bluuebunny/crossref_metadata_2025 huggingface dataset:
WE‐FG‐207B‐09: Experimental Assessment of Noise and Spatial Resolution in Virtual Non‐Contrast Dual‐Energy CT Images Across Multiple Patient Sizes and CT Systems
Authors: Montoya J , Ferrero A , Yu L , Leng S , McCollough C
Published: July 2016

Purpose:

To investigate the noise and spatial resolution properties of virtual non‐contrast (VNC) dual‐energy CT images compared to true non‐contrast (TNC) images across multiple patient sizes and CT systems.

Methods:

Torso‐shaped water phantoms with lateral widths of 25, 30, 35, 40 and 45 cm and a high resolution bar pattern phantom (Catphan CTP528) were scanned using 2nd and 3rd generation dual‐source CT systems (Scanner A: Somatom Definition Flash, Scanner B: Somatom Force, Siemens Healthcare) in dual‐energy scan mode with the same radiation dose for a given phantom size. Tube potentials of 80/Sn140 and 100/Sn140 on Scanner A and 80/Sn150, 90/Sn150 and 100/Sn150 on Scanner B were evaluated to examine the impact of spectral separation. Images were reconstructed using a medium sharp quantitative kernel (Qr40), 1.0‐mm thickness, 1.0‐mm interval and 20 cm field of view. Mixed images served as TNC images. VNC images were created using commercial software (Virtual Unenhanced, Syngo VIA Version VA30, Siemens Healthcare). The noise power spectrum (NPS), area under the NPS, peak frequency of the NPS and image noise were measured for every phantom size and tube potential combination in TNC and VNC images. Results were compared within and between CT systems.

Results:

Minimal shift in NPS peak frequencies was observed in VNC images compared to TNC for NPS having pronounced peaks. Image noise and area under the NPS were higher in VNC images compared to TNC images across all tube potentials and for scanner A compared to scanner B. Limiting spatial resolution was deemed to be identical between VNC and TNC images.

Conclusion:

Quantitative assessment of image quality in VNC images demonstrated higher noise but equivalent spatial resolution compared to TNC images. Decreased noise was observed in the 3rd generation dual‐source CT system for tube potential pairs having greater spectral separation.

Dr. McCollough receives research support from Siemens Healthcare
WE‐G‐BRC‐00: Experiences with TG100 in Clinical Use
Authors: Kim Grace Gwe‐Ya
Published: July 2016

Failure Mode and Effects Analysis (FMEA) originated as an industrial engineering technique used for risk management and safety improvement of complex processes. In the context of radiotherapy, the AAPM Task Group 100 advocates FMEA as the framework of choice for establishing clinical quality management protocols. However, there is concern that widespread adoption of FMEA in radiation oncology will be hampered by the perception that implementation of the tool will have a steep learning curve, be extremely time consuming and labor intensive, and require additional resources. To overcome these preconceptions and facilitate the introduction of the tool into clinical practice, the medical physics community must be educated in the use of this tool and the ease in which it can be implemented. Organizations with experience in FMEA should share their knowledge with others in order to increase the implementation, effectiveness and productivity of the tool.

This session will include a brief, general introduction to FMEA followed by a focus on practical aspects of implementing FMEA for specific clinical procedures including HDR brachytherapy, physics plan review and radiosurgery. A description of common equipment and devices used in these procedures and how to characterize new devices for safe use in patient treatments will be presented. This will be followed by a discussion of how to customize FMEA techniques and templates to one's own clinic. Finally, cases of common failure modes for specific procedures (described previously) will be shown and recommended intervention methodologies and outcomes reviewed.

Learning Objectives:

Understand the general concept of failure mode and effect analysis

Learn how to characterize new equipment for safety

Be able to identify potential failure modes for specific procedures and learn mitigation techniques

Be able to customize FMEA examples and templates for use in any clinic
WE‐G‐BRC‐02: Risk Assessment for HDR Brachytherapy
Authors: Mayadev J.
Published: July 2016

Failure Mode and Effects Analysis (FMEA) originated as an industrial engineering technique used for risk management and safety improvement of complex processes. In the context of radiotherapy, the AAPM Task Group 100 advocates FMEA as the framework of choice for establishing clinical quality management protocols. However, there is concern that widespread adoption of FMEA in radiation oncology will be hampered by the perception that implementation of the tool will have a steep learning curve, be extremely time consuming and labor intensive, and require additional resources. To overcome these preconceptions and facilitate the introduction of the tool into clinical practice, the medical physics community must be educated in the use of this tool and the ease in which it can be implemented. Organizations with experience in FMEA should share their knowledge with others in order to increase the implementation, effectiveness and productivity of the tool.

This session will include a brief, general introduction to FMEA followed by a focus on practical aspects of implementing FMEA for specific clinical procedures including HDR brachytherapy, physics plan review and radiosurgery. A description of common equipment and devices used in these procedures and how to characterize new devices for safe use in patient treatments will be presented. This will be followed by a discussion of how to customize FMEA techniques and templates to one's own clinic. Finally, cases of common failure modes for specific procedures (described previously) will be shown and recommended intervention methodologies and outcomes reviewed.

Learning Objectives:

Understand the general concept of failure mode and effect analysis

Learn how to characterize new equipment for safety

Be able to identify potential failure modes for specific procedures and learn mitigation techniques

Be able to customize FMEA examples and templates for use in any clinic
WE‐G‐BRC‐03: Risk Assessment for Physics Plan Review
Authors: Parker S.
Published: July 2016

Failure Mode and Effects Analysis (FMEA) originated as an industrial engineering technique used for risk management and safety improvement of complex processes. In the context of radiotherapy, the AAPM Task Group 100 advocates FMEA as the framework of choice for establishing clinical quality management protocols. However, there is concern that widespread adoption of FMEA in radiation oncology will be hampered by the perception that implementation of the tool will have a steep learning curve, be extremely time consuming and labor intensive, and require additional resources. To overcome these preconceptions and facilitate the introduction of the tool into clinical practice, the medical physics community must be educated in the use of this tool and the ease in which it can be implemented. Organizations with experience in FMEA should share their knowledge with others in order to increase the implementation, effectiveness and productivity of the tool.

This session will include a brief, general introduction to FMEA followed by a focus on practical aspects of implementing FMEA for specific clinical procedures including HDR brachytherapy, physics plan review and radiosurgery. A description of common equipment and devices used in these procedures and how to characterize new devices for safe use in patient treatments will be presented. This will be followed by a discussion of how to customize FMEA techniques and templates to one's own clinic. Finally, cases of common failure modes for specific procedures (described previously) will be shown and recommended intervention methodologies and outcomes reviewed.

Learning Objectives:

Understand the general concept of failure mode and effect analysis

Learn how to characterize new equipment for safety

Be able to identify potential failure modes for specific procedures and learn mitigation techniques

Be able to customize FMEA examples and templates for use in any clinic
WE‐G‐209‐00: Identifying Image Artifacts, Their Causes, and How to Fix Them
Authors: Pooley Robert
Published: July 2016

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts.

This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts.

Learning Objectives:

Identify common artifacts found clinically in digital radiography, CT, PET and MR.

Determine causes of various clinical artifacts from digital radiography, CT, PET and MR.

Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.
WE‐G‐209‐02: CT
Authors: Kofler J.
Published: July 2016

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts.

This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts.

Learning Objectives:

Identify common artifacts found clinically in digital radiography, CT, PET and MR.

Determine causes of various clinical artifacts from digital radiography, CT, PET and MR.

Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.
WE‐G‐209‐03: PET
Authors: Kemp B.
Published: July 2016

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts.

This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts.

Learning Objectives:

Identify common artifacts found clinically in digital radiography, CT, PET and MR.

Determine causes of various clinical artifacts from digital radiography, CT, PET and MR.

Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.
WE‐G‐209‐04: MRI
Authors: Pooley R.
Published: July 2016

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts.

This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts.

Learning Objectives:

Identify common artifacts found clinically in digital radiography, CT, PET and MR.

Determine causes of various clinical artifacts from digital radiography, CT, PET and MR.

Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.
WE‐H‐BRC‐03: Failure Mode and Effects Analysis in the First Clinical Implementation of a Novel Stereotactic Breast Radiotherapy Device: GammaPod™
Authors: Mossahebi S , Feigenberg S , Nichols E , Niu Y , Becker S , Prado K , Yi B , Yu C , Mutaf Y
Published: July 2016

Purpose:

GammaPod™, the first stereotactic radiotherapy device for early stage breast cancer treatment, has been recently installed and commissioned at our institution. A multidisciplinary working group applied the failure mode and effects analysis (FMEA) approach to perform a risk analysis.

Methods:

FMEA was applied to the GammaPod™ treatment process by: 1) generating process maps for each stage of treatment; 2) identifying potential failure modes and outlining their causes and effects; 3) scoring the potential failure modes using the risk priority number (RPN) system based on the product of severity, frequency of occurrence, and detectability (ranging 1–10). An RPN of higher than 150 was set as the threshold for minimal concern of risk. For these high‐risk failure modes, potential quality assurance procedures and risk control techniques have been proposed. A new set of severity, occurrence, and detectability values were re‐assessed in presence of the suggested mitigation strategies.

Results:

In the single‐day image‐and‐treat workflow, 19, 22, and 27 sub‐processes were identified for the stages of simulation, treatment planning, and delivery processes, respectively. During the simulation stage, 38 potential failure modes were found and scored, in terms of RPN, in the range of 9ߝ392. 34 potential failure modes were analyzed in treatment planning with a score range of 16ߝ200. For the treatment delivery stage, 47 potential failure modes were found with an RPN score range of 16ߝ392. The most critical failure modes consisted of breast‐cup pressure loss and incorrect target localization due to patient upper‐body alignment inaccuracies. The final RPN score of these failure modes based on recommended actions were assessed to be below 150.

Conclusion:

FMEA risk analysis technique was applied to the treatment process of GammaPod™, a new stereotactic radiotherapy technology. Application of systematic risk analysis methods is projected to lead to improved quality of GammaPod™ treatments.

Ying Niu and Cedric Yu are affiliated with Xcision Medical Systems.
WE‐H‐BRC‐08: Examining Credentialing Criteria and Poor Performance Indicators for IROC Houston's Anthropomorphic Head and Neck Phantom
Authors: Carson M , Molineu A , Taylor P , Followill D , Kry S
Published: July 2016

Purpose:

To analyze the most recent results of IROC Houston's anthropomorphic H&N phantom to determine the nature of failing irradiations and the feasibility of altering pass/fail credentialing criteria.

Methods:

IROC Houston's H&N phantom, used for IMRT credentialing for NCI‐sponsored clinical trials, requires that an institution's treatment plan must agree with measurement within 7% (TLD doses) and ≥85% pixels must pass 7%/4 mm gamma analysis. 156 phantom irradiations (November 2014 – October 2015) were re‐evaluated using tighter criteria: 1) 5% TLD and 5%/4 mm, 2) 5% TLD and 5%/3 mm, 3) 4% TLD and 4%/4 mm, and 4) 3% TLD and 3%/3 mm. Failure/poor performance rates were evaluated with respect to individual film and TLD performance by location in the phantom. Overall poor phantom results were characterized qualitatively as systematic (dosimetric) errors, setup errors/positional shifts, global but non‐systematic errors, and errors affecting only a local region.

Results:

The pass rate for these phantoms using current criteria is 90%. Substituting criteria 1ߝ4 reduces the overall pass rate to 77%, 70%, 63%, and 37%, respectively. Statistical analyses indicated the probability of noise‐induced TLD failure at the 5% criterion was <0.5%. Using criteria 1, TLD results were most often the cause of failure (86% failed TLD while 61% failed film), with most failures identified in the primary PTV (77% cases). Other criteria posed similar results. Irradiations that failed from film only were overwhelmingly associated with phantom shifts/setup errors (≥80% cases). Results failing criteria 1 were primarily diagnosed as systematic: 58% of cases. 11% were setup/positioning errors, 8% were global non‐systematic errors, and 22% were local errors.

Conclusion:

This study demonstrates that 5% TLD and 5%/4 mm gamma criteria may be both practically and theoretically achievable. Further work is necessary to diagnose and resolve dosimetric inaccuracy in these trials, particularly for systematic dose errors.

This work is funded by NCI Grant CA180803.
WE‐H‐BRC‐09: Simulated Errors in Mock Radiotherapy Plans to Quantify the Effectiveness of the Physics Plan Review
Authors: Gopan O , Kalet A , Smith W , Hendrickson K , Kim M , Young L , Nyflot M , Chvetsov A , Phillips M , Ford E
Published: July 2016

Purpose:

A standard tool for ensuring the quality of radiation therapy treatments is the initial physics plan review. However, little is known about its performance in practice. The goal of this study is to measure the effectiveness of physics plan review by introducing simulated errors into “mock” treatment plans and measuring the performance of plan review by physicists.

Methods:

We generated six mock treatment plans containing multiple errors. These errors were based on incident learning system data both within the department and internationally (SAFRON). These errors were scored for severity and frequency. Those with the highest scores were included in the simulations (13 errors total). Observer bias was minimized using a multiple co‐correlated distractor approach. Eight physicists reviewed these plans for errors, with each physicist reviewing, on average, 3/6 plans. The confidence interval for the proportion of errors detected was computed using the Wilson score interval.

Results:

Simulated errors were detected in 65% of reviews [51–75%] (95% confidence interval [CI] in brackets). The following error scenarios had the highest detection rates: incorrect isocenter in DRRs/CBCT (91% [73–98%]) and a planned dose different from the prescribed dose (100% [61–100%]). Errors with low detection rates involved incorrect field parameters in record and verify system (38%, [18–61%]) and incorrect isocenter localization in planning system (29% [8–64%]). Though pre‐treatment QA failure was reliably identified (100%), less than 20% of participants reported the error that caused the failure.

Conclusion:

This is one of the first quantitative studies of error detection. Although physics plan review is a key safety measure and can identify some errors with high fidelity, others errors are more challenging to detect. This data will guide future work on standardization and automation. Creating new checks or improving existing ones (i.e., via automation) will help in detecting those errors with low detection rates.
WE‐H‐BRA‐02: Radiobiological Modeling of Tumor Control Probability (TCP) and Radiation‐Induced Pneumonitis (RP) for Lung Cancer Patients Treated with Monte Carlo‐Based Lung SBRT
Authors: Pokhrel D , Sood S , Shen X , Badkul R , McClinton C , Jiang H , Mitchell M , Lominska C , Wang F
Published: July 2016

Purpose:

To present radiobiological modeling of TCP using tumor size‐adjusted BED(s‐BED)and PTV(D99) to lung SBRT patients treated with X‐ray Voxel Monte Carlo(XVMC) algorithm, apply parameterized Lyman‐NTCP model to predict grade‐2 RP and subsequently, compare with clinical outcomes/observations.

Methods:

Dosimetric parameters and clinical follow‐up for XVMC‐based lung‐SBRT patients were retrospectively evaluated. Patients were treated at Novalis‐TX with hybrid(2 non‐coplanar partial‐arcs plus 3–6 static‐beams)plan using HD‐MLC/6MV‐SRS‐beam.For TCP,s‐BED modelling was utilized: TCP=EXP[sBED‐TCD50]/k/(1.0+EXP[sBED‐TCD50]/k), where k=31Gy corresponding to TCD50=0Gy and s‐BED was defined as BED10 minus 10 times the tumor diameter(in centimeters)by Ohri et al.(IJROBP,2012). For 2‐yr local‐control, we used more‐realistic MC‐computed PTVD99 as a predictive parameter, s‐BED(D99).Due to relatively shorter median follow‐up interval(12‐months),Kaplan‐Meier curves were generated to estimate 2‐yr observed local‐control and compared to predicted‐rate by TCP modeling. For NTCP, we employed parameterized Lyman‐NTCP model utilizing normal‐lung DVH and α/β=3Gy fitted to predict grade‐2 RP after lung‐SBRT.

Results:

Total 108 patients (137 tumors) treated for 35–70Gy in 3–5 fractions, either primary‐lung(n=74)or metastatic‐lung(n=53)tumors were included.F or the given prescription dose with MC‐computed MUs, 2‐yr local‐control rates with s‐BED(D99) was 87±8%. Kaplan‐Meier generated observed local‐control rate at 2‐yr was 87.5%,suggesting that PTV(D99) could be a potential predictor (p‐value=0.38). Observed vs predicted TCP for primary‐lung tumors and metastatic tumors were 97% vs 88±7% and 94% vs 86±9%.NTCP model predicted well for symptomatic‐RP with predicted vs observed (3±5% vs 2%). Radiographic and clinically significant RP was observed in 13% and 2% of patients. Higher rates of radiographic change were observed in patients who received >50Gy compared to ≤50Gy(24% vs 10%).

Conclusion:

Utilizing MC‐computed PTVD99, our TCP results were well correlated with clinical outcome. The predicted grade‐2 RP rate was comparable to clinical observations. Clinical application of these radiobiological models may potentially allow for target dose escalation and/or lung‐toxicity reduction. Further validation of these radiobiological models with longer follow up interval for large cohorts of lung‐SBRT patients is anticipated.
WE‐H‐BRA‐04: Biological Geometries for the Monte Carlo Simulation Toolkit TOPASNBio
Authors: McNamara A , Perl J , Piersimoni P , Ramos‐Mendez J , Faddegon B , Held K , Paganetti H , Schuemann J
Published: July 2016

Purpose:

New advances in radiation therapy are most likely to come from the complex interface of physics, chemistry and biology. Computational simulations offer a powerful tool for quantitatively investigating radiation interactions with biological tissue and can thus help bridge the gap between physics and biology. The aim of TOPAS‐nBio is to provide a comprehensive tool to generate advanced radiobiology simulations.

Methods:

TOPAS wraps and extends the Geant4 Monte Carlo (MC) simulation toolkit. TOPAS‐nBio is an extension to TOPAS which utilizes the physics processes in Geant4‐DNA to model biological damage from very low energy secondary electrons. Specialized cell, organelle and molecular geometries were designed for the toolkit.

Results:

TOPAS‐nBio gives the user the capability of simulating biological geometries, ranging from the micron‐scale (e.g. cells and organelles) to complex nano‐scale geometries (e.g. DNA and proteins). The user interacts with TOPAS‐nBio through easy‐to‐use input parameter files. For example, in a simple cell simulation the user can specify the cell type and size as well as the type, number and size of included organelles. For more detailed nuclear simulations, the user can specify chromosome territories containing chromatin fiber loops, the later comprised of nucleosomes on a double helix. The chromatin fibers can be arranged in simple rigid geometries or within factual globules, mimicking realistic chromosome territories. TOPAS‐nBio also provides users with the capability of reading protein data bank 3D structural files to simulate radiation damage to proteins or nucleic acids e.g. histones or RNA. TOPAS‐nBio has been validated by comparing results to other track structure simulation software and published experimental measurements.

Conclusion:

TOPAS‐nBio provides users with a comprehensive MC simulation tool for radiobiological simulations, giving users without advanced programming skills the ability to design and run complex simulations.
WE‐H‐BRA‐05: Investigation of LET Spectral Dependence of the Biological Effects of Therapeutic Protons
Authors: Guan F , Bronk L , Kerr M , Wang X , Li Y , Peeler C , Sahoo N , Patel D , Mirkovic D , Titt U , Grosshans D , Mohan R
Published: July 2016

Purpose:

To investigate the dependence of biologic effect (BE) of therapeutic protons on LET spectra by comparing BEs with equal dose‐averaged LET (LETd) derived from different LET spectra using high‐throughput in vitro clonogenic survival assays.

Methods:

We used Geant4 to design the relevant experimental setups and perform the dose, LETd, and LET spectra calculations for spot‐scanning protons. The clonogenic assay was performed using the H460 lung cancer cell line cultured in 96‐well plates. In the first experimental setup (S1), cells were irradiated using 127.4 MeV protons with a 93.22 mm Lucite buildup resulting in a LETd value of 3.4 keV/µm in the cell layer. In the second experimental setup (S2), cells were irradiated by a combination of 127.4 MeV and 136.4 MeV protons with a 96.61 mm Lucite buildup. The LETd values in the cell layer were 11.4 keV/µm and 1.5 keV/µm respectively, but an average LETd of 3.4 keV/µm was obtained by adjusting the relative fluence of each beam. Ten discrete dose levels with 0.5 Gy increments were delivered.

Results:

In the two setups, the energies or LET spectra were different but resulted in identical LETd values. We quantified the dose contributions from high‐LET (≥10 keV/µm, threshold determined by previous experiments) events in the LET spectra separately for these two setups as 3.2% and 10.5%. The biologic effects at each identical dose level yielded statistically significant different survival curves (extra sum‐of‐squares F‐test, P<0.0001). The second setup with a higher contribution from high‐LET events exhibited the higher biologic effect with a dose enhancement factor of 1.17±0.03 at 0.10 surviving fraction.

Conclusion:

The dose‐averaged LET may not be an accurate indicator of the biological effects of protons. Detailed LET spectra may need to be considered explicitly to accurately quantify the biologic effects of protons.

Funding Support: U19 CA021239‐35, R21 CA187484‐01 and MDACC‐IRG
WE‐H‐202‐04: Advanced Medical Image Registration Techniques
Authors: Christensen G.
Published: July 2016

Deformable image registration has now been commercially available for several years, with solid performance in a number of sites and for several applications including contour and dose mapping. However, more complex applications have arisen, such as assessing response to radiation therapy over time, registering images pre‐ and post‐surgery, and auto‐segmentation from atlases. These applications require innovative registration algorithms to achieve accurate alignment. The goal of this session is to highlight emerging registration technology and these new applications. The state of the art in image registration will be presented from an engineering perspective. Translational clinical applications will also be discussed to tie these new registration approaches together with imaging and radiation therapy applications in specific diseases such as cervical and lung cancers.

Learning Objectives:

To understand developing techniques and algorithms in deformable image registration that are likely to translate into clinical tools in the near future.

To understand emerging imaging and radiation therapy clinical applications that require such new registration algorithms.

Research supported in part by the National Institutes of Health under award numbers P01CA059827, R01CA166119, and R01CA166703. Disclosures: Phillips Medical systems (Hugo), Roger Koch (Christensen) support, Varian Medical Systems (Brock), licensing agreements from Raysearch (Brock) and Varian (Hugo).; K. Brock, Licensing Agreement ‐ RaySearch Laboratories. Research Funding ‐ Varian Medical Systems; G. Hugo, Research grant from National Institutes of Health, award number R01CA166119.; G. Christensen, Research support from NIH grants CA166119 and CA166703 and a gift from Roger Koch. There are no conflicts of interest.
WE‐H‐207A‐02: Attenuation Correction in 4D‐PET Using a Single‐Phase Attenuation Map
Authors: Kalantari F , Wang J
Published: July 2016

Purpose:

4D‐PET imaging has been proposed as a potential solution to the respiratory motion effect in thoracic region. CT‐based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference of 4D‐PET and a single breath‐hold CT, motion artifacts are observed in the attenuation‐corrected PET images that can lead to error in tumor shape and uptake. We introduce a practical method for aligning single‐phase CT to all other 4D‐PET phases using a penalized non‐rigid demons registration.

Methods:

Individual 4D‐PET frames were reconstructed without AC. Non‐rigid Demons registration was used to derive deformation vector fields (DVFs) between the PET matched with CT phase and other 4D‐PET images. While attenuated PET images provide enough useful data for organ borders such as lung and liver, tumors are not distinguishable from background due to loss of contrast. To preserve tumor shape in different phases, from CT image an ROI covering tumor was excluded from non‐rigid transformation. Mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of tumor along with a non‐rigid transformation of other organs. 4D XCAT phantom with spherical tumors in lung with diameters ranging from 10 to 40 mm was used to evaluate the algorithm.

Results:

Motion related induced artifacts in attenuation‐corrected 4D‐PET images were significantly reduced. For tumors smaller than 20 mm, non‐rigid transformation was capable to provide quantitative results. However, for larger tumors, where tumor self‐attenuation is considerable, our combined method yields superior results.

Conclusion:

We introduced a practical method for deforming a single CT to match all 4D‐PET images for accurate AC. Although 4D‐PET data include insignificant anatomical information, we showed that they are still useful to estimate DVFs for aligning attenuation map and accurate AC.
WE‐H‐209‐00: Carson/Zagzebski Distinguished Lectureship: Image Guided Ultrasound Therapy
Authors: Wilson Thaddeus
Published: July 2016

Focused ultrasound has been shown to be the only method that allows noninvasive thermal coagulation of tissues and recently this potential has been explored for image‐guided drug delivery. In this presentation, the advances in ultrasound phased array technology for energy delivery, exposure monitoring and control will be discussed. Experimental results from novel multi‐frequency transmit/receive arrays will be presented. In addition, the feasibility of fully electronically focused and steered high power arrays with many thousands of transducer elements will be discussed. Finally, some of the recent clinical and preclinical results for the treatment of brain disease will be reviewed.

Learning Objectives:

Introduce FUS therapy principles and modern techniques

Discuss use of FUS for drug delivery

Cover the technology required to deliver FUS and monitor therapy

Present clinical examples of the uses of these techniques

This research was supported by funding from The Canada Research Chair Program, Grants from CIHR and NIH (no. EB003268).; K. Hynynen, Canada Foundation for Innovation; Canadian Institutes of Health Research; Focused Ultrasound Surgery Foundation; Canada Research Chair Program; Natural Sciences and Engineering Research Council of Canada; Ontario Research Fund; National Institutes of Health; Canadian Cancer Society Research Institute; The Weston Brain Institute; Harmonic Medical; Focused Ultrasound Instruments
WE‐H‐207B‐03: MRI Guidance in the Radiation Therapy Clinic: Site‐Specific Discussions
Authors: Shang C.
Published: July 2016

In recent years, steady progress has been made towards the implementation of MRI in external beam radiation therapy for processes ranging from treatment simulation to in‐room guidance. Novel procedures relying mostly on MR data are currently implemented in the clinic. This session will cover topics such as (a) commissioning and quality control of the MR in‐room imagers and simulators specific to RT, (b) treatment planning requirements, constraints and challenges when dealing with various MR data, (c) quantification of organ motion with an emphasis on treatment delivery guidance, and (d) MR‐driven strategies for adaptive RT workflows. The content of the session was chosen to address both educational and practical key aspects of MR guidance.

Learning Objectives:

Good understanding of MR testing recommended for in‐room MR imaging as well as image data validation for RT chain (e.g. image transfer, filtering for consistency, spatial accuracy, manipulation for task specific);

Familiarity with MR‐based planning procedures: motivation, core workflow requirements, current status, challenges;

Overview of the current methods for the quantification of organ motion;

Discussion on approaches for adaptive treatment planning and delivery.

T. Stanescu ‐ License agreement with Modus Medical Devices to develop a phantom for the quantification of MR image system‐related distortions.; T. Stanescu, N/A
TH‐A‐204‐00: Key Dosimetry Data ‐ Impact of New ICRU Recommendations
Authors: Tosh Ronald
Published: July 2016

The ICRU is currently finalizing a report on key data for radiation dosimetry. This multi‐year review has resulted in a number of recommendations regarding “fundamental” data that are used in dosimetry related to radiation therapy. This educational session will explain the background for the ICRU committee's work, the content and conclusions of the report and the impact on outputs, including NIST primary standards, ADCL calibration coefficients and clinical reference dosimetry. Parameters and beam modalities potentially affected by this report include:

The mean excitation energy, I, for graphite, air, and water,

The average energy required to create an ion pair in dry air (commonly referred to as W/e),

The uncertainty in the determination of air kerma in kV xrays

The absolute value of Co‐60 and Cs‐137 primary standards and the dissemination of calibration coefficients,

The determination of air kerma strength for Ir‐192 HDR brachytherapy sources

Ion chamber kQ factors for linac MV beams

Ion chamber kQ factors for proton beams.

The changes in reference dosimetry that would result from adoption of the ICRU recommendations are of the order of 0.5% to 1%, an effect that will not impact clinical dose delivery but will be detectable in the clinical setting.

This session will also outline how worldwide metrology is coordinated through the Convention of the Meter and therefore how the international dosimetry community will proceed with adopting these recommendations so that uniformity from country to country in reference dosimetry is maintained. Timelines and communications methods will also be discussed to ensure that users, such as clinical medical physicists, are not surprised when their chamber's calibration coefficient apparently changes.

Learning Objectives:

Understand the background for the ICRU committee's work on key dosimetry data.

Understand the proposed changes to key data and the impacts on reference dosimetry.

Understand the methodology and timeline for adoption of the ICRU recommendations.
TH‐AB‐201‐01: A Feasibility Study of Independent Dose Verification for CyberKnife
Authors: Sato A , Noda T , Keduka Y , Kawajiri T , Itano M , Yamazaki T , Tachibana H
Published: July 2016

Purpose:

CyberKnife irradiation is composed of tiny‐size, multiple and intensity‐modulated beams compared to conventional linacs. Few of the publications for Independent dose calculation verification for CyberKnife have been reported. In this study, we evaluated the feasibility of independent dose verification for CyberKnife treatment as Secondary check.

Methods:

The followings were measured: test plans using some static and single beams, clinical plans in a phantom and using patient's CT. 75 patient plans were collected from several treatment sites of brain, lung, liver and bone. In the test plans and the phantom plans, a pinpoint ion‐chamber measurement was performed to assess dose deviation for a treatment planning system (TPS) and an independent verification program of Simple MU Analysis (SMU). In the clinical plans, dose deviation between the SMU and the TPS was performed.

Results:

In test plan, the dose deviations were 3.3±4.5%, and 4.1±4.4% for the TPS and the SMU, respectively. In the phantom measurements for the clinical plans, the dose deviations were −0.2±3.6% for the TPS and −2.3±4.8% for the SMU. In the clinical plans using the patient's CT, the dose deviations were −3.0±2.1% (Mean±1SD). The systematic difference was partially derived from inverse square law and penumbra calculation.

Conclusion:

The independent dose calculation for CyberKnife shows −3.0±4.2% (Mean±2SD) and our study, the confidence limit was achieved within 5% of the tolerance level from AAPM task group 114 for non‐IMRT treatment. Thus, it may be feasible to use independent dose calculation verification for CyberKnife treatment as the secondary check.

This research is partially supported by Japan Agency for Medical Research and Development (AMED)
TH‐AB‐201‐02: A TG‐61 Calibration Method for the Zeiss Intrabeam with Spherical Applicators
Authors: Siochi R
Published: July 2016

Purpose:

To develop an independent in‐air TG‐61 based calibration method for the Zeiss Intrabeam 50 kV x‐ray source and spherical applicators.

Methods:

We used the Zeiss supplied parallel plate chamber (TN34013), calibrated in water, and a micrometer staged water phantom to verify the annual factory water based calibration per Zeiss protocol. For independence, a second TN34013 chamber was calibrated at an ADCL at various energies in air. TG‐61 HVL measurements were performed to determine this chamber's calibration factor. The backscatter factor was determined by two independent means: (1) measurement with correction for chamber holder and stem, and (2) analysis of scatter geometry and buildup based on ratios of applicator transfer functions for various applicator sizes. To compare in‐air data against water data, a correction from the backscatter setup to the clinical setup was measured and corrected for geometry differences. To compare the water data against the factory calibration, a factory supplied correction factor for geometry and measurement setup differences was applied.

Results:

The HVL is 0.89 mm‐Al, consistent with published literature. The backscatter factors were 1.124 and 1.128 for methods 1 and 2 respectively, so we used their average, 1.126. The correction from the backscatter setup to the clinical setup was 0.9992 for the specific calibration geometry we selected (4 cm diameter applicator with a source to detector distance of 22 mm). The resulting TG‐61 dose rate, corrected to water, was 0.5771 Gy/min. The Zeiss protocol in water gave 0.5803 Gy/min. The Zeiss calibration value, corrected for the output of the day, was 0.5768 Gy/min. These are all within 1% of each other.

Conclusion:

An independent in‐air TG‐61 based method was successfully developed and shown to be in excellent agreement with a water based protocol and the factory calibration.
TH‐AB‐BRB‐04: Quality Assurance for Advanced Digital Linac Implementations
Authors: Yu V.
Published: July 2016

Current state‐of‐the art digital C‐arm medical linear accelerators are capable of delivering radiation treatments with high level of automation, which affords coordinated motions of gantry, couch, and multileaf collimator (MLC) with dose rate modulations. The new machine capacity has shown the potential to bring substantially improved radiation dosimetry and/or delivery efficiency to many challenging diseases. Combining an integrated beam orientation optimization algorithm with automated machine navigation, markedly improved dose conformity has been achieved using 4ρ therapy. Trajectory modulated radiation therapy (TMAT) can be used to deliver highly conformal dose to partial breast or to carve complex dose distribution for therapy involving extended volumes such as total marrow and total lymph node treatment. Dynamic electron arc radiotherapy (DEAR) not only overcomes the deficiencies of conventional electron therapy in dose conformity and homogeneity but also achieves so without patient‐specific shields. The combination of MLC and couch tracking provides improved motion management of thoracic and abdominal tumors. A substantial body of work has been done in these technological advances for clinical translation. The proposed symposium will provide a timely review of these exciting opportunities.

Learning Objectives:

Recognize the potential of using digitally controlled linacs for clinically significant improvements in delivered dose distributions for various treatment sites.

Identify existing approaches to treatment planning, optimization and delivery for treatment techniques utilizing the advanced functions of digital linacs and venues for further development and improvement.

Understand methods for testing and validating delivery system performance.

Identify tools available on current delivery systems for implementation and control for such treatments.

Obtain the update in clinical applications, trials and regulatory approval.

K. Sheng, NIH U19AI067769, NIH R43CA183390, NIH R01CA188300, Varian Medical Systems

V. Yu, Varian Medical Systems, AAPM Summer Undergraduate Fellowship, NSF graduate fellowship

S. Nill, Elekta AB. Cancer Research UK under Programme C33589/A19727, NIHR Biomedical Research Centre at The Royal Marsden and The Institute of Cancer Research.
TH‐AB‐BRA‐03: Backscatter Dose Factors Re‐Evaluated for Inhomogeneities in the Presence of a 1.5 T Magnetic Field Using the GPUMCD Monte Carlo Algorithm
Authors: Ahmad S , Sarfehnia A , Sahgal A , Keller B
Published: July 2016

Purpose:

To quantify the backscatter dose factors near the interfaces for clinically relevant high atomic number materials using GPUMCD for the Elekta MRI Linac.

Methods:

Backscatter dose factors (BSDF) were calculated as the ratio of the dose with and without the presence of the heterogeneity. The BSDF's were calculated either in the absence or presence of an orthogonal 1.5 T magnetic field. Doses were scored in small voxels of side 1 mm in a water phantom with dimensions of 20×20×20 cm using GPUMCD (Elekta). The minimum uncertainty in dose calculations was kept to 0.5%. A slab of thickness 2 cm, representing the inhomogeneity, was placed inside the phantom with variable position from the surface of the phantom. The slab was filled with either bone, aluminum, titanium, stainless steel, or dental amalgam. The phantom was irradiated using particles sampled from a histogram which represented the true MRI Linac spectrum.

Results:

With the application of the 1.5 T magnetic field (B‐On), all of the BSDF's were reduced by at least 8% compared to the no magnetic field (B‐Off) cases. For the B‐Off case, the BSDF decreases exponentially with the upstream distance away from the interface. With B‐On, the BSDF decreases exponentially for titanium, SS, and amalgam. However, it remains constant for Aluminum. In the case of bone, the BSDF increases up to a distance of 4 mm away from the interface in the presence of the magnetic field.

Conclusion:

The BSDF does not depend upon the thickness of the homogeneous material above the inhomogeneity for either the B‐Off or B‐On cases. For all the materials investigated, the BSDF is lower at the interface for the B‐On case. The exponential fall‐off of the BSDF away from the interface is not valid for all the materials when the magnetic field is turned ON.

Funding support for this research was provided by Elekta
TH‐AB‐BRA‐04: Dosimetric Evaluation of MR‐Guided HDR Brachytherapy Planning for Cervical Cancer
Authors: Kamio Y , Barkati M , Beliveau‐Nadeau D
Published: July 2016

Purpose:

To perform a retrospective study on 16 patients that had both CT and T2‐weighted MR scans done at first fraction using the Utrecht CT/MR applicator (Elekta Brachytherapy) in order to evaluate uncertainties associated with an MR‐only planning workflow.

Methods:

MR‐workflow uncertainties were classified in three categories: reconstruction, registration and contouring. A systematic comparison of the CT and MR contouring, manual reconstruction and optimization process was performed to evaluate the impact of these uncertainties on the recommended GEC ESTRO DVH parameters: D90% and V100% for HR‐CTV as well as D2cc for bladder, rectum, sigmoid colon and small bowel. This comparison was done using the following four steps: 1. Catheter reconstruction done on MR images with original CT‐plan contours and dwell times. 2. OAR contours adjusted on MR images with original CT‐plan reconstruction and dwell times. 3. Both reconstruction and contours done on MR images with original CT‐plan dwell times. 4. Entire MR‐based workflow optimized dwell times reimported to the original CT‐plan.

Results:

The MR‐based reconstruction process showed average D2cc deviations of 4.5 ± 3.0%, 1.5 ± 2.0%, 2.5 ± 2.0% and 2.0 ± 1.0% for the bladder, rectum, sigmoid colon and small bowels respectively with a maximum of 10%, 6%, 6% and 4%. The HR‐CTV's D90% and V100% average deviations was found to be 4.0 ± 3.0%, and 2.0 ± 2.0% respectively with a maximum of 10% and 6%. Adjusting contours on MR‐images was found to have a similar impact. Finally, the optimized MR‐based workflow dwell times were found to still give acceptable plans when re‐imported to the original CT‐plan which validated the entire workflow.

Conclusion:

This work illustrates a systematic validation method for centers wanting to move towards an MR‐only workflow. This work will be expanded to model based reconstruction, PD‐weighted images and other types of applicators.