bluuebunny/crossref_metadata_2025 huggingface dataset:
TH‐CD‐207A‐10: Using the Gamma Index to Flag Changes in Anatomy During Radiation Therapy of Head and Neck Cancer
Authors: Schaly B , Kempe J , Mitchell S , Venkatesan V , Battista J
Published: July 2016

Purpose:

This article presents a fast algorithm for comparing 3‐D anatomy from Cone‐Beam CT (CBCT) imaging using the gamma comparison index and to demonstrate how this can be used to flag patients for possible re‐planning of treatment.

Methods:

CBCT scans acquired on a Varian linear accelerator during treatment were used as input to the gamma comparator using thresholds of 5 mm distance to agreement and 30 Hounsfield Unit CT number difference. The fraction 1 CBCT study was initially used as the reference. Should there be a re‐plan during treatment, the reference resets to the CBCT study acquired on the day 1 of the re‐plan. Histograms of failing pixels (γ > 1) were generated from each 3‐D gamma map. An indicator of anatomy congruence, the match quality parameter (MQP), was derived from failed pixel histograms using the 90th percentile gamma value. The MQP was plotted versus fraction number and related to actual repeat computed tomography (re‐CT) order dates as decided by a radiation oncologist. From this, decision criteria were derived for the algorithm to “trigger” re‐CT consideration and predictive power was scored using receiver‐operator characteristic (ROC) analysis.

Results:

The MQP plot generally showed that the on‐line match from CBCT image guidance deteriorated as the treatment progressed due to weight loss and tumor regression. The optimized MQP criteria for triggering re‐CT consideration demonstrated high sensitivity and specificity, consistent with actual re‐CT order dates within ± 3 fractions. Out of 20 patients that were actually re‐planned, the algorithm failed to trigger a re‐CT recommendation only twice and this was caused by CBCT ring artifacts.

Conclusion:

We have demonstrated that gamma comparisons can be used to evaluate CBCT‐acquired anatomy pairs and, from this, an algorithm can be “trained” to flag patients for possible re‐planning in a manner consistent with local radiation oncology practice.
TH‐CD‐206‐06: Regularized Composite Shape Prior Encoding Shape Relevance in Variational Image Segmentation
Authors: Zhao T , Ruan D
Published: July 2016

Purpose:

Variational image segmentation incorporating regularized composite shape prior (RCSP) based on a shape dictionary has demonstrated benefits in robustness and accuracy. However, it still has the risk of local minimum in a non‐convex optimization setting. This study aims to drive the variational segmentation towards global optimum by introducing hyper prior on the composite weights of RCSP, which encode the shape priors’ relevance to the specific segmentation task.

Methods:

In addition to using a RCSP to regularize the variational segmentation, where the RCSP is constructed by a linear combination of the shape dictionary, this study introduces a hyper prior on the linear weights of this shape composite. More specifically, geometric relevance of each shape in the dictionary to the unknown target segmentation is inferred from image based surrogate metrics. Such relevance value is used as hyper prior and imposed on the linear weights of the composite shapes. The resulted RCSP with hyper prior regularization is incorporated in a unified active contour optimization framework and a variational block‐descent algorithm is derived and implemented.

Results:

The performance was assessed on corpus callosum segmentation using a brain MR dataset, and compared with typical benchmark approaches. The resulted RCSP demonstrated proper composition of training data w.r.t. their individual geometric relevance. The accuracy of ultimate segmentation estimates yielded statistically significant improvement with mean and medium Dice similarity coefficient (DSC) of (.946, .963) compared to (.902, .919), (.932, .946), and (.944, .964) for ATLAS based scheme, Chan Vese active contour model and an existing RCSP model, respectively.

Conclusion:

This work has developed a hyper prior to encode shape priors’ geometric relevance for RCSP regularization in a variational segmentation framework, leading to superior segmentation over benchmark approaches.
TH‐CD‐209‐08: Quantification of the Interplay Effect in Proton Pencil Beam Scanning Treatment of Lung
Authors: Kang M , Huang S , Solberg T , Mayer R , Thomas A , Teo B , McDonough J , Simone C , Lin L
Published: July 2016

Purpose:

To quantify the dose degradation caused by the interplay effect based on a beam specific motion analysis in proton pencil beam scanning (PBS) treatment of lung tumors

Methods:

PBS plans were optimized on average CT using a beam‐specific PTV method for 10 consecutive patients with locally advanced non‐small‐cell‐lung‐cancer (NSCLC) treated with proton therapy to 6660/180 cGy. End inhalation (CT0) and end exhalation (CT50) were selected as the two extreme scenarios to acquire the relative stopping power ratio difference (Δrsp) for a respiration cycle. The water equivalent difference (ΔWET) per radiological path was calculated from the surface of patient to the iCTV by integrating the Δrsp of each voxel. The motion magnitude of each voxel within the target follows a quasi‐Gaussian distribution. A motion index (MI (>5mm WET)), defined as the percentage of target voxels with an absolute integral ΔWET larger than 5 mm, was adopted as a metric to characterize interplay. To simulate the treatment process, 4D dose was calculated by accumulating the spot dose on the corresponding respiration phase to the reference phase CT50 by deformable image registration based on spot timing and patient breathing phase.

Results:

The study indicated that the magnitude of target underdose in a single fraction plan is proportional to the MI (p<0.001), with larger motion equating to greater dose degradation and standard deviations. The target homogeneity, minimum, maximum and mean dose in the 4D dose accumulations of 37 fractions varied as a function of MI.

Conclusion:

The MI quantification metric can predict the level of dose degradation in PBS lung cancer treatment, which potentially serves as a clinical decision tool to assess whether patients are suitable to receive PBS treatment.
TH‐CD‐209‐09: Quickly Identifying Good Candidates for Proton Therapy From Geometric Considerations
Authors: Hall D , Trofimov A , Winey B , Liebsch N , Paganetti H
Published: July 2016

Purpose:

We developed a knowledge‐based model that can predict the patient‐specific benefits of proton therapy based upon geometric considerations. The model could also aid patient selection in model‐based clinical trials or help justify clinical decisions to insurance companies.

Methods:

The knowledge‐based method trains a model upon existing proton treatment plans, exploiting correlations between dose and distance‐to‐target. Each OAR is split into concentric subvolumes surrounding the target volume, and a skew‐normal PDF is fit to the dose distribution found within each shell. The model learns from shared trends in how the best‐fit skew‐normal parameters depend upon distance‐to‐target. It can then predict feasible OAR DVHs for a new patient (without a proton plan) based upon their geometry. The expected benefits of proton therapy are assessed by comparing the predicted DVHs to those of an IMRT plan, using a metric such as the equivalent uniform dose (EUD).

Results:

A model was trained for clival chordoma, owing to its geometric complexity and the multitude of nearby OARs. The model was trained using 20 patients and validated with a further 20 patients, and considers several different OARs. The predicted EUD was in good agreement with that of the actual proton plan. The coefficient of determination (R‐squared) was 85% overall, 92% for cochleas, 80% for optic chiasm and 79% for spinal cord. The model exhibited no signs of bias or overfitting. When compared to an IMRT plan, the model could classify whether a patient will experience a gain or a loss with an accuracy between 75% and 95%, depending upon the OAR.

Conclusion:

We developed a model that can quickly and accurately predict the patient‐specific benefits of proton therapy in clival chordoma patients, though models could be trained for other tumor sites.

This work is funded by National Cancer Institute grant U19 CA 021239.
TH‐CD‐207B‐02: An Automated Technique to Measure Spatial Resolution in Clinical CT Images: Application to Patient Data
Authors: Sanders J , Ding A , Samei E
Published: July 2016

Purpose:

To evaluate an automated technique for measuring spatial resolution across a database of clinical CT exams.

Methods:

A fully automated algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge‐spread function (ESF) across the patient's skin and converting the results into scalar values, frequency at 50% RI, f50. The program was previously validated against observer data. This algorithm was applied to a database of CT images from our hospital that were reconstructed with different reconstruction algorithms (filtered back‐projection and iterative) and reconstruction kernels (soft and hard). The results were analyzed in terms of mean and variability within reconstruction methods and kernel aspects of the protocols.

Results:

The automated algorithm successfully measured the RI index from all of the clinical datasets examined. The measured f50 values increased with harder kernels for both FBP and iterative reconstruction. The mean f50 was 0.30 ± 0.02 mm‐1 and 0.42 ± 0.03 mm‐1 for images reconstructed with soft and hard kernels, respectively, using filtered back‐projection. The corresponding values for iterative reconstructions were 0.34 ± 0.02 mm‐1 and 0.39 ± 0.03 mm‐1, respectively. Overall, there was more variability in the f50 measurements made on datasets reconstructed with a hard kernel. The differences were statistically significant (p<0.05).

Conclusion:

Clinically‐informed, patient‐specific spatial resolution can be measured from clinical datasets. The method is sufficiently sensitive to reflect changes in spatial resolution due to different reconstruction parameters. The method can be applied to automatically assess the spatial resolution of patient images and quantify dependencies that may not be captured in phantom data.
TH‐CD‐207B‐03: How to Quantify Temporal Resolution in X‐Ray MDCT Imaging?
Authors: Budde A , Li Y , Hsieh J , Chen G
Published: July 2016

Purpose:

In modern CT scanners, a quantitative metric to assess temporal response, namely, to quantify the temporal resolution (TR), remains elusive. Rough surrogate metrics, such as half of the gantry rotation time for single source CT, a quarter of the gantry rotation time for dual source CT, or measurements of motion artifact's size, shape, or intensity have previously been used. In this work, a rigorous framework which quantifies TR and a practical measurement method are developed.

Methods:

A motion phantom was simulated which consisted of a single rod that is in motion except during a static period at the temporal center of the scan, termed the TR window. If the image of the motion scan has negligible motion artifacts compared to an image from a totally static scan, then the system has a TR no worse than the TR window used. By repeating this comparison with varying TR windows, the TR of the system can be accurately determined. Motion artifacts were also visually assessed and the TR was measured across varying rod motion speeds, directions, and locations. Noiseless fan beam acquisitions were simulated and images were reconstructed with a short‐scan image reconstruction algorithm.

Results:

The size, shape, and intensity of motion artifacts varied when the rod speed, direction, or location changed. TR measured using the proposed method, however, was consistent across rod speeds, directions, and locations.

Conclusion:

Since motion artifacts vary depending upon the motion speed, direction, and location, they are not suitable for measuring TR. In this work, a CT system with a specified TR is defined as having the ability to produce a static image with negligible motion artifacts, no matter what motion occurs outside of a static window of width TR. This framework allows for practical measurement of temporal resolution in clinical CT imaging systems.

Funding support: GE Healthcare; Conflict of Interest: Employee, GE Healthcare.
TH‐CD‐207B‐07: Noise Modeling of Single Photon Avalanche Diode (SPAD) for Photon Counting CT Applications
Authors: Cheng Z , Zheng X , Deen J , Peng H , Xing L
Published: July 2016

Purpose:

Silicon photomultiplier (SiPM) has recently emerged as a promising photodetector for biomedical imaging applications. Due to its high multiplication gain (comparable to PMT), fast timing, low cost and compactness, it is considered a good candidate for photon counting CT. Dark noise is a limiting factor which impacts both energy resolution and detection dynamic range. Our goal is to develop a comprehensive model for noise sources for SiPM sensors.

Methods:

The physical parameters used in this work were based upon a test SPAD fabricated in 130nm CMOS process. The SPAD uses an n+/p‐well junction, which is isolated from the p‐substrate by a deep n‐well junction. Inter‐avalanche time measurement was used to record the time interval between two adjacent avalanche pulses. After collecting 1×106 counts, the histogram was obtained and multiple exponential fitting process was used to extract the lifetime associated with the traps within the bandgap.

Results:

At room temperature, the breakdown voltage of the SPAD is ∼11.4V and shows a temperature coefficient of 7.7mV/°C. The dark noise of SPAD increases with both the excess biasing voltage and temperature. The primary dark counts from the model were validated against the measurement results. A maximum relative error of 8.7% is observed at 20 °C with an excess voltage of 0.5V. The probabilities of after‐pulsing are found to be dependent of both temperature and excess voltage. With 0.5V excess voltage, the after‐pulsing probability is 63.5% at ‐ 30 °C and drops to ∼6.6% at 40 °C.

Conclusion:

A comprehensive noise model for SPAD sensor was proposed. The model takes into account of static, dynamic and statistical behavior of SPADs. We believe that this is the first SPAD circuit simulation model that includes the band‐to‐band tunneling dark noise contribution and temporal dependence of the after‐pulsing probability.
TH‐CD‐207B‐08: Relationship Between Pixel Noise and Task‐Specific Low Contrast Detectability for Various Patient Sizes in Abdomen CT
Authors: Nute J , Zhou Y , Scott A , Lee C
Published: July 2016

Purpose:

To establish a relationship between pixel noise and the statistically defined minimum detectable contrast for various phantom sizes in order to provide a means for dose modulation driven by the task‐specific low contrast detectability.

Methods:

Seven anthropomorphically‐shaped abdomen phantoms (TE01‐TE08, CIRS) were employed to mimic a wide range of patient sizes. Each phantom was scanned on a Siemens 64‐slice mCT using a range of CTDIvol values (1–38mGy) with an average of 19 dose levels per phantom. Pixel noise was determined from the pixel standard deviations in the uniform phantom background of the images. The low contrast detectability was characterized in the following manner: adjacent slices were subtracted and regions representing uniform phantom background were partitioned to matrices with elements matching the size of the lesion (1.8–10 mm). For each dose level and lesion size, the mean pixel value from each matrix element was computed and the distribution was tested against Gaussian. The minimum detectable contrast (MDC) was defined by 3.29 multiplied by the standard deviation of the aforementioned distribution. We proposed that MDC is proportional to pixel noise and inversely proportional to the lesion size and that the proportionality factor is a function of the phantom size. This model was used to fit the MDC data and the dependency of the proportionality factor on the phantom size was examined.

Results:

Pixel noise distributions were found to be Gaussian (p<0.05) in over 99% of cases. The proportionality factor of our model was found to be stable as the phantom size changes (mean = 0.301, coefficient of variation ranges from −2.42% to 5.22%).

Conclusion:

The relationship between pixel noise and task‐specific MDC has been characterized for a range of patient sizes. This relationship is the first step in establishing dose modulation driven by patient‐ and task‐specific low contrast detectability.
TH‐CD‐207B‐12: Quantification of Clinical Feedback On Image Quality Differences Between Two CT Scanner Models
Authors: Bache S , Liu X , Loyer E , Rong J
Published: July 2016

Purpose:

This work sought to quantify a radiology team's assessment of image quality differences between two CT scanner models currently in clinical use, with emphasis on noise and low‐contrast detectability (LCD).

Methods:

A water phantom and a Kagaku anthropomorphic body phantom were scanned on GE Discovery CT750 HD and LightSpeed VCT scanners (4 each) with identical scan parameters and reconstructed to 2.5mm/5.0mm thicknesses. Images of water phantom were analyzed at the scanner console with a built‐in LCD tool that uses statistical methods to compute requisite CT‐number contrast for 95% confidence in detection of a user‐defined object size. LCD value was computed for 5mm, 3mm, and 1mm objects. Analysis of standard deviation and LCD values were performed on Kagaku phantom images within liver, stomach, and spleen. LCD value was computed for 4mm, 3mm, and 1mm objects using a benchmarked MATLAB implementation of the GE scanner‐console tool.

Results:

Water LCD values were larger (poorer performance) for all HD scanners compared to VCT scanners. Mean scanner model difference in requisite CT‐number contrast for 5mm, 3mm, and 1mm objects for 5.0mm/2.5mm images was 3.0%/3.4% (p=0.02/p=0.10), 5.3%/5.7% (0.00002/0.02), and 8.5%/8.2% (0.0004/0.002), respectively. Mean standard deviations within Kagaku phantom ROIs were greater in HD compared to VCT images, with mean differences for the liver, stomach, and spleen for 5.0mm/2.5mm of 16%/12% (p=0.04/0.10), 8%/12% (0.15/0.11), and 16%/15% (0.05/0.11), respectively. Mean LCD value difference between HD and VCT scanners over all ROIs for 4mm, 3m, and 1mm objects and 5.0mm/2.5mm was 34%/9%, 16%/8%, and 18%/10%, respectively. HD scanners outperformed VCT scanners only for the 4mm stomach object.

Conclusion:

Using both water and anthropomorphic phantoms, it was shown that HD scanners are outperformed by VCT scanners with respect to noise and LCD in a consistent and in most cases statistically significant manner. The relationship between statistical and clinical significance demands further work.
TH‐EF‐BRC‐00: TG‐100 Workshop
Authors: Dunscombe Peter
Published: July 2016

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

Learning Objectives:

To review the principles of Process Mapping, Failure Modes and Effects Analysis and Fault Tree Analysis.

To gain familiarity with these three techniques in a small group setting.

To share and discuss experiences with the three techniques with faculty and participants.

Director, TreatSafely, LLC. Director, Center for the Assessment of Radiological Sciences. Occasional Consultant to the IAEA and Varian.
TH‐EF‐BRC‐02: FMEA
Authors: Huq M.
Published: July 2016

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

Learning Objectives:

To review the principles of Process Mapping, Failure Modes and Effects Analysis and Fault Tree Analysis.

To gain familiarity with these three techniques in a small group setting.

To share and discuss experiences with the three techniques with faculty and participants.

Director, TreatSafely, LLC. Director, Center for the Assessment of Radiological Sciences. Occasional Consultant to the IAEA and Varian.
TH‐D‐BRC‐04: Panel Member
Authors: Yu C.
Published: July 2016

Interest in proton therapy has increased dramatically in the past couple of years, especially in the United States. There certainly is an important place for proton therapy in the arsenal of cancer treatments. Its dosimetric advantage and potential for low toxicity makes it the perfect partner for photons and other cancer treatment modalities.

Often there is a belief that the new technology ought to be better but many believe that they should be widely adopted in the clinic only after evidence has shown that they are at least as safe and efficacious as existing technologies, which are often less expensive. This is the case for proton radiotherapy.

This session being both educational and debate will provide a good review of basics and technological advancement as well as a comprehensive clinical update for both proton and photon therapy.

Future technology developments and how they will impact the potential dosimetric advantage of proton therapy will be discussed. Particularly the debate will focus on whether these developments will close or widen the gap between photon and proton therapy.

Learning Objectives:

To review challenges, limitations, and recent and future developments in proton therapy.

To review challenges, limitations, recent and future developments in photon radiotherapy.

To review current clinical trials and challenging clinical cases.

C. Yu, No company or organization that my presentation mentions provided me with financial support. I am the Founder and CEO of Xcision Medical Systems, LLC. However, my presentation will not mention any product or technology developed by Xcision.
TH‐D‐BRB‐00: An Introduction to Research and Clinical Development Using Treatment Planning System APIs
Authors: Popple Richard
Published: July 2016

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

Learning Objectives:

Understand the scripting capabilities available in several treatment planning systems

Learn how to get started using scripting capabilities

Understand the best practices for safe script deployment in a clinical environment

R. Popple, Varian Medical Systems has provided research support unrelated to the topic of this session.R. Cardan, Varian Medical Systems for grant research, product evaluation, and teaching honorarium.
TH‐E‐201‐02: Hands‐On Physics Teaching of Residents in Diagnostic Radiology
Authors: Zhang J.
Published: July 2016

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

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

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

Learning Objectives:

Learn updated physics requirements for radiology residents

Pursue effective approaches to teach physics to radiology residents

Learn expectation of physics teaching from resident perspective

J. Zhang, This topic is partially supported by RSNA Education Scholar Grant
TH‐EF‐BRC‐03: Fault Tree Analysis
Authors: Thomadsen B.
Published: July 2016

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

Learning Objectives:

To review the principles of Process Mapping, Failure Modes and Effects Analysis and Fault Tree Analysis.

To gain familiarity with these three techniques in a small group setting.

To share and discuss experiences with the three techniques with faculty and participants.

Director, TreatSafely, LLC. Director, Center for the Assessment of Radiological Sciences. Occasional Consultant to the IAEA and Varian.
TH‐EF‐204‐06: Closing
Authors: Borras C.
Published: July 2016

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

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

Learning Objectives:

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

To learn about detectors suitable for small fields

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

To provide an overview of the IAEA small field dosimetry recommendations

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

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

To appreciate specific challenges of IMRT implementation

J. Seuntjens, Natural Sciences and Engineering Research Council; Canadian Institutes of Health Research
TH‐EF‐BRB‐08: Robotic Motion Compensation for Radiation Therapy: A 6DOF Phantom Study
Authors: Belcher AH , Liu X , Wiersma R
Published: July 2016

Purpose:

The high accuracy of frame‐based stereotactic radiosurgery (SRS), which uses a rigid frame fixed to the patient's skull, is offset by potential drawbacks of poor patient compliance and clinical workflow restrictions. Recent research into frameless SRS has so far resulted in reduced accuracy. In this study, we investigate the use of a novel 6 degree‐of‐freedom (6DOF) robotic head motion cancellation system that continuously detects and compensates for patient head motions during a SRS delivery. This approach has the potential to reduce invasiveness while still achieving accuracies better or equal to traditional frame‐based SRS.

Methods:

A 6DOF parallel kinematics robotics stage was constructed, and controlled using an inverse kinematics‐based motion compensation algorithm. A 6DOF stereoscopic infrared (IR) marker tracking system was used to monitor real‐time motions at sub‐millimeter and sub‐degree levels. A novel 6DOF calibration technique was first applied to properly orient the camera coordinate frame to match that of the LINAC and robotic control frames. Simulated head motions were measured by the system, and the robotic stage responded to these 6DOF motions automatically, returning the reflective marker coordinate frame to its original position.

Results:

After the motions were introduced to the system in the phantom‐based study, the robotic stage automatically and rapidly returned the phantom to LINAC isocenter. When errors exceeded the compensation lower threshold of 0.25 mm or 0.25 degrees, the system registered the 6DOF error and generated a cancellation trajectory. The system responded in less than 0.5 seconds and returned all axes to less than 0.1 mm and 0.1 degree after the 6DOF compensation was performed.

Conclusion:

The 6DOF real‐time motion cancellation system was found to be effective at compensating for translational and rotational motions to current SRS requirements. This system can improve frameless SRS by automatically returning patients to isocenter with high 6DOF accuracy.
TH‐EF‐BRB‐11: Volumetric Modulated Arc Therapy for Total Body Irradiation
Authors: Ouyang L , Folkerts M , Hrycushko B , Lamphier R , Lee H , Yan Y , Jiang S , Timmerman R , Desai N , Abulrahman R , Gu X
Published: July 2016

Purpose:

To develop a modern, patient‐comfortable total body irradiation (TBI) technique suitable for standard‐sized linac vaults.

Methods:

An indexed rotatable immobilization system (IRIS) was developed to make possible total‐body CT imaging and radiation delivery on conventional couches. Treatment consists of multi‐isocentric volumetric modulated arc therapy (VMAT) to the upper body and parallel‐opposed fields to the lower body. Each isocenter is indexed to the couch and includes a 180° IRIS rotation between the upper and lower body fields. VMAT fields are optimized to satisfy lung dose objectives while achieving a uniform therapeutic dose to the torso. End‐to‐end tests with a rando phantom were used to verify dosimetric characteristics. Treatment plan robustness regarding setup uncertainty was assessed by simulating global and regional isocenter setup shifts on patient data sets. Dosimetric comparisons were made with conventional extended distance, standing TBI (cTBI) plans using a Monte Carlo‐based calculation. Treatment efficiency was assessed for eight courses of patient treatment.

Results:

The IRIS system is level and orthogonal to the scanned CT image plane, with lateral shifts <2mm following rotation. End‐to‐end tests showed surface doses within ±10% of the prescription dose, field junction doses within ±15% of prescription dose. Plan robustness tests showed <15% changes in dose with global setup errors up to 5mm in each direction. Local 5mm relative setup errors in the chest resulted in < 5% dose changes. Local 5mm shift errors in the pelvic and upper leg junction resulted in <10% dose changes while a 10mm shift error causes dose changes up to 25%. Dosimetric comparison with cTBI showed VMAT‐TBI has advantages in preserving chest wall dose with flexibility in leveraging the PTV‐body and PTV‐lung dose.

Conclusion:

VMAT‐TBI with the IRIS system was shown clinically feasible as a cost‐effective approach to TBI for standard‐sized linac vaults.
TH‐EF‐BRA‐01: 5D Respiratory Motion Model Based Iterative Reconstruction Method for 4DCBCT
Authors: Liu J , Low D , Gao H
Published: July 2016

Purpose:

The 4DCBCT image reconstruction suffers from the insufficient number of projections and the error from projection binning. We have recently developed a 5D respiratory motion model based iterative reconstruction method (5D method) for 4DCBCT in a proof‐of‐concept 2D setting. The 5D method reconstructs a reference image and two time‐independent vector fields without projection binning, based on which any temporal phase at each projection can be generated. As a result, the 5D method needs fewer number of projections and is free from binning error. This work is to develop a 3D version of the 5D method.

Methods:

The 5D method is based on the 5D respiratory motion model, for which the tidal volume and airflow are measured together with projection data. To reconstruct a reference image and two time‐independent vector fields that are needed to generate any temporal phase for each projection, the 5D method is formulated as a optimization problem with total variation (TV) regularization on both reference image and vector fields. The problem is solved by the proximal alternating minimization algorithm, during which the split Bregman method is used to reconstruct the reference image, and the Chambolle's duality‐based algorithm is used to reconstruct the vector fields.

Results:

The proposed 5D method was validated in simulation based on measurements of a lung patient, in comparison with the state‐of‐art spatiotemporal‐TV‐based 4DCBCT iterative method. And the results suggest that the 5D method had significantly improved reconstruction image quality and reduced quantitative error.

Conclusion:

A novel iterative image reconstruction method for 4DCBCT based on 5D respiratory motion model has been developed with no projection binning requirement and improved reconstruction image quality.

Jiulong Liu and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).
TH‐EF‐BRA‐09: Direct Comparison of T2‐Based Respiratory‐Correlated 4DMRI Reconstructed from Simultaneous Internal Navigator and External Bellows
Authors: Li G , Olek D , Wei J , Kadbi M , Tyagi N , Zakian K , Mechalakos J , Deasy J , Hunt M
Published: July 2016

Purpose:

To optimize T2‐based respiratory‐correlated 4DMRI for motion simulation, we evaluated the image quality after 4D reconstruction based on the two respiratory surrogates acquired independently and concurrently during the same breathing period.

Methods:

Both internal navigator and external bellows were employed simultaneously during a 4DMRI acquisition on seven volunteers scanned coronally and sagittally under an IRB‐approved protocol. The navigator was positioned at the right diaphragm dome while the bellows was placed at the upper abdomen. Using the navigator as the primary surrogate, prospective amplitude‐binning was used to fill respiratory bins and anatomic slices to complete the amplitud‐elocation table on the fly to reconstruct a single‐breath 4DMRI. Five bins in both inhalation and exhalation were used, forming a 10‐bin 4DMRI. Following the same binning method, a bellows‐based 4DMRI was then reconstructed retrospectively using a MATLAB programs developed for the rebinning and data analysis. The two surrogates were compared on 1D breathing waveforms and 4D image quality around the diaphragms. The waveform comparison included correlations in inhalation and exhalation, hysteresis analysis by ellipsoidal fitting, and histogram analysis for slice redistribution in bellows‐based bins. Image quality comparison between the navigator‐based and bellows‐based 4DMRI included motion artifact visualization and phase‐shift quantification at the right and left diaphragms.

Results:

The correlation between the navigator and bellows is usually higher in inhalation than exhalation. Their non‐linear relationship is represented using ellipsoidal fitting with minor‐to‐major‐axis ratio of 0.2–0.5 and by cross‐correlation with phase shifts (0.2–2). Overall, navigator‐based 4DMRI has superior image quality, although artifacts at anatomy distant to the navigator, such as the left diaphragm, are observed.

Conclusion:

This is the first time that two‐differently‐binned 4DMRI image sets from the same breathing period have been directly compared. Navigator‐based 4DMRI is generally superior to bellows‐based 4DMRI, making it clearly suitable for tumor delineation in future clinical applications.

This study is in part supported by the NIH (U54CA137788/U54CA132378). Also, this research is collaborated with Philips Healthcare.
TH‐EF‐207A‐03: Photon Counting Implementation Challenges Using An Electron Multiplying Charged‐Coupled Device Based Micro‐CT System
Authors: Podgorsak A , Bednarek D , Rudin S , Ionita C
Published: July 2016

Purpose:

To successfully implement and operate a photon counting scheme on an electron multiplying charged‐coupled device (EMCCD) based micro‐CT system.

Methods:

We built an EMCCD based micro‐CT system and implemented a photon counting scheme. EMCCD detectors use avalanche transfer registries to multiply the input signal far above the readout noise floor. Due to intrinsic differences in the pixel array, using a global threshold for photon counting is not optimal. To address this shortcoming, we generated a threshold array based on sixty dark fields (no x‐ray exposure). We calculated an average matrix and a variance matrix of the dark field sequence. The average matrix was used for the offset correction while the variance matrix was used to set individual pixel thresholds for the photon counting scheme. Three hundred photon counting frames were added for each projection and 360 projections were acquired for each object. The system was used to scan various objects followed by reconstruction using an FDK algorithm.

Results:

Examination of the projection images and reconstructed slices of the objects indicated clear interior detail free of beam hardening artifacts. This suggests successful implementation of the photon counting scheme on our EMCCD based micro‐CT system.

Conclusion:

This work indicates that it is possible to implement and operate a photon counting scheme on an EMCCD based micro‐CT system, suggesting that these devices might be able to operate at very low x‐ray exposures in a photon counting mode. Such devices could have future implications in clinical CT protocols.

NIH Grant R01EB002873; Toshiba Medical Systems Corp.
TH‐F‐202‐03: Advances in MRI for Radiation Therapy
Authors: Cai J.
Published: July 2016

MRI has excellent soft tissue contrast and can provide both anatomical and physiological information. It is becoming increasingly important in radiation therapy for treatment planning, image‐guided radiation therapy, and treatment assessment. It is critically important at this time point to educate and update our medical physicists about MRI to prepare for the upcoming surge of MRI applications in radiation therapy. This session will review important basics of MR physics, pulse sequence designs, and current radiotherapy application, as well as showcase exciting new developments in MRI that can be potentially useful in radiation therapy.

Learning Objectives:

To learn basics of MR physics and understand the differences between various pulse sequences

To review current applications of MRI in radiation therapy.To discuss recent MRI advances for future MRI guided radiation therapy

Partly supported by NIH (1R21CA165384).; W. Miller, Research supported in part by Siemens Healthcare; G. Li, My clinical research is in part supported by NIH U54CA137788. I have a collaborative research project with Philips Healthcare.; J. Cai, jing cai
TH‐E‐209‐00: Radiation Dose Monitoring and Protocol Management
Authors: Palmer Matthew
Published: July 2016

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data‐driven protocol management and informed case follow up are now feasible.

Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co‐exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex.

Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home‐grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope.

Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home‐grown IT solution and dose data analysis framework.

Learning Objectives:

Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice

Review examples of data available from a variety of systems and how it managed and conveyed.

Reflect on the role of the physicist in radiation dose awareness.
TH‐E‐209‐01: Fluoroscopic Dose Monitoring and Patient Follow‐Up Program at Massachusetts General Hospital
Authors: Liu B.
Published: July 2016

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data‐driven protocol management and informed case follow up are now feasible.

Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co‐exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex.

Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home‐grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope.

Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home‐grown IT solution and dose data analysis framework.

Learning Objectives:

Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice

Review examples of data available from a variety of systems and how it managed and conveyed.

Reflect on the role of the physicist in radiation dose awareness.
TH‐F‐201‐00: Writing Good Multiple Choice Questions
Authors: Bloch Charles
Published: July 2016

Multiple choice questions are a tool medical physicists encounter throughout their careers. They are a commonly used method of assessment during our early didactic training (graduate school, residency and board certification). They are used throughout our MOC process both in SAMs and online CE. And they are used for the MOC exam every 10 years. While we have significant training in answering these multiple choice questions, we rarely receive training in how to construct effective multiple choice questions. This is important too, as it is medical physicists who are creating the exams at academic institutions, for the AAPM SAMs and online CE as well as for the ABR exams (both initial and MOC). While there are rigorous scientific methods for evaluating the quality of questions in an exam that has been taken, creating good questions (stem) and multiple choice answers (distractors) requires skill and practice. This talk will cover some of the do's and don'ts for creating good multiple choice questions.

Item analysis of answers to multiple choice questions can reveal a great deal about the quality of the questions. Questions can be measured in terms of their difficulty and ability to discriminate between examinees. The distractors themselves can be evaluated for their ability to discriminate as well. And finally the overall test can be evaluated for reliability. We will discuss some of the specifics of item analysis as well as provide guidelines for constructing good tests items.

Learning Objectives:

Understand rules for writing a good stem

Understand rules for writing good distractors