction method with motion‐compensation was proposed to reconstruct the final Result.

Results:

The proposed method was evaluated using three groups of simulated ECG‐gated angiograms with increasing amount of residual vessel motion. The reconstruction results of the proposed method were quantitatively evaluated using Maximum Mean Overlap (MMO) and Relative Radius Error (RRE) metrics, where larger MMO value and smaller RRE value means a better reconstruction. The MMOs (ECG gated reconstruction vs. motion‐compensated reconstruction) for the three groups were (0.94, 0.87, 0.79) vs. (0.96, 0.93, 0.89); The RREs were (7.7, 15.6, 23.3) vs. (4.2, 4.3, 7.1). The reconstruction Result was comparable to that of state‐of‐the‐art method.

Conclusion:

We have developed and validated a motion‐compensated reconstruction method to handle the residual vessel motion which degrades the ECG gated reconstruction. The method could effectively estimate and compensate the vessel motion, and thus improve the reconstruction quality.
WE‐G‐207‐03: Mask Guided Image Reconstruction (MGIR): A Novel Method for Ultra‐Low‐Dose 3D and Enhanced 4D Cone‐Beam Computer‐Tomography
Authors: Park C , Zhang H , Chen Y , Fan Q , Kahler D , Li J , Liu C , Lu B
Published: June 2015

Purpose:

Recently, compressed sensing (CS) based iterative reconstruction (IR) method is receiving attentions to reconstruct high quality cone beam computed tomography (CBCT) images using sparsely sampled or noisy projections. The aim of this study is to develop a novel baseline algorithm called Mask Guided Image Reconstruction (MGIR), which can provide superior image quality for both low‐dose 3DCBCT and 4DCBCT under single mathematical framework.

Methods:

In MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions where anatomical structures are 1) within the priori‐defined mask and 2) outside the mask. Then we update each part of images alternatively thorough solving minimization problems based on CS type IR. For low‐dose 3DCBCT, the former region is defined as the anatomically complex region where it is focused to preserve edge information while latter region is defined as contrast uniform, and hence aggressively updated to remove noise/artifact. In 4DCBCT, the regions are separated as the common static part and moving part. Then, static volume and moving volumes were updated with global and phase sorted projection respectively, to optimize the image quality of both moving and static part simultaneously.

Results:

Examination of MGIR algorithm showed that high quality of both low‐dose 3DCBCT and 4DCBCT images can be reconstructed without compromising the image resolution and imaging dose or scanning time respectively. For low‐dose 3DCBCT, a clinical viable and high resolution head‐and‐neck image can be obtained while cutting the dose by 83%. In 4DCBCT, excellent quality 4DCBCT images could be reconstructed while requiring no more projection data and imaging dose than a typical clinical 3DCBCT scan.

Conclusion:

The results shown that the image quality of MGIR was superior compared to other published CS based IR algorithms for both 4DCBCT and low‐dose 3DCBCT. This makes our MGIR algorithm potentially useful in various on‐line clinical applications.

Provisional Patent: UF#15476; WGS Ref. No. U1198.70067US00
WE‐G‐207‐06: 3D Fluoroscopic Image Generation From Patient‐Specific 4DCBCT‐Based Motion Models Derived From Physical Phantom and Clinical Patient Images
Authors: Dhou S , Cai W , Hurwitz M , Williams C , Rottmann J , Mishra P , Myronakis M , Cifter F , Berbeco R , Ionascu D , Lewis J
Published: June 2015

Purpose:

Respiratory‐correlated cone‐beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra‐ and inter‐fractional changes. We develop a method to generate patient‐specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery.

Methods:

Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCA coefficients iteratively through comparison of the cone‐beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions.

Results:

4DCBCT‐based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time.

Conclusion:

This study showed the feasibility of deriving 4DCBCT‐based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT‐based motion models were found to account for the 3D non‐rigid motion of the patient anatomy during treatment and have the potential to localize tumor and other patient anatomical structures at treatment time even when inter‐fractional changes occur.

This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc., Palo Alto, CA. The project was also supported, in part, by Award Number R21CA156068 from the National Cancer Institute.
WE‐G‐207‐08: Imaging Dose Reduction and Scatter Removal in Cone Beam CT Via Random Undersampling: A Simulation Study
Authors: Shen C , Chen L , Xu Y , Tian Z , Ng M , Zeng T , Lou Y , Zhu L , Jia X
Published: June 2015

Purpose:

Cone‐beam CT (CBCT) is widely used in image‐guided radiation therapy. The high imaging dose from repeated uses is a clinical concern and its image quality is impeded by a large amount of scattered photons. We propose to solve these two problems via a random undersampling method. We have performed Monte Carlo (MC) simulation studies for an initial test of the method.

Methods:

We propose to place a moving beam blocker with a random blocking pattern in front of the x‐ray source. It blocks a projection with a random pattern, which varies among projections. Scatter signal is measured in the deliberately created shadows, which is further interpolated to the entire projection. After removing the interpolated scatter from the total signal in the un‐blocked area, the cleaned data were used for CBCT reconstruction under a Tight Frame (TF) based iterative method. The random sampling yields a projection matrix that has a better numerical property compared to regular undersampling, permitting better image reconstruction.

Results:

360 CBCT projections of a head‐and‐neck cancer patient were generated via MC simulations. We first reconstructed CBCTs using 90 full projections with only primary data. The RMS error was 16%. When scattered photons were included in the projection, reduced contrast was observed and the RMS error was 22%. In our proposed method, 360 projections were used, but each of them was randomly blocked by 75% of pixels. Scatter estimation and was performed and the corrected data were used in reconstruction, yielding a reconstruction error of 15%. In these two approaches, the imaging doses were both reduced by ∼75% compared to a full scan with 360 unblocked projections.

Conclusion:

we proposed a method to solve the imaging dose and scatter problem in CBCT in a unified manner. Preliminary simulation studies demonstrated its efficacy.
WE‐G‐201‐00: Mobile Viewing Devices
Authors: Walz‐Flannigan Alisa
Published: June 2015

Many health care organizations are adopting mobile applications for patient care. These tools can provide the opportunity for improvements in timely access to patient images. With new possibilities for patient image viewing, it is sensible to take a closer look at what handheld devices might provide and how they are being used.

Three speakers: a radiologist, an imaging research scientist, and a clinical medical physicist provide input into different aspects of image viewing on handheld devices.

1. Patrick Luetmer, M.D., Radiologist

Provides a radiologist's perspective of how mobile technologies best fit into patient care workflows, including how patient image viewing is done differently on a mobile platform compared to a PACS workstation and what types of decisions are being made from handheld devices.

2. Aldo Badano, Ph.D., Imaging Research Scientist

Provides an overview of technological properties of handheld devices and describes how image viewing with handheld devices impacts the image information that is visible under ideal and clinical conditions.

3. Dr. Alisa Walz‐Flannigan, Ph.D., Clinical Medical Physicist

Provides an overview of different strategies for setup and quality control as relevant for handheld devices.

This session is related to the ongoing work of Task Group No. 260 “Considerations for the Use of Handheld Devices for Viewing Medical Images”.

Learning Objectives:

To understand how mobile devices for image viewing are being used to enhance patient care

To understand how technological properties of various mobile devices combine with device usage to impact the information visible in a medical image

To gain awareness of different options for configuring and testing handheld devices for medical image viewing

Dr. Aldo Badano has the following: Cooperative Research and Development Agreement (CRADA #123‐07) with BARCO.
WE‐G‐201‐01: A Radiologist Perspective on Mobile View Devices
Authors: Luetmer P.
Published: June 2015

Many health care organizations are adopting mobile applications for patient care. These tools can provide the opportunity for improvements in timely access to patient images. With new possibilities for patient image viewing, it is sensible to take a closer look at what handheld devices might provide and how they are being used.

Three speakers: a radiologist, an imaging research scientist, and a clinical medical physicist provide input into different aspects of image viewing on handheld devices.

1. Patrick Luetmer, M.D., Radiologist

Provides a radiologist's perspective of how mobile technologies best fit into patient care workflows, including how patient image viewing is done differently on a mobile platform compared to a PACS workstation and what types of decisions are being made from handheld devices.

2. Aldo Badano, Ph.D., Imaging Research Scientist

Provides an overview of technological properties of handheld devices and describes how image viewing with handheld devices impacts the image information that is visible under ideal and clinical conditions.

3. Dr. Alisa Walz‐Flannigan, Ph.D., Clinical Medical Physicist

Provides an overview of different strategies for setup and quality control as relevant for handheld devices.

This session is related to the ongoing work of Task Group No. 260 “Considerations for the Use of Handheld Devices for Viewing Medical Images”.

Learning Objectives:

To understand how mobile devices for image viewing are being used to enhance patient care

To understand how technological properties of various mobile devices combine with device usage to impact the information visible in a medical image

To gain awareness of different options for configuring and testing handheld devices for medical image viewing

Dr. Aldo Badano has the following: Cooperative Research and Development Agreement (CRADA #123‐07) with BARCO.
WE‐G‐201‐03: Setup, QC, and Usage Considerations for Mobile Image Viewing Platforms
Authors: Walz‐Flannigan A.
Published: June 2015

Many health care organizations are adopting mobile applications for patient care. These tools can provide the opportunity for improvements in timely access to patient images. With new possibilities for patient image viewing, it is sensible to take a closer look at what handheld devices might provide and how they are being used.

Three speakers: a radiologist, an imaging research scientist, and a clinical medical physicist provide input into different aspects of image viewing on handheld devices.

1. Patrick Luetmer, M.D., Radiologist

Provides a radiologist's perspective of how mobile technologies best fit into patient care workflows, including how patient image viewing is done differently on a mobile platform compared to a PACS workstation and what types of decisions are being made from handheld devices.

2. Aldo Badano, Ph.D., Imaging Research Scientist

Provides an overview of technological properties of handheld devices and describes how image viewing with handheld devices impacts the image information that is visible under ideal and clinical conditions.

3. Dr. Alisa Walz‐Flannigan, Ph.D., Clinical Medical Physicist

Provides an overview of different strategies for setup and quality control as relevant for handheld devices.

This session is related to the ongoing work of Task Group No. 260 “Considerations for the Use of Handheld Devices for Viewing Medical Images”.

Learning Objectives:

To understand how mobile devices for image viewing are being used to enhance patient care

To understand how technological properties of various mobile devices combine with device usage to impact the information visible in a medical image

To gain awareness of different options for configuring and testing handheld devices for medical image viewing

Dr. Aldo Badano has the following: Cooperative Research and Development Agreement (CRADA #123‐07) with BARCO.
WE‐G‐210‐00: Advances in Breast Ultrasound Imaging
Authors: Duric Neb
Published: June 2015

This session focuses on recent developments in breast ultrasound imaging, covering clinical practice as well as clinical and pre‐clinical research. Current status of ultrasound screening will be reviewed, followed by discussions of emerging technologies at various stages of regulatory and technical development. The session strives to provide the attendee with a view of a continuum of imaging advances starting with the present and spanning the near and long term future.

Learning Objectives:

Understand current state of ultrasound screening for breast cancer

Learn about current availability of whole breast ultrasound

Appreciate the current barriers to stronger adoption of screening ultrasound

Learn about attempts to drive adoption of screening ultrasound (e.g. breast density laws)

Learn about ultrasound tomography as an emerging technique for breast imaging

Learn about the regulatory status of emerging techniques such as ultrasound tomography

Learn about the developmental status of combined 3‐D ultrasound and Mammography systems

Learn about photo‐acoustic imaging and its potential future role in breast imaging
WE‐G‐210‐02: Ultrasound Tomography: A Breast Imaging Modality Whose Time Has Come
Authors: Duric N.
Published: June 2015

This session focuses on recent developments in breast ultrasound imaging, covering clinical practice as well as clinical and pre‐clinical research. Current status of ultrasound screening will be reviewed, followed by discussions of emerging technologies at various stages of regulatory and technical development. The session strives to provide the attendee with a view of a continuum of imaging advances starting with the present and spanning the near and long term future.

Learning Objectives:

Understand current state of ultrasound screening for breast cancer

Learn about current availability of whole breast ultrasound

Appreciate the current barriers to stronger adoption of screening ultrasound

Learn about attempts to drive adoption of screening ultrasound (e.g. breast density laws)

Learn about ultrasound tomography as an emerging technique for breast imaging

Learn about the regulatory status of emerging techniques such as ultrasound tomography

Learn about the developmental status of combined 3‐D ultrasound and Mammography systems

Learn about photo‐acoustic imaging and its potential future role in breast imaging
TH‐A‐213‐00: Small Field Dosimetry: Overview of AAPM TG‐155 and the IAEAAAPM Code of Practice
Authors: Das Indra
Published: June 2015

Modern radiotherapy techniques such as SRS/SRT, SBRT, IMRT, VMAT as well as specialized machines such as Tomotherapy, CyberKnife and Gamma Knife use small photon fields with at least one dimension <3 cm. Dosimetry in such small fields is challenging because of large detector perturbations due to non‐equilibrium conditions, occlusion of the primary photon source and large dose gradients across the field. Many small‐size dosimeters have been proposed for use in small fields. However, their characteristics especially the volume averaging and fluence perturbations have only recently been adequately understood. An IAEA‐AAPM working group has provided a framework for reference dosimetry in non‐compliant beams and the measurement of field output factors small fields (1). The AAPM TG‐155 (2) has adopted this framework to provide guidelines on relative dosimetry. This course explains the code of practice for absolute dosimetry that is under review and discusses the availability of correction factors to convert detector readings to doses. TG‐155 defines small field conditions, provides recommendations for suitable detectors and recommendations for good working practice for relative dosimetry (PDD, TMR, output factor, etc.) and dose calculations based on the new formulation. It also discusses beam modeling and dose calculations as a critical step in clinical utilization of small field radiotherapy.

Alfonso et al, Med Phys 35, 5179–5186 (2008).

Das et al, Med Phys (under review, 2014)

Learning Objectives:

Concepts and recommended procedures in the IAEA‐AAPM code of practice for dosimetry of small fields.

Physics of dosimetry in non‐equilibrium conditions and definition of small fields

Recommended procedures for relative dosimetry in TG‐1554.

Choice of detectors for small field dosimetry, perturbations and corrections for dosimetry

Understand the detector properties required for small field measurements

Understand the advantages and limitations of commercially available detectors for small field dosimetry

Research supported with operating grants from CIHR, NSERC, and BIOWin, a program funded at the Universite Catholique Louvain by the Walloon Government (Belgium). Student stipends supported by Medical Physics Research Training Network funded by the Collaborative Research and Training Experience program of the NSERC.

Seuntjens: support by Sun Nuclear Corporation
TH‐A‐213‐01: Small Field Dosimetry: Overview of AAPM TG‐155
Authors: Das I.
Published: June 2015

Modern radiotherapy techniques such as SRS/SRT, SBRT, IMRT, VMAT as well as specialized machines such as Tomotherapy, CyberKnife and Gamma Knife use small photon fields with at least one dimension <3 cm. Dosimetry in such small fields is challenging because of large detector perturbations due to non‐equilibrium conditions, occlusion of the primary photon source and large dose gradients across the field. Many small‐size dosimeters have been proposed for use in small fields. However, their characteristics especially the volume averaging and fluence perturbations have only recently been adequately understood. An IAEA‐AAPM working group has provided a framework for reference dosimetry in non‐compliant beams and the measurement of field output factors small fields (1). The AAPM TG‐155 (2) has adopted this framework to provide guidelines on relative dosimetry. This course explains the code of practice for absolute dosimetry that is under review and discusses the availability of correction factors to convert detector readings to doses. TG‐155 defines small field conditions, provides recommendations for suitable detectors and recommendations for good working practice for relative dosimetry (PDD, TMR, output factor, etc.) and dose calculations based on the new formulation. It also discusses beam modeling and dose calculations as a critical step in clinical utilization of small field radiotherapy.

Alfonso et al, Med Phys 35, 5179–5186 (2008).

Das et al, Med Phys (under review, 2014)

Learning Objectives:

Concepts and recommended procedures in the IAEA‐AAPM code of practice for dosimetry of small fields.

Physics of dosimetry in non‐equilibrium conditions and definition of small fields

Recommended procedures for relative dosimetry in TG‐1554.

Choice of detectors for small field dosimetry, perturbations and corrections for dosimetry

Understand the detector properties required for small field measurements

Understand the advantages and limitations of commercially available detectors for small field dosimetry

Research supported with operating grants from CIHR, NSERC, and BIOWin, a program funded at the Universite Catholique Louvain by the Walloon Government (Belgium). Student stipends supported by Medical Physics Research Training Network funded by the Collaborative Research and Training Experience program of the NSERC.

Seuntjens: support by Sun Nuclear Corporation
TH‐A‐213‐02: IAEA/AAPM Code of Practice for the Dosimetry of Static Small Photon Fields
Authors: Seuntjens J.
Published: June 2015

Modern radiotherapy techniques such as SRS/SRT, SBRT, IMRT, VMAT as well as specialized machines such as Tomotherapy, CyberKnife and Gamma Knife use small photon fields with at least one dimension <3 cm. Dosimetry in such small fields is challenging because of large detector perturbations due to non‐equilibrium conditions, occlusion of the primary photon source and large dose gradients across the field. Many small‐size dosimeters have been proposed for use in small fields. However, their characteristics especially the volume averaging and fluence perturbations have only recently been adequately understood. An IAEA‐AAPM working group has provided a framework for reference dosimetry in non‐compliant beams and the measurement of field output factors small fields (1). The AAPM TG‐155 (2) has adopted this framework to provide guidelines on relative dosimetry. This course explains the code of practice for absolute dosimetry that is under review and discusses the availability of correction factors to convert detector readings to doses. TG‐155 defines small field conditions, provides recommendations for suitable detectors and recommendations for good working practice for relative dosimetry (PDD, TMR, output factor, etc.) and dose calculations based on the new formulation. It also discusses beam modeling and dose calculations as a critical step in clinical utilization of small field radiotherapy.

Alfonso et al, Med Phys 35, 5179–5186 (2008).

Das et al, Med Phys (under review, 2014)

Learning Objectives:

Concepts and recommended procedures in the IAEA‐AAPM code of practice for dosimetry of small fields.

Physics of dosimetry in non‐equilibrium conditions and definition of small fields

Recommended procedures for relative dosimetry in TG‐1554.

Choice of detectors for small field dosimetry, perturbations and corrections for dosimetry

Understand the detector properties required for small field measurements

Understand the advantages and limitations of commercially available detectors for small field dosimetry

Research supported with operating grants from CIHR, NSERC, and BIOWin, a program funded at the Universite Catholique Louvain by the Walloon Government (Belgium). Student stipends supported by Medical Physics Research Training Network funded by the Collaborative Research and Training Experience program of the NSERC.

Seuntjens: support by Sun Nuclear Corporation
TH‐AB‐304‐05: Predicting Distant Failure in Lung SBRT Using Clinical Parameters
Authors: Zhou Z , Cannon N , Folkerts M , Iyengar P , Choy H , Timmerman R , Jiang S , Wang J
Published: June 2015

Purpose:

To predict distant failure in lung Stereotactic Body Radiation Therapy (SBRT) using clinical parameters by machine learning algorithms with a new optimal parameter selection strategy.

Methods:

Support Vector Machine (SVM) based method is used to construct the model to predict distant failure using 143 lung cancer patients underwent SBRT at our institute. Meanwhile, Artificial Neural Network (ANN) and Logistic Regression (LR) based methods are applied for comparisons. The clinical parameters for each patient include demographic parameters (4), tumor characteristics (6), treatment faction schemes (2) and pretreatment medicines (6). The total number of clinical parameters is 18. The model construction method consists of two steps: (1) selecting optimal parameter set by a new Clonal Selection Algorithm (CSA); and (2) constructing SVM, ANN and LR based models for predicting distant failure in lung SBRT. Selecting optimal parameter set is considered as a combinatorial optimization problem. The proposed CSA method is one of the evolutionary algorithms that can obtain global optimal solutions, overcoming the limitation of the ranking based selection method that lead to local optimization. In addition, to overcome the effect of imbalanced data in training process, a Synthetic Minority Over‐sampling Technique (SMOTE) is applied. Sensitivity, specificity and accuracy are used to evaluate the performance of the constructed models.

Results:

The accuracies for ANN, LR and SVM are 70.59%, 72.04%, 75.47%, respectively. The sensitivities for ANN, LR and SVM are 76%, 60.47% and 82%, while the specificities for the three models are 58.14%, 69.77% and 60.47%.

Conclusion:

A new CSA based parameter selection method is proposed. The SVM with the proposed CSA optimal parameter set selection strategy can achieve better performance than ANN and LR for predicting distant failure in lung SBRT patients based on clinical parameters.
TH‐AB‐304‐11: The Influence of Radiotherapy Treatment Method On Dose Distribution and Its Relation to Patient Outcome in the SCOPE 1 Oesophageal Cancer Trial Using Type B Algorithms
Authors: Carrington R , Spezi E , Gwynne S , Dutton P , Hurt C , Crosby T , Staffurth J
Published: June 2015

By applying the Mean Distance to Conformity (MDC) index to the dose distribution of a radiotherapy plan, the conformity of the 95% isodose line to the Planning Treatment Volume (PTV) can be measured, allowing both overdosing of normal tissue and underdosing of the target volume to be measured by OverMDC and UnderMDC respectively. The aim of this study was to analyse this aspect of treatment planning, in addition to volume of PTV and the treatment delivery method (3D conformal or Intensity‐Modulated Radiotherapy), and relate to patient outcome within the context of clinical trial.The OverMDC and UnderMDC of the 95% isodose line (50Gy prescribed dose) to the PTV was calculated for 97 patients from the UK SCOPE 1 trial on definitive chemoradiotherapy in oesophageal cancer. Data preparation was performed in CERR, Kaplan‐Meier and multivariate analysis undertaken in EUCLID and further tests in Excel and SPSS. A statistically significant breakpoint in the overall survival data, independent of cetuximab, was found with OverMDC (0.44cm, p<0.05). This was not the case with UnderMDC. There was a statistically significant difference in PTV volume either side of the OverMDC breakpoint (Mann Whitney p<0.001) and in OverMDC value dependent on the treatment delivery method (mean IMRT=0.21cm, mean 3D‐CRT=0.41cm Mann Whitney p<0.001). Re‐planning the worst performing patients according to OverMDC from 3D‐CRT to VMAT resulted in a mean reduction in OverMDC of 0.28cm (0.16–0.40cm). OverMDC was not significant in multivariate analysis that included age, sex, staging, tumour type, and position.We have shown in univariate analysis that a patient's OverMDC is correlated with overall survival. OverMDC is strongly related to IMRT and to a lesser extent with PTV volume. We recommend that VMAT planning should be used for oesophageal planning when available and that attention should be paid to the conformity of the 95% to the PTV.

Rhys Carrington's PhD is funded by Cancer Research Wales (Grant Number: 2445)
TH‐AB‐BRB‐03: Automated Complexity Analysis of Volumetric Modulated Arc Therapy Plans
Authors: Younge K C , Matuszak M M , Janes L A , Anderson C J R , Moran J M , Roberts D A
Published: June 2015

Purpose:

Volumetric modulated arc therapy (VMAT) plans can become excessively complex with little additional dosimetric benefit due to the degenerative nature of inverse planning. Our goal is to improve the efficiency and quality of the VMAT planning process through the use of an automated complexity metric script.

Methods:

A metric that quantifies the complexity of VMAT plans by evaluating individual segment modulation was developed at our institution. This metric finds the ratio of the MLC leaf side length over aperture area for each control point, and calculates an MU‐weighted average of all controls points in the plan. A plug‐in script was created to enable use of the metric within our commercial treatment planning system. The script calculates the complexity metric and then compares it to metrics from previous clinical VMAT plans, all of which have passed patient specific pre‐treatment quality assurance. To set a threshold complexity value, we used the complexity metric script to analyze 517 clinical VMAT plans created in 2013–14 that passed QA (composite analysis, 95% of points passing 4%/1mm) and 57 that failed QA. This threshold was optimized based on the resulting true and false positive rates.

Results:

With the clinically set threshold, the complexity metric has a true positive rate of 44% for identifying plans that failed QA with a corresponding false positive rate of 6%. The false positives correspond to highly modulated plans, which may benefit from being reoptimized even though they initially passed patient specific QA.

Conclusion:

Our in‐house complexity metric script has the ability to streamline the VMAT planning and treatment process by alerting the planner when overly complex plans are generated. Those plans can be reoptimized before pre‐treatment QA is performed to attempt to reduce the plan complexity and therefore improve the plan delivery accuracy.

This project was supported in part by P01CA059827.
TH‐AB‐BRB‐07: A Feasibility Study for Personalized Fractionation Schedule for Lung Cancer
Authors: Kim M , Stewart R , Phillips M
Published: June 2015

Purpose:

Investigate the feasibility of using spatio‐temporal optimization, i.e., fractionation schedule optimization combined with IMRT to select the patient‐specific fractionation schedule that best maximizes the tumor biologically equivalent dose (BED).

Methods and materials:

The optimal fractionation schedule for a patient depends on the tumor and organ at‐risk (OAR) sensitivity to fraction size (i.e., α/β), the effective tumor doubling time, and the size and location of tumor target relative to one or more OAR. We used a novel spatio‐temporal optimization method to identify the number of fractions N that maximizes the tumor BED using 3D BED distribution for sixteen lung phantom cases. The selection of the optimal fractionation schedule used equivalent 30‐fraction OAR constraints for the heart (Dmean < 45 Gy), lungs (Dmean < 20 Gy), cord (Dmax < 45 Gy), esophagus (Dmax < 63 Gy), and unspecified tissues (D05 < 63 Gy). To asses plan quality, we considered the min, mean, max and D95 tumor BED and the equivalent uniform dose (EUD) for optimized plans to the corresponding BED values for a conventional IMRT plan (60 Gy in 30 fractions). A sensitivity analysis was performed to assess the effects on optimal fractionation schedule of the effective tumor doubling time (Td = 3–100 days) and lag‐time for accelerated repopulation (Tk = 0 to 10 days)

Results:

For a tumor α/β = 10Gy, tumor max, min, mean, and D95 BED were about 20% larger than the BED for the conventional prescription. The EUD for the optimized fractionation schedule was up to 17% larger than conventional prescription. For fast proliferating tumor (Td < 10 days), there was no significant increase in tumor dose but the treatment course could be shortened, offering convenience for patients and efficient allocation of resources.