bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐T‐643: Quality Study of Beam Angle Optimization Algorithm In IMRT Plan for Cervix Cancer Radiotherapy
Authors: Pang T , Yang B , Qiu J , Zhang F
Published: July 2013

Purpose: To evaluate the benefit of Beam angle optimization (BAO) algorithm for organ sparing in IMRT plans for cervical cancer Methods: Twelve cervical cancer patients were planned using Eclipse planning system. The structures of target volume and organs‐at‐risk (OAR) were delineated by the attending physician. Institutional standard of 9 equally spaced beam IMRT plan, and a 9 field IMRT plan with beam orientation optimized by BAO algorithm were performed for each patient .The BAO seeks patient‐specific beam angle optimization based on PTV‐OAR geometry and given dose sparing constraints. Therefore, it is expected that BAO‐plans would offer additional organ sparing benefit by optimization of the beam angles. All plans are normalized to prescription dose covering 95% of PTV volume. Results: There is no obvious quality improvement by using beam angle optimization. Specifically, minimum target coverage that measures the PTV volume covered by 95% of prescription dose (V95%) is lower in BAO plans. As a Result, the Conformity Index and Homogeneity Index are worse in BAO‐plans. For OAR sparing, there was no significant difference in bladder V30 and D40. No significant difference was observed for V30, V40 in rectum. The small bowel DVH showed that V40 and Dmax increased by 0.6% and 1.4 Gy respectively. The V10,V30, Dmean of bone marrow increased by 1.2%,5.6%,1.3Gy respectively,the cauda equina D0.1cc was increased by 2 Gy. At last, there was no significant difference in femoral heads D5%. Conclusion: These is no significant benefit of the BAO algorithm for either PTV coverage or OAR sparing for cervical cancer IMRT plans. For sites like cervical cancer, the target volumes have very complicated relationships with the OARs, the BAO is not capable of analyzing such complicated PTV‐OAR relationship, hence, equally spaced 9 beam configuration maybe more robust in achieving balanced clinical goals.
SU‐E‐T‐644: Time‐Resolved Stochastic IMRT Planning
Authors: Roy A , Nohadani O
Published: July 2013

Purpose: To develop a stochastic time‐resolved model that accounts for spatiotemporal changes in tumor over the extended course of the treatment. Furthermore, we aim to mitigate the effect of uncertainties, yet generate clinically acceptable plans even in worst‐case scenarios. The performance of the method is demonstrated based on a clinical lung cancer case. Method: Distinct tumor regression scenarios (from slow shrinkage to fast shrinkage) and their associated probabilities are constructed based on data from past studies. We minimize deviations from prescribed dose by taking all regression scenarios into account. These deviations are taken with respect to entire volume of interest, which consists of (right lung, left lung, heart, esophagus, spinal cord, tumor and tissue), over all time‐periods (5 weeks). Results: Conventional models disregarding tumor regression lead to significant overdose on OAR as time progresses, producing V 2 0> > 30%, hence beyond the threshold. The nominal time‐resolved model allows for redistribution of the dose based on tumor regression, leading to a V 2 0 < 19%, whilst improving the tumor coverage. On the other hand, when regression assumptions deviate from the realized, tumor coverage is sub‐optimal and clinically not acceptable. The proposed stochastic time‐resolved model mitigates the effect of lack of specific knowledge about tumor regression. In particular, it meets dose criterion for tumor, whilst sparing the OAR (V2 0 < 23%) even in the worst‐case scenario. Conclusion: Traditional models degrade amidst tumor regression, especially at latter time‐periods. The nominal time‐resolved model allows redistribution of doses based on tumor regression, enhancing OAR sparing, but holds only when assumptions are met. The stochastic model accounts for uncertainties in tumor regression and produces clinically acceptable plans, even in the worst‐case scenario when assumptions are not met.
SU‐E‐T‐645: Beam Selection for 4Pi Non‐Coplanar Converging (4PiNC) Delivery Using a Genetic Algorithm (GA)
Authors: Cho D , Wang S , Sabbas A , Chao K , Chang J
Published: July 2013

Purpose: To develop a GA for selecting 4PiNC beams that optimize the planning target volume (PTV) coverage and organ at risk (OAR) sparing. Methods: A simple treatment planning system was implemented for studying 4PiNC beam delivery. In this system, 4PiNC beams were delivered in a conical fashion where the cone angle was the angle between the central axis of the beam and the transverse iso‐plane. We used an ideal spherical phantom with a radius of 10 cm. The 4PiNC beams consisted of 263 beams on 9 (0°, ±20°, ±40°, ±60°, ±80°) cones. The PTV was a sphere (radius=1.4cm) centered at the isocenter and the OAR was another sphere (radius=2cm) 3mm apart from the PTV. The dose in each voxel was calculated using the output factors, tissue‐maxima ratios and off‐axis ratios of a 6MV beam. An GA was developed to select the beams by minimizing a cost function of important factors including conformity index and maximal OAR doses. For each generation, the GA produces a number of offspring by randomly turning on or off a group of randomly selected beams from the parent. The cost function for each offspring is evaluated and the offspring with the minimum cost function is selected as the parent for the next generation. This process is repeated until all preset constraints are met. Results: For the PTV only case the GA selected 165 out of total 263 beams that minimized the conformity index to 1.00. With the OAR, 130 out of total 263 beams were selected for producing the best conformity index, 1.10 while maintaining the maximal OAR dose within acceptable levels. Conclusion: We have developed a GA for 4PiNC beam selection and demonstrated that a subset of the 4PiNC beams are sufficient for optimal PTV coverage and OAR sparing. This work was partially supported by a DOD grant DOD W81XWH1010862.
SU‐E‐T‐653: Predicting Objective Function Weights for IMRT Prostate Treatment Planning Using Patient Anatomy
Authors: Lee T , Hammad M , Chan T , Craig T , Sharpe M
Published: July 2013

Purpose: To develop a prediction model for objective function weights for intensity‐modulated radiation therapy (IMRT) prostate treatment planning with multiple objectives using geometry information from patient anatomy. Methods: A previously developed inverse optimization method (IOM) was used to reverse‐engineer optimal objective function weights (inverse weights) from an observed treatment plan. We developed a regression model to predict the weights for IMRT prostate treatment planning using patient anatomy from 25 patients. The ratio of the overlap volumes of the rectum and bladder with the planning target volume expanded by 1cm was used to predict the bladder and rectum weights. The femoral head weights were included in the model as a small fixed weight (1%). The model was validated using leave‐one‐out cross‐validation. We evaluated the model by comparing the treatment plans generated through inverse planning using the inverse weights from IOM and the predicted weights from the regression model. Results: On average, V54Gy for the bladder was 36.1% using the inverse weights and 36.6% using the predicted weights. V70Gy for the bladder was 23.2% (inverse) and 23.5% (predicted). For the rectum, V54Gy was 34.6% (inverse) and 33.9% (predicted), and V70Gy was 22.6% (inverse) and 22.3% (predicted). For each criterion, the difference between the inverse and predicted metrics was not statistically significant. All treatment plans from the predicted weights satisfied the clinical criteria. Conclusion: Our results show that objective function weights are well‐predicted by the regression model. This approach may support the genesis of personalized weights in IMRT treatment planning. This research was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Ontario Graduate Scholarship (OGS).
SU‐E‐T‐656: Multi‐Criteria Direct Aperture Optimization
Authors: Salari E , Unkelbach J
Published: July 2013

Purpose: Multi‐criteria optimization has been applied to IMRT planning, mainly in the fluence‐map optimization stage, to interactively explore the trade‐off between conflicting treatment objectives. However, the subsequent leaf‐sequencing step may degrade the plan quality due to dose discrepancies. To circumvent this issue, this study aims at developing multi‐criteria optimization approaches to IMRT planning using direct aperture optimization methods. Methods: The direct aperture optimization problem is formulated and solved using a multi‐criteria optimization approach. In particular, a solution method is developed to obtain a collection of apertures that can adequately span the entire Pareto surface. To that end, the column generation method for direct aperture optimization is extended to a multi‐criteria setting in which apertures that can improve the entire Pareto surface are sequentially identified and added to the aperture collection. More specifically, we approximate the improvement rate of an aperture in the Pareto surface by sampling Pareto‐optimal points and measuring the cumulative improvement rate of the aperture at those sampling points. Results: Our solution method is tested on a paraspinal case in which the trade‐off between target coverage and spinal cord sparing is studied. We compare the trade‐off curves obtained using our solution method and two other related heuristics. The computational results validate that the proposed method obtains a balanced approximation of the Pareto surface over a wide range of clinically relevant plans. Conclusion: We have developed a multi‐criteria direct aperture optimization method that allows for conducting the trade‐off exploration directly in the space of deliverable plans, thereby avoiding dose discrepancies caused by the leaf‐sequencing stage.
SU‐E‐T‐669: Dose Interplay Effects in Stereotactic Radiosurgery (SRS) of Multiple Brain Lesions
Authors: Ma L , Sahgal A , Wang B , Hossain S , Ahmad S , Larson D
Published: July 2013

Purpose: Volumetric modulated arc therapy (VMAT) has enabled rapid treatments of multiple brain tumors with a single or few isocenters. We investigated inter‐lesion dose interplay effects for such a treatment and compared against standard multi‐isocenteric Gamma Knife (GK) or dynamic‐conformal‐arc (DCA) SRS deliveries. Methods: A patient case with 12 intracranial targets and simulated cases with 2–60 targets in the brain parenchyma were used for the study. For the patient case, all targets and organs‐at‐risk were contoured by a senior clinician. A subset of 3, 6, 9 and 12 targets were then planned at different institutions for GK, DCA and VMAT SRS. Identical dose‐volume constraints to the targets and critical structures were applied. Each target was prescribed with 20 Gy covering at least 99% of the target volume. Relationships between the mean 4‐Gy to 12‐Gy isodose volumes per lesion versus increasing number of lesions were analyzed for each modality. Results: For all the cases, 12‐Gy isodose volumes per lesion exhibited negligible dependence with the increasing number of targets for GK SRS and DCA deliveries. However, for VMAT delivery, a strong statistically significant dependence with increasing number of targets was found at all levels of isodose volumes. For example, the increase in the 12‐Gy volumes of the patient case was 0.068+/−0.016 cc/lesion (p=0.05) for the VMAT delivery in contrast to 0.0+/−0.0 cc/lesion (p < 0.0001) for both GK and DCA deliveries. The increase in the 4‐Gy isodose volumes was 2.79+/−0.40 cc/lesion (p=0.02) for the VMAT delivery, and 2.13+/−0.15 cc/lesion (p=0.005) for the DCA delivery in contrast to 0.08+/−0.29 cc/lesion (p=0.10) for the GK delivery. Conclusion: Significant dose interplay effects were found for single‐or few‐isocenter VMAT SRS of multiple lesions, somewhat for multi‐isocenteric DCA SRS, but nearly negligible for GK SRS treatments.
SU‐E‐T‐671: Is There Really a Favorable Image Data Set Between Free‐Breathing, Average Or Maximum Intensity Projections for Peripheral Lung SBRT?
Authors: Mihailidis D , Whaley L , Harmon M , Raja P , Farinash L , Tomara P
Published: July 2013

Purpose: This work investigates the dosimetric impact of 4D‐CT treatment planning for lung SBRT. We compare treatment planning and dosimetric characteristic between plans optimized on free‐breathing (FB) scans then, computed on maximum and average intensity projections (MIP and AIP). Which data set is more favorable for planning and dose calculations between fully‐optimized plans on MIP or AIP versus FB? Methods: A small number of patients with peripheral lung lesions treated with SBRT in our center with an Oncor‐160MLC system, were selected for this study. All patients received a FB helical scan to the entire chest and a 4D‐CT scan to a smaller volume that includes the lesion. Internal target volume (ITV) was first delineated on the MIP and a 5mm margin to it, defined the PTV. Multi‐field (7–11) inversely optimized planning was done first on the FB set, and then it was transferred to registered MIP and AIP for re‐calculation (with heterogeneities), after having propagated and segmented onto MIP and AIP sets all organs‐at‐risk (OARs), respectively. Additonal plans were created with re‐optimization of the beam fluences on AIP and MIP sets. All plans were compared based on dosimetric parameters, distributions and dose‐volume histograms (DVHs). Results: Dosimetric characteristics of FB with re‐calculated AIP and MIP plans were similar overall with those of MIP being slightly higher of the three. Interestingly, the re‐optimized plans give lower target and involved lung doses most likely due to different average lung CT‐numbers between FB, MIP and AIP sets. Conclusion: For peripheral lung lesions, planning for SBRT with intensity modulation is challenges as different imaging data sets have similar dosimetric characteristics. Re‐optimization of the plans on MIP and AIP give a better indication as to which data set is appropriate to be utilized. A more robust protocol is needed for lung 4D‐CT treatment planning.
SU‐E‐T‐673: Factors Influencing Normal Brain Dose for Single‐Isocenter Multi‐Target Radiosurgery
Authors: Yuan Y , Thomas E , Clark G , FIveash J , Popple R
Published: July 2013

Purpose: To evaluate the effects of number of arcs, collimator angle, variable secondary collimator size, and optimization objectives on normal brain dose. Methods: Ten patients treated for multiple cranial metastases were retrospectively planned for single‐isocenter VMAT. All plans were optimized using a standardized objective function and were normalized such that 99% of the total target volume received 18 Gy. Multiple variables were utilized in planning, including numbers of arcs (2 versus 4), collimator angles (45° versus selected per beam to minimize area of normal brain exposed in the beams‐eye‐view), jaw tracking (fixed versus trailing MLC leaf), and a low dose constraint for healthy brain (mean dose 2 Gy versus no constraint). Plan quality was evaluated by conformity index, gradient index, mean absolute volume of normal brain receiving 1.8 Gy (V10), 4.5 Gy (V25), 12 Gy (V12Gy), and normal brain mean dose. Results: Conformity index, gradient index, and V12Gy were not significantly dependent on the factors considered. The low dose constraint reduced the brain mean dose by 56 cGy (13.7% reduction relative to no low dose constraint). Other factors did not have a significant effect on mean dose. The low dose constraint decreased V25 and V10 by 136 cc (28.8% reduction) and 128 cc (12.7% reduction), respectively. Collimator angle and jaw tracking each reduced V25 and V10 by up to 32 cc and 40 cc, respectively. Compared to 2 arcs, 4 arcs decreased V25 by 20 cc and increased V10 by 38 cc. Conclusion: Limiting the normal brain mean dose in the optimization objective function significantly reduces the low dose spill into the normal brain without changing target coverage. Jaw tracking and appropriate selection of collimator also reduces the low dose volume, but to a lesser extent.
SU‐E‐T‐688: Software to Evaluate the Effect of Applicator Translations and Rotations On HDR Plans
Authors: Bakhtiari M , Schmitt J , Zarkoob K , Aroumougame V , Sarfaraz M , Rodgers J
Published: July 2013

Purpose: The rotation and translation of the catheters used in High Dose Rate (HDR) brachytherapy can potentially change the dosimetric outcome of the intended treatment plan. Geometric verification performed before each fraction are not adequate. Tools and techniques should be developed that evaluates the change in dose distribution for possible rotations and translation of the catheters before each treatment. Methods: A software program was developed that imports the treatment planning systems dicom files, rotates and translates the device based on the values provided by the user, and recalculates the dose distribution in the patients structures. A TG‐43 formalism was used to calculate the dose distribution. The program evaluates the dose to selected critical structures to determine if re‐planning is necessary. A variety of clinical cases including strut‐adjusted volume implant (SAVI), MammoSite, Cantura, Tandom and Ovoids, Cylinder, and skin applicators were studied. Results: SAVI cases appeared to be the most sensitive to rotations depending on the distance of the chest wall or the skin from the closest dwell position and also to the dwell times. For SAVI cases where the skin or chest wall are at a distance larger than ∼1.5 cm from the closest dwell position, the effect of any degree of rotation results in a dosimetric deviation of less than 5%. On the other hand for the cases where the skin is closer than ∼1.5 cm from the closest dwell position, a small rotation of 10 degree in some cases results in over dosing as large as 50% to the skin. Conclusion: The complexity of the plans in SAVI cases leads to a nonlinear dependence of the dosimetric outcome versus amount of rotation and/or translation.
SU‐E‐T‐697: Correlation Between Day 0 Post‐Implant Dosimetry Parameters and Differences in Pre‐and Post‐Implant Prostate Volume‐How Much Can Post‐Plan Quality Be Improved Through Better Assessment of Volume for Permanent Interstitial I‐125 Prostate Implants?
Authors: Dolan J , Wolthuis B , Shasha D , Ambrose R , Santoro J , Furhang E
Published: July 2013

Purpose: To evaluate the relationship between the difference in pre‐and post‐implant prostate volume and post‐implant dosimetric parameters for pre‐planned permanent interstitial prostate implants. Methods: Between January 2007 and December 2011, 964 patients underwent TRUS guided interstitial prostate I‐125 brachytherapy either as monotherapy (MPD 144Gy) or in combination with external irradiation (MPD 108Gy). All procedures and contouring for pre‐and post‐planning was performed by a single physician. Post‐implant dosimetric analysis was performed on CTs taken on the day of implant. Differences in prostate volume as determined by TRUS and CT were evaluated by computing a parameter, δvol, defined as the TRUS prostate volume (VTrus) minus the CT prostate volume (VCT) divided by VTrus. Implants were grouped into the following categories based on their post‐implant dosimetry: 1.Hot (D90>120% and V150>70%); 2. Cold (D90<80%) and; 3.) Standard. Differences in δvol across groups were evaluated. D90, V100 and V150 were plotted against their corresponding δvol values. Results: Overall, the average and standard deviation of δvol, D90, V100 and V150 was 0.0%+/−17.6, 101%+/−12.9, 89.3%+/− 7.0, and 47%+/−12.8, respectively. For the standard, hot, and cold groups, the average and standard deviation of δvol was 0.3%+/−15.5, − 18.0%+/−9.3 and 26.6%+/−24.0, respectively. Plots of the dosimetric parameters versus δvol show wide dispersion, for example R^2 = 0.422 for the D90 plot, but they strongly suggest a downward slope, highlighting the fact that cases with a large difference between VTrus and VCT are more likely to have nonstandard dosimetry than cases with a small difference in these volumes. It is noted that there are cases with δvol close to 0 that have nonstandard post‐plan dosimetry. Conclusion: Our work demonstrates that limiting variation in δvol may reduce but not eliminate the occurrence of nonstandard post‐plans.
SU‐E‐CAMPUS‐T‐04: A Delivery Method of Tumor Tracking Radiation Beam Using a Beam Switching Interface for Irregular Breathing
Authors: Lee S , Hu E , Yu C , Lasio G , Yi B
Published: July 2013

Purpose: Dose rate regulated Tracking (DRRT) is known to be an efficient method which adaptively deliver tracking treatments when patient breathing is irregular. The interface for the dose rate controlling, however, is not commercially available. The Motion Management Interface (MMI, Varian Medical System, CA), which provides beam on/off switching during treatment is available for clinic. This study is to test if delivering the adaptive tumor tracking is feasible for irregular breathing using beam switching with MMI. Methods: Fifty‐five free breathing RPM traces acquired from lung cancer patients are used. The first day RPM traces of the patients are utilized to design preprogrammed tracking MLC patterns, of which periods are intentionally reduced by 20% in order to catch up the variation of patient breathing irregularity in the treatment day. Eligibility criteria for this technique is variation of amplitude and period less than 20%. An algorithm which determines beam on/off every 100 ms by considering the preprogrammed (MLC) positions and current breathing positions is developed. Tracking error and delivery efficiency is calculated by simulating the beam‐switching adaptive tracking from the RPM traces. Results: Breathing patterns of 38 patients (70%) met the eligibility criteria. Tracking errors of all of the cases who meet the criteria are less than 2mm (average 1.4mm) and the average delivery efficiency was 71%. Those of rest of the cases are 1.9 mm and 48%. Conclusions: Beam switching is effectively equivalent to the dose rate regulation for DRRT. Adaptive tracking with beam switching is feasible if patient selection is based on the eligibility criteria. NIH R01CA133539
SU‐F‐500‐03: Modeling Nonstationary Noise and Task‐Based Detectability in CT Images Computed by Filtered Backprojection and Model‐Based Iterative Reconstruction
Authors: Gang G , Stayman J , Zbijewski W , Siewerdsen J
Published: July 2013

Purpose: Nonstationarity of noise poses a major challenge to the modeling and optimization of CT imaging systems, particularly those employing iterative reconstruction. This work presents theoretical models for the spatially varying noise and spatial resolution properties of filtered‐backprojection (FBP) and penalized‐likelihood (PL) reconstruction and provides a method to exploit spatially varying PL regularization to improve task‐based detectability. Methods: A cascaded systems model was adapted to predict the local noise‐power spectrum (NPS) and modulation transfer function (MTF) at each voxel location in FBP by separately calculating the fluence and system gains for each ray passing through the voxel. For PL reconstruction with a quadratic penalty, the implicit function theorem and second‐order Taylor expansion were used to derive the covariance matrix and point spread function, the Fourier transforms of which yield NPS and MTF under assumptions of local stationarity and shift‐invairance, respectively. Detectability index was computed for the non‐prewhitening observer model for simple imaging tasks, including asymmetric tasks corresponding to structures of particular orientation. Spatially‐varying PL regularization maps were designed to control noise and resolution in a manner hypothesized to improve detectability. Results: The NPS in both FBP and PL reconstructions was shown to be anisotropic, spatially‐varying, and object‐dependent, with PL carrying greater spatial variation in MTF due to stronger regularization of projection data in regions of greater attenuation. Complex dependencies were revealed between detectability and the object, spatial location, and regularization. Use of a spatially‐varying PL regularization map improved overall detectability beyond that achievable by constant regularization, with greater advantage observed for asymmetric tasks. Conclusion: The theoretical models successfully predicted local NPS and MTF in both FBP and PL reconstructions. The models demonstrated utility in knowledgeable selection of reconstruction parameters that improve task‐based detectability and provide a valuable guide to the development of CT systems employing conventional and iterative reconstruction methods. National Institutes of Health Grant No.: 2R01‐CA‐112163‐02
SU‐F‐500‐04: Motion Mitigation in Active Scanning Proton Therapy for Lung Cancer: A 4D Monte Carlo Study
Authors: Grassberger C , Dowdell S , Sharp G , Paganetti H
Published: July 2013

Purpose: To study the efficacy of various rescanning techniques and gating in the mitigation of motion interplay effects in hypofractioned lung treatments employing actively scanned protons. Methods: 5 lung cancer patients with varying tumor size (21.1–82.3cc) and motion amplitude (2.9– 30.6mm) were simulated employing 4D Monte Carlo simulations and deformable image registration. We investigated 2 different spot sizes (σ∼12mm and ∼3mm), 3 different rescanning techniques (layered, volumetric, breath‐sampled volumetric) and respiratory gating. Changes in the resulting dose distribution in the target were determined using equivalent uniform dose (EUD), dose homogeneity, minimum and mean dose, in the lung through V5, V20 and mean lung dose (MLD). Results: For patients with motion amplitudes <20mm, rescanning successfully maintains EUD within the target. For the large spot size 2 paintings are sufficient, while at least 6 are required for the small spot size. Rescanning also reduces the dependence on the initial breathing phase. The average variation of the EUD with initial breathing phase is reduced from 4% without rescanning to 2.5% for 2x‐and 0.7% for 10x‐rescanning. Breath‐sampling the timing of the paintings is effective, leading to EUDs that are, on average, 5.3% higher than for the same number of consecutive rescans. Volumetric rescanning is sensitive to synchronization effects with the breathing cycle, reducing its effectiveness in 4 out of 50 scenarios studied, while no such effects were observed for layered rescanning. Rescanning has no significant effect on normal lung V 20, V 5 and MLD, though it reduces maximum lung dose by 2.2Gy(RBE) on average. Gating improves normal lung sparing, reducing V20 and MLD by up to 10% and 7.4Gy(RBE). Conclusion: Rescanning offers the possibility to mitigate interplay effects in the target up to a motion of 20mm in this patient cohort. Gating performs similar or better, additionally significantly sparing lung tissue. This project was supported by the National Cancer Institute Grant No. R01 CA111590
MO‐A‐137‐02: Comparative Efficacy of Image‐Guided Adaptive Treatment Strategies for Prostate Radiation Therapy Via Virtual Clinical Trials
Authors: Sharma M , Williamson J , Siebers J
Published: July 2013

Purpose: To determine potential dosimetric benefits of image guided adaptive radiation therapy treatment (IGART) strategies for intermediate risk prostate cancer via automated virtual clinical trials (VCTs). Materials and Methods: A 19 patient cohort with 8‐13 CT images was used to compare different IGART strategies. The IMRT prescription was 46 Gy/23 fractions to the prostate and seminal‐vesicle PTVs, followed by a 40 Gy/20 fractions prostate boost. For each patient, daily IGART imaging was simulated by random selection from available images. The VCTs simulated three different IGART‐IMRT strategies; (A0) initial planning only with 5 mm PTV margins; (A1) daily re‐planning without considering prior dose; and (A2) online daily re‐planning for each fraction considering prior dose obtained via deformable dose mapping (A1 and A2, no PTV margin). For each strategy, daily dose was deformably mapped using Demons‐based displacement vector fields and accumulated to estimate the treatment dose. Strategies were compared via dosimetric adherence to constraints (CTV D98=86.4, D2<94.6Gy), and objectives (CTV D98<86.4, D2<91.2Gy; bladder D2<90, D20<70, D30<56, D50<39, EUD=0 Gy; and rectum D2<83, D20<70, D30<56, D50<39, EUD=0 Gy). Results: A0 had larger doses to 20, 30, and 50% rectal (30±20%) and bladder (40±20%) volumes than A1 and A2 (p<0.001). Rectal and bladder D2s were also respectively higher in A0 by (15±13%) and (24±14%) (p=0.002 and 0.00001 respectively). Comparing A1 and A2, no significant differences were found in prostate D98 (p=0.4) or bladder D2 (p=0.33). Significant differences were found for the rectum (D5,A2>D5A1, p=0.02) . Conclusion: IGART utilizing daily re‐planning (A1 and A2) has dosimetric advantages over conventional IMRT for critical structures, particularly high‐dose regions, without compromising PTV coverage. Due to inherent deformation vector field inaccuracies, daily re‐planning based on prior dose (A2) showed poor rectal sparing than A1. NIH grant P01 CA 116602 and Philips Medical Systems
MO‐A‐137‐04: Robustness of Bone Marrow Sparing in Intensity Modulated Proton Therapy for Cervical Cancer
Authors: Dinges E , Wang D
Published: July 2013

Purpose: To determine the effectiveness of pelvic bone marrow sparing by utilizing intensity modulated proton therapy (IMPT) in the treatment of cervical cancer, in comparison to that of intensity modulated photon therapy (IMXT); and to investigate the robustness of the bone marrow sparing by IMPT under range uncertainty and patient setup uncertainty. Methods: 3‐field IMPT was planned for five enrolled patients. DVH objectives for PTV and organs‐at‐risk (OAR) aimed to give 45 Gy to the tumor in 25 fractions, matching those of the IMXT plan delivered clinically. The percentage volumes of bone marrow receiving 10 Gy and 20 Gy were set to be reduced in IMPT compared with IMXT. The dose from the IMPT plan was then recalculated in uncertainty scenarios which were combinations of systematic 3% density errors and uniformly random patient setup errors of (0.6cm, 0.6cm, 0.6cm). The robustness of target coverage and bone marrow sparing through the whole course of 25 fractions was then analyzed. Results: In the static scenario, the IMPT plan achieved the same or better PTV coverage and OAR sparing compared to IMXT, and reduced the percentage volume of bone marrow receiving 15 Gy or larger dose (V15Gy) to 32.3% from 60.0% on average. Robustness analysis showed that proper CTV coverage is preserved over the whole course of treatment with the presumed range and positioning errors. The reduction of bone marrow dose is also statistically significant and robust under those uncertainties, with a minimum reduction of V15Gy to 39.9% from 60.0%. Conclusion: IMPT can significantly reduce the volume of active bone marrow receiving low dose radiation, therefore potentially decreasing hematologic toxicity in concurrent chemoradiation therapy for cervical cancer. Bone marrow sparing by IMPT is robust in the context of range and positioning uncertainties.
MO‐A‐137‐06: A Stochastic Optimization Approach to Adaptive Lung Radiation Therapy Treatment Planning
Authors: Long T , Matuszak M , Schipper M , Epelman M , Kong F , Ten Haken R , Romeijn E
Published: July 2013

Purpose: We have demonstrated that the ratio between a lung cancer patient's TGFβ1 level two weeks into treatment versus pre‐treatment is a predictive biomarker for radiation induced lung toxicity (RILT). Instead of adapting to this new information only when the data is available, we present a stochastic optimization model that can explicitly incorporate this future knowledge into adaptive lung radiation therapy treatment planning. Methods: A two‐stage stochastic treatment plan optimization model is developed that accommodates knowledge of a patient's predisposition to RILT that would be obtained during treatment. The goal of the stochastic model is to maximize the population probability of local tumor control (LTC) after 2 years while controlling the probability of RILT. Two adaptive strategies are considered: (1) bounding the expected proportion of the entire population that will experience RILT, and (2) bounding the probability that each individual patient will experience RILT. These strategies were compared to a non‐adaptive treatment planning strategy that uses a simple bound on the mean lung dose to control the probability of RILT. Results: This technique is applied to lung cancer cases that are treated in daily fractions over a six‐week period. The tradeoffs between the probability of RILT and LTC are observed for each strategy. Both adaptive strategies dominate (are always better than) the non‐adaptive treatment plans in the worst‐case sense (i.e., highest probability among all treated patients), while adaptive strategy (1) dominates it in the population sense in terms of the tradeoff between probability of RILT and expected probability of LTC. Conclusion: By incorporating future knowledge into a two‐stage stochastic IMRT treatment planning model, superior adaptive treatment plans can be obtained that improve both population and worst‐case outcomes for patients. In addition, this modeling paradigm provides treatment planners a tool to help personalize treatment plans for individual patients. Troy Long is on a NSF Graduate Research Fellowship. Data collection was assisted by R01CA142840 grant.
MO‐A‐137‐09: Reduced Order Prioritized Optimization for IMRT Planning
Authors: Rivera L , Yorke E , Kowalski A , Radke R , Jackson A
Published: July 2013

Purpose: A prioritized optimization scheme is introduced to improve the previously proposed Reduced Order Constrained Optimization (ROCO) method for generating clinically competitive IMRT plans. The improvement eliminates manual repetition of the ROCO constrained optimization stage to automatically produce an IMRT plan with target coverage equivalent to and organ‐at‐risk (OAR) doses lower than those in the original plan. Methods: The prioritized optimization consists of three stages. The first is creation of a baseline ROCO plan with initial constraints for all the OARs based on the clinical protocol and the planner's expertise. This process involves constrained optimization over a low‐dimensional parameter space and is able to directly satisfy requested dose limits. In the second stage, certain critical OAR dose constraints are selected to be further reduced, and the constrained optimization phase of ROCO is re‐applied. These constraints are reduced simultaneously by a constant dose until PTV coverage metrics (D95) are violated (maintaining all other constraints from the previous stage). The third stage sequentially pushes each individual OAR constraint on a priority list until PTV D95s are violated (maintaining all other constraints from previous stages). Results: The prioritized optimization scheme was tested on the simulation image sets of 10 head‐and‐neck patients. The prioritized ROCO scheme automatically improved OAR protection with equivalent target coverage (i.e., 6.5% average lower dose in cord, 7.7% in brainstem, 4.4% in the left parotid and 5.4% in the right parotid) automatically in comparison to the first‐stage plans. While 26 minutes of constrained optimizations on average were required to obtain these superior plans, no human interaction is involved until plan evaluation. Conclusion: After initial site‐and patient‐specific decisions by the planner, the proposed prioritized optimization method runs automatically and produces superior plans than the original ROCO method, avoiding intermediate manual evaluation. This publication was supported in part by Grant Number 1R01CA148876‐03 from the National Cancer Institute (NCI). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Cancer Institute, National Institutes of Health.
MO‐C‐500‐00: President's Symposium: Introduction S Donaldson*, RSNA President
Authors: Hricak H , Jaffray D , Hazle J
Published: July 2013

Unprecedented advances in molecular biology, biomedical imaging and information technology have opened up new avenues towards precision medicine, in which treatments are and will be tailored to specific diagnoses and their unique manifestations in individual patients. In oncology, the application of precision medicine offers tremendous hopes for improving outcomes but it also poses great challenges. Cancer is fundamentally a disease of genetic missteps or misregulation. Cancers are genetically heterogeneous, undergoing constant evolution (or Darwinian Dynamics) as they progress. Not only do biological features differ within primary tumors, but in up to 50% of cancers, metastases de‐differentiate and demonstrate different biological features in different matrices (e.g., bone vs. liver vs. lung). Tissue and serum assays alone cannot sufficiently capture the spatial and temporal diversity of tumor biology. Precise, spatially localized molecularly‐based evaluation of disease that incorporates genomics is essential. Conventional anatomic imaging will continue to be indispensible for localizing cancer and determining where it has spread for both diagnostic and radiation therapy purposes. However, as precision medicine takes hold, the role of imaging in evaluating tumor biology will become even more important. Molecular imaging and the new field of radiogenomics holds great promise for advancing our ability to image tumor biology. Further, the relatively recent enhanced understanding of the human genome is driving transformational changes in cancer research. As we will see from the first two talks of this session, genomics will be the driving factor in cancer research for the foreseeable future. As medical physicists we must consider how that impacts our science ‐ ‐‐which is the application of physics principles to biology and medicine. While we have traditionally focused on rather narrow aspects of physics related to radiation oncology and biomedical imaging, we must ask ourselves how we should evolve in these areas to address the cancer research challenges of the future and “Is it time for us to embrace other aspects of medical physics?” Further, in order for the next generation of medical physicists to participate in cancer research, much less have a significant impact, we must at a minimum consider new dimensions to our educational programs. For example, how can we expect to participate in contemporary cancer research if we have such a limited understanding of molecular genetics and cancer biology that we can' tt communicate effectively with our scientific peers?In this session we will give an overview of precision and genomic medicine with the impact on diagnostic imaging (Hricak), how this will impact the practice of radiation oncology (Jaffray) a general perspective on how we should be addressing issues of research and education in this new era (Hazle).
MO‐D‐105‐02: Veteran Health Administration : Radiation Oncology Quality and Safety Initiative (VHA‐ROQSI)
Authors: Kapoor R , Palta J , Hagan M
Published: July 2013

Purpose: The overall goal of VHA‐ROQSI is to monitor quality, safety, and effectiveness of radiotherapy within VHA. The electronic infrastructure developed to achieve these objectives can serve as a model for the radiation oncology community at large. Method and Material: The VHA‐ROQSI is an initiative of the VHAs National Radiation Oncology Program office with an objective of electronically collecting and aggregating data to assess quality and safety of radiation treatment delivery and determine disease site‐specific outcomes. The data collected will include; information on radiotherapy planning, delivery equipment, services provided patient volume, and quality assurance activities at each facility, calibration, accreditation and credentialing status of each facility. The integrated infrastructure will facilitate a rapid Web‐based proactive peer review of all complex treatment plans and it will allow each facility to report adverse events and near miss information on patients for review by radiation oncology domain experts. The de‐identified outcome data on patients will be abstracted directly from the hospital information system for population‐based outcome analysis. Results: We have designed an electronic infrastructure that minimizes key strokes and multiple entries of redundant data by end users to accomplish each one of the aforementioned objectives. The prototypes of various modules for electronic data collection have been developed and are in beta testing. Once completed, the integrated system will facilitate peer review of complex treatment plans, collection of data elements for treatment quality and outcome assessment, and tracking of adverse events and near misses on patient treatments. Conclusion: The VHA‐ROQSI overcomes the challenge of submitting redundant data to disparate sources. This electronic infrastructure will circumvent the need for separate registries for outcome, quality, and safety tracking under development by various stakeholders at the present time. Disclosure: Rishabh Kapoor: Stocks: TSG Innovations Inc.
MO‐D‐105‐04: A Nation‐Wide Three Level Audit Service ‐ the Australian Experience
Authors: Lehmann J , Kenny J , Lye J , Dunn L , Williams I
Published: July 2013

In February 2011, the Australian Government launched the Australian Clinical Dosimetry Service (ACDS) a three year trial of an independent dosimetric auditing service for Australia. The ACDS has designed and implemented a three level audit program, each succeeding level with a more complex and challenging geometry. It is similar to other audit programs internationally, but is unique in its coverage, national participation (voluntary and free service), audit design and final review process. The ACDS has utilised existing audit protocols, adapted and expanded components of those as needed. The final protocols have been rigorously tested inhouse. The Level I audit is a remotely conducted point dose verification under reference conditions. It was introduced using TLD detectors and has been transitioned to OSLD, following validation of the OSLD technology and setup. By August 2013, each clinical linac in Australia will have received at least one Level I photon beam audit. The Level II audit investigates treatment planning and delivery using a synthetic CT data set and planar array measurements in different geometries. It tests the components treatment planning and linac dose delivery independent of the CT imaging.The Level III audit is an end‐to‐end test. An anthropomorphic phantom is taken through the complete chain of procedures experienced by a patient in a radiotherapy facility. In their first implementation the ACDS Level II and III audits, which are performed by an onsite team, investigate inhomogeneities, wedges and asymmetric fields. Additionally, the Level Ib has been implemented as an onsite reference geometry audit. It uses the facility's watertank and otherwise independent equipment to verify dose delivery for all beams under reference conditions. This audit has been very popular for new installations. Audit design philosophy, tolerance levels, results, lessons learned and future directions (intensity modulated/rotational therapy, flattening‐filter free beams, SRS) will be reviewed and discussed. The Australian Clinical Dosimetry Service is a joint initiative between the Australian Department of Health and Ageing and the Australian Radiation Protection and Nuclear Safety Agency
MO‐D‐105‐05: A Novel Web‐Based Tool for Quantification of VMAT/IMRT Treatment Plan Quality
Authors: Fan M , DeBlois F , Sultanem K , Stroian G
Published: July 2013

Purpose: To develop a novel web‐based tool for VMAT/IMRT treatment plan evaluation and to design a unique plan Quality Index (QI) quantifier to aid in decision‐making for SRS, SBRT, and ENT treatment planning and evaluationMethods: A high level Python web‐framework, Django, is used to develop the web application. Django uses an SQL‐like database for data storage and retrieval. The front‐end of the web application is styled with CSS and written in HTML. Tumor site dependent evaluation templates for SRS, SBRT and ENT plans are created in collaboration with physicians at our institution. Previously approved treatment plans are imported into the web application to populate the database for analysis. With physician feedback, retrospective treatment plans are subjected to scoring algorithms to develop a plan QI. Results: The web tool is currently deployed internally at our institution for VMAT treatment planners. The web site also serves as a portal for site‐specific treatment planning instructions. Specific plan details are imported to an SQL‐like database when treatment plans are pushed to the tool. The electronic nature of the database allows new retrospective studies to be easily conducted. A site specific QI is developed to quantify SRS, SBRT, and ENT plan quality. When the tool is used, QIs are generated automatically and a histogram of site specific QIs is produced. This information can then be used to evaluate the best candidate plan for treatment approval. The database can be used to query legacy plan specific details in order to extract the optimization objectives that best fit the anatomy and prescription doses from a new planning case. Conclusion: The full implementation of the tool aims to standardize and unify the planning and evaluation of IMRT/VMAT techniques. Validation of the QI robustness will include correlation with clinical outcome and inter‐institutional case studies.
MO‐D‐108‐02: A Secondary Monitor Unit Calculation Algorithm Using Superposition of Symmetric, Open Fields for IMRT and VMAT Treatment Plans
Authors: Watts A , Gibbons J , Chu C
Published: July 2013

Purpose: To perform a secondary dose calculation for an IMRT or VMAT plan to a point on or off axis within 2% using open field data. Methods: The calculation is performed by subdividing dose into the contributions from each opposing leaf pair for a given MLC configuration. Leaf pair dose is determined by drawing four rectangular fields based on leaf positions that are symmetric about the point of calculation. Field dose is determined using isocentric monitor unit calculation formalism with open field data. Superposition of these fields yields the dose from the leaf pair to the point. VMAT plans are approximated by a static MLC configuration at four degree intervals. The algorithm requires standard open field data (e.g., Scps, TPRs), and the MLC control point information. These calculations were done with additional measured small field output factors down to a 1.2 cm2. Algorithm doses were compared with homogeneous and heterogeneous Pinnacle calculations of a series of prostate, head and neck, and chest wall treatment plans. For each treatment plan the calculation point was taken as the isocenter and/or the center of the PTV. Delivery techniques included SMLC‐IMRT and VMAT. Results: Good agreement was obtained between doses calculated by the algorithm and the Pinnacle Treatment Planning System. For homogeneous cases, the total calculated doses were within 2% for all patient plans. Individual beam errors were as high as 7.8% with an average of 2.8%. Larger errors were associated for beam segments with leaf positions very near the calculation point. Larger errors were also found for heterogeneous calculations, where a simple ratio of TPR correction factor was utilized in the algorithm. Conclusion: Results demonstrate that clinically acceptable agreement is obtained using this method. Further improvement could be made with more accurate heterogeneity correction factors and/or incorporation of MLC leaf end effects. This work was supported in part by a research agreement with Oncology Data Systems, Inc.