bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐F‐BRD‐04: Development of a Secondary MU Calculation Tool for An Integrated MR‐LINAC
Authors: Chen G , Li X
Published: July 2014

Purpose:

To develop a fast secondary MU calculation tool for an integrated MR‐Linac, an emerging technology for delivering image‐guided on‐line adaptive therapy.

Methods:

A software tool was developed to implement a modified Clarkson integration algorithm for point‐dose calculation, considering the dosimtric effect of a magnetic field. A research planning system, considering the presence of a perpendicular 1.5 T magnetic field, was used to extract the beam data (e.g., depth doses and beam profiles) required for the MU calculation in homogeneous phantom of 60×60×40 cm3 for a prototype of MR‐Linac integrating a 1.5 T MR scanner with 6MV photon beams. These dosimetric data may be replaced with those to be collected during the commissioning measurement of the MR‐Linac.

Results:

The presence of the magnetic field resulted in noticeable changes including (1) shifts in beam profiles for small fields (< 2×2 cm2), and (2) changes in central‐axis doses when one of field edges is < 2 cm away from the central axis. For example, the maximum change in central‐axis dose was up to 8% for one of the field borders with a distance away from the central axis of <1 cm. These changes are relevant for the MU calculation particularly for IMRT and VMAT, where most of segments are small. These magnetic field affected beam profiles and depth doses were included in the software tool. The MU calculations from the software tool for selective representative plans were found to agree with those from the research planning system within 10%.

Conclusion:

The presence of a perpendicular magnetic field results in noticeable changes in beam profiles and depth doses for small fields. These changes are included in the secondary MU calc33u3lation to be used as a redundancy check for an integrated MR‐Linac.
SU‐F‐BRD‐05: Dosimetric Comparison of Protocol‐Based SBRT Lung Treatment Modalities: Statistically Significant VMAT Advantages Over Fixed‐ Beam IMRT
Authors: Best R , Harrell A , Geesey C , Libby B , Wijesooriya K
Published: July 2014

Purpose:

The purpose of this study is to inter‐compare and find statistically significant differences between flattened field fixed‐beam (FB) IMRT with flattening‐filter free (FFF) volumetric modulated arc therapy (VMAT) for stereotactic body radiation therapy SBRT.

Methods:

SBRT plans using FB IMRT and FFF VMAT were generated for fifteen SBRT lung patients using 6 MV beams. For each patient, both IMRT and VMAT plans were created for comparison. Plans were generated utilizing RTOG 0915 (peripheral, 10 patients) and RTOG 0813 (medial, 5 patients) lung protocols. Target dose, critical structure dose, and treatment time were compared and tested for statistical significance. Parameters of interest included prescription isodose surface coverage, target dose heterogeneity, high dose spillage (location and volume), low dose spillage (location and volume), lung dose spillage, and critical structure maximum‐ and volumetric‐dose limits.

Results:

For all criteria, we found equivalent or higher conformality with VMAT plans as well as reduced critical structure doses. Several differences passed a Student's t‐test of significance: VMAT reduced the high dose spillage, evaluated with conformality index (CI), by an average of 9.4%±15.1% (p=0.030) compared to IMRT. VMAT plans reduced the lung volume receiving 20 Gy by 16.2%±15.0% (p=0.016) compared with IMRT. For the RTOG 0915 peripheral lesions, the volumes of lung receiving 12.4 Gy and 11.6 Gy were reduced by 27.0%±13.8% and 27.5%±12.6% (for both, p<0.001) in VMAT plans. Of the 26 protocol pass/fail criteria, VMAT plans were able to achieve an average of 0.2±0.7 (p=0.026) more constraints than the IMRT plans.

Conclusions:

FFF VMAT has dosimetric advantages over fixed beam IMRT for lung SBRT. Significant advantages included increased dose conformity, and reduced organs‐at‐risk doses. The overall improvements in terms of protocol pass/fail criteria were more modest and will require more patient data to establish difference trends of more statistical significance.
SU‐F‐BRD‐06: Dosimetric Cost of a GTV Margin for Simultaneous Integrated Intra‐ Prostatic Boost Treatments
Authors: Studenski M , Abramowitz M , Dogan N , Pollack A
Published: July 2014

Purpose:

Quantify the dosimetric cost for a margin around the MRI‐defined high risk GTV for simultaneous integrated intra‐prostatic boosts (SIIB) treated with RapidArc.

Methods:

For external beam radiotherapy of the prostate, a 3‐7 mm PTV margin is typically used to account for setup and intra‐fraction uncertainties after adjusting for inter‐fraction motion. On the other hand, our current paradigm is to treat the MRI‐defined high risk GTV with no margin. In this work, 11 patients treated SIIB (7 post‐prostatectomy, 4 intact prostate) with RapidArc were re‐planned with 1‐5 mm margins around the GTV to quantify dosimetric effects. Two 358 degree, 10 MV RapidArcs were used to deliver 68 Gy (76.5 Gy boost) to the post‐prostatectomy patients and 80 Gy (86 Gy boost) to the intact prostates. Paired, two tail t‐tests were used to determine if there were any significant differences (p<0.05) in the total MUs and dosimetric parameters used to evaluate rectum, bladder, and PTV dose with and without margin.

Results:

The average GTV volume without margin was 8.1cc (2.8% of the PTV volume) while the average GTV volume with a 5 mm margin was 20.1cc (9.0% of the PTV volume). GTV volumes ranged from 0.2% of the PTV volume up to 33.0%. Despite these changes in volume, the only statistical difference was found for the rectal V65 Gy with a 5 mm margin (18.6% vs. 19.4%; p‐value = 0.026) when all patients were considered as a single group. No difference was found when analyzed as two groups. The rectum V40Gy, bladder V40Gy and V65Gy, PTV Dmax and D95% or the total MUs did not show any significant difference for any margin.

Conclusion:

A 4 mm margin on the high risk GTV is possible with no statistically significant change in dosimetry or total MUs. Further work will assess the appropriate margin required for intra‐prostatic boosts.
SU‐F‐BRD‐07: Empirical Derivation of Site‐Specific Margin Formulas
Authors: Conroy L , Quirk S , Smith W
Published: July 2014

Purpose:

To empirically derive margin formulas from existing clinical radiotherapy plans accounting for respiratory motion and setup uncertainties.

Methods:

We simulated realistic treatment scenarios, including respiratory motion and setup errors. Individual probability density functions (PDF) from respiratory data were used to simulate respiratory motion. Random (σ) and systematic (Σ) setup errors were modeled as Gaussian distributions. One‐dimensional dose profiles were extracted from existing radiotherapy plans and convolved with respiratory PDFs and random error distributions to produce blurred dose profiles. Each blurred dose profile was then shifted 1000 times by randomly sampling the simulated systematic error distribution. Margins were determined from the distance between the simulated treatment and the original 95% isodose level. An equation was fit for each (σ, Σ) combination to derive margin formulas for 90% of the population receiving 95% dose. This methodology can be applied to different tumor sites. Here, dose profiles were extracted from partial breast 3DCRT plans in the anterior‐posterior (AP) and superior‐inferior (SI) directions. Respiratory motion data was from healthy volunteers, and a clinically relevant range of random and systematic setup errors (standard deviations 1 – 4 mm) was determined from the literature.

Results:

The PBI margin formulas in the AP and SI directions for 95% dose coverage for 90% of the population were very similar: M= 0.68σ + 1.54Σ and M= 0.72σ + 1.50Σ, respectively. Systematic setup errors had the largest influence on required margin size, whereas realistic respiratory amplitude had minimal impact. The derived formulas resulted in a smaller systematic component than commonly‐used theoretical margin recipes.

Conclusion:

We have demonstrated a method to derive empirical margin formulas from existing patient radiotherapy plans, incorporating realistic respiratory motion and appropriate ranges of random and systematic error. Site‐specific margin formulas may be better suited to patient populations than theoretically derived, ideal geometry general margin formulas.
SU‐F‐BRD‐08: Guaranteed Epsilon‐Optimal Treatment Plans with Minimum Number of Beams for SBRT Using RayStation
Authors: Yarmand H , Winey B , Craft D
Published: July 2014

Purpose:

To efficiently find quality‐guaranteed treatment plans with the minimum number of beams for stereotactic body radiation therapy using RayStation.

Methods:

For a pre‐specified pool of candidate beams we use RayStation (a treatment planning software for clinical use) to identify the deliverable plan which uses all the beams with the minimum dose to organs at risk (OARs) and dose to the tumor and other structures in specified ranges. Then use the dose matrix information for the generated apertures from RayStation to solve a linear program to find the ideal plan with the same objective and constraints allowing use of all beams. Finally we solve a mixed integer programming formulation of the beam angle optimization problem (BAO) with the objective of minimizing the number of beams while remaining in a predetermined epsilon‐optimality of the ideal plan with respect to the dose to OARs. Since the treatment plan optimization is a multicriteria optimization problem, the planner can exploit the multicriteria optimization capability of RayStation to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing quality. For the numerical experiments two liver cases and one lung case with 33 non‐coplanar beams are considered.

Results:

The ideal plan uses an impractically large number of beams. The proposed technique reduces the number of beams to the range of practical application (5 to 9 beams) while remaining in the epsilon‐optimal range of 1% to 5% optimality gap.

Conclusion:

The proposed method can be integrated into a general algorithm for fast navigation of the ideal dose distribution Pareto surface and finding the treatment plan with the minimum number of beams, which corresponds to the delivery time, in epsilon‐optimality range of the desired ideal plan.

The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center and partially by RaySearch Laboratories.
SU‐F‐BRD‐09: Is It Sufficient to Use Only Low Density Tissue‐Margin to Compensate Inter‐Fractionation Setup Uncertainties in Lung Treatment?
Authors: Nie K , Qin S , Yue N , Chen T , Millevoi R , Guo J
Published: July 2014

Purpose:

In lung radiation treatment, PTV is formed with a margin around GTV (or CTV/ITV). Although GTV is most likely of water equivalent density, the PTV margin may be formed with the surrounding low‐density tissues, which may lead to unreal dosimetric plan. This study is to evaluate whether the concern of dose calculation inside the PTV with only low density margin could be justified in lung treatment.

Methods:

Three SBRT cases were analyzed. The PTV from the original plan (Plan‐O) was created with a 5–10 mm margin outside the ITV to incorporate setup errors and all mobility from 10 respiratory phases. Test plans were generated with the GTV shifted to the PTV edge to simulate the extreme situations with maximum setup uncertainties. Two representative positions as the very posterior‐superior (Plan‐PS) and anterior‐inferior (Plan‐AI) edge were considered. The virtual GTV was assigned a density of 1.0 g.cm−3 and surrounding lung, including the PTV margin, was defined as 0.25 g.cm−3. Also, additional plan with a 1mm tissue‐margin instead of full lung‐margin was created to evaluate whether a composite‐margin (Plan‐Comp) has a better approximation for dose calculation. All plans were generated on the average CT using Analytical Anisotropic Algorithm with heterogeneity correction on and all planning parameters/monitor unites remained unchanged. DVH analyses were performed for comparisons.

Results:

Despite the non‐static dose distribution, the high‐dose region synchronized with tumor positions. This might due to scatter conditions as greater doses were absorbed in the solid‐tumor than in the surrounding low‐density lungtissue. However, it still showed missing target coverage in general. Certain level of composite‐margin might give better approximation for the dosecalculation.

Conclusion:

Our exploratory results suggest that with the lungmargin only, the planning dose of PTV might overestimate the coverage of the target during treatment. The significance of this overestimation might warrant further investigation.
SU‐F‐BRD‐10: Lung IMRT Planning Using Standardized Beam Bouquet Templates
Authors: Yuan L , Wu Q J. , Yin F , Ge Y
Published: July 2014

Purpose:

We investigate the feasibility of choosing from a small set of standardized templates of beam bouquets (i.e., entire beam configuration settings) for lung IMRT planning to improve planning efficiency and quality consistency, and also to facilitate automated planning.

Methods:

A set of beam bouquet templates is determined by learning from the beam angle settings in 60 clinical lung IMRT plans. A k‐medoids cluster analysis method is used to classify the beam angle configuration into clusters. The value of the average silhouette width is used to determine the ideal number of clusters. The beam arrangements in each medoid of the resulting clusters are taken as the standardized beam bouquet for the cluster, with the corresponding case taken as the reference case. The resulting set of beam bouquet templates was used to re‐plan 20 cases randomly selected from the database and the dosimetric quality of the plans was evaluated against the corresponding clinical plans by a paired t‐test. The template for each test case was manually selected by a planner based on the match between the test and reference cases.

Results:

The dosimetric parameters (mean±S.D. in percentage of prescription dose) of the plans using 6 beam bouquet templates and those of the clinical plans, respectively, and the p‐values (in parenthesis) are: lung Dmean: 18.8±7.0, 19.2±7.0 (0.28), esophagus Dmean: 32.0±16.3, 34.4±17.9 (0.01), heart Dmean: 19.2±16.5, 19.4±16.6 (0.74), spinal cord D2%: 47.7±18.8, 52.0±20.3 (0.01), PTV dose homogeneity (D2%‐D99%): 17.1±15.4, 20.7±12.2 (0.03). The esophagus Dmean, cord D02 and PTV dose homogeneity are statistically better in the plans using the standardized templates, but the improvements (<5%) may not be clinically significant. The other dosimetric parameters are not statistically different.

Conclusion:

It's feasible to use a small number of standardized beam bouquet templates (e.g. 6) to generate plans with quality comparable to that of clinical plans.

Partially supported by NIH/NCI under grant #R21CA161389 and a master research grant by Varian Medical System.
SU‐F‐BRD‐11: Prediction of Dosimetric Endpoints From Patient Geometry Using Neural Nets
Authors: O' Connell D , Chow P , Agazaryan N , Jani S , Low D , Lamb J
Published: July 2014

Purpose:

The previously‐published overlap volume histogram (OVH) technique lends itself naturally to prediction of the dose received by a given volume of tissue (e.g. D90) in intensity‐modulated radiotherapy (IMRT) treatment plans. Here we extend the OVH technique using artificial neural networks in order to predict the volume of tissue receiving a given dose (e.g. V90) in both prostate IMRT and conventional breast radiotherapy.

Methods:

Twenty‐nine prostate treatment plans and forty‐three breast treatment plans were analyzed. The spatial relationships between the prostate and rectum and between the breast and ipsilateral lung were characterized using OVHs. The OVH is a cumulative histogram representing the fractional volume of the risk organ overlapped by a series of isotropic expansions of the planning target volume (PTV). Seven cases were identified as outliers and replanned. OVH points were used as inputs to a one hidden layer feed forward artificial neural network with quality parameters of the corresponding plan, such as the rectum V50, as targets. A 3‐fold cross‐validation was used to estimate the prediction error.

Results:

The root mean square (RMS) error between the predicted rectum V50s and the planned values was 2.3, which was 35% of the standard deviation of V50 for the twenty‐nine plans. The RMS error of prediction of V20 of the ipsilateral lung in breast cases was 3.9, which was 90% of the standard deviation of the V20 values in the breast plan database.

Conclusion:

This study demonstrates that artificial neural nets can be used to extend the OVH technique to predict dosimetric endpoints taking the form of a volume receiving a given dose, rather than the minimum dose received by a given volume. Prediction of ipsilateral lung dose in breast radiotherapy using the OVH technique remains a work in progress.
SU‐F‐BRD‐12: Prostate Cancer Dose Escalation Including Lymph Nodes: A Planning Study
Authors: Wu Q , Song H , Salama J
Published: July 2014

Purpose:

Dose escalation improves local control for prostate cancer but not overall survival (OS), only systemic therapy such as ADT can improve OS. One explanation is that occult diseases in the lymph nodes (LNs) are either not treated, or treated at inadequate level. This study explores dose escalation using IMRT with reduced margins.

Methods:

14 previously treated patients were selected. The CTV1 includes prostate and seminal vesicles, and CTV2 includes pelvic LNs. OARs include rectum, bladder, small bowel, femoral heads, and penile bulb. Reference plan (RP) was designed to follow RTOG‐0521, with 10 mm margin for PTVs. In phase I, both PTVs are prescribed to 1.8 Gy/fx for 26 fractions. In phase II, PTV1 is boosted for another 16 fractions. In dose escalation plans (DEPs), margins from 0 to 10 mm are added to form PTVs, which are prescribed to 1.8 Gy/fx for 42 fractions. 95% of PTVs are covered by prescription.

Results:

The CTV1/CTV2 has volume of 63±20 and 415±132 cc. To keep bladder Dmean same as in RP, margin must be ≤6 mm in DEPs. Similarly, margin needs to be ≤7 mm for rectum Dmean. For small bowel, even at margin of 0, Dmean and EUDs on DEPs are higher than RP, because RP was also IMRT. Instead, QUANTEC criteria of “45Gy volume<195cc” was adopted. 6/14 patients fail this criteria in RP. For the remaining 8 patients, margins of ≤7(3) mm are necessary for 6(2) patients, respectively.

Conclusion:

To escalate LNs to full dose, planning margins need to be ≤6 mm to achieve same tolerance for rectum and bladder. A large variation in patient anatomy exists for small bowel and dose escalation was possible for half of patients with ≤6 mm margin. Investigations of whether and how ≤6 mm margin can be achieved through image guidance are needed.
SU‐F‐BRD‐13: Quantum Annealing Applied to IMRT Beamlet Intensity Optimization
Authors: Nazareth D , Spaans J
Published: July 2014

Purpose:

We report on the first application of quantum annealing (QA) to the process of beamlet intensity optimization for IMRT. QA is a new technology, which employs novel hardware and software techniques to address various discrete optimization problems in many fields.

Methods:

We apply the D‐Wave Inc. proprietary hardware, which natively exploits quantum mechanical effects for improved optimization. The new QA algorithm, running on this hardware, is most similar to simulated annealing, but relies on natural processes to directly minimize the free energy of a system. A simple quantum system is slowly evolved into a classical system, representing the objective function. To apply QA to IMRT‐type optimization, two prostate cases were considered. A reduced number of beamlets were employed, due to the current QA hardware limitation of ∼500 binary variables. The beamlet dose matrices were computed using CERR, and an objective function was defined based on typical clinical constraints, including dose‐volume objectives. The objective function was discretized, and the QA method was compared to two standard optimization Methods: simulated annealing and Tabu search, run on a conventional computing cluster.

Results:

Based on several runs, the average final objective function value achieved by the QA was 16.9 for the first patient, compared with 10.0 for Tabu and 6.7 for the SA. For the second patient, the values were 70.7 for the QA, 120.0 for Tabu, and 22.9 for the SA. The QA algorithm required 27–38% of the time required by the other two methods.

Conclusion:

In terms of objective function value, the QA performance was similar to Tabu but less effective than the SA. However, its speed was 3–4 times faster than the other two methods. This initial experiment suggests that QA‐based heuristics may offer significant speedup over conventional clinical optimization methods, as quantum annealing hardware scales to larger sizes.
SU‐F‐BRD‐14: The Effect of Radiation‐Induced Esophageal Swelling On Dose‐Volume Histograms
Authors: Niedzielski J , Yang J , Martel M , Tucker S , Briere T , Gomez D
Published: July 2014

Purpose:

Acute esophagitis results in esophageal swelling. Here we evaluate the effect of this response on DVH metrics calculated throughout the course of radiation therapy.

Methods:

Twenty‐nine NSCLC patients were identified who received weekly CT imaging, and varying esophagitis grades (11 grade0 patients, 12 grade2 patients, 6 grade3 patients), using CTCAE scoring criteria. Deformable image registration was used to map the planning esophagus contour to the weekly CT images. Treatment plans were recalculated on each weekly 4DCT and DVH metrics for the esophagus were compared to the delivered treatment plan. DVH metrics were also extracted for esophagus planning‐at‐risk volumes (PRV) with 1–3mm uniform expansions.

Results:

The esophagus V50 increased as the treatment progressed by 2.3±0.7cc and 9.0±1.1cc, for the grade 0 and grade 2/3 patients, respectively. The mean esophageal dose (MED) increased by 3.5±0.9Gy, and 8.0±1.1Gy for the grade 0 and grade 2/3 patients, respectively. In some cases where the planned V50 was similar, it remained the same at the end of treatment for grade 0 cases, but increased for higher grade cases. These apparent changes in delivered dose, as expressed by the DVH, are mostly attributed to volume changes in the regions of esophagitis. In addition, portions of the esophagus of some patients moved into highdose regions. The 2mm PRV was able to account for these differences in all but 1 of the 18 G2/3 patients. The 1mm PRV produced the closest DVH metrics calculated from the average weekly plans compared to the true treatment plan.

Conclusion:

Esophagus radiation response affects DVH parameters throughout treatment, especially patients with high toxicity. This effect must be considered when comparing DVHs calculated using daily IGRT CT images with those from the original planning CT (e.g. for adaptive planning). Adding a margin to the esophagus can account for variation in DVH metrics.
SU‐F‐BRD‐15: The Impact of Dose Calculation Algorithm and Hounsfield Units Conversion Tables On Plan Dosimetry for Lung SBRT
Authors: Kuo L , Yorke E , Lim S , Mechalakos J , Rimner A
Published: July 2014

Purpose:

To assess dosimetric differences in IMRT lung stereotactic body radiotherapy (SBRT) plans calculated with Varian AAA and Acuros (AXB) and with vendor‐supplied (V) versus in‐house (IH) measured Hounsfield units (HU) to mass and HU to electron density conversion tables.

Methods:

In‐house conversion tables were measured using Gammex 472 density‐plug phantom. IMRT plans (6 MV, Varian TrueBeam, 6–9 coplanar fields) meeting departmental coverage and normal tissue constraints were retrospectively generated for 10 lung SBRT cases using Eclipse Vn 10.0.28 AAA with in‐house tables (AAA/IH). Using these monitor units and MLC sequences, plans were recalculated with AAA and vendor tables (AAA/V) and with AXB with both tables (AXB/IH and AXB/V). Ratios to corresponding AAA/IH values were calculated for PTV D95, D01, D99, mean‐dose, total and ipsilateral lung V20 and chestwall V30. Statistical significance of differences was judged by Wilcoxon Signed Rank Test (p<0.05).

Results:

For HU<−400 the vendor HU‐mass density table was notably below the IH table. PTV D95 ratios to AAA/IH, averaged over all patients, are 0.963±0.073 (p=0.508), 0.914±0.126 (p=0.011), and 0.998±0.001 (p=0.005) for AXB/IH, AXB/V and AAA/V respectively. Total lung V20 ratios are 1.006±0.046 (p=0.386), 0.975±0.080 (p=0.514) and 0.998±0.002 (p=0.007); ipsilateral lung V20 ratios are 1.008±0.041(p=0.284), 0.977±0.076 (p=0.443), and 0.998±0.018 (p=0.005) for AXB/IH, AXB/V and AAA/V respectively. In 7 cases, ratios to AAA/IH were within ± 5% for all indices studied. For 3 cases characterized by very low lung density and small PTV (19.99±8.09 c.c.), PTV D95 ratio for AXB/V ranged from 67.4% to 85.9%, AXB/IH D95 ratio ranged from 81.6% to 93.4%; there were large differences in other studied indices.

Conclusion:

For AXB users, careful attention to HU conversion tables is important, as they can significantly impact AXB (but not AAA) lung SBRT plans. Algorithm selection is also important for small targets in low density lung.
SU‐F‐BRF‐01: A GPU Framework for Developing Interactive High‐Resolution Patient‐Specific Biomechanical Models
Authors: Neylon J , Qi S , Sheng K , Kupelian P , Santhanam A
Published: July 2014

Purpose:

To develop a GPU‐based framework that can generate highresolution and patient‐specific biomechanical models from a given simulation CT and contoured structures, optimized to run at interactive speeds, for addressing adaptive radiotherapy objectives.

Method:

A Massspring‐damping (MSD) model was generated from a given simulation CT. The model's mass elements were generated for every voxel of anatomy, and positioned in a deformation space in the GPU memory. MSD connections were established between neighboring mass elements in a dense distribution. Contoured internal structures allowed control over elastic material properties of different tissues. Once the model was initialized in GPU memory, skeletal anatomy was actuated using rigid‐body transformations, while soft tissues were governed by elastic corrective forces and constraints, which included tensile forces, shear forces, and spring damping forces. The model was validated by applying a known load to a soft tissue block and comparing the observed deformation to ground truth calculations from established elastic mechanics.

Results:

Our analyses showed that both local and global load experiments yielded results with a correlation coefficient R2 > 0.98 compared to ground truth. Models were generated for several anatomical regions. Head and neck models accurately simulated posture changes by rotating the skeletal anatomy in three dimensions. Pelvic models were developed for realistic deformations for changes in bladder volume. Thoracic models demonstrated breast deformation due to gravity when changing treatment position from supine to prone. The GPU framework performed at greater than 30 iterations per second for over 1 million mass elements with up to 26 MSD connections each.

Conclusions:

Realistic simulations of site‐specific, complex posture and physiological changes were simulated at interactive speeds using patient data. Incorporating such a model with live patient tracking would facilitate real time assessment of variations of the actual anatomy and delivered dose for adaptive intervention and re‐planning.
SU‐F‐BRF‐02: Automated Lung Segmentation Method Using Atlas‐Based Sparse Shape Composition with a Shape Constrained Deformable Model
Authors: Zhou J , yan z , zhang s , Zhang B , Lasio G , Prado K , D' Souza W
Published: July 2014

Purpose:

To develop an automated lung segmentation method, which combines the atlas‐based sparse shape composition with a shape constrained deformable model in thoracic CT for patients with compromised lung volumes.

Methods:

Ten thoracic computed tomography scans for patients with large lung tumors were collected and reference lung ROIs in each scan was manually segmented to assess the performance of the method. We propose an automated and robust framework for lung tissue segmentation by using single statistical atlas registration to initialize a robust deformable model in order to perform fine segmentation that includes compromised lung tissue. First, a statistical image atlas with sparse shape composition is constructed and employed to obtain an approximate estimation of lung volume. Next, a robust deformable model with shape prior is initialized from this estimation. Energy terms from ROI edge potential and interior ROI region based potential as well as the initial ROI are combined in this model for accurate and robust segmentation.

Results:

The proposed segmentation method is applied to segment right lung on three CT scans. The quantitative results of our segmentation method achieved mean dice score of (0.92–0.95), mean accuracy of (0.97,0.98), and mean relative error of (0.10,0.16) with 95% CI. The quantitative results of previously published RASM segmentation method achieved mean dice score of (0.74,0.96), mean accuracy of (0.66,0.98), and mean relative error of (0.04, 0.38) with 95% CI. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance compared with a robust active shape model method.

Conclusion:

The atlas‐based segmentation approach achieved relatively high accuracy with less variance compared to RASM in the sample dataset and the proposed method will be useful in image analysis applications for lung nodule or lung cancer diagnosis and radiotherapy assessment in thoracic computed tomography.
SU‐F‐BRF‐03: Quality Assurance of Deformable Image Registration in Radiotherapy
Authors: Watkins W.T. , Bzdusek K. , Siebers J.V.
Published: July 2014

Purpose:

To introduce methods to analyze Deformable Image Registration (DIR) and identify regions of potential DIR errors.

Methods:

DIR Deformable Vector Fields (DVFs) quantifying patient anatomic changes were evaluated using the Jacobian determinant and the magnitude of DVF curl as functions of tissue density and tissue type. These quantities represent local relative deformation and rotation, respectively. Large values in dense tissues can potentially identify non‐physical DVF errors. For multiple DVFs per patient, histograms and visualization of DVF differences were also considered. To demonstrate the capabilities of methods, we computed multiple DVFs for each of five Head and Neck (H' N) patients (P1–P5) via a Fast‐symmetric Demons (FSD) algorithm and via a Diffeomorphic Demons (DFD) algorithm, and show the potential to identify DVF errors.

Results:

Quantitative comparisons of the FSD and DFD registrations revealed <0.3 cm DVF differences in >99% of all voxels for P1, >96% for P2, and >90% of voxels for P3. While the FSD and DFD registrations were very similar for these patients, the Jacobian determinant was >50% in 9–15% of soft tissue and in 3–17% of bony tissue in each of these cases. The volumes of large soft tissue deformation were consistent for all five patients using the FSD algorithm (mean 15%±4% volume), whereas DFD reduced regions of large deformation by 10% volume (785 cm3) for P4 and by 14% volume (1775 cm3) for P5. The DFD registrations resulted in fewer regions of large DVF‐curl; 50% rotations in FSD registrations averaged 209±136 cm3 in soft tissue and 10±11 cm3 in bony tissue, but using DFD these values were reduced to 42±53 cm3 and 1.1±1.5 cm3, respectively.

Conclusion:

Analysis of Jacobian determinant and curl as functions of tissue density can identify regions of potential DVF errors by identifying non‐physical deformations and rotations.

Collaboration with Phillips Healthcare, as indicated in authorship.
SU‐F‐BRF‐04: Evaluation of Five Commercially‐Available Algorithms for Deformable Image Registration
Authors: Shah A , Pukala J , Johnson P , Staton R , Meeks S
Published: July 2014

Purpose:

Deformable image registration (DIR) is increasingly being used in various clinical applications. Although there are several DIR packages all making successful attempts at modeling complex anatomical changes using even more complex mathematical approximations, they are all subject to various uncertainties. Many studies have attempted to quantify the spatial uncertainty with DIR. This is the first study to compare the uncertainty for interfraction DIR for 5 different commercially‐available algorithms. The aim of this study was to benchmark the performance of the most commonlyused DIR algorithms offered through these 5 software packages: Eclipse, MIM, Pinnacle, RaySearch, and Velocity.

Methods:

A set of 10 virtual H' N phantoms [Pukala et al. MedPhys. 40(11) 2013] with known deformations were used to determine the spatial errors that might be seen when performing DIR. The “ground‐truth” deformation vector field (DVF) was compared to the DVF output of the 5 commercially‐available algorithms in order to evaluate spatial errors for six regions of interest (ROIs): brainstem, cord, mandible, left parotid, right parotid, and the external body contour.

Results:

We found that each software package had varying uncertainties with the various ROIs, but were generally all comparable to one another – with mean spatial errors for each algorithm below 3.5 mm for each ROI (averaged across all phantoms). We also found that no single algorithm was the clear winner over the other 4 algorithms. However, at times, we found huge maximum errors in our results (e.g. phantom #9 maximum errors: right parotid = 22.9 mm, external contour = 30.5mm) with the varying DIR algorithms.

Conclusion:

Although our evaluation was limited to H' N patients, we show that our methods are a single‐assessment analysis tool that could be used by any physicist, within any type of facility, to compare their DIR software before initiating widespread use within their daily radiotherapy practice.
SU‐F‐BRF‐05: Influence of Rigid Registration On the Deformable Registration Quality in the Context of Atlas Contouring
Authors: von Lavante E , Galerneau C , Gooding M
Published: July 2014

Purpose:

Deformable registration requires a rigid registration as an initialization. Normally, a global rigid is assumed acceptable. However, for many use‐cases, such as atlas contouring, there is no obvious “best” global rigid. Thus, we have investigated how a rigid registration affects the deformable registration in the context of atlas contouring and if a “global best” rigid registration can be found.

Methods:

All possible combinations of source and target images from a database of 7 expertly delineated head and neck images (26 organs) were evaluated. For each source‐target‐pair, the image centroids were aligned, and subsequently rigid registrations were simulated by sweeping the target over an isotropic grid (−100mm to +100mm with respect to centroid alignment, in 10mm steps). Deformable registration was performed following each initialization using commercial software (RTx, Mirada Medical, Oxford, UK). Contours were transformed from source to target. DICE coefficients between the transformed and original contours were calculated on the target. Successful registration was taken to be where DICE was within 80% of the maximum achievable. The capture range was determined by fitting a least‐squares ellipsoid to the space of initialisations resulting in success. The mean of the ellipsoid centers determined the “best” global rigid registration, and the distance of each ellipsoid center to this was computed.

Results:

The extent of the capture range averaged over all organs and cases was x=64.3mm, y=51.4mm, z=32.3mm. The standard deviation of the ellipsoid centers from the “best” rigid was x=37.8mm, y=56.6mm, z=38.6mm. This per‐organ deviation from the global rigid is in the same order of magnitude than the capture range of the deformable algorithm.

Conclusion:

Finding the “best” rigid registration is an ill‐posed problem, as the optimum rigid registration will differ between target organs. Thus, having an algorithm with a large capture range is essential to a good deformable registration.

All authors were employed by Mirada Medical Ltd., Oxford, Oxfordshire, United Kingdom.
SU‐E‐QI‐04: Curve Fitting of Time‐Density Data From CT Circulation Timing Scans for Estimation of Cardiac Output
Authors: Ogden K , Scalzetti E , Rajebi H
Published: July 2014

Purpose:

To develop a robust algorithm for fitting gamma variate functions to time‐density data acquired during a circulation time scan in preparation for a CT pulmonary angiogram (CTPA).

Methods:

Timedensity information in the main pulmonary artery (MPA), ascending aorta (AA), and descending aorta (DA) was retrospectively collected for 10 patients undergoing CTPA. Measurements prior to the arrival of contrast were used to estimate the baseline (blood) density value. The estimated contrast arrival delay time was varied over a range of values and the maximum correlation coefficient was used to estimate the delay time. In a second approach, an additional step was performed by shifting the data in time relative to the best‐fit gamma variate and calculating a mean‐squared difference (MSD). The minimum MSD was used to find a new estimate of the delay time, after which a new gamma variate fit was performed. This process was iterated five times. The final gamma variate fit was used to estimate the cardiac output (CO).

Results:

The mean CO for all patients and all vessels was 6.8 l/min for both methods. To compare the robustness of the two methods, coefficient of variation (CV) of CO for the three vessels was computed for each patient. For method 1, the average CV was 0.054, for method 2 it was 0.023. Using method 2, the CV decreased for all but one patient, for whom it increased from 0.01 to 0.02. On average the CV was reduced by 57% using method 2.

Conclusion:

Cardiac output may be estimated by using the time‐dilution data collected during a circulation timing scan acquired at CTPA. Care must be taken in fitting a model to the data to ensure robust results. The method described has proven to reduce the variability in CO values estimated for different vessels in a single scan.
SU‐F‐BRD‐16: Under Dose Regions Recalculated by Monte Carlo Cannot Predict the Local Failure for NSCLC Patients Treated with SBRT
Authors: Liu H , Cherian S , Stephans K , Videtic G , Qi P , Xia P , Zhuang T
Published: July 2014

Purpose:

To investigate whether Monte Carlo (MC) recalculated dose distributions can predict the geometric location of the recurrence for nonsmall cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).

Methods:

Thirty NSCLC patients with local recurrence were retrospectively selected for this study. The recurred gross target volumes (rGTV) were delineated on the follow‐up CT/PET images and then rigidly transferred via imaging fusion to the original planning CTs. Failure pattern was defined according to the overlap between the rGTV and planning GTV (pGTV) as: (a) in‐field failure (≥80%), (b) marginal failure (20%–80%), and (c) out‐of‐field failure (≤20%). All clinical plans were calculated initially with pencil beam (PB) with or without heterogeneity correction dependent of protocols. These plans were recalculated with MC with heterogeneity correction. Because of non‐uniform dose distributions in the rGTVs, the rGTVs were further divided into four regions: inside the pGTV (GTVin), inside the PTV (PTVin), outside the pGTV (GTVout), and outside the PTV (PTVout). The mean doses to these regions were reported and analyzed separately.

Results:

Among 30 patients, 10 patients had infield recurrences, 15 marginal and 5 out‐of‐field failures. With MC calculations, D95 and D99 of the PTV were reduced by (10.6 ± 7.4)% and (11.7 ± 7.9)%. The average MC calculated mean doses of GTVin, GTVout, PTVin and PTVout were 48.2 ± 5.3 Gy, 48.2 ± 5.5 Gy, 46.3 ± 6.2 Gy and 46.6 ± 5.6 Gy, respectively. No significant dose differences between GTVin and GTVout (p=0.65), PTVin and PTVout (p=0.19) were observed, using the paired students t‐test.

Conclusion:

Although the PB calculations underestimated the tumor target doses, the geometric location of the recurrence did not correlate with the mean doses of subsections of the recurrent GTV. Under dose regions recalculated by MC cannot predict the local failure for NSCLC patients treated with SBRT.
Enhanced directivity with array gratings
Authors: Cray Benjamin A. , Moss Geoffrey R.
Published: July 2014

A planewave, incident on a panel, produces an acoustic trace wavelength that propagates along the surface of the panel. The trace wavelength excites the panel into vibration, creating structural waves within the panel that propagate. These structural waves can be purposely Bragg scattered, creating replicas of the trace wavenumber. The replicas are shifted in wavenumber precisely by the inverse of the periodic separation distance ℓ. Hence, in principle, it should be possible to resolve the acoustic trace wavelength from one of the shifted replicas of the panel's response. The incident angle can then be ascertained from the replicated trace wavelengths.
Temporal signal processing of dolphin biosonar echoes from salmon prey
Authors: Au Whitlow W. L. , “Helen” Ou Hui
Published: July 2014

Killer whales project short broadband biosonar clicks. The broadband nature of the clicks provides good temporal resolution of echo highlights and allows for the discriminations of salmon prey. The echoes contain many highlights as the signals reflect off different surfaces and parts of the fish body and swim bladder. The temporal characteristics of echoes from salmon are highly aspect dependent and six temporal parameters were used in a support vector machine to discriminate between species. Results suggest that killer whales can classify salmon based on their echoes and provide some insight as to which features might enable the classification.
Comparison between parallel transfer matrix method and admittance sum method
Authors: Verdière Kévin , Panneton Raymond , Elkoun Saïd , Dupont Thomas , Leclaire Philippe
Published: July 2014

A transfer matrix method to predict absorption coefficient and transmission loss of parallel assemblies of materials which can be expressed by a 2 × 2 transfer matrix was published recently. However, the usual method based on the sum of admittances is largely used to predict also surface admittance of parallel assemblies. This paper aims to highlight differences between both methods through three examples on a parallel assembly backed by (1) a rigid wall, (2) an air cavity, and (3) an anechoic termination.
Temporal characteristics of speech: The effect of age and speech style
Authors: Bóna Judit
Published: July 2014

Aging affects temporal characteristics of speech. It is still a question how these changes occur in different speech styles which require various cognitive skills. In this paper speech rate, articulation rate, and pauses of 20 young and 20 old speakers are analyzed in four speech styles: spontaneous narrative, narrative recalls, a three-participant conversation, and reading aloud. Results show that age has a significant effect only on speech rate, articulation rate, and frequency of pauses. Speech style has a higher effect on temporal parameters than speakers' age.
The effect of context duration on Mandarin listeners' tone normalization
Authors: Luo Xin , Ashmore Krista B.
Published: July 2014

Tone normalization has been observed in Mandarin listeners, who contrastively adjust tone recognition using context pitch cues. This study tested the effect of context duration on Mandarin tone normalization. The target tones varied from Tone 1 (high-flat) to Tone 2 (mid-rising). The preceding phrase was modified to have different durations with 160- or 200-Hz mean fundamental frequencies (F0s). The results showed that the high-F0 context elicited significantly more Tone-2 responses than the low-F0 context, even when the contexts were 125 ms. The contrastive context effect saturated with the 250-ms contexts, indicating a 250-ms critical context duration for robust tone normalization.
The effect of acoustic forcing on an airfoil tonal noise mechanism
Authors: Schumacher Karn L. , Doolan Con J. , Kelso Richard M.
Published: July 2014

The response of the boundary layer over an airfoil with cavity to external acoustic forcing, across a sweep of frequencies, was measured. The boundary layer downstream of the cavity trailing edge was found to respond strongly and selectively at the natural airfoil tonal frequencies. This is considered to be due to enhanced feedback. However, the shear layer upstream of the cavity trailing edge did not respond at these frequencies. These findings confirm that an aeroacoustic feedback loop exists between the airfoil trailing edge and a location near the cavity trailing edge.
Fast nearfield to farfield conversion algorithm for circular synthetic aperture sonar
Authors: Plotnick Daniel S. , Marston Philip L. , Marston Timothy M.
Published: July 2014

Monostatic circular synthetic aperture sonar (CSAS) images are formed by processing azimuthal angle dependent backscattering from a target at a fixed distance from a collocated source/receiver. Typical CSAS imaging algorithms [Ferguson and Wyber, J. Acoust. Soc. Am. 117, 2915–2928 (2005)] assume scattering data are taken in the farfield. Experimental constraints may make farfield measurements impractical and thus require objects to be scanned in the nearfield. Left uncorrected this results in distortions of the target image and in the angular dependence of features. A fast approximate Hankel function based algorithm is presented to convert nearfield data to the farfield. Images and spectrograms of an extended target are compared for both cases.
Comments on the low frequency radiation impedance of a duct exhausting a hot gas
Authors: Hirschberg Avraham , Hoeijmakers Maarten
Published: July 2014

The influence of convection and temperature on the radiation impedance of an open duct termination exhausting a hot gas is commonly described by a complex theory. A simplified analytical expression is proposed for low frequencies. Both models assume a free jet with uniform velocity bounded by infinitely thin shear layers. The convective velocity that should be assumed when applying these models to a non-uniform outflow is uncertain. A simplified version of the so-called Vortex Sound Theory demonstrates that the convective velocity one should assume is lower than the jet centerline velocity.
Identification of significant intrinsic mode functions for the diagnosis of induction motor fault
Authors: Cho Sangjin , Shahriar Md. Rifat , Chong Uipil
Published: July 2014

For the analysis of non-stationary signals generated by a non-linear process like fault of an induction motor, empirical mode decomposition (EMD) is the best choice as it decomposes the signal into its natural oscillatory modes known as intrinsic mode functions (IMFs). However, some of these oscillatory modes obtained from a fault signal are not significant as they do not bear any fault signature and can cause misclassification of the fault instance. To solve this issue, a novel IMF selection algorithm is proposed in this work.
Estimation of voice-onset time in continuous speech using temporal measures
Authors: Prathosh A. P. , Ramakrishnan A. G. , Ananthapadmanabha T. V.
Published: July 2014

This paper proposes an automatic acoustic-phonetic method for estimating voice-onset time of stops. This method requires neither transcription of the utterance nor training of a classifier. It makes use of the plosion index for the automatic detection of burst onsets of stops. Having detected the burst onset, the onset of the voicing following the burst is detected using the epochal information and a temporal measure named the maximum weighted inner product. For validation, several experiments are carried out on the entire TIMIT database and two of the CMU Arctic corpora. The performance of the proposed method compares well with three state-of-the-art techniques.