bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐T‐791: Validation of a Determinant Based Photon Transport Solver in Dose Perturbed By Diverse Media
Authors: Kuo H , Tome W , Yaparpalvi R , Garg M , Bodner W , Kalnicki S
Published: June 2015

Purpose:

To validate a determinant based photon transport solver in dose imparted within different transition zone between different medium.

Methods:

Thickness (.2cm,.5cm, 1cm, 3cm) from various materials (Air ‐ density=0.0012g/cm3, Cork‐0.19g/cm3, Lung‐0.26g/cm3, Bone‐1.85g/cm3, Aluminum (Al)‐2.7g/cm3, Titanium (Ti)‐4.42g/cm3, Iron (Fe)‐8g/cm3) were sandwiched by 10cm solid water. 6MV were used to study the calculation difference between a superposition photon beam model (AAA) and the determinant based Boltzmann photon transport solver (XB) at the upstream (I) and downstream boarder (II) of the medium, within the medium (III), and at far distance downstream away from medium (IV). Calculation was validated with available thickness of Air, Cork, Lung, Al, Ti and Fe. Results are presented as the ratio of the dose at the point with medium perturbation to the same point dose without perturbation.

Results:

Zone I showed different backscatter enhancement from high‐density materials within the 5mm of the upstream border. AAA showed no backscatter at all, XB showed good agreement beyond 1mm upstream (1.18 vs 1.14, 1.09 vs 1.10, and 1.04 vs 1.05 for Fe, Ti, and Fe, respectively). Zone II showed a re‐buildup after exiting high‐density medium and Air but no build up for density close to water in both of the measurement and XB. AAA yielded the opposite results in Zone II. XB and AAA showed in Zone III very different absorption in high density medium and the Air. XB and measurement had high concordance regarding photon attenuation in Zone IV. AAA showed less agreement especially when the medium was Air or Fe.

Conclusion:

XB compared well with measurement in regions 1mm away from the interface. Planning using XB should be beneficial for External Beam Planning in situations with large air cavity, very low lung density, compact bone, and any kind of metal implant.
SU‐E‐T‐794: Validation of the MCNPX Monte Carlo Model of the Ocular Beam Line at the Proton Therapy Center Houston
Authors: Titt U , Suzuki K
Published: June 2015

Purpose:

The PTCH is preparing the ocular proton beam nozzle for clinical use. Currently commissioning measurements are being performed using films, diodes and ionization chambers. In parallel, a Monte Carlo model of the beam line was created for integration into the automated Monte Carlo treatment plan computation system, MC2. This work aims to compare Monte Carlo predictions to measured proton doses in order to validate the Monte Carlo model.

Methods:

A complete model of the double scattering ocular beam line has been created and is capable of simulating proton beams with a comprehensive set of beam modifying devices, including eleven different range modulator wheels. Simulations of doses in water were scored and compare to ion chamber measurements of depth doses, lateral dose profiles extracted from half beam block exposures of films, and diode measurements of lateral penumbrae at various depths.

Results:

All comparison resulted in an average relative entrance dose difference of less than 3% and peak dose difference of less than 2%. All range differences were smaller than 0.2 mm. The differences in the lateral beam profiles were smaller than 0.2 mm, and the differences in the penumbrae were all smaller than 0.4%.

Conclusion:

All available data shows excellent agreement of simulations and measurements. More measurements will have to be performed in order to completely and systematically validate the model. Besides simulating and measuring PDDs and lateral profiles of all remaining range modulator wheels, the absolute dosimetry factors in terms of number of source protons per monitor unit have to be determined.
SU‐E‐T‐796: Variation of Surface Photon Energy Spectra On Bone Heterogeneity and Beam Obliquity Between Flattened and Unflattened Beam
Authors: Chow J , Owrangi A , Grigorov G
Published: June 2015

Purpose:

This study investigates the spectra of surface photon energy and energy fluence in the bone heterogeneity and beam obliquity using flattened and unflattened photon beams. The spectra were calculated in a bone and water phantom using Monte Carlo simulation (the EGSnrc code).

Methods:

Spectra of energy, energy fluence and mean energy of the 6 MV flattened and unflattened photon beams (field size = 10 × 10 cm2) produced by a Varian TrueBEAM linear accelerator were calculated at the surfaces of a bone and water phantom using Monte Carlo simulations. The spectral calculations were repeated with the beam angles turned from 0° to 15°, 30° and 45° in the phantoms.

Results:

It is found that the unflattened photon beams contained more photons in the low‐energy range of 0 – 2 MeV than the flattened beams with a flattening filter. Compared to the water phantom, both the flattened and unflattened beams had slightly less photons in the energy range < 0.4 MeV when a bone layer of 1 cm is present under the phantom surface. This shows that the presence of the bone decreased the low‐energy photons backscattered to the phantom surface. When the photon beams were rotated from 0° to 45°, the number of photon and mean photon energy increased with the beam angle. This is because both the flattened and unflattened beams became more hardened when the beam angle increased. With the bone heterogeneity, the mean energies of both photon beams increased correspondingly. This is due to the absorption of low‐energy photons by the bone, resulting in more significant beam hardening.

Conclusion:

The photon spectral information is important in studies on the patient's surface dose enhancement when using unflattened photon beams in radiotherapy.
SU‐E‐T‐800: Verification of Acurose XB Dose Calculation Algorithm at Air Cavity‐Tissue Interface Using Film Measurement for Small Fields of 6‐MV Flattening Filter‐Free Beams
Authors: Kang S , Chung J , Suh T
Published: June 2015

Purpose:

To verify the dose accuracy of Acuros XB (AXB) dose calculation algorithm at air‐tissue interface using inhomogeneous phantom for 6‐MV flattening filter‐free (FFF) beams.

Methods:

An inhomogeneous phantom included air cavity was manufactured for verifying dose accuracy at the air‐tissue interface. The phantom was composed with 1 and 3 cm thickness of air cavity. To evaluate the central axis doses (CAD) and dose profiles of the interface, the dose calculations were performed for 3 × 3 and 4 × 4 cm2 fields of 6 MV FFF beams with AAA and AXB in Eclipse treatment plainning system. Measurements in this region were performed with Gafchromic film. The root mean square errors (RMSE) were analyzed with calculated and measured dose profile. Dose profiles were divided into inner‐dose profile (>80%) and penumbra (20% to 80%) region for evaluating RMSE. To quantify the distribution difference, gamma evaluation was used and determined the agreement with 3%/3mm criteria.

Results:

The percentage differences (%Diffs) between measured and calculated CAD in the interface, AXB shows more agreement than AAA. The %Diffs were increased with increasing the thickness of air cavity size and it is similar for both algorithms. In RMSEs of inner‐profile, AXB was more accurate than AAA. The difference was up to 6 times due to overestimation by AAA. RMSEs of penumbra appeared to high difference for increasing the measurement depth. Gamma agreement also presented that the passing rates decreased in penumbra.

Conclusion:

This study demonstrated that the dose calculation with AXB shows more accurate than with AAA for the air‐tissue interface. The 2D dose distributions with AXB for both inner‐profile and penumbra showed better agreement than with AAA relative to variation of the measurement depths and air cavity sizes.
SU‐E‐T‐801: Verification of Dose Information Passed Through 3D‐Printed Products
Authors: Jeong S , Kim D , Chung W , Yoon M , Shin D , Chung M
Published: June 2015

Purpose:

When quality assurance (QA) of patient treatment beam is performed, homogeneous water equivalent phantom which has different structure from patient's internal structure is normally used. In these days, it is possible to make structures which have same shapes of human organs with commercialization of 3D‐printer. As a Result, structures with same shape of human organs made by 3D‐printer could be used to test qualification of treatment beam with greater accuracy than homogeneous water phantom. In this study, we estimated the dose response of 3D‐printer materials to test the probability as a humanoid phantom or new generation of compensator tool.

Methods:

The rectangular products with variety densities (50%, 75% and 100%) were made to verify their characteristics. The products for experiment group and solid water phantom and air for control group with 125 cubic centimeters were put on solid water phantom with enough thickness. CT image of two products were acquired to know their HU values and to know about their radiologic characteristics. 6MV beams with 500MU were exposed for each experiment. Doses were measured behind the 3D‐printed products. These measured doses were compared to the results taken by TPS.

Results:

Absorbed dose penetrated from empty air is normalized to 100%. Doses measured from 6MV photon beams penetrated from 50%, 75% and 100% products were 99%, 96% and 84%, respectively. HU values of 50%, 75% and 100% products are about −910, −860 and −10.

Conclusion:

3D‐printer can produce structures which have similar characteristics with human organ. These results would be used to make similar phantoms with patient information.

This work was supported by the Nuclear Safety Research Program (Grant No. 1305033 and 1403019) of the Korea Radiation Safety Foundation and the Nuclear Safety and Security Commission and Radiation Technology Development Program (2013M2A2A4027117) of the Republic of Korea.
SU‐E‐T‐803: Verification of QUANTEC Lyman Kutcher Burman (LKB) Model for Grade>=2(2+) Late Rectal Complication Rates Using a Database of 79 Prostate Patients Treated with IMRT
Authors: Fatyga M , Schild S , Vora S , Schild M , Wong W , Liu X , Li J , Wu T
Published: June 2015

Purpose:

QUANTEC review of best parameters for the LKB NTCP model of rectal complications is based exclusively on datasets obtained with 3D conformal techniques. The report suggests that inherent differences in rectal dose distributions obtained with IMRT techniques could require modification of the parameters which provide the best fit to clinical data.

Methods:

We compiled a database of 79 prostate patients who were treated with an IMRT technique to a dose of 77.4 Gy, 1.8Gy/fx, with an integrated boost to 81–83Gy in a sub‐volume of a prostate which was identified on a pre‐treatment MRI study. Rectal toxicities were graded according to CTCAE v4 by a physician who retrospectively reviewed patient's medical records. Late grade 2+ toxicities were defined as toxicities occurring later than 90 days following the end of treatment. We defined the model in terms of parameters, m,n and TD_50, as recommended in the Quantec report. We converted the dose to 2Gy equivalent dose using linear‐quadratic model with alpha over beta of 3Gy. We applied QUANTEC model to our data and compared results to our own fit of LKB model using two sample t‐test.

Results:

Grade 2+ late rectal toxicity occurred in 4% (3/79 patients). The best fit of LKB model to data was obtained for n = 0.26, m = 0.25, and TD_50 = 81.53Gy. The two sample t‐test yielded p value of 0.67. Average NTCP predicted by our parametrization is 3.8% while average NTCP predicted by QUANTEC parametrization is 3.5%.

Conclusion:

Predictions of late rectal toxicities in IMRT patients using LKB model with parameters from QUANTEC report match observed toxicity rates. Independent fit of LKB model to IMRT data produces somewhat different parameter set, but two parametrizations are equivalent within statistical uncertainties.
SU‐E‐T‐806: Very Fast GPU‐Based IMPT Dose Computation
Authors: Sullivan A , Brand M
Published: June 2015

Purpose:

Designing particle therapy treatment plans is a dosimetrist‐in‐the‐loop optimization wherein the conflicting constraints of achieving a desired tumor dose distribution must be balanced against the need to minimize the dose to nearby OARs. IMPT introduces an additional, inner, numerical optimization step in which the dosimetrist's current set of constraints are used to determine the weighting of beam spots. Very fast dose calculations are needed to enable the dosimetrist to perform many iterations of the outer optimization in a commercially reasonable time.

Methods:

We have developed a GPU‐based convolution‐type dose computation algorithm that more accurately handles heterogeneities than earlier algorithms by redistributing energy from dose computed in a water volume. The depth dependence of the beam size is handled by pre‐processing Bragg curves using a weighted superposition of Gaussian bases. Additionally, scattering, the orientation of treatment ports, and the non‐parallel propagation of beams are handled by large, but sparse, energy‐redistribution matrices that implement affine transforms.

Results:

We tested our algorithm using a brain tumor dataset with 1 mm voxels and a single treatment port from the patient's anterior through the sinuses. The resulting dose volume is 100 × 100 × 230 mm with 66,200 beam spots on a 3 × 3 × 2 mm grid. The dose computation takes <1 msec on a GeForce GTX Titan GPU with the Gamma passing rate for 2mm/2% criterion of 99.1% compared to dose calculated by an alternative dose algorithm based on pencil beams. We will present comparisons to Monte Carlo dose calculations.

Conclusion:

Our high‐speed dose computation method enables the IMPT spot weights to be optimized in <1 second, resulting in a nearly instantaneous response to user changes to dose constraints. This permits the creation of higher quality plans by allowing the dosimetrist to evaluate more alternatives in a short period of time.
SU‐E‐T‐807: VMAT Vs. DIMRT Vs. SsIMRT Assessing the Dosimetric Parameters of Cervical Carcinoma Treatment with a 20‐Patient Sample
Authors: Duan J
Published: June 2015

Purpose:

The purpose of this study is to assess the dosimetric parameters of cervical carcinoma treatment using 3 different radiation therapy delivery

Methods:

volumetric‐modulated arc therapy (VMAT), the static‐field dynamic multileaf collimator intensity‐modulated radiation therapy (dIMRT) and the static‐field step‐and‐shoot intensity‐modulated radiotherapy (ssIMRT).

Methods:

Twenty patients with cervical carcinoma were selected to be planned with dual arc VMAT, dIMRT and ssIMRT using Monaco 3.3 TPS on the Axesse™ linear accelerator in this investigation. The total dose of the planning target volume (PTV) is 60Gy. The homogeneity index (HI), conformity index (CI), dose volume histograms (DVHs), delivery efficiency, dose of organs at risks (bladder, rectum, and femoral heads), were all measured.

Results:

Dose distribution in 3 different radiation therapy delivery methods satisfied clinical requirements. Mean HI of PTV with VMAT, dIMRT and ssIMRT is 1.08, 1.10, and 1.09 (p>0.05). Mean CI of PTV with VMAT, dIMRT and ssIMRT is 0.82, 0.8 and 0.8 (p>0.05). For the DVH of V10, V20 and V30 in bladder, there was a significant difference: VMAT>dIMRT=ssIMRT (p <0.05). For the DVH of V40 and V50, there was a significant difference: VMAT<dIMRT=ssIMRT (p <0.05). The DVHs of rectum and femoral heads also reflected a similar characteristic with bladder that VMAT gave a higher dose than dIMRT and ssIMRT in low‐dose regions (p <0.05), but gave a lower dose than dIMRT and ssIMRT in high‐dose regions (p <0.05). For the delivery efficiency, there was a significant difference: VMAT > dIMRT >ssIMRT (p <0.05).

Conclusion:

The results show that VMAT has a great advantage in delivery efficiency than dIMRT and ssIMRT, without compromise to the PTV coverage, HI and CI. The delivery methods should be considered under the actual cervical carcinoma radiotherapy situation.
SU‐E‐T‐812: Volumetric Modulated Arc Therapy‐Total Body Irradiation (VMAT‐TBI) V.s. Conventional Extended SSD‐TBI (cTBI): A Dosimetric Comparisom
Authors: Ouyang L , Folkerts M , Lee H , Ramirez E , Timmerman R , Abdulrahman R , Jiang S , Gu X
Published: June 2015

Purpose:

To perform a dosimetric evaluation on a new developed volumetric modulated arc therapy based total body irradiation (VMAT‐TBI).

Methods:

Three patients were CT scanned with an indexed rotatable body frame to get whole body CT images. Concatenated CT images were imported in Pinnacle treatment planning system and whole body and lung were contoured as PTV and organ at risk, respectively. Treatment plans were generated by matching multiple isocenter volumetric modulated arc (VMAT) fields of the upper body and multiple isocenter parallel‐opposed fields of the lower body. For each plan, 1200 cGy in 8 fractions was prescribed to the whole body volume and the lung dose was constrained to a mean dose of 750 cGy. Such a two‐level dose plan was achieved by inverse planning of the torso VMAT fields. For comparison, conventional standing TBI (cTBI) plans were generated on the same whole body CT images at an extended SSD (550cm).The shape of compensators and lung blocks are simulated using body segments and lung contours Compensation was calculated based on the patient CT images, in mimic of the standing TBI treatment. The whole body dose distribution of cTBI plans were calculated with a home‐developed GPU Monte Carlo dose engine. Calculated cTBI dose distribution was prescribed to the mid‐body point at umbilical level.

Results:

The VMAT‐TBI treatment plans of three patients’ plans achieved 80.2%±5.0% coverage of the total body volume within ±10% of the prescription dose, while cTBI treatment plans achieved 72.2%±4.0% coverage of the total body volume. The averaged mean lung dose of all three patients is lower for VMAT‐TBI (7.48 cGy) than for cTBI (8.96 cGy).

Conclusion:

The proposed patient comfort‐oriented VMAT‐TBI technique provides for a uniform dose distribution within the total body while reducing the dose to the lungs.
SU‐F‐BRD‐05: Robustness of Dose Painting by Numbers in Proton Therapy
Authors: Montero A Barragan , Sterpin E , Lee J
Published: June 2015

Purpose:

Proton range uncertainties may cause important dose perturbations within the target volume, especially when steep dose gradients are present as in dose painting. The aim of this study is to assess the robustness against setup and range errors for high heterogeneous dose prescriptions (i.e., dose painting by numbers), delivered by proton pencil beam scanning.

Methods:

An automatic workflow, based on MATLAB functions, was implemented through scripting in RayStation (RaySearch Laboratories). It performs a gradient‐based segmentation of the dose painting volume from 18FDG‐PET images (GTVPET), and calculates the dose prescription as a linear function of the FDG‐uptake value on each voxel. The workflow was applied to two patients with head and neck cancer. Robustness against setup and range errors of the conventional PTV margin strategy (prescription dilated by 2.5 mm) versus CTV‐based (minimax) robust optimization (2.5 mm setup, 3% range error) was assessed by comparing the prescription with the planned dose for a set of error scenarios.

Results:

In order to ensure dose coverage above 95% of the prescribed dose in more than 95% of the GTVPET voxels while compensating for the uncertainties, the plans with a PTV generated a high overdose. For the nominal case, up to 35% of the GTVPET received doses 5% beyond prescription. For the worst of the evaluated error scenarios, the volume with 5% overdose increased to 50%. In contrast, for CTV‐based plans this 5% overdose was present only in a small fraction of the GTVPET, which ranged from 7% in the nominal case to 15% in the worst of the evaluated scenarios.

Conclusion:

The use of a PTV leads to non‐robust dose distributions with excessive overdose in the painted volume. In contrast, robust optimization yields robust dose distributions with limited overdose.

RaySearch Laboratories is sincerely acknowledged for providing us with RayStation treatment planning system and for the support provided.
SU‐F‐BRD‐06: Robust Dose Calculation in Intensity Modulated Proton Therapy
Authors: Brosch R , Liu W
Published: June 2015

Purpose:

Commissioning data for intensity modulated proton therapy (IMPT) must be post‐processed by fits to ad‐hoc functions to derive the dose calculation kernel parameters in a treatment planning system (TPS). Whether from experimental measurement or Monte Carlo simulation, the limited and noisy nature of such data makes this task very challenging. We present a method to improve the modeling of the lateral dose distribution of clinical energy proton beams in water to commission an in‐house IMPT dose calculation engine.

Methods:

A linear sum of three Gaussian distribution functions was fitted to the lateral dose data in logarithmic scale. Starting values of fitting solutions were determined from the Generalized Highland Approximation. We exhaustively optimized the combinations of data weights with upper bounds of the fitting solutions to minimize confidence intervals of the fitting solutions while maintaining the coefficient of determination (R2).

Results:

Across all energies, average confidence bounds improved 72.88% [Max: 88.28%, Min: 55.05%] for small angle coulomb scattering, 114.25% [409.13%, 66.72%,] for nuclear scattering, and 68.66% [141.09%, 33.27%] for large angle coulomb scattering, while the coefficients of determination of the fits (R2) remained comparable. On average R 2 only changed 0.18% and were very close to 1 (approx. 0.999). Wilcoxon signed rank tests comparing unweighted/unbounded fits with weighted/bounded fits averaged 0.0146 (Max: 0.177, Min: 7.05×10−⁷) for small angle Coulomb, 0.0903 (0.945, 7.05×10−⁷) for nuclear, and 0.254 (0.871, 1.86×10−⁶) for large angle Coulomb scattering. This allows rejection of the null hypothesis for small angle Coulomb scattering at the 0.015 level and nuclear interaction at the 0.1 level.

Conclusion:

Optimal weights assigned to IMPT lateral dose data minimized fitting to stochastic noise in the tail region. Optimizing the upper bounds of fitting parameters improved the robustness of fitting solutions. Both led to a more physically meaningful dose calculation kernel for the TPS.

NIH/NCI K25CA168984, Eagles Cancer Research Career Development, The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, Mayo ASU Seed Grant, and The Kemper Marley Foundation.
SU‐F‐BRD‐09: A Random Walk Model Algorithm for Proton Dose Calculation
Authors: Yao W , Farr J
Published: June 2015

Purpose:

To develop a random walk model algorithm for calculating proton dose with balanced computation burden and accuracy.

Methods:

Random walk (RW) model is sometimes referred to as a density Monte Carlo (MC) simulation. In MC proton dose calculation, the use of Gaussian angular distribution of protons due to multiple Coulomb scatter (MCS) is convenient, but in RW the use of Gaussian angular distribution requires an extremely large computation and memory. Thus, our RW model adopts spatial distribution from the angular one to accelerate the computation and to decrease the memory usage. From the physics and comparison with the MC simulations, we have determined and analytically expressed those critical variables affecting the dose accuracy in our RW model.

Results:

Besides those variables such as MCS, stopping power, energy spectrum after energy absorption etc., which have been extensively discussed in literature, the following variables were found to be critical in our RW model: (1) inverse squared law that can significantly reduce the computation burden and memory, (2) non‐Gaussian spatial distribution after MCS, and (3) the mean direction of scatters at each voxel. In comparison to MC results, taken as reference, for a water phantom irradiated by mono‐energetic proton beams from 75 MeV to 221.28 MeV, the gamma test pass rate was 100% for the 2%/2mm/10% criterion. For a highly heterogeneous phantom consisting of water embedded by a 10 cm cortical bone and a 10 cm lung in the Bragg peak region of the proton beam, the gamma test pass rate was greater than 98% for the 3%/3mm/10% criterion.

Conclusion:

We have determined key variables in our RW model for proton dose calculation. Compared with commercial pencil beam algorithms, our RW model much improves the dose accuracy in heterogeneous regions, and is about 10 times faster than MC simulations.
SU‐F‐BRD‐11: A Virtual Simulator Designed for Collision Prevention in Proton Therapy
Authors: Jung H , Kum O , Park H , Choi D , Han Y
Published: June 2015

Purpose:

In proton therapy, collisions between patient and nozzle potentially occur in attaining minimal air gap due to the large nozzle structure. Thus, we developed software predicting the collisions of the nozzle and patient by simulating treatments.

Methods:

3D modeling of a gantry inner‐floor, nozzle and robotic‐couch was done by using the SolidWorks based on the manufacturer's machine data. To obtain patient body information, a 3D‐scanner was utilized to scan a patient right before CT scanning. From the acquired images, a 3D‐image of the patient's body contour was reconstructed. The accuracy of the image was confirmed against the CT image for a humanoid phantom. The machine components and the virtual patient were combined on the treatment‐room coordinate system, resulting in a virtual simulator. The simulator simulated the motion of its components such as rotation and translation of gantry, nozzle and couch, in real scale. Collision, if any, was examined both in static mode and dynamic mode. The static mode checks only at fixed positions of the machine's components while dynamic mode examines while one component is in motion. Collision was notified if any voxel of two components, for example a nozzle and a patient or couch, overlapped when calculating volume locations. The event and collision point are visualized and colliding volumes are reported.

Results:

All components were successfully assembled and the motions could be accurately controlled. The 3D‐shape of a phantom agreed with CT images within a deviation of 2 mm. Collision situations can be simulated within minutes and the results are displayed and reported.

Conclusion:

The developed software will be useful in improving patient safety and clinical efficiency for proton therapy.

This work was supported by the National Research Foundation of Korea funded by Ministry of Science, ICT & Future Planning (2012M3A9B6055201, 2013M2A2A7043507), and Samsung Medical Center grant (GFO1130081).
SU‐F‐BRB‐02: Towards Quantitative Clinical Decision On Deep Inspiration Breath Hold (DIBH) Or Prone for Left‐Sided Breast Irradiation
Authors: Lin H , Gao Y , Liu T , Gelblum D , Ho A , Powell S , Tang X , Xu X
Published: June 2015

Purpose:

To develop quantitative clinical guidelines between supine Deep Inspiratory Breath Hold (DIBH) and prone free breathing treatments for breast patients, we applied 3D deformable phantoms to perform Monte Carlo simulation to predict corresponding Dose to the Organs at Risk (OARs).

Methods:

The RPI‐adult female phantom (two selected cup sizes: A and D) was used to represent the female patient, and it was simulated using the MCNP6 Monte Carlo code. Doses to OARs were investigated for supine DIBH and prone treatments, considering two breast sizes. The fluence maps of the 6‐MV opposed tangential fields were exported. In the Monte Carlo simulation, the fluence maps allow each simulated photon particle to be weighed in the final dose calculation. The relative error of all dose calculations was kept below 5% by simulating 3*10⁷ photons for each projection.

Results:

In terms of dosimetric accuracy, the RPI Adult Female phantom with cup size D in DIBH positioning matched with a DIBH treatment plan of the patient. Based on the simulation results, for cup size D phantom, prone positioning reduced the cardiac dose and the dose to other OARs, while cup size A phantom benefits more from DIBH positioning. Comparing simulation results for cup size A and D phantom, dose to OARs was generally higher for the large breast size due to increased scattering arising from a larger portion of the body in the primary beam. The lower dose that was registered for the heart in the large breast phantom in prone positioning was due to the increase of the distance between the heart and the primary beam when the breast was pendulous.

Conclusion:

Our 3D deformable phantom appears an excellent tool to predict dose to the OARs for the supine DIBH and prone positions, which might help quantitative clinical decisions. Further investigation will be conducted.

National Institutes of Health R01EB015478
SU‐F‐BRB‐03: Quantifying Patient Motion During Deep‐Inspiration Breath‐Hold Using the ABC System with Simultaneous Surface Photogrammetry
Authors: Cheung Y , Rahimi A , Sawant A
Published: June 2015

Purpose:

Active breathing control (ABC) has been used to reduce treatment margin due to respiratory organ motion by enforcing temporary breath‐holds. However, in practice, even if the ABC device indicates constant lung volume during breath‐hold, the patient may still exhibit minor chest motion. Consequently, therapists are given a false sense of security that the patient is immobilized. This study aims at quantifying such motion during ABC breath‐holds by monitoring the patient chest motion using a surface photogrammetry system, VisionRT.

Methods:

A female patient with breast cancer was selected to evaluate chest motion during ABC breath‐holds. During the entire course of treatment, the patient's chest surface was monitored by a surface photogrammetry system, VisionRT. Specifically, a user‐defined region‐of‐interest (ROI) on the chest surface was selected for the system to track at a rate of ∼3Hz. The surface motion was estimated by rigid image registration between the current ROI image captured and a reference image. The translational and rotational displacements computed were saved in a log file.

Results:

A total of 20 fractions of radiation treatment were monitored by VisionRT. After removing noisy data, we obtained chest motion of 79 breath‐hold sessions. Mean chest motion in AP direction during breath‐holds is 1.31mm with 0.62mm standard deviation. Of the 79 sessions, the patient exhibited motion ranging from 0–1 mm (30 sessions), 1–2 mm (37 sessions), 2–3 mm (11 sessions) and >3 mm (1 session).

Conclusion:

Contrary to popular assumptions, the patient is not completely still during ABC breath‐hold sessions. In this particular case studied, the patient exhibited chest motion over 2mm in 14 out of 79 breath‐holds. Underestimating treatment margin for radiation therapy with ABC could reduce treatment effectiveness due to geometric miss or overdose of critical organs.

The senior author receives research funding from NIH, VisionRT, Varian Medical Systems and Elekta
SU‐F‐BRB‐07: A Plan Comparison Tool to Ensure Robustness and Deliverability in Online‐Adaptive Radiotherapy
Authors: Hill P , Labby Z , Bayliss R A , Geurts M , Bayouth J
Published: June 2015

Purpose:

To develop a plan comparison tool that will ensure robustness and deliverability through analysis of baseline and online‐adaptive radiotherapy plans using similarity metrics.

Methods:

The ViewRay MRIdian treatment planning system allows export of a plan file that contains plan and delivery information. A software tool was developed to read and compare two plans, providing information and metrics to assess their similarity. In addition to performing direct comparisons (e.g. demographics, ROI volumes, number of segments, total beam‐on time), the tool computes and presents histograms of derived metrics (e.g. step‐and‐shoot segment field sizes, segment average leaf gaps). Such metrics were investigated for their ability to predict that an online‐adapted plan reasonably similar to a baseline plan where deliverability has already been established.

Results:

In the realm of online‐adaptive planning, comparing ROI volumes offers a sanity check to verify observations found during contouring. Beyond ROI analysis, it has been found that simply editing contours and re‐optimizing to adapt treatment can produce a delivery that is substantially different than the baseline plan (e.g. number of segments increased by 31%), with no changes in optimization parameters and only minor changes in anatomy. Currently the tool can quickly identify large omissions or deviations from baseline expectations. As our online‐adaptive patient population increases, we will continue to develop and refine quantitative acceptance criteria for adapted plans and relate them historical delivery QA measurements.

Conclusion:

The plan comparison tool is in clinical use and reports a wide range of comparison metrics, illustrating key differences between two plans. This independent check is accomplished in seconds and can be performed in parallel to other tasks in the online‐adaptive workflow. Current use prevents large planning or delivery errors from occurring, and ongoing refinements will lead to increased assurance of plan quality.
SU‐F‐BRB‐08: How Many Parameters Are Required to Characterize DVHs in Clinical Circumstance?
Authors: Chen Z , Wang J , Hu W
Published: June 2015

Purpose:

The aim of this study is to assess how many parameters are required to characterize the DVH curves by principal component analysis (PCA) in two tumors sites.

Methods:

Two tumor sites including nasopharyngeal cancer and lung cancer were enrolled in this study. Each tumor site contains 5 patients. Multiple criteria optimization (MCO) algorithm was used to generate the plan database to cover all the possible optimization solution in RayStation (RaySearch Laboratories AB, Sweden). The constraints and trade‐off objectives setting were based on the QUANTEC research and planning experience. The target and normal tissue DVHs were export to MATLAB. Each DVH on plans were resampled into 101 points for principal component analysis. A threshold of 95% was used to decide how many components should be selected to characterize DVH curves. Finally, we evaluate the accuracy of the data extraction by regenerating DVH from the selected principal components (PCs). The D95 of PTV, max‐dose of spinal cord and brainstem, mean dose of parotid and other related organs at risk in nasopharyngeal cancer; and the D95 of PTV, the V20Gy of lung‐PTV, and mean dose of heart in lung cancer were analyzed.

Results:

The PCs used to characterize DVH were 1–3 in nasopharyngeal cancer, 2–3 in lung cancer. The regenerated DVHs were coincided with the original DVHs in both cancers. The mean dose differences of all clinical points between the regenerated and the original were 0, and the maximize deviation is less than 100cGy except some parameters in the nasopharynx cancer, which has the maximal dose difference of 177cGy in spinal cord and 608cGy in brainstem.

Conclusion:

It is feasible to characterize the DVH curves by no more than 3 principal independent variables in nasopharyngeal cancer and lung cancer.
SU‐F‐BRB‐11: An Integrated Alternating Direction Method of Multipliers for Treatment Planning Optimization
Authors: Zarepisheh M , Ye Y , Xing L
Published: June 2015

Purpose:

To propose a new parallel‐friendly optimization algorithm, based on alternating direction method of multipliers (ADMM), for solving optimization problems emerging in treatment planning and imaging

Methods:

ADMM, emerging as a powerful tool for distributed optimization, is employed here for IMRT treatment planning. We modify the existing ADMM by integrating that with two optimization techniques known as Barzilai‐Borwein gradient method and line search. We apply original and integrated ADMM, with various penalty parameter values, on three IMRT treatment planning cases and we compare their performance. Each algorithm terminates once it found a solution within the relative error of 1E‐4 from the optimal solution. We also compare the performance of original and integrated ADMM against the commercial optimization software CPLEX.

Results:

Our experiments on three different cancer sites (prostate, head and neck, and GYN) indicate that integrated ADMM is much faster than original ADMM (5.8 times faster on average). Moreover, while the performance of original ADMM heavily depends on the selected penalty parameter, integrated ADMM performs very robust against the penalty parameter. Compared to the commercial software CPLEX, integrated ADMM turns out to be around 4–7 times faster.

Conclusion:

Integrated ADMM is a very efficient optimization algorithm to cope with the large‐scale optimization problems. It is a parallel‐friendly optimization algorithm and provides an idea platform for cloud‐based treatment planning and imaging.
MO‐A‐BRB‐00: Electronic Charting in EBRT and Brachytherapy
Authors: Mechalakos James
Published: June 2015

The process of converting to an electronic chart for radiation therapy can be daunting. It requires a dedicated committee to first research and choose appropriate software, to review the entire documentation policy and flow of the clinic, to convert this system to electronic form or if necessary, redesign the system to more easily conform to the electronic process. Those making the conversion and those who already use electronic charting would benefit from the shared experience of those who have been through the process in the past. Therefore TG262 was convened to provide guidance on electronic charting for external beam radiation therapy and brachytherapy.

This course will present the results of an internal survey of task group members on EMR practices in External Beam Radiation Therapy as well as discuss important issues in EMR development and structure for both EBRT and brachytherapy.

Learning Objectives:

Be familiarized with common practices and pitfalls in development and maintenance of an electronic chart in Radiation Oncology

Be familiarized with important issues related to electronic charting in External Beam Radiation Therapy

Be familiarized with important issues related to electronic charting in Brachytherapy
MO‐AB‐BRA‐03: Calorimetry‐Based Absorbed Dose to Water Measurements Using Interferometry
Authors: Flores‐Martinez E , Malin M , DeWerd L
Published: June 2015

Purpose:

Interferometry‐based calorimetry is a novel technique to measure radiation‐induced temperature changes allowing the measurement of absorbed dose to water (ADW). There are no mechanical components in the field. This technique also has the possibility of obtaining 2D dose distributions. The goal of this investigation is to calorimetrically‐measure doses between 2.5 and 5 Gy over a single projection in a photon beam using interferometry and compare the results with doses calculated using the TG‐51 linac calibration.

Methods:

ADW was determined by measuring radiation‐induced phase shifts (PSs) of light passing through water irradiated with a 6 MV photon beam. A 9×9×9 cm3 glass phantom filled with water and placed in an arm of a Michelson interferometer was irradiated with 300, 400, 500 and 600 monitor units. The whole system was thermally insulated to achieve sufficient passive temperature control. The depth of measurement was 4.5 cm with a field size of 7×7 cm2. The intensity of the fringe pattern was monitored with a photodiode and used to calculate the time‐dependent PS curve. Data was acquired 60 s before and after the irradiation. The radiation‐induced PS was calculated by taking the difference in the pre‐ and post‐irradiation drifts extrapolated to the midpoint of the irradiation. Results were compared to computed doses.

Results:

Average comparison of calculated ADW values with interferometry‐measured values showed an agreement to within 9.5%. k=1 uncertainties were 4.3% for calculations and 14.7% for measurements. The dominant source of uncertainty for the measurements was a temperature drift of about 30 µK/s caused by heat conduction from the interferometer's surroundings.

Conclusion:

This work presented the first absolute ADW measurements using interferometry in the dose range of linac‐based radiotherapy. Future work to improve measurements’ reproducibility includes the implementation of active thermal control techniques.
MO‐AB‐207‐00: ACR Update in MR, CT, Nuclear Medicine, and Mammography
Authors: Kofler James
Published: June 2015

A goal of an imaging accreditation program is to ensure adequate image quality, verify appropriate staff qualifications, and to assure patient and personnel safety. Currently, more than 35,000 facilities in 10 modalities have been accredited by the American College of Radiology (ACR), making the ACR program one of the most prolific accreditation options in the U.S. In addition, ACR is one of the accepted accreditations required by some state laws, CMS/MIPPA insurance and others. Familiarity with the ACR accreditation process is therefore essential to clinical diagnostic medical physicists. Maintaining sufficient knowledge of the ACR program must include keeping up‐to‐date as the various modality requirements are refined to better serve the goals of the program and to accommodate newer technologies and practices. This session consists of presentations from authorities in four ACR accreditation modality programs, including magnetic resonance imaging, computed tomography, nuclear medicine, and mammography. Each speaker will discuss the general components of the modality program and address any recent changes to the requirements.

Learning Objectives:

To understand the requirements of the ACR MR Accreditation program. The discussion will include accreditation of whole‐body general purpose magnets, dedicated extremity systems well as breast MRI accreditation. Anticipated updates to the ACR MRI Quality Control Manual will also be reviewed.

To understand the requirements of the ACR CT accreditation program, including updates to the QC manual as well as updates through the FAQ process.

To understand the requirements of the ACR nuclear medicine accreditation program, and the role of the physicist in annual equipment surveys and the set up and supervision of the routine QC program.

To understand the current ACR MAP Accreditation requirement and present the concepts and structure of the forthcoming ACR Digital Mammography QC Manual and Program.
MO‐AB‐207‐02: ACR Update in MR
Authors: Price R.
Published: June 2015

A goal of an imaging accreditation program is to ensure adequate image quality, verify appropriate staff qualifications, and to assure patient and personnel safety. Currently, more than 35,000 facilities in 10 modalities have been accredited by the American College of Radiology (ACR), making the ACR program one of the most prolific accreditation options in the U.S. In addition, ACR is one of the accepted accreditations required by some state laws, CMS/MIPPA insurance and others. Familiarity with the ACR accreditation process is therefore essential to clinical diagnostic medical physicists. Maintaining sufficient knowledge of the ACR program must include keeping up‐to‐date as the various modality requirements are refined to better serve the goals of the program and to accommodate newer technologies and practices. This session consists of presentations from authorities in four ACR accreditation modality programs, including magnetic resonance imaging, computed tomography, nuclear medicine, and mammography. Each speaker will discuss the general components of the modality program and address any recent changes to the requirements.

Learning Objectives:

To understand the requirements of the ACR MR Accreditation program. The discussion will include accreditation of whole‐body general purpose magnets, dedicated extremity systems well as breast MRI accreditation. Anticipated updates to the ACR MRI Quality Control Manual will also be reviewed.

To understand the requirements of the ACR CT accreditation program, including updates to the QC manual as well as updates through the FAQ process.

To understand the requirements of the ACR nuclear medicine accreditation program, and the role of the physicist in annual equipment surveys and the set up and supervision of the routine QC program.

To understand the current ACR MAP Accreditation requirement and present the concepts and structure of the forthcoming ACR Digital Mammography QC Manual and Program.
MO‐AB‐201‐03: The Alphabet Soup of Regulatory Compliance: Being Prepared for Inspections
Authors: Kroger L.
Published: June 2015

The role of the Radiation Safety Officer at a medical facility can be complicated. The complexity of the position is based on the breadth of services provided at the institution and the nature of the radioactive materials license. Medical practices are constantly changing and the use of ionizing radiation continues to rise in this area. Some of the newer medical applications involving radiation have unique regulatory and safety issues that must be addressed. Oversight of the uses of radiation start at the local level (radiation safety officer, radiation safety committee) and are heavily impacted by outside agencies (i.e. Nuclear Regulatory Commission, State Radiologic Health, The Joint Commission (TJC), etc).

This session will provide both an overview of regulatory oversight and essential compliance practices as well as practical ways to assess and introduce some of the new applications utilizing radioactive materials into your medical facility.

Learning Objectives:

Regulatory Compliance and Safety with New Radiotherapies: Spheres and Ra‐223 (Lance Phillips)

Understand the radioactive materials license amendment process to add new radiotherapies (i.e., SIR‐Spheres, Therasphere, Xofigo).

Understand the AU approval process for microspheres and Xofigo.

Examine the training and handling requirements for new procedures.

Understand the process involved with protocol development, SOP in order to define roles and responsibilities.

The RSO and The RSC: Challenges and Opportunities (Colin Dimock)

Understand how to form an effective Committee.

Examine what the Committee does for the Program and the RSO.

Understand the importance of Committee engagement.

Discuss the balance of the complimentary roles of the RSO and the Committee.

The Alphabet Soup of Regulatory Compliance: Being Prepared for Inspections (Linda Kroger)

Recognize the various regulatory bodies and organizations with oversight or impact in Nuclear Medicine, Radiology and Radiation Oncology.

Examine 10CFR35 requirements as they relate to the everyday practice of Nuclear Medicine and Radiation Oncology.

Understand the nature of available guidance documents (e.g., NUREG 1556).

Examine the commonalities between TJC and CMS preparedness.