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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
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DOE OSTI2014

SU-E-T-580: Comparison of Cervical Carcinoma IMRT Plans From Four Commercial Treatment Planning Systems (TPS)

Purpose: Different treatment planning systems (TPS) use different treatment optimization and leaf sequencing algorithms. This work compares cervical carcinoma IMRT plans optimized with four commercial TPSs to investigate the plan quality in terms of target conformity and delivery efficiency. Methods: Five cervical carcinoma cases were planned with the Corvus, Monaco, Pinnacle and Xio TPSs by experienced planners using appropriate optimization parameters and dose constraints to meet the clinical acceptance criteria. Plans were normalized for at least 95% of PTV to receive the prescription dose (Dp). Dose-volume histograms and isodose distributions were compared. Other quantities such as Dmin(the minimum dose received by 99% of GTV/PTV), Dmax(the maximum dose received by 1% of GTV/PTV), D100, D95, D90, V110%, V105%, V100% (the volume of GTV/PTV receiving 110%, 105%, 100% of Dp), conformity index(CI), homogeneity index (HI), the volume of receiving 40Gy and 50 Gy to rectum (V40,V50) ; the volume of receiving 30Gy and 50 Gy to bladder (V30,V50) were evaluated. Total segments and MUs were also compared. Results: While all plans meet target dose specifications and normal tissue constraints, the maximum GTVCI of Pinnacle plans was up to 0.74 and the minimum of Corvus plans was only 0.21, these four TPSs PTVCI had significant difference. The GTVHI and PTVHI of Pinnacle plans are all very low and show a very good dose distribution. Corvus plans received the higer dose of normal tissue. The Monaco plans require significantly less segments and MUs to deliver than the other plans. Conclusion: To deliver on a Varian linear-accelerator, the Pinnacle plans show a very good dose distribution. Corvus plans received the higer dose of normal tissue. The Monaco plans have faster beam delivery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-615: Investigation of the Dosimetric Impact of Tandem Loading in the Treatment of Cervical Cancer for HDR Brachytherapy Procedures

Purpose: To quantify the dosimetric impact of the tandem loading in the treatment of cervical cancer for HDR brachytherapy procedures. Methods: Ten patients were evaluated, each of whom received 5 fractions of treatment. Tandem and ovoid sets were inserted into the uterine cavity based on institutional protocols and procedures. Following insertion and stabilization, CT image sets of 1.5mm slice thickness were acquired and sent to the Oncentra V4.3 Treatment Planning System. Critical structures such as the CTV, bladder, rectum, sigmoid, and bowel were contoured and a fractional dose of 5.5Gy was prescribed to Point A for each patient. Six different treatment plans were created for each fraction using varying tandem weightings; from 0.5 to 1.4 times that of the ovoids. Surface dose evaluation of various ovoid diameters, 2.0-3.5cm, at the vaginal fornices was also investigated. Results: Critical structures were evaluated based on varying dose and volume constraints, in particular the 2.0 cc volume recommendation cited by the gynecological GEC-ESTRO working group. Based on dose volume histogram evaluation, a reduction of dose to the critical structures was most often discovered when the tandem weighting was increased. CTV coverage showed little change as the tandem weighting was varied. Ovoid surface dose decreased by 50-65% as the tandem weighting increased. Conclusion: The advantage of 3D planning with HDR brachytherapy is the dose optimization for each individual treatment plan. This investigation shows that by utilizing large tandem weightings, 1.4 times greater than the ovoid, one can still achieve adequate coverage of the CTV and relatively low doses to the critical structures. In some cases, one would still have to optimize further per individual case. In addition, the ovoid surface dose was greatly decreased when large tandem weighting was utilized; especially for small ovoid diameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-616: Comparison of Plan Dose Accuracy for Anterior Vs. Lateral Fields in Proton Therapy of Prostate Cancer

Purpose: With the anticipated introduction of in vivo range verification methods, the use of anterior fields for proton therapy of prostate cancer may become an attractive treatment option, and improve upon the dose distributions achievable with conventional lateral-opposed fields. This study aimed to evaluate and compare the planned dose accuracy for lateral versus anterior oblique field arrangements. Methods: Four patients with low/intermediate risk prostate cancer, participating in a clinical trial at our institution, were selected for this study. All patients were treated using lateral-opposed fields (LAT). The clinical target volume (CTV) received a total dose of 79.2 Gy in 44 fractions. Anterior oblique research plans (ANT) were created using the clinical planning system, and featured beams with ±35-degree gantry angle, 1.2 cm aperture margins, 3-mm range compensator smearing and no range uncertainty margins. Monte Carlo (MC) simulations were performed for both beam arrangements using TOPAS. Dose volume histograms were analyzed and compared for planned and MC dose distributions. Differences between MC and planned DVH parameters were computed as a percentage of the total prescribed dose. Results: For all patients, CTV dose was systematically lower (∼2–2.5%) for MC than the plan. This discrepancy was slightly larger (∼0.5%) for LAT compared to ANT plans for all cases. Although the dose differences for bladder and anterior rectal wall remained within 0.7% for all LAT cases, they were slightly larger for ANT plans, especially for case 3 due to larger patient size and MC-plan range difference. The EUD difference for femoral heads was within 0.6% for both LAT and ANT cases. Conclusion: The dose calculated by the treatment planning system using pencil beam algorithm agrees with MC to within 2.5% and is comparable for lateral and anterior scenarios. The dose agreement in the anterior rectal wall is range- and hence, patient-dependent for ANT treatments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-617: A Feasibility Study of Navigation Based Multi Criteria Optimization for Advanced Cervical Cancer IMRT Planning

Purpose: This study aims to validate multi-criteria optimization (MCO) against standard intensity modulated radiation therapy (IMRT) optimization for advanced cervical cancer in RayStation (v2.4, RaySearch Laboratories, Sweden). Methods: 10 advanced cervical cancer patients IMRT plans were randomly selected, these plans were designed with step and shoot optimization, new plans were then designed with MCO based on these plans,while keeping optimization conditions unchanged,comparison was made between both kinds of plans including the dose volume histogram parameters of PTV and OAR,and were analysed by pairing-t test. Results: We normalize the plan so that 95% volume of PTV achieved the prescribed dose(50Gy). The volume of radiation 10, 20, 30, and 40 Gy of the rectum were reduced by 14.7%,26.8%,21.1%,10.5% respectively(P≥0.05). The mean dose of rectum were reduced by 7.2Gy(P≤0.05). There were no significant differences for the dosimetric parameters for the bladder. Conclusion: In comparision with standard IMRT optimization, MCO reduces the dose of organs at risk with the same PTV coverage,but the result needs further clinical evalution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-629: Feasibility Study of Treating Multiple Brain Tumors with Large Number of Noncoplanar IMRT Beams

Purpose: To study the feasibility of treating multiple brain tumors withlarge number of noncoplanar IMRT beams. Methods: Thirty beams are selected from 390 deliverable beams separated by six degree in 4pi space. Beam selection optimization is based on a column generation algorithm. MLC leaf size is 2 mm. Dose matrices are calculated with collapsed cone convolution and superposition method in a 2 mm by 2mm by 2 mm grid. Twelve brain tumors of various shapes, sizes and locations are used to generate four plans treating 3, 6, 9 and 12 tumors. The radiation dose was 20 Gy prescribed to the 100% isodose line. Dose Volume Histograms for tumor and brain were compared. Results: All results are based on a 2 mm by 2 mm by 2 mm CT grid. For 3, 6, 9 and 12 tumor plans, minimum tumor doses are all 20 Gy. Mean tumor dose are 20.0, 20.1, 20.1 and 20.1 Gy. Maximum tumor dose are 23.3, 23.6, 25.4 and 25.4 Gy. Mean ventricles dose are 0.7, 1.7, 2.4 and 3.1 Gy.Mean subventricular zone dose are 0.8, 1.3, 2.2 and 3.2 Gy. Average Equivalent uniform dose (gEUD) values for tumor are 20.1, 20.1, 20.2 and 20.2 Gy. The conformity index (CI) values are close to 1 for all 4 plans. The gradient index (GI) values are 2.50, 2.05, 2.09 and 2.19. Conclusion: Compared with published Gamma Knife treatment studies, noncoplanar IMRT treatment plan is superior in terms of dose conformity. Due to maximum limit of beams per plan, Gamma knife has to treat multiple tumors separately in different plans. Noncoplanar IMRT plans theoretically can be delivered in a single plan on any modern linac with an automated couch and image guidance. This warrants further study of using noncoplanar IMRT as a viable treatment solution for multiple brain tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-641: Development and Verification of Automatic Reading Dose of Interest From Eclipse's DVH

Purpose: According to clinical and research requirement, we develop a function of automatic reading dose of interest from dose volume histogram(DVH), to replace the traditional method with a mouse one by one point, and it's also verified. Methods: The DVH automatic reading function will be developed in an in-house developed radiotherapy information management system(RTIMS), which is based on Apache+PHP+MySQL. A DVH ASCII file is exported from Varian Eclipse V8.6, which includes the following contents: 1. basic information of patient; 2. dose information of plan; 3. dose information of structures, including basic information and dose volume data of target volume and organ at risk. And the default exported dose volume data also includes relative doses by 1% step and corresponding absolute doses and cumulative relative volumes, and the volumes are 4 decimal fraction. Clinically, we often need read the doses of some integer percent volumes, such as D50 and D30. So it couldn't be directly obtained from the above data, but we can use linear interpolation bye the near volumes and doses: Dx=D2−(V2−Vx)*(D2−D1)/(V2−V1), and program a function to search, read and calculate the corresponding data. And the doses of all preseted volume of interest of all structures can be automatically read one by one patient, and saved as a CSV file. To verify it, we select 24 IMRT plans for prostate cancer, and doses of interest are PTV D98/D95/D5/D2, bladder D30/D50, and rectum D25/D50. Two groups of data, using the automatic reading method(ARM) and pointed dose method(PDM), are analyzed with SPSS 16. The absolute difference=D-ARM-D-PDM, relative difference=absolute difference*100%/prescription dose(7600cGy). Results: The differences are as following: PTV D98/D95/D5/D2: −0.04%/− 0.04%/0.13%/0.19%, bladder D30/D50: −0.02%/0.01%, and rectum D25/D50: 0.03%/0.01%. Conclusion: Using this function, the error is very small, and can be neglected. It could greatly improve the efficiency of clinical work. Project supported by the National Natural Science Foundation of China (Grant No.81101694)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-QI-20: A Review of Advanced PET and CT Image Features for the Evaluation of Tumor Response

Purpose: To review the literature in using quantitative PET and CT image features for the evaluation of tumor response. Methods: We reviewed and summarized more than fifty papers that use advanced, quantitative PET/CT image features for the evaluation of tumor response. We also discussed future works on extracting disease-specific features, combining multiple and complementary features in response modeling, delineating tumor in multimodality images, and exploring biological explanations of these advanced features. Results: Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features (characterizing spatial distribution of FDG uptake) have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Conclusions: Advanced, quantitative FDG PET/CT image features have been shown promising for the evaluation of tumor response. With the emerging multi-modality imaging performed at multiple time points for each patient, it becomes more important to analyze the serial images quantitatively, select and combine both complementary and contradictory information from various sources, for accurate and personalized evaluation of tumor response to therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-CAMPUS-I-06: Y90 PET/CT for the Instantaneous Determination of Both Target and Non-Target Absorbed Doses Following Hepatic Radioembolization

Purpose The process of converting Yttrium-90 (Y90) PET/CT images into 3D absorbed dose maps will be explained. The simple methods presented will allow the medical physicst to analyze Y90 PET images following radioembolization and determine the absorbed dose to tumor, normal liver parenchyma and other areas of interest, without application of Monte-Carlo radiation transport or dose-point-kernel (DPK) convolution. Methods Absorbed dose can be computed from Y90 PET/CT images based on the premise that radioembolization is a permanent implant with a constant relative activity distribution after infusion. Many Y90 PET/CT publications have used DPK convolution to obtain 3D absorbed dose maps. However, this method requires specialized software limiting clinical utility. The Local Deposition method, an alternative to DPK convolution, can be used to obtain absorbed dose and requires no additional computer processing. Pixel values from regions of interest drawn on Y90 PET/CT images can be converted to absorbed dose (Gy) by multiplication with a scalar constant. Results There is evidence that suggests the Local Deposition method may actually be more accurate than DPK convolution and it has been successfully used in a recent Y90 PET/CT publication. We have analytically compared dose-volume-histograms (DVH) for phantom hot-spheres to determine the difference between the DPK and Local Deposition methods, as a function of PET scanner point-spread-function for Y90. We have found that for PET/CT systems with a FWHM greater than 3.0 mm when imaging Y90, the Local Deposition Method provides a more accurate representation of DVH, regardless of target size than DPK convolution. Conclusion Using the Local Deposition Method, post-radioembolization Y90 PET/CT images can be transformed into 3D absorbed dose maps of the liver. An interventional radiologist or a Medical Physicist can perform this transformation in a clinical setting, allowing for rapid prediction of treatment efficacy by comparison to published tumoricidal thresholds.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-F-BRD-03: Determination of Plan Robustness for Systematic Setup Errors Using Trilinear Interpolation

Purpose: Treatment plan evaluations in radiotherapy are currently ignoring the dosimetric impact of setup uncertainties. The determination of the robustness for systematic errors is rather computational intensive. This work investigates interpolation schemes to quantify the robustness of treatment plans for systematic errors in terms of efficiency and accuracy. Methods: The impact of systematic errors on dose distributions for patient treatment plans is determined by using the Swiss Monte Carlo Plan (SMCP). Errors in all translational directions are considered, ranging from −3 to +3 mm in mm steps. For each systematic error a full MC dose calculation is performed leading to 343 dose calculations, used as benchmarks. The interpolation uses only a subset of the 343 calculations, namely 9, 15 or 27, and determines all dose distributions by trilinear interpolation. This procedure is applied for a prostate and a head and neck case using Volumetric Modulated Arc Therapy with 2 arcs. The relative differences of the dose volume histograms (DVHs) of the target and the organs at risks are compared. Finally, the interpolation schemes are used to compare robustness of 4- versus 2-arcs in the head and neck treatment plan. Results: Relative local differences of the DVHs increase for decreasing number of dose calculations used in the interpolation. The mean deviations are <1%, 3.5% and 6.5% for a subset of 27, 15 and 9 used dose calculations, respectively. Thereby the dose computation times are reduced by factors of 13, 25 and 43, respectively. The comparison of the 4- versus 2-arcs plan shows a decrease in robustness; however, this is outweighed by the dosimetric improvements. Conclusion: The results of this study suggest that the use of trilinear interpolation to determine the robustness of treatment plans can remarkably reduce the number of dose calculations. This work was supported by Varian Medical Systems. This work was supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-F-BRF-03: Quality Assurance of Deformable Image Registration in Radiotherapy

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 cm{sup 3}) for P4 and by 14% volume (1775 cm{sup 3}) for P5. The DFD registrations resulted in fewer regions of large DVF-curl; 50% rotations in FSD registrations averaged 209±136 cm{sup 3} in soft tissue and 10±11 cm{sup 3} in bony tissue, but using DFD these values were reduced to 42±53 cm{sup 3} and 1.1±1.5 cm{sup 3}, 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.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-A-BRD-02: Noise Suppression for Dual-Energy CT Through Entropy Minimization

Purpose: In dual energy CT (DECT), noise amplification during signal decomposition significantly limits the utility of basis material images. Since clinically relevant objects contain a limited number of materials, we propose to suppress noise in decomposed images through entropy minimization within a 2D transformation space. Distinct from other noise suppression techniques, the entropy minimization method does not estimate and suppress noise based on spatial variations of signals and thus maximally preserves image spatial resolution. Methods: From decomposed images, we first generate a 2D plot of scattered data points, using basis material densities as coordinates. Data points representing the same material generate a cluster with a highly asymmetric shape. We orient an axis by minimizing the entropy in a 1D histogram of these points projected onto the axis. To suppress noise, we replace the pixel values of decomposed images with center-of-mass values in the direction perpendicular to the optimized axis. The proposed method's performance is assessed using a Catphan 600 phantom and an anthropomorphic head phantom. Electron density calculations are used to quantify its accuracy. Our results are compared to those without noise suppression, with a filtering method, and with a recently developed iterative method. Results: On both phantoms, the proposed method reduces noise standard deviations of the decomposed images by at least on order of magnitude. In the Catphan study, this method retains the spatial resolution of the CT images and increases the accuracy of electron density calculations. In the head phantom study, the proposed method outperforms the others in retaining fine, intricate structures. Conclusion: This work shows that the proposed method of noise suppression through entropy minimization for DECT suppresses noise without loss of spatial resolution while increasing electron density calculation accuracy. Future investigations will analyze possible bias and incorporate spatial information into the technique for further noise reduction. The work is partially supported by the NIH under the grant number R21EB012700.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

MO-A-BRD-09: A Data-Mining Algorithm for Large Scale Analysis of Dose-Outcome Relationships in a Database of Irradiated Head-And-Neck (HN) Cancer Patients

Purpose: To develop a framework for automatic extraction of clinically meaningful dosimetric-outcome relationships from an in-house, analytic oncology database. Methods: Dose-volume histograms (DVH) and clinical outcome-related structured data elements have been routinely stored to our database for 513 HN cancer patients treated from 2007 to 2014. SQL queries were developed to extract outcomes that had been assessed for at least 100 patients, as well as DVH curves for organs-at-risk (OAR) that were contoured for at least 100 patients. DVH curves for paired OAR (e.g., left and right parotids) were automatically combined and included as additional structures for analysis. For each OAR-outcome combination, DVH dose points, D(V{sub t}), at a series of normalized volume thresholds, V{sub t}=[0.01,0.99], were stratified into two groups based on outcomes after treatment completion. The probability, P[D(V{sub t})], of an outcome was modeled at each V{sub t} by logistic regression. Notable combinations, defined as having P[D(V{sub t})] increase by at least 5% per Gy (p<0.05), were further evaluated for clinical relevance using a custom graphical interface. Results: A total of 57 individual and combined structures and 115 outcomes were queried, resulting in over 6,500 combinations for analysis. Of these, 528 combinations met the 5%/Gy requirement, with further manual inspection revealing a number of reasonable models based on either reported literature or proximity between neighboring OAR. The data mining algorithm confirmed the following well-known toxicity/outcome relationships: dysphagia/larynx, voice changes/larynx, esophagitis/esophagus, xerostomia/combined parotids, and mucositis/oral mucosa. Other notable relationships included dysphagia/pharyngeal constrictors, nausea/brainstem, nausea/spinal cord, weight-loss/mandible, and weight-loss/combined parotids. Conclusion: Our database platform has enabled large-scale analysis of dose-outcome relationships. The current data-mining framework revealed both known and novel dosimetric and clinical relationships, underscoring the potential utility of this analytic approach. Multivariate models may be necessary to further evaluate the complex relationship between neighboring OARs and observed outcomes. This research was supported through collaborations with Elekta, Philips, and Toshiba.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-C-17A-10: Comparison of Dose Deformable Accumulation by Using Parallel and Serial Approaches

Purpose: The uncertainty of dose accumulation over multiple CT datasets with deformable fusion may have significant impact on clinical decisions. In this study, we investigate the difference of two dose summation approaches involving deformable fusion. Methods: Five patients, four external beam and one brachytherapy(BT), were chosen for the study. The BT patient was treated with CT-based HDR. The CT image sets acquired in the imageguidance process (8-11 CTs/patient) were used to determine the dose delivered to the four external beam patients. (prostate, pelvis, lung and head and neck). For the HDR patient (cervix), five CT image sets and the corresponding BT plans were used. In total 44 CT datasets and RT dose/plans were imported into the image fusion software MiM (6.0.4) for analysis.For each of the five clinical cases, the dose from each fraction was accumulated into the primary CT dataset by using both Parallel and Serial approaches. The dose-volume histogram (DVH) for CTV and selected organs-at-risks (OAR) were generated. The D95(CTV), OAR(mean) and OAR(max) for the four external beam cases the D90(CTV), and the max dose to bladder and rectum for the BT case were compared. Results: For the four external beam patients, the difference in D95(CTV) were <1.2% PD between the parallel and the serial approaches. The differences of the OAR(mean) and the OAR(max ) range from 0 to 3.7% and <1% PD respectively. For the HDR patient, the dose difference for D90 is 11% PD while that of the max dose to bladder and rectum were 11.5% and 23.3% respectively. Conclusion: For external beam treatments, the parallel and serial approaches have <5% difference probably because tumor volume and OAR have less changes from fraction to fraction. For the brachytherapy case, >10% dose difference between the two approaches was observed as significant volume changes of tumor and OAR were observed among treatment fractions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-C-17A-13: Uncertainty Evaluation of CT Image Deformable Registration for H and N Cancer Adaptive Radiotherapy

Purpose: To evaluate uncertainties of organ specific Deformable Image Registration (DIR) for H and N cancer Adaptive Radiation Therapy (ART). Methods: A commercial DIR evaluation tool, which includes a digital phantom library of 8 patients, and the corresponding “Ground truth Deformable Vector Field” (GT-DVF), was used in the study. Each patient in the phantom library includes the GT-DVF created from a pair of CT images acquired prior to and at the end of the treatment course. Five DIR tools, including 2 commercial tools (CMT1, CMT2), 2 in-house (IH-FFD1, IH-FFD2), and a classic DEMON algorithms, were applied on the patient images. The resulting DVF was compared to the GT-DVF voxel by voxel. Organ specific DVF uncertainty was calculated for 10 ROIs: Whole Body, Brain, Brain Stem, Cord, Lips, Mandible, Parotid, Esophagus and Submandibular Gland. Registration error-volume histogram was constructed for comparison. Results: The uncertainty is relatively small for brain stem, cord and lips, while large in parotid and submandibular gland. CMT1 achieved best overall accuracy (on whole body, mean vector error of 8 patients: 0.98±0.29 mm). For brain, mandible, parotid right, parotid left and submandibular glad, the classic Demon algorithm got the lowest uncertainty (0.49±0.09, 0.51±0.16, 0.46±0.11, 0.50±0.11 and 0.69±0.47 mm respectively). For brain stem, cord and lips, the DVF from CMT1 has the best accuracy (0.28±0.07, 0.22±0.08 and 0.27±0.12 mm respectively). All algorithms have largest right parotid uncertainty on patient #7, which has image artifact caused by tooth implantation. Conclusion: Uncertainty of deformable CT image registration highly depends on the registration algorithm, and organ specific. Large uncertainty most likely appears at the location of soft-tissue organs far from the bony structures. Among all 5 DIR methods, the classic DEMON and CMT1 seem to be the best to limit the uncertainty within 2mm for all OARs. Partially supported by research grant from Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-G-17A-03: MR-Based Cortical Bone Segmentation for PET Attenuation Correction with a Non-UTE 3D Fast GRE Sequence

Purpose: To determine the feasibility of identifying cortical bone on MR images with a short-TE 3D fast-GRE sequence for attenuation correction of PET data in PET/MR. Methods: A water-fat-bone phantom was constructed with two pieces of beef shank. MR scans were performed on a 3T MR scanner (GE Discovery™ MR750). A 3D GRE sequence was first employed to measure the level of residual signal in cortical bone (TE{sub 1}/TE{sub 2}/TE{sub 3}=2.2/4.4/6.6ms, TR=20ms, flip angle=25°). For cortical bone segmentation, a 3D fast-GRE sequence (TE/TR=0.7/1.9ms, acquisition voxel size=2.5×2.5×3mm{sup 3}) was implemented along with a 3D Dixon sequence (TE{sub 1}/TE{sub 2}/TR=1.2/2.3/4.0ms, acquisition voxel size=1.25×1.25×3mm{sup 3}) for water/fat imaging. Flip angle (10°), acquisition bandwidth (250kHz), FOV (480×480×144mm{sup 3}) and reconstructed voxel size (0.94×0.94×1.5mm{sup 3}) were kept the same for both sequences. Soft tissue and fat tissue were first segmented on the reconstructed water/fat image. A tissue mask was created by combining the segmented water/fat masks, which was then applied on the fast-GRE image (MRFGRE). A second mask was created to remove the Gibbs artifacts present in regions in close vicinity to the phantom. MRFGRE data was smoothed with a 3D anisotropic diffusion filter for noise reduction, after which cortical bone and air was separated using a threshold determined from the histogram. Results: There is signal in the cortical bone region in the 3D GRE images, indicating the possibility of separating cortical bone and air based on signal intensity from short-TE MR image. The acquisition time for the 3D fast-GRE sequence was 17s, which can be reduced to less than 10s with parallel imaging. The attenuation image created from water-fat-bone segmentation is visually similar compared to reference CT. Conclusion: Cortical bone and air can be separated based on intensity in MR image with a short-TE 3D fast-GRE sequence. Further research is required to optimize the strategy to reduce Gibbs artifacts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-C-17A-10: Patient Features Based Dosimetric Pareto Front Prediction In Esophagus Cancer Radiotherapy

Purpose: The purpose of this study is to study the feasibility of the dosimetric pareto front (PF) prediction based on patient anatomic and dosimetric parameters for esophagus cancer patients. Methods: Sixty esophagus patients in our institution were enrolled in this study. A total 2920 IMRT plans were created to generated PF for each patient. On average, each patient had 48 plans. The anatomic and dosimetric features were extracted from those plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose and PTV homogeneous index (PTVHI) were recorded for each plan. The principal component analysis (PCA) was used to extract overlap volume histogram (OVH) features between PTV and other critical organs. The full dataset was separated into two parts include the training dataset and the validation dataset. The prediction outcomes were the MHD and MLD for the current study. The spearman rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The PF was fit by the the stepwise multiple regression method. The cross-validation method was used to evaluation the model. Results: The mean prediction error of the MHD was 465 cGy with 100 repetitions. The most correlated factors were the first principal components of the OVH between heart and PTV, and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 195 cGy. The most correlated factors were the first principal components of the OVH between lung and PTV, and the overlap between lung and PTV in Z-axis. Conclusion: It is feasible to use patients anatomic and dosimetric features to generate a predicted PF. Additional samples and further studies were required to get a better prediction model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-F-BRF-07: Accuracy of Routine Treatment Planning 4D and DIBH CT Delineation of the Left Anterior Descending Artery in Radiotherapy

Purpose: To assess the feasibility of routine treatment planning 4DCT and deep inspiration breath-hold (DIBH) to accurately contour the left anterior descending artery (LAD), a primary indicator of cardiac toxicity, for radiotherapy treatment planning of breast cancer. Methods: Ten subjects were imaged with a cardiac-gated MRI protocol to determine the displacement of a ROI that included the LAD. The subjects performed a series of breath-hold maneuvers to obtain short-axis and radial views, which were resampled to create a 3D-volume. Tissue motion was determined using a multi-resolution 3D optical flow deformable image registration algorithm. The ROI motion was then used as a spatial boundary to characterize the blurring motion of the LAD in ten patients during clinical 4DCT and DIBH protocols. A radiologist contoured the LAD. Coronary motion-induced blurring artifacts were quantified by applying an unsharp filter to accentuate the LAD despite motion-blurring. The 4DCT maximum inhalation and exhalation respiratory phases were co-registered to determine the LAD displacement during tidal respiration, as visualized in 4DCT. Results: The average 90{sup th} percentile heart motion for the ROI was 0.7±0.1mm(LR), 1.3±0.6mm(SI), 0.6±0.2mm(AP) in the cardiac-gated MRI cohort. The average relative increase in the number of voxels comprising the LAD contour was 69.4±4.5% for the DIBH. During tidal respiration, the average relative increase in the LAD contour was 69.3±5.9% and 67.9±4.6% for inhalation and exhalation respiratory phases respectively. The average 90{sup th} percentile LAD motion was 4.8±1.1mm(LR), 0.9±0.4mm(SI), 1.9±0.6mm(AP) for the 4DCT cohort, in the absence of cardiac-gating. Conclusion: Uncompensated coronary motion was the dominant form of motion blurring present in the CT images due to the high frequency of the cardiac cycle relative to the respiratory cycle. The 4D and DIBH CT contour delineation of the LAD was consistently overestimated without cardiac-gating, which could have led to inaccurate dose volume histogram indicators in clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-F-18C-09: Mammogram Surveillance Using Texture Analysis for Breast Cancer Patients After Radiation Therapy

Purpose: To study the feasibility of applying cancer risk model established from treated patients to predict the risk of recurrence on follow-up mammography after radiation therapy for both ipsilateral and contralateral breast. Methods: An extensive set of textural feature functions was applied to a set of 196 Mammograms from 50 patients. 56 Mammograms from 28 patients were used as training set, 44 mammograms from 22 patients were used as test set and the rest were used for prediction. Feature functions include Histogram, Gradient, Co-Occurrence Matrix, Run-Length Matrix and Wavelet Energy. An optimum subset of the feature functions was selected by Fisher Coefficient (FO) or Mutual Information (MI) (up to top 10 features) or a method combined FO, MI and Principal Component (FMP) (up to top 30 features). One-Nearest Neighbor (1-NN), Linear Discriminant Analysis (LDA) and Nonlinear Discriminant Analysis (NDA) were utilized to build a risk model of breast cancer from the training set of mammograms at the time of diagnosis. The risk model was then used to predict the risk of recurrence from mammogram taken one year and three years after RT. Results: FPM with NDA has the best classification power in classifying the training set of the mammogram with lesions versus those without lesions. The model of FPM with NDA achieved a true positive (TP) rate of 82% compared to 45.5% of using FO with 1-NN. The best false positive (FP) rates were 0% and 3.6% in contra-lateral breast of 1-year and 3-years after RT, and 10.9% in ipsi-lateral breast of 3-years after RT. Conclusion: Texture analysis offers high dimension to differentiate breast tissue in mammogram. Using NDA to classify mammogram with lesion from mammogram without lesion, it can achieve rather high TP and low FP in the surveillance of mammogram for patient with conservative surgery combined RT.

60 APPLIED LIFE SCIENCES↗