bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐B‐BRA‐08: Panel Member
Authors: Hazle J.
Published: July 2016

In the current rapidly changing Healthcare environment, many groups are competing for limited resources. How can medical physicists position themselves to be a relevant stakeholder in the discussion of how those resources are allocated Our value goes beyond what can be shown in a business plan and is heavily involved with safety and quality.

Three areas will be explored:

What is our value?

Who needs to receive that message?

How do we communicate that message?

To help frame the discussion in terms of how other stakeholders may view the value of medical physicists, a physician and an administrator will present their perspective.

Lastly, a multidisciplinary panel will present real life examples of strategies that can be utilized today to establish the value of medical physicists. The presentation of these examples will lead into an interactive question and answer time.

V. Willcut, I work for Elekta. There was no research associated with this talk.
SU‐C‐204‐05: Magnetic Resonance‐Induced Adaptive Response to Orthovoltage Radiation Therapy in FSa and SA‐NH Mouse Tumor Cell Lines
Authors: Mendel K , Miller R , Murley J , Sadinski M , Grdina D
Published: July 2016

Purpose:

To assess the effect of pre‐treatment Magnetic Resonance Imaging (MRI) on cell survival following orthovoltage radiation therapy.

Methods:

This in vitro study examined the survival of FSa cells (extracted from methylcholanthrene‐induced fibrosarcoma in the flank of a C3H female mouse) and SA‐NH cells (derived from a spontaneously arising murine sarcoma tumor) having undergone an MRI scan prior to radiation exposure. Cell cultures were kept at 37 C, in a humidified environment with 5% CO2, and were grown to confluence prior to the start of the experiment. Each cell culture underwent two, 25 minute MRIs spaced 24 hours apart using a standard brain imaging protocol. The cultures were exposed to a 2 Gy dose of radiation beginning 15 minutes after the end of each MRI scan. Irradiations were performed by a Philips RT250 X‐ray generator at 250 kVp and 15 mA. All MR imaging was performed on a 1.5 T Philips Achieva scanner using a head and neck vasculature coil.

Results:

Cells given an MRI scan prior to radiation exhibited an increase in mean surviving fraction of 10.8% and 9.6% in FSa and SA‐NH cells, respectively. The difference was found to be statistically significant in both cell types by a student two‐tailed t test with P = 0.011 and P < 0.001 for FSa and SA‐NH, respectively.

Conclusion:

MRI may cause an increase in radio‐resistance in FSa and SA‐NH cells. If this biological effect is found to be consistent across other cell types and voltage ranges, these results could help inform treatment planning by improving our understanding of the joint effects of MRI and ionizing radiation.

This work was supported in part under NIH grant numbers T32 EB002103, NCI R01‐CA 132998, DOE Low Dose Program/Project Grant DE‐413 SC0001271. DJ Grdina is a paid consultant to Pinnacle Biologics. DJ Grdina and JS Murley are minority equity partners in Pinnacle Oncology LLC.
SU‐C‐204‐07: Radiation Therapy as a Potential Treatment for Obesity: Initial Data from a Preclinical Investigation
Authors: Pasciak A , Bradley Y , Nodit L , Bourgeois A , Paxton B , Arepally A
Published: July 2016

Purpose:

To evaluate the feasibility of Yttrium‐90 (90Y) radionuclide therapy as a potential treatment for obesity in a porcine model. As the only appetite‐stimulating hormone, localized targeting of ghrelin‐producing X/A cells in the fundus of the stomach using 90Y may reduce serum ghrelin levels and decrease hunger.

Methods:

Under approval of the University of Tennessee IACUC, 8 young female pigs aged 12–13 weeks and weighing 21.8–28.1 Kg were included in this study. Six animals underwent transfemoral angiography as part of a two‐day procedure involving: (1) infusion of 99mTc‐MAA, followed by nuclear scintigraphy and contrast‐enhanced CT for treatment‐planning and (2) administration of resin 90Y microspheres into the stomach fundus. Calibrated 90Y activities were infused into the main left gastric and the gastric artery arising from the splenic to yield predetermined fundal absorbed doses. Control animals underwent a sham procedure with saline and contrast. Weekly animal weight and serum ghrelin were measured along with post‐euthanasia histologic analyses of mucosal integrity and ghrelin immunoreactive cell‐density.

Results:

90Y radioembolization was administered to six pigs in dosages from 46.3 to 105.1 MBq resulting in average fundal absorbed doses between 35.5 and 91.9 Gy. No animal showed any signs of pain or GI complication through the duration of the study. Ghrelin immunoreactive cell‐density was significantly lower in treated vs. control animals in both the stomach fundus (13.5 vs 34.8, P < 0.05) and body (11.2 vs 19.8, P < 0.05). A trend towards decreased weight gain in treated animals as well as a decrease in explanted stomach volume was also noted.

Conclusion:

The safety and technical feasibility of radiation therapy using 90Y radioembolization as a potential treatment for obesity has been demonstrated at fundal absorbed doses over 90 Gy. Preliminary data is suggestive of short‐term safety and potential efficacy, however, further animal studies are required.

Project was funded by SIRTex medical ltd
SU‐C‐201‐03: Ionization Chamber Collection Efficiency in Pulsed Radiation Fields of High Pulse Dose
Authors: Gotz M , Karsch L , Pawelke J
Published: July 2016

Purpose:

To investigate the reduction of collection efficiency of ionization chambers (IC) by volume recombination and its correction in pulsed fields of very high pulse dose.

Methods:

Measurements of the collection efficiency of a plane‐parallel advanced Markus IC (PTW 34045, 1mm electrode spacing, 300V nominal voltage) were obtained for collection voltages of 100V and 300V by irradiation with a pulsed electron beam (20MeV) of varied pulse dose up to approximately 600mGy (0.8nC liberated charge). A reference measurement was performed with a Faraday cup behind the chamber. It was calibrated for the liberated charge in the IC by a linear fit of IC measurement to reference measurement at low pulse doses. The results were compared to the commonly used two voltage approximation (TVA) and to established theories for volume recombination, with and without considering a fraction of free electrons. In addition, an equation system describing the charge transport and reactions in the chamber was solved numerically.

Results:

At 100V collection voltage and moderate pulse doses the established theories accurately predict the observed collection efficiency, but at extreme pulse doses a fraction of free electrons needs to be considered. At 300V the observed collection efficiency deviates distinctly from that predicted by any of the established theories, even at low pulse doses. However, the numeric solution of the equation system is able to reproduce the measured collection efficiency across the entire dose range of both voltages with a single set of parameters.

Conclusion:

At high electric fields (3000V/cm here) the existing theoretical descriptions of collection efficiency, including the TVA, are inadequate to predict pulse dose dependency. Even at low pulse doses they might underestimate collection efficiency. The presented, more accurate numeric solution, which considers additional effects like electric shielding by the charges, might provide a valuable tool for future investigations.

This project was funded by the German ministry of research and education (BMBF) under grant number: 03Z1N511 and by the state of Saxony under grant number: B 209
SU‐C‐201‐07: Towards Clinical Cherenkov Emission Dosimetry: Stopping Power‐To‐Cherenkov Power Ratios and Beam Quality Specification of Clinical Electron Beams
Authors: Zlateva Y , Seuntjens J , El Naqa I
Published: July 2016

Purpose:

We propose a Cherenkov emission (CE)‐based reference dosimetry method, which in contrast to ionization chamber‐based dosimetry, employs spectrum‐averaged electron restricted mass collision stopping power‐to‐Cherenkov power ratios (SCRs), and we examine Monte Carlo‐calculated SCRs and beam quality specification of clinical electron beams.

Methods:

The EGSnrc user code SPRRZnrc was modified to compute SCRs instead of stopping‐power ratios (single medium: water; cut‐off: CE threshold (observing Spencer‐Attix conditions); CE power: Frank‐Tamm). SCRs are calculated with BEAMnrc for realistic electron beams with nominal energies of 6–22 MeV from three Varian accelerators (TrueBeam Clinac 21EX, Clinac 2100C/D) and for mono‐energetic beams of energies equal to the mean electron energy at the water surface. Sources of deviation between clinical and mono‐energetic SCRs are analyzed quantitatively. A universal fit for the beam‐quality index R50 in terms of the depth of 50% CE C50 is carried out.

Results:

SCRs at reference depth are overestimated by mono‐energetic values by up to 0.2% for a 6‐MeV beam and underestimated by up to 2.3% for a 22‐MeV beam. The variation is mainly due to the clinical beam spectrum and photon contamination. Beam angular spread has a small effect across all depths and energies. The influence of the electron spectrum becomes increasingly significant at large depths, while at shallow depths and high beam energies photon contamination is predominant (up to 2.0%). The universal data fit reveals a strong linear correlation between R50 and C50 (ρ > 0.99999).

Conclusion:

CE is inherent to radiotherapy beams and can be detected outside the beam with available optical technologies, which makes it an ideal candidate for out‐of‐beam high‐resolution 3D dosimetry. Successful clinical implementation of CE dosimetry hinges on the development of robust protocols for converting measured CE to radiation dose. Our findings constitute a key step towards clinical CE dosimetry.
SU‐C‐BRC‐02: Accelerating Linear Boltzmann Transport Equation by An Asymptotic‐Preserving Scheme
Authors: Chen G , Chen H , Hong X , Tang M , Gao H
Published: July 2016

Purpose:

Linear Boltzmann transport equation (LBTE) is as accurate as the Monte Carlo method for dose calculation. This work is to develop an asymptotic‐preserving (AP) scheme to accelerate the LBTE, i.e., to achieve the same accuracy with significantly reduced number of spatial grids.

Methods:

In this proof‐of‐concept study, two‐dimensional LBTE is solved by the discrete ordinate method. The Level‐Symmetric (LQn) quadrature set is employed for angular discretization of LBTE. The Henyey‐Greenstein scattering function is used for simulating the anisotropic scattering. For the AP scheme, the anisotropic scattering kernel is discretized as a scattering matrix and its difference with the analytical form is minimized with some constraints that are introduced to preserve the diffusive limit. Since LBTE is linear, the solution on each grid is approximated by linear combination of characteristic solutions and a special solution. A four‐point cell‐centered scheme is used to establish the linear system of the final solution with unknowns and a finite difference scheme connects the unknowns at four edge centers of the cell to solve this system.

Results:

First, compared with the exact analytical solution, the discrete L2 norm of the numerical error of the proposed method is less than 0.03 percents when the order of quadrature set is larger than 6 (i.e., more than 48 angles), even when the spatial grid is reduced to 8 by 8. Second, when using fewer spatial grids, the proposed method is more accurate than the conventional Source Iteration method.

Conclusion:

The AP scheme is developed for accelerating LBTE, and the accurate results can be achieved with significantly reduced number of spatial grids.

The authors were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).
SU‐C‐BRC‐03: Development of a Novel Strategy for On‐Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy
Authors: Yang Y M , Bush K , Han B , Xing L
Published: July 2016

Purpose:

Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed.

Methods:

Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms.

Results:

We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region.

Conclusion:

Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.
SU‐C‐BRC‐05: Monte Carlo Calculations to Establish a Simple Relation of Backscatter Dose Enhancement Around High‐Z Dental Alloy to Its Atomic Number
Authors: Utsunomiya S , Kushima N , Katsura K , Tanabe S , Hayakawa T , Sakai H , Yamada T , Takahashi H , Abe E , Wada S , Aoyama H
Published: July 2016

Purpose:

To establish a simple relation of backscatter dose enhancement around a high‐Z dental alloy in head and neck radiation therapy to its average atomic number based on Monte Carlo calculations.

Methods:

The PHITS Monte Carlo code was used to calculate dose enhancement, which is quantified by the backscatter dose factor (BSDF). The accuracy of the beam modeling with PHITS was verified by comparing with basic measured data namely PDDs and dose profiles. In the simulation, a high‐Z alloy of 1 cm cube was embedded into a tough water phantom irradiated by a 6‐MV (nominal) X‐ray beam of 10 cm × 10 cm field size of Novalis TX (Brainlab). The ten different materials of high‐Z alloys (Al, Ti, Cu, Ag, Au‐Pd‐Ag, I, Ba, W, Au, Pb) were considered. The accuracy of calculated BSDF was verified by comparing with measured data by Gafchromic EBT3 films placed at from 0 to 10 mm away from a high‐Z alloy (Au‐Pd‐Ag). We derived an approximate equation to determine the relation of BSDF and range of backscatter to average atomic number of high‐Z alloy.

Results:

The calculated BSDF showed excellent agreement with measured one by Gafchromic EBT3 films at from 0 to 10 mm away from the high‐Z alloy. We found the simple linear relation of BSDF and range of backscatter to average atomic number of dental alloys. The latter relation was proven by the fact that energy spectrum of backscatter electrons strongly depend on average atomic number.

Conclusion:

We found a simple relation of backscatter dose enhancement around high‐Z alloys to its average atomic number based on Monte Carlo calculations. This work provides a simple and useful method to estimate backscatter dose enhancement from dental alloys and corresponding optimal thickness of dental spacer to prevent mucositis effectively.
SU‐C‐BRC‐07: Parametrized GPU Accelerated Electron Monte Carlo Second Check
Authors: Haywood J
Published: July 2016

Purpose:

I am presenting a parameterized 3D GPU accelerated electron Monte Carlo second check program.

Method:

I wrote the 3D grid dose calculation algorithm in CUDA and utilized an NVIDIA GeForce GTX 780 Ti to run all of the calculations. The electron path beyond the distal end of the cone is governed by four parameters: the amplitude of scattering (AMP), the mean and width of a Gaussian energy distribution (E and α), and the percentage of photons. In my code, I adjusted all parameters until the calculated PDD and profile fit the measured 10×10 open beam data within 1%/1mm. I then wrote a user interface for reading the DICOM treatment plan and images in Python. In order to verify the algorithm, I calculated 3D dose distributions on a variety of phantoms and geometries, and compared them with the Eclipse eMC calculations. I also calculated several patient specific dose distributions, including a nose and an ear. Finally, I compared my algorithm's computation times to Eclipse's.

Results:

The calculated MU for all of the investigated geometries agree with the TPS within the TG‐114 action level of 5%. The MU for the nose was < 0.5 % different while the MU for the ear at 105 SSD was ∼2 %. Calculation times for a 12MeV 10×10 open beam ranged from 1 second for a 2.5 mm grid resolution with ∼15 million particles to 33 seconds on a 1 mm grid with ∼460 million particles. Eclipse calculation runtimes distributed over 10 FAS workers were 9 seconds to 15 minutes respectively.

Conclusion:

The GPU accelerated second check allows quick MU verification while accounting for patient specific geometry and heterogeneity.
SU‐C‐BRB‐01: Automated Dose Deformation for Re‐Irradiation
Authors: Lim S , Kainz K , Li X
Published: July 2016

Purpose:

An objective of retreatment planning is to minimize dose to previously irradiated tissues. Conventional retreatment planning is based largely on best‐guess superposition of the previous treatment's isodose lines. In this study, we report a rigorous, automated retreatment planning process to minimize dose to previously irradiated organs at risk (OAR).

Methods:

Data for representative patients previously treated using helical tomotherapy and later retreated in the vicinity of the original disease site were retrospectively analyzed in an automated fashion using a prototype treatment planning system equipped with a retreatment planning module (Accuray, Inc.). The initial plan's CT, structures, and planned dose were input along with the retreatment CT and structure set. Using a deformable registration algorithm implemented in the module, the initially planned dose and structures were warped onto the retreatment CT. An integrated third‐party sourced software (MIM, Inc.) was used to evaluate registration quality and to contour overlapping regions between isodose lines and OARs, providing additional constraints during retreatment planning. The resulting plan and the conventionally generated retreatment plan were compared.

Results:

Jacobian maps showed good quality registration between the initial plan and retreatment CTs. For a right orbit case, the dose deformation facilitated delineating the regions of the eyes and optic chiasm originally receiving 13 to 42 Gy. Using these regions as dose constraints, the new retreatment plan resulted in V50 reduction of 28% for the right eye and 8% for the optic chiasm, relative to the conventional plan. Meanwhile, differences in the PTV dose coverage were clinically insignificant.

Conclusion:

Automated retreatment planning with dose deformation and definition of previously‐irradiated regions allowed for additional planning constraints to be defined to minimize re‐irradiation of OARs. For serial organs that do not recover from radiation damage, this method provides a more precise and quantitative means to limit cumulative dose.

This research is partially supported by Accuray, Inc
SU‐C‐BRB‐02: Automatic Planning as a Potential Strategy for Dose Escalation for Pancreas SBRT?
Authors: Wang S , Zheng D , Ma R , Lin C , Zhu X , Lei Y , Enke C , Zhou S
Published: July 2016

Purpose:

Stereotactic body radiation therapy (SBRT) has been suggested to provide high rates of local control for locally advanced pancreatic cancer. However, the close proximity of highly radiosensitive normal tissues usually causes the labor‐intensive planning process, and may impede further escalation of the prescription dose. The present study evaluates the potential of an automatic planning system as a dose escalation strategy.

Methods:

Ten pancreatic cancer patients treated with SBRT were studied retrospectively. SBRT was delivered over 5 consecutive fractions with 6 ∼ 8Gy/fraction. Two plans were generated by Pinnacle Auto‐Planning with the original prescription and escalated prescription, respectively. Escalated prescription adds 1 Gy/fraction to the original prescription. Manually‐created planning volumes were excluded in the optimization goals in order to assess the planning efficiency and quality simultaneously. Critical organs with closest proximity were used to determine the plan normalization to ensure the OAR sparing. Dosimetric parameters including D100, and conformity index (CI) were assessed.

Results:

Auto‐plans directly generate acceptable plans for 70% of the cases without necessity of further improvement, and two more iterations at most are necessary for the rest of the cases. For the pancreas SBRT plans with the original prescription, autoplans resulted in favorable target coverage and PTV conformity (D100 = 96.3% ± 1.48%; CI = 0.88 ± 0.06). For the plans with the escalated prescriptions, no significant target under‐dosage was observed, and PTV conformity remains reasonable (D100 = 93.3% ± 3.8%, and CI = 0.84 ± 0.05).

Conclusion:

Automatic planning, without substantial human‐intervention process, results in reasonable PTV coverage and PTV conformity on the premise of adequate OAR sparing for the pancreas SBRT plans with escalated prescription. The results highlight the potential of autoplanning as a dose escalation strategy for pancreas SBRT treatment planning. Further investigations with a larger number of patients are necessary.

The project is partially supported by Philips Medical Systems
SU‐C‐BRB‐04: Delineation Uncertainty Maps: Proof of Concept Study for Recurrent Gynaecological Cancers
Authors: Bernstein D , Kamerling C , Nill S , Taylor A , Oelfke U
Published: July 2016

Purpose:

To create a novel infrastructure which allows clinicians to record their GTV delineation uncertainty; to generate delineation uncertainty maps from this data and compare them to clinical GTVs.

Methods:

A contouring concept was developed in which clinicians draw up to two GTV boundaries per CT slice corresponding to the inner and outermost possible boundaries the GTV may have.A new uncertainty contouring tool was implemented in our research treatment planning system (TPS, DynaPlan) to accommodate these contour pairs and the derivation of delineation probability maps. 3D probability maps were generated from the contour pairs based on the minimum Chebyshev distance, at each pixel within the contours, from each boundary. The probability associated with each pixel was defined as the ratio of its distance from the inner boundary to the sum of its distances from each boundary.These tools were used to create probability maps using contours produced by a clinician experienced in treating recurrent gynaecological cancers. The corresponding 50% probability volumes (GTVP50) were compared against the observers corresponding clinical GTV (GTVC) contour, created in accordance with local clinical protocols, using the Jaccard Index.

Results:

This approach was successfully implemented within the research TPS. Comparisons between GTVC and GTVP50 were made for 10 recurrences from 9 patients. GTVC was larger than GTVP50 (p<0.01), with mean±s.d. volumes of 69.6±55.4cm3 and 61.6±53.7cm3 respectively, and a corresponding Jaccard Index of 0.83±0.11.

Conclusion:

Individual clinician's delineation uncertainty can be recorded and a corresponding uncertainty map derived. This is a crucial step in improving the handling of delineation uncertainty and moving away from population based margins, using techniques such as probabilistic treatment planning. Contours produced for recurrent gynaecological GTVs show the clinical GTV to be consistently larger than volume corresponding to 50% probability. Future work is to investigate non‐linear methods for generating these probability maps.

This report is independent research arising from an NIHR/HEE Healthcare Science Doctoral Research Fellowship, David Bernstein, HCS‐DRF‐2014‐05‐005, supported by National Institute for Health Research (NIHR). The views expressed in this publication are those of the author(s); not necessarily those of the NHS, NIHR, Health Education England or Department of Health.
SU‐C‐BRB‐06: Dosimetric Impact of Breast Contour Reconstruction Errors in GammaPod Stereotactic Radiotherapy
Authors: Niu Y , Becker S , Yu C , Mutaf Y
Published: July 2016

Purpose:

The first GammaPod™ unit, a dedicated prone stereotactic treatment device for early stage breast cancer, has been installed and commissioned at University of Maryland School of Medicine. The objective of this study was to investigate potential dosimetric impact of inaccurate breast contour.

Methods:

In GammaPod treatments, patient's beast is immobilized by a breast cup device (BCID) throughout the entire same‐day imaging and treatment procedure. 28 different BICD sizes are available to accommodate patients with varying breast sizes. A mild suction helps breast tissue to conform to the shape of the cup with selected size. In treatment planning, dose calculation utilizes previously calculated dose distributions for available cup geometry rather than the breast shape from CT image. Patient CT images with breast cups indicate minor geometric discrepancy between the matched shape of the cup and the breast contour, i.e., the contour size is larger or smaller. In order to investigate the dosimetric impact of these discrepancies, we simulated such discrepancies and reassessed the dose to target as well as skin.

Results:

In vicinity of skin, hot/cold spots were found when matched cup size was smaller/larger than patient's breast after comparing the corrected dose profiles from Monte Carlo simulation with the planned dose from TPS. The overdosing/underdosing of target could yield point dose differences as large as 5% due to these setup errors (D95 changes within 2.5%). Maximal skin dose was overestimated/underestimated up to 25%/45% when matched cup size was larger/smaller than real breast contour.

Conclusion:

The dosimetric evaluation suggests substantial underdosing/overdosing with inaccurate cup geometry during planning, which is acceptable for current clinical trial. Further studies are needed to evaluate such impact to treating small volume close to skin.
SU‐C‐BRB‐07: Threshold‐Driven Optimization for Reference‐Based Auto‐Planning
Authors: Long T , Chen M , Jiang S , Lu W
Published: July 2016

Purpose:

To study the procedure of reference‐based auto‐planning for treatment plan optimization and develop a threshold‐driven optimization methodology for automatically generating a treatment plan that is motivated by a reference DVH and/or dose distribution. We study threshold‐driven optimization for reference‐based auto‐planning (TORA).

Methods:

Commonly used voxel‐based quadratic penalties have three components: an overdose weight, and underdose weight, and some target dose threshold. Conventional planning using such a function involves iteratively updating the preference weights while keeping the thresholds constant, an unintuitive and inconsistent method for planning towards some target DVH. In auto‐planning, current cutting‐edge techniques also focus on the preference weights while fixing the threshold values. However, driving the optimization by threshold values can achieve similar plans without the extreme updates usually required of the weight parameters. The proposed methodology directly relates reference information to threshold values, which influence the optimization in a more impactful, intuitive way than the preference weights.

Results:

This methodology was applied to a prostate cancer case as a proof‐of‐concept. Both IMRT and VMAT treatment planning models were able to closely achieve a reference DVH. Other cases and modalities will be studied.

Conclusion:

This auto‐planning technique has the potential to be very effective for auto‐planning based on reference plans. As dose prediction and data‐driven planning becomes more prevalent in the clinical setting, incorporating such data into the treatment planning model in a clear, effective way will be crucial for efficient planning. Conventional methods of determining objective function parameters for a voxel‐based quadratic objective function have shortcomings and a threshold‐focused objective tuning should be explored, especially in the realm of efficient auto‐planning.

Supported by Cancer Prevention & Research Institute of Texas (CPRIT) ‐ ID RP150485
SU‐C‐BRA‐01: Interactive Auto‐Segmentation for Bowel in Online Adaptive MRI‐Guided Radiation Therapy by Using a Multi‐Region Labeling Algorithm
Authors: Lu Y , Chen I , Kashani R , Wan H , Maughan N , Muccigrosso D , Parikh P
Published: July 2016

Purpose:

In MRI‐guided online adaptive radiation therapy, re‐contouring of bowel is time‐consuming and can impact the overall time of patients on table. The study aims to auto‐segment bowel on volumetric MR images by using an interactive multi‐region labeling algorithm.

Methods:

5 Patients with locally advanced pancreatic cancer underwent fractionated radiotherapy (18–25 fractions each, total 118 fractions) on an MRI‐guided radiation therapy system with a 0.35 Tesla magnet and three Co‐60 sources. At each fraction, a volumetric MR image of the patient was acquired when the patient was in the treatment position. An interactive two‐dimensional multi‐region labeling technique based on graph cut solver was applied on several typical MRI images to segment the large bowel and small bowel, followed by a shape based contour interpolation for generating entire bowel contours along all image slices. The resulted contours were compared with the physician's manual contouring by using metrics of Dice coefficient and Hausdorff distance.

Results:

Image data sets from the first 5 fractions of each patient were selected (total of 25 image data sets) for the segmentation test. The algorithm segmented the large and small bowel effectively and efficiently. All bowel segments were successfully identified, auto‐contoured and matched with manual contours. The time cost by the algorithm for each image slice was within 30 seconds. For large bowel, the calculated Dice coefficients and Hausdorff distances (mean±std) were 0.77±0.07 and 13.13±5.01mm, respectively; for small bowel, the corresponding metrics were 0.73±0.08and 14.15±4.72mm, respectively.

Conclusion:

The preliminary results demonstrated the potential of the proposed algorithm in auto‐segmenting large and small bowel on low field MRI images in MRI‐guided adaptive radiation therapy. Further work will be focused on improving its segmentation accuracy and lessening human interaction.
SU‐C‐BRA‐05: Delineating High‐Dose Clinical Target Volumes for Head and Neck Tumors Using Machine Learning Algorithms
Authors: Cardenas C , Wong A , Mohamed A , Yang J , Court L , Rao A , Fuller C , Aristophanous M
Published: July 2016

Purpose:

To develop and test population‐based machine learning algorithms for delineating high‐dose clinical target volumes (CTVs) in H&N tumors. Automating and standardizing the contouring of CTVs can reduce both physician contouring time and inter‐physician variability, which is one of the largest sources of uncertainty in H&N radiotherapy.

Methods:

Twenty‐five node‐negative patients treated with definitive radiotherapy were selected (6 right base of tongue, 11 left and 9 right tonsil). All patients had GTV and CTVs manually contoured by an experienced radiation oncologist prior to treatment. This contouring process, which is driven by anatomical, pathological, and patient specific information, typically results in non‐uniform margin expansions about the GTV. Therefore, we tested two methods to delineate high‐dose CTV given a manually‐contoured GTV: (1) regression‐support vector machines(SVM) and (2) classification‐SVM. These models were trained and tested on each patient group using leave‐one‐out cross‐validation. The volume difference(VD) and Dice similarity coefficient(DSC) between the manual and auto‐contoured CTV were calculated to evaluate the results. Distances from GTV‐to‐CTV were computed about each patient's GTV and these distances, in addition to distances from GTV to surrounding anatomy in the expansion direction, were utilized in the regression‐SVM method. The classification‐SVM method used categorical voxel‐information (GTV, selected anatomical structures, else) from a 3×3×3cm3 ROI centered about the voxel to classify voxels as CTV.

Results:

Volumes for the auto‐contoured CTVs ranged from 17.1 to 149.1cc and 17.4 to 151.9cc; the average(range) VD between manual and auto‐contoured CTV were 0.93 (0.48–1.59) and 1.16(0.48–1.97); while average(range) DSC values were 0.75(0.59–0.88) and 0.74(0.59–0.81) for the regression‐SVM and classification‐SVM methods, respectively.

Conclusion:

We developed two novel machine learning methods to delineate high‐dose CTV for H&N patients. Both methods showed promising results that hint to a solution to the standardization of the contouring process of clinical target volumes.

Varian Medical Systems grant
SU‐C‐BRA‐06: Automatic Brain Tumor Segmentation for Stereotactic Radiosurgery Applications
Authors: Liu Y , Stojadinovic S , Jiang S , Timmerman R , Abdulrahman R , Nedzi L , Gu X
Published: July 2016

Purpose:

Stereotactic radiosurgery (SRS), which delivers a potent dose of highly conformal radiation to the target in a single fraction, requires accurate tumor delineation for treatment planning. We present an automatic segmentation strategy, that synergizes intensity histogram thresholding, super‐voxel clustering, and level‐set based contour evolving methods to efficiently and accurately delineate SRS brain tumors on contrast‐enhance T1‐weighted (T1c) Magnetic Resonance Images (MRI).

Methods:

The developed auto‐segmentation strategy consists of three major steps. Firstly, tumor sites are localized through 2D slice intensity histogram scanning. Then, super voxels are obtained through clustering the corresponding voxels in 3D with reference to the similarity metrics composited from spatial distance and intensity difference. The combination of the above two could generate the initial contour surface. Finally, a localized region active contour model is utilized to evolve the surface to achieve the accurate delineation of the tumors. The developed method was evaluated on numerical phantom data, synthetic BRATS (Multimodal Brain Tumor Image Segmentation challenge) data, and clinical patients’ data. The auto‐segmentation results were quantitatively evaluated by comparing to ground truths with both volume and surface similarity metrics.

Results:

DICE coefficient (DC) was performed as a quantitative metric to evaluate the auto‐segmentation in the numerical phantom with 8 tumors. DCs are 0.999±0.001 without noise, 0.969±0.065 with Rician noise and 0.976±0.038 with Gaussian noise. DC, NMI (Normalized Mutual Information), SSIM (Structural Similarity) and Hausdorff distance (HD) were calculated as the metrics for the BRATS and patients’ data. Assessment of BRATS data across 25 tumor segmentation yield DC 0.886±0.078, NMI 0.817±0.108, SSIM 0.997±0.002, and HD 6.483±4.079mm. Evaluation on 8 patients with total 14 tumor sites yield DC 0.872±0.070, NMI 0.824±0.078, SSIM 0.999±0.001, and HD 5.926±6.141mm.

Conclusion:

The developed automatic segmentation strategy, which yields accurate brain tumor delineation in evaluation cases, is promising for its application in SRS treatment planning.
SU‐C‐202‐04: Adapting Biologically Optimized Dose Escalation Based On Mid‐Treatment PET/CT for Non‐Small‐Cell Lung Cancer
Authors: Zhang P , Kuo L , Yorke E , Hu Y , Lockney N , Mageras G , Deasy J , Rimner A
Published: July 2016

Purpose:

To develop a biological modeling strategy which incorporates the response observed on the mid‐treatment PET/CT into a dose escalation design for adaptive radiotherapy of non‐small‐cell lung cancer.

Method:

FDG‐PET/CT was acquired midway through standard fractionated treatment and registered to pre‐treatment planning PET/CT to evaluate radiation response of lung cancer. Each mid‐treatment PET voxel was assigned the median SUV inside a concentric 1cm‐diameter sphere to account for registration and imaging uncertainties. For each voxel, the planned radiation dose, pre‐ and mid‐treatment SUVs were used to parameterize the linear‐quadratic model, which was then utilized to predict the SUV distribution after the full prescribed dose. Voxels with predicted post‐treatment SUV≥2 were identified as the resistant target (response arm). An adaptive simultaneous integrated boost was designed to escalate dose to the resistant target as high as possible, while keeping prescription dose to the original target and lung toxicity intact. In contrast, an adaptive target volume was delineated based only on the intensity of mid‐treatment PET/CT (intensity arm), and a similar adaptive boost plan was optimized. The dose escalation capability of the two approaches was compared.

Result:

Images of three patients were used in this planning study. For one patient, SUV prediction indicated complete response and no necessary dose escalation. For the other two, resistant targets defined in the response arm were multifocal, and on average accounted for 25% of the pre‐treatment target, compared to 67% in the intensity arm. The smaller response arm targets led to a 6Gy higher mean target dose in the adaptive escalation design.

Conclusion:

This pilot study suggests that adaptive dose escalation to a biologically resistant target predicted from a pre‐ and mid‐treatment PET/CT may be more effective than escalation based on the mid‐treatment PET/CT alone. More plans and ultimately clinical protocols are needed to validate this approach.

MSKCC has a research agreement with Varian Medical System
SU‐C‐202‐06: Design and Development of a Non‐Rigid Phantom Ventilating Air Quantitatively Evaluating CT‐Based Pulmonary Ventilation Imaging
Authors: Miyakawa S , Tachibana H , Moriya S , Kurosawa T , Sato M
Published: July 2016

Purpose:

A validation study using human or sheep for CT pulmonary ventilation (CT‐V) imaging are inefficient and partially unstable. In this study, we designed and developed non‐rigid phantom ventilating air to quantitatively evaluate the CT‐V image.

Methods:

The phantom consisted of an acryl cylinder filled with polyurethane foam designed to pulmonic alveoli and a polyurethane membrane was attached to the inferior end of the phantom to simulate a lung diaphragm. Also, trachea‐shaped polyurethane tubes were covered by the foam and the tubes passed through the outside in order to exchange a gas. Lung arteries were also modeled with polyurethane and were located adjacent to the trachea model. Two 3D‐CT scans were performed at exhale and inhale using an air contrast agent of xenon gas, respectively. The exhale 3D‐CT was deformed to the inhale 3D‐CT using the in‐house program with the NiftyReg. Sixteen landmarks were assigned around trachea and lung arteries in the inhale image and the deformed exhale image. Target Registration Error (TRE) for each landmark between the two images was calculated for commissioning of our program. CT‐V image was generated using Jacobian determinant metrics (JD). Subsequently, HU value change between the two images was measured. The correlation coefficient was calculated between the JD and the HU change.

Results:

The deformable and ventilation phantom shows a variety of displacement for each landmark (1 mm − 20 mm). The mean TRE was 4.5 ± 4.7 mm (Maximum: 12.3 mm). The relationship between the JD and the HU change shows high correlation. (R = −0.86). At the several landmarks where TRE values were over 3 mm, the correlation was poor.

Conclusion:

The phantom may be a useful QA tool to validate CT‐V imaging. We will improve our deformable image registration program for CT‐V imaging with the efficient way using the phantom.
SU‐C‐207A‐01: A Novel Maximum Likelihood Method for High‐Resolution Proton Radiography/proton CT
Authors: Collins‐Fekete C , Schulte R , Beaulieu L , Seco J
Published: July 2016

Purpose:

Multiple Coulomb scattering is the largest contributor to blurring in proton imaging. Here we tested a maximum likelihood least squares estimator (MLLSE) to improve the spatial resolution of proton radiography (pRad) and proton computed tomography (pCT).

Methods:

The object is discretized into voxels and the average relative stopping power through voxel columns defined from the source to the detector pixels is optimized such that it maximizes the likelihood of the proton energy loss. The length spent by individual protons in each column is calculated through an optimized cubic spline estimate. pRad images were first produced using Geant4 simulations. An anthropomorphic head phantom and the Catphan line‐pair module for 3‐D spatial resolution were studied and resulting images were analyzed. Both parallel and conical beam have been investigated for simulated pRad acquisition. Then, experimental data of a pediatric head phantom (CIRS) were acquired using a recently completed experimental pCT scanner. Specific filters were applied on proton angle and energy loss data to remove proton histories that underwent nuclear interactions. The MTF10% (lp/mm) was used to evaluate and compare spatial resolution.

Results:

Numerical simulations showed improvement in the pRad spatial resolution for the parallel (2.75 to 6.71 lp/cm) and conical beam (3.08 to 5.83 lp/cm) reconstructed with the MLLSE compared to averaging detector pixel signals. For full tomographic reconstruction, the improved pRad were used as input into a simultaneous algebraic reconstruction algorithm. The Catphan pCT reconstruction based on the MLLSE‐enhanced projection showed spatial resolution improvement for the parallel (2.83 to 5.86 lp/cm) and conical beam (3.03 to 5.15 lp/cm). The anthropomorphic head pCT displayed important contrast gains in high‐gradient regions. Experimental results also demonstrated significant improvement in spatial resolution of the pediatric head radiography.

Conclusion:

The proposed MLLSE shows promising potential to increase the spatial resolution (up to 244%) in proton imaging.
SU‐C‐207A‐02: Proton Radiography Using Pencil Beam Scanning and a Novel, Low‐Cost Range Telescope
Authors: Dolney D , Mayers G , Newcomer M , Weiss D , Meekins E , Bollinger D , Desai N , Maughan R , Solberg T , Hollebeek R
Published: July 2016

Purpose:

While the energy of therapeutic proton beams can be adjusted to penetrate to any given depth in water, range uncertainties arise in patients due in part to imprecise knowledge of the stopping power of protons in human tissues [1]. Proton radiography is one approach to reduce the beam range uncertainty [2], thereby allowing for a reduction in treatment margins and dose escalation.

Methods:

The authors have adapted a novel detector technology based on Micromesh Gaseous Structure (“Micromegas”) for proton therapy beams and have demonstrated fine spatial and time resolution of magnetically scanned proton pencil beams, as well as wide dynamic range for dosimetry [3]. The authors have constructed a prototype imaging system comprised of 5 Micromegas layers. Proton radiographs were obtained downstream of solid water assemblies. The position‐sensitive monitor chambers in the IBA proton delivery nozzle provide the beam entrance position.

Results:

Our technique achieves spatial resolution as low as 300 µm and water‐equivalent thickness (WET) resolution as good as 0.02% (60 µm out of 31 cm total thickness). The dose delivered to the patient is kept below 2 cGy. The spatial resolution as a function of sample rate and number of delivered protons is found to be near the theoretical Cramer‐Rao lower bound. By extrapolating the CR bound, we argue that the imaging dose could be further lowered to 1 mGy, while still achieving submillimeter spatial resolution, by achievable instrumentation and beam delivery modifications.

Conclusion:

For proton radiography, high spatial and WET resolution can be achieved, with minimal additional dose to patient, by using magnetically scanned proton pencil beams and Micromegas detectors.
SU‐C‐207A‐04: Accuracy of Acoustic‐Based Proton Range Verification in Water
Authors: Jones KC , Vander Stappen F , Sehgal CM , Avery S
Published: July 2016

Purpose:

To determine the accuracy and dose required for acoustic‐based proton range verification (protoacoustics) in water.

Methods:

Proton pulses with 17 µs FWHM and instantaneous currents of 480 nA (5.6 × 107 protons/pulse, 8.9 cGy/pulse) were generated by a clinical, hospital‐based cyclotron at the University of Pennsylvania. The protoacoustic signal generated in a water phantom by the 190 MeV proton pulses was measured with a hydrophone placed at multiple known positions surrounding the dose deposition. The background random noise was measured. The protoacoustic signal was simulated to compare to the experiments.

Results:

The maximum protoacoustic signal amplitude at 5 cm distance was 5.2 mPa per 1 × 107 protons (1.6 cGy at the Bragg peak). The background random noise of the measurement was 27 mPa. Comparison between simulation and experiment indicates that the hydrophone introduced a delay of 2.4 µs. For acoustic data collected with a signal‐to‐noise ratio (SNR) of 21, deconvolution of the protoacoustic signal with the proton pulse provided the most precise time‐of‐flight range measurement (standard deviation of 2.0 mm), but a systematic error (−4.5 mm) was observed.

Conclusion:

Based on water phantom measurements at a clinical hospital‐based cyclotron, protoacoustics is a potential technique for measuring the proton Bragg peak range with 2.0 mm standard deviation. Simultaneous use of multiple detectors is expected to reduce the standard deviation, but calibration is required to remove systematic error. Based on the measured background noise and protoacoustic amplitude, a SNR of 5.3 is projected for a deposited dose of 2 Gy.