bluuebunny/crossref_metadata_2025 huggingface dataset:
WE‐AB‐204‐02: Definition of D&I/AAPM Efforts (Stephen Avery/Will Ngwa)
Authors: Avery S.
Published: July 2016

Many efforts have been made to increase diversity in the science workforce. In order for us to be competitive in innovation and ingenuity we need to reach out to any source of intellectual talent. Having greater diversity can only increase the creativity in medical physics. In order for students to succeed academically they need role models and mentors with whom they can identify. Literature has shown that racial and ethnic diversity has both direct and indirect positive effects on the educational outcomes, career advancement and motivation of students. Diversity not only focuses on race, ethnicity and gender, but it can also include socioeconomic status, sexual orientation and more. Underrepresented populations have had low numbers over the years not only in medical physics but also in the sciences in general. With the rapidly changing face of our country we need to address how we attract and train the next generation of scientists to stay competitive. It is necessary to examine the role that diversity and inclusion play in the long term goals of institutions, workplaces and classrooms. To increase innovation we must engage people from all walks of life with different perspectives and life experiences to solve the problems that we will face. Diversity should be viewed as a strategy to achieve our goals instead of acts of good citizenship. Many of today's businesses and corporations have discovered that embracing diversity prepares future leaders in today's global market.

This lecture will provide insight to how differences within our society can drive innovation. We will provide an overview of the role diversity and inclusion plays in the clinic, education and research to develop the future workforce in medical physics.

Learning Objectives:

Understanding the role diversity and inclusion plays in medical physics.

The importance of developing education and research strategies for a global workforce.

How to develop a roadmap to diversity excellence within AAPM.
WE‐AB‐204‐07: D&I in Global Health
Authors: Alfonso‐Laguardia R.
Published: July 2016

Many efforts have been made to increase diversity in the science workforce. In order for us to be competitive in innovation and ingenuity we need to reach out to any source of intellectual talent. Having greater diversity can only increase the creativity in medical physics. In order for students to succeed academically they need role models and mentors with whom they can identify. Literature has shown that racial and ethnic diversity has both direct and indirect positive effects on the educational outcomes, career advancement and motivation of students. Diversity not only focuses on race, ethnicity and gender, but it can also include socioeconomic status, sexual orientation and more. Underrepresented populations have had low numbers over the years not only in medical physics but also in the sciences in general. With the rapidly changing face of our country we need to address how we attract and train the next generation of scientists to stay competitive. It is necessary to examine the role that diversity and inclusion play in the long term goals of institutions, workplaces and classrooms. To increase innovation we must engage people from all walks of life with different perspectives and life experiences to solve the problems that we will face. Diversity should be viewed as a strategy to achieve our goals instead of acts of good citizenship. Many of today's businesses and corporations have discovered that embracing diversity prepares future leaders in today's global market.

This lecture will provide insight to how differences within our society can drive innovation. We will provide an overview of the role diversity and inclusion plays in the clinic, education and research to develop the future workforce in medical physics.

Learning Objectives:

Understanding the role diversity and inclusion plays in medical physics.

The importance of developing education and research strategies for a global workforce.

How to develop a roadmap to diversity excellence within AAPM.
WE‐A‐BRC‐00: The Quality Gap
Authors: Palta Jatinder
Published: July 2016

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments.

Learning Objectives:

Understand the impact of clinical and technical quality on outcomes

Understand the importance of quality care in radiation oncology

Learn to assess the impact of quality on clinical outcomes

D. Followill, NIH Grant CA180803
WE‐A‐BRC‐03: Lessons Learned: IROC Audits
Authors: Followill D.
Published: July 2016

Quality and safety in healthcare are inextricably linked. There are compelling data that link poor quality radiation therapy to inferior patient survival. Radiation Oncology clinical trial protocol deviations often involve incorrect target volume delineation or dosing, akin to radiotherapy incidents which also often involve partial geometric miss or improper radiation dosing. When patients with radiation protocol variations are compared to those without significant protocol variations, clinical outcome is negatively impacted. Traditionally, quality assurance in radiation oncology has been driven largely by new technological advances, and safety improvement has been driven by reactive responses to past system failures and prescriptive mandates recommended by professional organizations and promulgated by regulators. Prescriptive approaches to quality and safety alone often do not address the huge variety of process and technique used in radiation oncology. Risk‐based assessments of radiotherapy processes provide a mechanism to enhance quality and safety, both for new and for established techniques. It is imperative that we explore such a paradigm shift at this time, when expectations from patients as well as providers are rising while available resources are falling. There is much we can learn from our past experiences to be applied towards the new risk‐based assessments.

Learning Objectives:

Understand the impact of clinical and technical quality on outcomes

Understand the importance of quality care in radiation oncology

Learn to assess the impact of quality on clinical outcomes

D. Followill, NIH Grant CA180803
WE‐AB‐BRB‐00: Session in Memory of Robert J. Shalek: High Resolution Dosimetry from 2D to 3D to Real‐Time 3D
Authors: Li Harold
Published: July 2016

Despite widespread IMRT treatments at modern radiation therapy clinics, precise dosimetric commissioning of an IMRT system remains a challenge. In the most recent report from the Radiological Physics Center (RPC), nearly 20% of institutions failed an end‐to‐end test with an anthropomorphic head and neck phantom, a test that has rather lenient dose difference and distance‐to‐agreement criteria of 7% and 4 mm. The RPC report provides strong evidence that IMRT implementation is prone to error and that improved quality assurance tools are required. At the heart of radiation therapy dosimetry is the multidimensional dosimeter. However, due to the limited availability of water‐equivalent dosimetry materials, research and development in this important field is challenging. In this session, we will review a few dosimeter developments that are either in the laboratory phase or in the pre‐commercialization phase. 1) Radiochromic plastic. Novel formulations exhibit light absorbing optical contrast with very little scatter, enabling faster, broad beam optical CT design. 2) Storage phosphor. After irradiation, the dosimetry panels will be read out using a dedicated 2D scanning apparatus in a non‐invasive, electro‐optic manner and immediately restored for further use. 3) Liquid scintillator. Scintillators convert the energy from x‐rays and proton beams into visible light, which can be recorded with a scientific camera (CCD or CMOS) from multiple angles. The 3D shape of the dose distribution can then be reconstructed. 4) Cherenkov emission imaging. Gated intensified imaging allows video‐rate passive detection of Cherenkov emission during radiation therapy with the room lights on.

Learning Objectives:

To understand the physics of a variety of dosimetry techniques based upon optical imaging

To investigate the strategies to overcome respective challenges and limitations

To explore novel ideas of dosimeter design

Supported in part by NIH Grants R01CA148853, R01CA182450, R01CA109558. Brian Pogue is founder and president of the company DoseOptics LLC, dedicated to developing and commercializing the first dedicated Cerenkov imaging camera and system for radiation dose imaging. Work reported in this talk does not involve the use of DoseOptics technology.; H. Li, this work was supported in part by NIH Grant No. R01CA148853; S. Beddar, NIH funding R01‐CA182450
WE‐AB‐BRB‐04: Cherenkov Imaging for Radiation Therapy Dose Verification On Patients
Authors: Pogue B.
Published: July 2016

Despite widespread IMRT treatments at modern radiation therapy clinics, precise dosimetric commissioning of an IMRT system remains a challenge. In the most recent report from the Radiological Physics Center (RPC), nearly 20% of institutions failed an end‐to‐end test with an anthropomorphic head and neck phantom, a test that has rather lenient dose difference and distance‐to‐agreement criteria of 7% and 4 mm. The RPC report provides strong evidence that IMRT implementation is prone to error and that improved quality assurance tools are required. At the heart of radiation therapy dosimetry is the multidimensional dosimeter. However, due to the limited availability of water‐equivalent dosimetry materials, research and development in this important field is challenging. In this session, we will review a few dosimeter developments that are either in the laboratory phase or in the pre‐commercialization phase. 1) Radiochromic plastic. Novel formulations exhibit light absorbing optical contrast with very little scatter, enabling faster, broad beam optical CT design. 2) Storage phosphor. After irradiation, the dosimetry panels will be read out using a dedicated 2D scanning apparatus in a non‐invasive, electro‐optic manner and immediately restored for further use. 3) Liquid scintillator. Scintillators convert the energy from x‐rays and proton beams into visible light, which can be recorded with a scientific camera (CCD or CMOS) from multiple angles. The 3D shape of the dose distribution can then be reconstructed. 4) Cherenkov emission imaging. Gated intensified imaging allows video‐rate passive detection of Cherenkov emission during radiation therapy with the room lights on.

Learning Objectives:

To understand the physics of a variety of dosimetry techniques based upon optical imaging

To investigate the strategies to overcome respective challenges and limitations

To explore novel ideas of dosimeter design

Supported in part by NIH Grants R01CA148853, R01CA182450, R01CA109558. Brian Pogue is founder and president of the company DoseOptics LLC, dedicated to developing and commercializing the first dedicated Cerenkov imaging camera and system for radiation dose imaging. Work reported in this talk does not involve the use of DoseOptics technology.; H. Li, this work was supported in part by NIH Grant No. R01CA148853; S. Beddar, NIH funding R01‐CA182450
WE‐AB‐BRA‐04: Investigation of MRI Derived Thermal Dose Models
Authors: MacLellan C , Fuentes D , Espinoza H , Prabhu S , Rao G , Weinberg J , Stafford R
Published: July 2016

Purpose:

To develop and investigate a novel thermal dose model methodology using MR temperature imaging (MRTI) and post‐treatment MRI changes as a surrogate of tissue damage in clinical laser ablation of the brain.

Methods:

Post‐treatment contrast enhanced T1‐weighted images were registered to MRTI acquired during two MR‐guided thermal ablation procedures. The non‐enhancing central region and hyperintense ring of vascular disruption characteristic of the thermal lesion were segmented manually and resampled into the 2D geometry of the MRTI. Regions immediately inside and outside the ring were classified as nonviable and viable tissue, respectively (N=1860). Logistic regression was performed on these classifications using thermal dose (Ω) calculated via four Arrhenius dose models from the literature (Henriques (H), Weaver & Stoll (WS), Diller & Klutke (DK), and Brown (B)). The optimal (O) Arrhenius dose model was found by iteratively changing the parameters of the Arrhenius model, Ea and A, until logistic model deviance was minimized.

Results:

Deviance of the Henriques model was closest to the optimized model (360 (H), 630 (WS), 438 (DK), 803(B), 330(O)). The thermal dose required to achieve a 90% probability of nonviability was 1.4 (H), 2.65 (WS), 1.8 (D), 4.5 (B), 1.1 (O) for each model. Agreement between the area of >90% nonviability between each model and the optimal model was 0.97 (H), 0.89(WS), 0.94(DK), and 0.88(B) using the Dice Similarity Coefficient.

Conclusion:

A methodology for deriving new thermal dose models from clinically used surrogates of tissue damage has been developed and tested. The logistic model suggests that the common dose threshold of Ω=1 may overestimate tissue damage. Good agreement is observed between the nonviable regions predicted by the optimized model and literature models. However, agreement between models is expected to decrease for longer ablation procedures designed to create larger thermal lesions and is an opportunity for further study.
WE‐AB‐BRA‐05: PET‐Guided Delivery Quality Evaluation of Yttrium‐90 Microsphere Radioembolizaton for Hepatocellular Carcinoma Patients: The Optimal Sequence of Radioembolizaton and Chemoembolization Treatments
Authors: Lin M , Saboury B
Published: July 2016

Purpose:

Selective‐internal‐radiation‐therapy (SIRT) and transarterial‐chemoembolization (TACE) are commonly used for treatment of liver tumors. The use of TACE, which is macroembolic, prior to SIRT may cause hemodynamic changes in tumor vasculature that impair yttrium‐90 (90Y) microsphere delivery to the targeted lesions. This work aims to quantify dosimetric tumor coverage using 90Y positron emission tomography (PET) dosimetry after SIRT alone compared to TACE followed by SIRT.

Methods:

A total of 40 consecutive hepatocellular carcinoma (HCC) SIRT patients who had a post‐SIRT 90Y PET/CT scan were evaluated. The patient‐specific‐3D‐dose was reconstructed from the PET images. Patients were categorized into two groups: patients received TACE prior SIRT procedure (n=18) and patient received SIRT alone (n=22). The lesions and liver were delineated by a senior radiologist. We evaluated both the lesion‐specific dose‐volume‐histogram (DVH) and the selectivity index (SI) defined as the ratio of the average dose inside the total lesion(s) and the average dose of the normal liver. The SI values of patients were compared based on whether TACE was previously used.

Results:

A wide spectrum was observed in the lesion‐specific DVH‐evaluation and SI appeared to be suitable of evaluating the quality of each SIRT infusion. The average SI of the entire patient group was 3.0, i.e. targeted lesion receiving three times higher dose than normal liver. The average SI was 1.8 for patients who had prior TACE and 3.9 for patients who did not have prior TACE (p=0.008). 85% of the patients with prior TACE demonstrated poor 90Y‐microsphere delivery (SI <2) while none demonstrated excellent delivery (SI >4). On the other hand, the incidence SI >4 among patients with no prior TACE was 37%.

Conclusion:

3D dose evaluation using post‐SIRT PET suggests that 90Y microsphere delivery to liver tumors is impaired among patients who received prior TACE compared to those who receive SIRT alone.
WE‐AB‐BRA‐11: Improved Imaging of Permanent Prostate Brachytherapy Seed Implants by Combining an Endorectal X‐Ray Sensor with a CT Scanner
Authors: Steiner J , Matthews K , Jia G
Published: July 2016

Purpose:

To test feasibility of the use of a digital endorectal x‐ray sensor for improved image resolution of permanent brachytherapy seed implants compared to conventional CT.

Methods:

Two phantoms simulating the male pelvic region were used to test the capabilities of a digital endorectal x‐ray sensor for imaging permanent brachytherapy seed implants. Phantom 1 was constructed from acrylic plastic with cavities milled in the locations of the prostate and the rectum. The prostate cavity was filled a Styrofoam plug implanted with 10 training seeds. Phantom 2 was constructed from tissue‐equivalent gelatins and contained a prostate phantom implanted with 18 strands of training seeds. For both phantoms, an intraoral digital dental x‐ray sensor was placed in the rectum within 2 cm of the seed implants. Scout scans were taken of the phantoms over a limited arc angle using a CT scanner (80 kV, 120–200 mA). The dental sensor was removed from the phantoms and normal helical CT and scout (0 degree) scans using typical parameters for pelvic CT (120 kV, auto‐mA) were collected. A shift‐and add tomosynthesis algorithm was developed to localize seed plane location normal to detector face.

Results:

The endorectal sensor produced images with improved resolution compared to CT scans. Seed clusters and individual seed geometry were more discernable using the endorectal sensor. Seed 3D locations, including seeds that were not located in every projection image, were discernable using the shift and add algorithm.

Conclusion:

This work shows that digital endorectal x‐ray sensors are a feasible method for improving imaging of permanent brachytherapy seed implants. Future work will consist of optimizing the tomosynthesis technique to produce higher resolution, lower dose images of 1) permanent brachytherapy seed implants for post‐implant dosimetry and 2) fine anatomic details for imaging and managing prostatic disease compared to CT images.

Funding: LSU Faculty Start‐up Funding. Disclosure: XDR Radiography has loaned our research group the digital x‐ray detector used in this work. CoI: None.
WE‐AB‐207A‐02: John's Equation Based Consistency Condition and Incomplete Projection Restoration Upon Circular Orbit CBCT
Authors: Ma J , Qi H , Wu S , Yan H , Xu Y , Zhou L
Published: July 2016

Purpose:

In transmitted X‐ray tomography imaging, projections are sometimes incomplete due to a variety of reasons, such as geometry inaccuracy, defective detector cells, etc. To address this issue, we have derived a direct consistency condition based on John's Equation, and proposed a method to effectively restore incomplete projections based on this consistency condition.

Methods:

Through parameter substitutions, we have derived a direct consistency condition equation from John's equation, in which the left side is only projection derivative of view and the right side is projection derivative of other geometrical parameters. Based on this consistency condition, a projection restoration method is proposed, which includes five steps: 1) Forward projecting reconstructed image and using linear interpolation to estimate the incomplete projections as the initial result; 2) Performing Fourier transform on the projections; 3) Restoring the incomplete frequency data using the consistency condition equation; 4) Performing inverse Fourier transform; 5) Repeat step 2)∼4) until our criteria is met to terminate the iteration.

Results:

A beam‐blocking‐based scatter correction case and a bad‐pixel correction case were used to demonstrate the efficacy and robustness of our restoration method. The mean absolute error (MAE), signal noise ratio (SNR) and mean square error (MSE) were employed as our evaluation metrics of the reconstructed images. For the scatter correction case, the MAE is reduced from 63.3% to 71.7% with 4 iterations. Compared with the existing Patch's method, the MAE of our method is further reduced by 8.72%. For the bad‐pixel case, the SNR of the reconstructed image by our method is increased from 13.49% to 21.48%, with the MSE being decreased by 45.95%, compared with linear interpolation method.

Conclusion:

Our studies have demonstrated that our restoration method based on the new consistency condition could effectively restore the incomplete projections, especially for their high frequency component.
WE‐AB‐206‐01: Diagnostic Ultrasound Imaging Quality Assurance
Authors: Zagzebski J.
Published: July 2016

The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. The goal of this ultrasound hands‐on workshop is to demonstrate quality control (QC) testing in diagnostic ultrasound and to provide updates in ACR ultrasound accreditation requirements. The first half of this workshop will include two presentations reviewing diagnostic ultrasound QA/QC and ACR ultrasound accreditation requirements. The second half of the workshop will include live demonstrations of basic QC tests. An array of ultrasound testing phantoms and ultrasound scanners will be available for attendees to learn diagnostic ultrasound QC in a hands‐on environment with live demonstrations and on‐site instructors. The targeted attendees are medical physicists in diagnostic imaging.

Learning Objectives:

Gain familiarity with common elements of a QA/QC program for diagnostic ultrasound imaging

dentify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools

Learn ACR ultrasound accreditation requirements

Jennifer Walter is an employee of American College of Radiology on Ultrasound Accreditation.
WE‐AB‐209‐01: A Monte Carlo‐Based Method to Include Random Errors in Robust Optimization
Authors: Barragan Montero A , Souris K , Lee J , Sterpin E
Published: July 2016

Purpose:

To develop an efficient method to implement random set‐up errors and organ motion in robust optimization for proton therapy treatment planning.

Methods:

The plans were created with an in‐house robust optimizer, coupled with a super‐fast Monte Carlo (MC) engine (less than 1 minute for final dose). MC simulates random errors by shifting randomly the starting point of each particle, according to their probability distribution. Such strategy assumes a sufficient number of treatment fractions. Two strategies are presented: 1) Full robust optimization with beamlets that already include the effect of random errors and 2) Mixed robust optimization, where the nominal beamlets are involved but a correction term C modifies the prescription. Starting from C=0, the method alternates optimization of the spot weights with the nominal beamlets and updates of C, with C=Drandom‐Dnominal and where Drandom results from a regular MC computation (without pre‐computed beamlets) that simulates random errors. Updates of C can be triggered as often as necessary by running the MC engine with the last corrected values for the spot weights as input. The method was applied to lung and prostate cases. For both patients the range error was set to 3%, systematic setup error to 5mm and standard deviation for random errors to 5 mm. Comparison between full robust optimization and the mixed strategy (with 3 updates of C) is presented.

Results:

Target coverage was far below the clinical constraints (D95 > 95% of the prescribed dose) for plans where random errors were not simulated, especially for lung case. However, by using the proposed strategies the plans achieved a target coverage above clinical constraints.

Conclusion:

Full robust optimization gives better results than the mixed strategy, but the latter can be useful in cases where a MC engine is not available or too computationally intensive for beamlets calculation.
WE‐AB‐209‐02: A New Inverse Planning Framework with Principle‐Based Modeling of Inter‐Structural Dosimetric Tradeoffs
Authors: Liu H , Dong P , Xing L
Published: July 2016

Purpose:

Traditional radiotherapy inverse planning relies on the weighting factors to phenomenologically balance the conflicting criteria for different structures. The resulting manual trial‐and‐error determination of the weights has long been recognized as the most time‐consuming part of treatment planning. The purpose of this work is to develop an inverse planning framework that parameterizes the inter‐structural dosimetric tradeoff among with physically more meaningful quantities to simplify the search for a clinically sensible plan.

Methods:

A permissible dosimetric uncertainty is introduced for each of the structures to balance their conflicting dosimetric requirements. The inverse planning is then formulated as a convex feasibility problem, which aims to generate plans with acceptable dosimetric uncertainties. A sequential procedure (SP) is derived to decompose the model into three submodels to constrain the uncertainty in the planning target volume (PTV), the critical structures, and all other structures to spare, sequentially. The proposed technique is applied to plan a liver case and a head‐and‐neck case and compared with a conventional approach.

Results:

Our results show that the strategy is able to generate clinically sensible plans with little trial‐and‐error. In the case of liver IMRT, the fractional volumes to liver and heart above 20Gy are found to be 22% and 10%, respectively, which are 15.1% and 33.3% lower than that of the counterpart conventional plan while maintaining the same PTV coverage. The planning of the head and neck IMRT show the same level of success, with the DVHs for all organs at risk and PTV very competitive to a counterpart plan.

Conclusion:

A new inverse planning framework has been established. With physically more meaningful modeling of the inter‐structural tradeoff, the technique enables us to substantially reduce the need for trial‐and‐error adjustment of the model parameters and opens new opportunities of incorporating prior knowledge to facilitate the treatment planning process.
WE‐AB‐209‐04: Biological Evaluation of Universal Multi‐Criteria Optimization VMAT Prostate Plans
Authors: Guerrero M , Chen S
Published: July 2016

Purpose:

In recent years Multi‐Criteria Optimization (MCO) has become commercially available as a potential optimization method for intensity modulated and volumetric arc therapies (IMRT and VMAT). The purpose of our work is to develop a universal set of objectives and constraints to generate prostate cancer MCO plans with VMAT and evaluate them using biological metrics.

Methods:

We randomly selected ten prostate plans (two‐arc VMAT) for patients with intermediate risk prostate cancer prescribed 75.6–79.2Gy to the prostate and seminal vesicles. We compared the plan scores to our clinical plans generated with standard IMRT optimization techniques. The planning target volumes (PTV) were 5–10 mm set‐up margin expansion of the gross target volume. Using the same two arcs we generated MCO plans with a standard set of constraints and objectives using Raystation v4.5. The dose‐volume histograms (DVH) for the (PTV), rectum and bladder were exported and used to calculate tumor control probability (TCP) and the complication‐free tumor control probability P+ using biological models from the literature. We classified the plans by their level of difficulty based on the rectum‐PTV overlap and develop MCO plans with similar levels of conformality as the clinical plans.

Results:

The P+ values of the MCO plans had an average of 86.4%±2.3% and were equivalent to the clinical plans (P+ average of 85.0%±2.1%, p‐value=0.33). The MCO NTCP values for the rectum ranged from 0.7% to 20% and were highly correlated with rectum‐PTV overlap. NTCP values for the bladder were less than 1% for all MCO plans.

Conclusion:

MCO VMAT prostate plans obtained with standardized objectives and constraints generate biologically equivalent plans to the clinical plans generated with standard optimization techniques.
WE‐AB‐209‐06: Dynamic Collimator Trajectory Algorithm for Use in VMAT Treatment Deliveries
Authors: MacDonald L , Thomas C , Syme A
Published: July 2016

Purpose:

To develop advanced dynamic collimator positioning algorithms for optimal beam's‐eye‐view (BEV) fitting of targets in VMAT procedures, including multiple metastases stereotactic radiosurgery procedures.

Methods:

A trajectory algorithm was developed, which can dynamically modify the angle of the collimator as a function of VMAT control point to provide optimized collimation of target volume(s). Central to this algorithm is a concept denoted “whitespace”, defined as area within the jaw‐defined BEV field, outside of the PTV, and not shielded by the MLC when fit to the PTV. Calculating whitespace at all collimator angles and every control point, a two‐dimensional topographical map depicting the tightness‐of‐fit of the MLC was generated. A variety of novel searching algorithms identified a number of candidate trajectories of continuous collimator motion. Ranking these candidate trajectories according to their accrued whitespace value produced an optimal solution for navigation of this map.

Results:

All trajectories were normalized to minimum possible (i.e. calculated without consideration of collimator motion constraints) accrued whitespace. On an acoustic neuroma case, a random walk algorithm generated a trajectory with 151% whitespace; random walk including a mandatory anchor point improved this to 148%; gradient search produced a trajectory with 137%; and bi‐directional gradient search generated a trajectory with 130% whitespace. For comparison, a fixed collimator angle of 30° and 330° accumulated 272% and 228% of whitespace, respectively. The algorithm was tested on a clinical case with two metastases (single isocentre) and identified collimator angles that allow for simultaneous irradiation of the PTVs while minimizing normal tissue irradiation.

Conclusion:

Dynamic collimator trajectories have the potential to improve VMAT deliveries through increased efficiency and reduced normal tissue dose, especially in treatment of multiple cranial metastases, without significant safety concerns that hinder immediate clinical implementation.
WE‐AB‐209‐09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy
Authors: Dong P , Ungun B , Boyd S , Xing L
Published: July 2016

Purpose:

To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency.

Methods:

The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state‐of‐the‐art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. To avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain).

Results:

Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case.

Conclusion:

The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.
WE‐AB‐209‐12: Quasi Constrained Multi‐Criteria Optimization for Automated Radiation Therapy Treatment Planning
Authors: Watkins W.T. , Siebers J.V.
Published: July 2016

Purpose:

To introduce quasi‐constrained Multi‐Criteria Optimization (qcMCO) for unsupervised radiation therapy optimization which generates alternative patient‐specific plans emphasizing dosimetric tradeoffs and conformance to clinical constraints for multiple delivery techniques.

Methods:

For N Organs At Risk (OARs) and M delivery techniques, qcMCO generates M(N+1) alternative treatment plans per patient. Objective weight variations for OARs and targets are used to generate alternative qcMCO plans. For 30 locally advanced lung cancer patients, qcMCO plans were generated for dosimetric tradeoffs to four OARs: each lung, heart, and esophagus (N=4) and 4 delivery techniques (simple 4‐field arrangements, 9‐field coplanar IMRT, 27‐field non‐coplanar IMRT, and non‐coplanar Arc IMRT). Quasi‐constrained objectives included target prescription isodose to 95% (PTV‐D95), maximum PTV dose (PTV‐Dmax)< 110% of prescription, and spinal cord Dmax<45 Gy. The algorithm's ability to meet these constraints while simultaneously revealing dosimetric tradeoffs was investigated. Statistically significant dosimetric tradeoffs were defined such that the coefficient of determination between dosimetric indices which varied by at least 5 Gy between different plans was >0.8.

Results:

The qcMCO plans varied mean dose by >5 Gy to ipsilateral lung for 24/30 patients, contralateral lung for 29/30 patients, esophagus for 29/30 patients, and heart for 19/30 patients. In the 600 plans computed without human interaction, average PTV‐D95=67.4±3.3 Gy, PTV‐Dmax=79.2±5.3 Gy, and spinal cord Dmax was >45 Gy in 93 plans (>50 Gy in 2/600 plans). Statistically significant dosimetric tradeoffs were evident in 19/30 plans, including multiple tradeoffs of at least 5 Gy between multiple OARs in 7/30 cases. The most common statistically significant tradeoff was increasing PTV‐Dmax to reduce OAR dose (15/30 patients).

Conclusion:

The qcMCO method can conform to quasi‐constrained objectives while revealing significant variations in OAR doses including mean dose reductions >5 Gy. Clinical implementation will facilitate patient‐specific decision making based on achievable dosimetry as opposed to accept/reject models based on population derived objectives.
WE‐B‐201‐01: Introduction: Not Everything You Read Is True
Authors: Schlesinger D.
Published: July 2016

Evidence is growing to suggest that many published clinical results cannot be replicated. At the same time, the number of published clinical papers is steadily increasing and most if not all base their conclusions on evidence provided by formal statistical tests. Medical physicists have a critical need to understand and be able to interpret the methods and results of these studies in order to judge their scientific quality and relevance. However many medical physicists have minimal or no training in the sort of practical statistical methods commonly found in the literature. They may therefore have an inadequate ability to detect statistical errors and limitations that are an unfortunately too frequent occurrence in clinical papers.

In this session we will use published examples to demonstrate common statistical errors frequently encountered in peer‐reviewed literature, distinctive symptoms that can help detect these errors, and explanations for how they might have been corrected. In the process, we will explain some of the basic concepts of inferential statistics. Some specific case studies we will cover will include misunderstanding the meaning of p‐values and clinical significance, misinterpreting statistical power, not accounting for multiple‐hypothesis testing, ignoring missing data, and faulty survival analysis.

Learning Objectives:

Learn about the presence of statistical problems in published studies

Identify common signs and symptoms of potential problems in various types of statistical tests

Learn methods for correctly implementing statistical analyses of the type commonly found in clinical publications
WE‐B‐BRC‐00: Concepts in Risk‐Based Assessment
Authors: Fraass Benedick
Published: July 2016

Prospective quality management techniques, long used by engineering and industry, have become a growing aspect of efforts to improve quality management and safety in healthcare. These techniques are of particular interest to medical physics as scope and complexity of clinical practice continue to grow, thus making the prescriptive methods we have used harder to apply and potentially less effective for our interconnected and highly complex healthcare enterprise, especially in imaging and radiation oncology.

An essential part of most prospective methods is the need to assess the various risks associated with problems, failures, errors, and design flaws in our systems. We therefore begin with an overview of risk assessment methodologies used in healthcare and industry and discuss their strengths and weaknesses. The rationale for use of process mapping, failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by TG‐100 will be described, as well as suggestions for the way forward. This is followed by discussion of radiation oncology specific risk assessment strategies and issues, including the TG‐100 effort to evaluate IMRT and other ways to think about risk in the context of radiotherapy. Incident learning systems, local as well as the ASTRO/AAPM ROILS system, can also be useful in the risk assessment process. Finally, risk in the context of medical imaging will be discussed. Radiation (and other) safety considerations, as well as lack of quality and certainty all contribute to the potential risks associated with suboptimal imaging.

The goal of this session is to summarize a wide variety of risk analysis methods and issues to give the medical physicist access to tools which can better define risks (and their importance) which we work to mitigate with both prescriptive and prospective risk‐based quality management methods.

Learning Objectives:

Description of risk assessment methodologies used in healthcare and industry

Discussion of radiation oncology‐specific risk assessment strategies and issues

Evaluation of risk in the context of medical imaging and image quality

E. Samei: Research grants from Siemens and GE
WE‐B‐BRC‐02: Risk Analysis and Incident Learning
Authors: Fraass B.
Published: July 2016

Prospective quality management techniques, long used by engineering and industry, have become a growing aspect of efforts to improve quality management and safety in healthcare. These techniques are of particular interest to medical physics as scope and complexity of clinical practice continue to grow, thus making the prescriptive methods we have used harder to apply and potentially less effective for our interconnected and highly complex healthcare enterprise, especially in imaging and radiation oncology.

An essential part of most prospective methods is the need to assess the various risks associated with problems, failures, errors, and design flaws in our systems. We therefore begin with an overview of risk assessment methodologies used in healthcare and industry and discuss their strengths and weaknesses. The rationale for use of process mapping, failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by TG‐100 will be described, as well as suggestions for the way forward. This is followed by discussion of radiation oncology specific risk assessment strategies and issues, including the TG‐100 effort to evaluate IMRT and other ways to think about risk in the context of radiotherapy. Incident learning systems, local as well as the ASTRO/AAPM ROILS system, can also be useful in the risk assessment process. Finally, risk in the context of medical imaging will be discussed. Radiation (and other) safety considerations, as well as lack of quality and certainty all contribute to the potential risks associated with suboptimal imaging.

The goal of this session is to summarize a wide variety of risk analysis methods and issues to give the medical physicist access to tools which can better define risks (and their importance) which we work to mitigate with both prescriptive and prospective risk‐based quality management methods.

Learning Objectives:

Description of risk assessment methodologies used in healthcare and industry

Discussion of radiation oncology‐specific risk assessment strategies and issues

Evaluation of risk in the context of medical imaging and image quality

E. Samei: Research grants from Siemens and GE
WE‐DE‐201‐06: Impact of Temporal Image Coregistration Methods On 3D Internal Dose Calculations in Targeted Radionuclide Therapy
Authors: Besemer A , Marsh I , Bednarz B
Published: July 2016

Purpose:

The calculation of 3D internal dose calculations in targeted radionuclide therapy requires the acquisition and temporal coregistration of a serial PET/CT or SPECT/CT images. This work investigates the dosimetric impact of different temporal coregistration methods commonly used for 3D internal dosimetry.

Methods:

PET/CT images of four mice were acquired at 1, 24, 48, 72, 96, 144 hrs post‐injection of 124I‐CLR1404. The therapeutic 131I‐CLR1404 absorbed dose rate (ADR) was calculated at each time point using a Geant4‐based MC dosimetry platform using three temporal image coregistration

Methods:

(1) no coregistration (NC), whole body sequential CT‐CT affine coregistration (WBAC), and individual sequential ROI‐ROI affine coregistration (IRAC). For NC, only the ROI mean ADR was integrated to obtain ROI mean doses. For WBAC, the CT at each time point was coregistered to a single reference CT. The CT transformations were applied to the corresponding ADR images and the dose was calculated on a voxel‐basis within the whole CT volume. For IRAC, each individual ROI was isolated and sequentially coregistered to a single reference ROI. The ROI transformations were applied to the corresponding ADR images and the dose was calculated on a voxel‐basis within the ROI volumes.

Results:

The percent differences in the ROI mean doses were as large as 109%, 88%, and 32%, comparing the WBAC vs. IRAC, NC vs. IRAC, and NC vs. WBAC methods, respectively. The CoV in the mean dose between the all three methods ranged from 2–36%. The pronounced curvature of the spinal cord was not adequately coregistered using WBAC which resulted in large difference between the WBAC and IRAC.

Conclusion:

The method used for temporal image coregistration can result in large differences in 3D internal dosimetry calculations. Care must be taken to choose the most appropriate method depending on the imaging conditions, clinical site, and specific application.

This work is partially funded by NIH Grant R21 CA198392‐01.
WE‐DE‐201‐09: Performance of HDR Ring Surface Applicator Printed by 3D Printer
Authors: Xu Z , Baker J , Hsia A , Ryu S
Published: July 2016

Purpose:

The commercially available Leipzig‐style Cone for High Dose Rate (HDR) Brachytherapy has a steep depth dose curve and a non‐uniform dose distribution. This work shows the performance of a Ring Surface Applicator created using a 3D printer that can generate a better dose distribution. Calculated doses were verified with film measurement.

Methods:

The water equivalent red‐ABS plastic was used to print the Ring Surface Applicator which hosts three catheters: a center piece with a straight catheter and two concentric rings with diameters of 3.5 and 5.5 cm. Gafchromic EBT2 film, Epson Expression 10000 flatbed scanner, and the online software at radiochromic.com were used to analyze the measured data. 10cm×10cm piece of film was sandwiched between two 15×10×5cm3 polystyrene phantoms. The applicator was positioned directly on top of the phantom. Measurement was done using dwell time and positions calculated by Eclipse BrachyVision treatment planning system (RTP).

Results:

Depth dose curve was generated from the plan and measurement. The results show that the measured and calculated depth dose were in agreement (<3%) from surface to 4mm depth. A discrepancy of 6% was observed at 5 mm depth, where the dose is typically prescribed to. For depths deeper than 5 mm, the measured doses were lower than those calculated by Eclipse BrachyVision. This can be attributed to a combination of simple calculation algorithm using TG‐43 and the lack of inhomogeneity correction. Dose profiles at 5 mm depth were also generated from TPS calculation and measured with film. The measured and calculated profiles are similar. Consistent with the depth dose curve, the measured dose is lower than the calculated.

Conclusion:

Our results showed that the Ring Surface Applicator, printed using 3D printer, can generate more uniform dose distribution within the target volume and can be safely used in the clinic.
WE‐DE‐BRC‐01: TG‐100 Overview
Authors: Huq M.
Published: July 2016

This SAMs Therapy Educational Course will introduce participants to the tools recommended by TG 100 for use in the development of a risk‐based Quality Management Program. The Course will start with an Overview of the background and rationale behind the TG 100 initiative, from which its charge was developed. After setting the scene, four 15 minute presentations will introduce the principal components of the soon to be published Report of TG 100. These are Process Mapping, Failure Modes and Effects Analysis, Fault Tree Analysis and the development of a QA/QM risk‐based Program. There will be time for two short exercises based on Failure Modes and Effects Analysis and a Discussion before the SAMs questions which will conclude the session.

Learning Objectives:

To appreciate the underlying philosophy of the TG 100 initiative.

To gain a brief overview of the principal risk‐based tools recommended by TG 100.

In an informal workshop format, to explore, at an introductory level, the use of risk analysis as proposed by TG 100 as a prelude to the development of a Quality Management Program.
WE‐DE‐BRC‐02: Process Maps
Authors: Palta J.
Published: July 2016

This SAMs Therapy Educational Course will introduce participants to the tools recommended by TG 100 for use in the development of a risk‐based Quality Management Program. The Course will start with an Overview of the background and rationale behind the TG 100 initiative, from which its charge was developed. After setting the scene, four 15 minute presentations will introduce the principal components of the soon to be published Report of TG 100. These are Process Mapping, Failure Modes and Effects Analysis, Fault Tree Analysis and the development of a QA/QM risk‐based Program. There will be time for two short exercises based on Failure Modes and Effects Analysis and a Discussion before the SAMs questions which will conclude the session.

Learning Objectives:

To appreciate the underlying philosophy of the TG 100 initiative.

To gain a brief overview of the principal risk‐based tools recommended by TG 100.

In an informal workshop format, to explore, at an introductory level, the use of risk analysis as proposed by TG 100 as a prelude to the development of a Quality Management Program.