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At least 1,027 records · Page 57

TU-G-BRB-02: Clinical Trials in Particle Therapy - Open Questions

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. The lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.

60 APPLIED LIFE SCIENCES↗

TU-G-BRB-03: IROC Houston’s Proton Beam Validation for Clinical Trials

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. The lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.

60 APPLIED LIFE SCIENCES↗

TU-G-BRB-04: Digital Phantoms for Developing Protocols in Particle Therapy

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. The lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.

60 APPLIED LIFE SCIENCES↗

TU-G-BRB-05: Panel Discussion: Clinical Trials in Proton and Ion Therapy - Are We Ready?

Proton therapy, in particular, and ion therapy, just beginning, are becoming an increasing focus of attention in clinical radiation oncology and medical physics. Both modalities have been criticized of lacking convincing evidence from randomized trials proving their efficacy, justifying the higher costs involved in these therapies. This session will provide an overview of the current status of clinical trials in proton therapy, including recent developments in ion therapy. As alluded to in the introductory talk by Dr. Schulte, opinions are diverging widely as to the usefulness and need for clinical trials in particle therapy and the challenge of equipoise. The lectures will highlight some of the challenges that surround clinical trials in particle therapy. One, presented by Dr. Choy from UT Southwestern, is that new technology and even different types of particles such as helium and carbon ions are introduced into this environment, increasing the phase space of clinical variables. The other is the issue of medical physics quality assurance with physical phantoms, presented by Mrs. Taylor from IROC Houston, which is more challenging because 3D and 4D image guidance and active delivery techniques are in relatively early stages of development. The role of digital phantoms in developing clinical treatment planning protocols and as a QA tool will also be highlighted by Dr. Lee from NCI. The symposium will be rounded off by a panel discussion among the Symposium speakers, arguing pro or con the need and readiness for clinical trials in proton and ion therapy. Learning Objectives: To get an update on the current status of clinical trials allowing or mandating proton therapy. Learn about the status of planned clinical trials in the U.S. and worldwide involving ion therapy. Discuss the challenges in the design and QA of clinical trials in particle therapy. Learn about existing and future physical and computational anthropomorphic phantoms for charged particle clinical trial development and support. Research reported in this presentation is supported by the National Cancer Institute of the National; Institutes of Health under Award Number P20CA183640.

60 APPLIED LIFE SCIENCES↗

TU-F-CAMPUS-T-05: Replacement Computational Phantoms to Estimate Dose in Out-Of-Field Organs and Tissues

Purpose: To estimate the absorbed dose in organs and tissues at risk for radiogenic cancer for children receiving photon radiotherapy for localized brain tumors (LBTs) by supplementing their missing body anatomies with those of replacement computational phantoms. Applied beyond the extent of the RT Images collected by computed tomography simulation, these phantoms included RT Image and RT Structure Set objects that encompassed sufficient extents and contours for dosimetric calculations. Method: Nine children, aged 2 to 14 years, who received three-dimensional conformal radiotherapy for low-grade LBTs, were randomly selected for this study under Institutional-Review-Board protocol. Because the extents of their RT Images were cranial only, they were matched for size and sex with patients from a previous study with larger extents and for whom contours of organs at risk for radiogenic cancer had already been delineated. Rigid fusion was performed between the patients’ data and those of the replacement computational phantoms using commercial software. In-field dose was calculated with a clinically-commissioned treatment planning system, and out-of-field dose was estimated with an analytical model. Results: Averaged over all nine children and normalized for a therapeutic dose of 54 Gy prescribed to the PTV, where the PTV is the GTV, the highest mean organ doses were 3.27, 2.41, 1.07, 1.02, 0.24, and 0.24 Gy in the non-tumor remainder, red bone marrow, thyroid, skin, breasts, and lungs, respectively. The mean organ doses ranged by a factor of 3 between the smallest and largest children. Conclusion: For children receiving photon radiotherapy for LBTs, we found their doses in organs at risk for second cancer to be non-negligible, especially in the non-tumor remainder, red bone marrow, thyroid, skin, breasts, and lungs. This study demonstrated the feasibility for patient dosimetry studies to augment missing patient anatomy by applying size- and sex-matched replacement computational phantoms with pre-contoured organs. Funding is in part by the Fogarty International Center award K01TW008409, and the Portland Chapter of the Achievement Rewards for College Scientists. The content is solely the responsibility of the authors, and does not necessarily represent the official views of the sponsors. The authors declare no conflict of interest.

60 APPLIED LIFE SCIENCES↗

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images), image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.

60 APPLIED LIFE SCIENCES↗

WE-AB-204-01: Performance Characterization of Regularized-Reconstruction Algorithm for 90Y PET/CT Images

Purpose: {sup 90}Y PET/CT imaging and quantification have recently been suggested as an approach of treatment verification. However, due to low positron yield (32ppm), the {sup 90}Y-PET/CT images are very noisy. Iterative reconstruction techniques that employ regularization, e.g. block sequential regularized expectation maximization (BSREM) algorithm (recently implemented on GE scanners – QClear™), has the potential to increase quantitative accuracy with lower noise penalty compared to OSEM. Our aim is to investigate the performance of RR algorithms in {sup 90}Y PET/CT studies. Methods: A NEMA IEC phantom filled with 3GBq {sup 90}YCl{sub 2} (to simulate patient treatment) was imaged on GE-D690 for 1800s/bed. The sphere-to-background ratio of 7. The data were reconstructed using OSEM and BSREM with PSF modeling and TOF correction while varying the iterations (IT) from 1–6 with fixed 24subsets. For BSREM, the edge-preservation parameter (γ ) was 2 and the penalty-parameters (β) was varied 350–950. In all cases a post-reconstruction filter of 5.2mm (2pixel) transaxial and standard z-axis were used. Sphere average activity concentration (AC) and background standard deviation (SD) were then calculated from VOIs drawn in the spheres and background. Results: Increasing IT from 1to6, the %SD in OSEM increased from 30% to 80%, whereas %SD in BSREM images increased by <5% for all βs. BSREM with β=350 didn’t offer any improvement over OSEM (convergence of mean achieved at 2 IT, in this study). Increasing β from 350 to 950 reduced the AC accuracy of small spheres (<20mm) by 10% and noise from 40% to 20%, which resulted in CNR increase from 11 to 17. Conclusion: In count-limited studies such as {sup 90}Y PET/CT, BSREM can be used to suppress image noise and increase CNR at the expense of a relatively small decrease of quantitative accuracy. The BSREM parameters need to be optimized for each study depending on the radionuclides and count densities. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA13898 and was also partly supported by General Electric.

60 APPLIED LIFE SCIENCES↗

WE-EF-303-03: A New Aperture-Based Imaging System for Prompt-Gamma Range Verification of Proton Beam Therapy

Purpose: To develop and characterize a novel aperture-based imaging system for high-energy gamma-rays. This collimated system will provide 2-dimensional imaging capability for verification of proton beam range and Bragg peak dose via prompt-gamma detection. Methods: A multi-knife-edge slit collimator has been designed, constructed, and characterized via simulations and experimental measurements. The 20×20×7.5 cm{sup 3} tungsten collimator and accompanying LSO scintillation detector were simulated using the TOPAS Geant4 -based Monte Carlo package. Iterative reconstruction methods were combined with point response functions to characterize the imaging performance of the system. The response of the system has begun to be characterized experimentally as well, using 2.6 MeV gamma-rays from Th-228. Results: Both simulation and experimental results indicate that this collimated system provides 2-D imaging capability in the energy range of interest for prompt-gamma dose verification. In the current configuration, with collimator to source distance of 13 cm, image reconstruction of point sources resulted in spatial resolution (FWHM) of approximately 4 mm in both x-and y-directions in the imaging plane. The accuracy of positioning the point sources is less than 1 mm. Conclusion: This work has characterized, via simulation and measurements, a novel multi-knife-edge slit collimator in front of a more conventional position-sensitive LSO scintillator detector. The multi-slit pattern is designed to increase detection efficiency and provide spatial information in 2-dimensions -- an improvement over a single-slit collimator design. The thickness and density of the collimator will allow this detection system to perform well in an environment with high gamma flux, while ultimately providing peak determination accuracy on the order of 1 mm. This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award Number: DE-NA0000979 through the Nuclear Science and Security Consortium.

60 APPLIED LIFE SCIENCES↗

WE-EF-210-06: Ultrasound 2D Strain Measurement of Radiation-Induced Toxicity: Phantom and Ex Vivo Experiments

Purpose: Radiation-induced fibrosis is a common long-term complication affecting many patients following cancer radiotherapy. Standard clinical assessment of subcutaneous fibrosis is subjective and often limited to visual inspection and palpation. Ultrasound strain imaging describes the compressibility (elasticity) of biological tissues. This study’s purpose is to develop a quantitative ultrasound strain imaging that can consistently and accurately characterize radiation-induce fibrosis. Methods: In this study, we propose a 2D strain imaging method based on deformable image registration. A combined affine and B-spline transformation model is used to calculate the displacement of tissue between pre-stress and post-stress B-mode image sequences. The 2D displacement is estimated through a hybrid image similarity measure metric, which is a combination of the normalized mutual information (NMI) and normalized sum-of-squared-differences (NSSD). And 2D strain is obtained from the gradient of the local displacement. We conducted phantom experiments under various compressions and compared the performance of our proposed method with the standard cross-correlation (CC)- based method using the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. In addition, we conducted ex-vivo beef muscle experiment to further validate the proposed method. Results: For phantom study, the SNR and CNS values of the proposed method were significantly higher than those calculated from the CC-based method under different strains. The SNR and CNR increased by a factor of 1.9 and 2.7 comparing to the CC-based method. For the ex-vivo experiment, the CC-based method failed to work due to large deformation (6.7%), while our proposed method could accurately detect the stiffness change. Conclusion: We have developed a 2D strain imaging technique based on the deformable image registration, validated its accuracy and feasibility with phantom and ex-vivo data. This 2D ultrasound strain imaging technology may be valuable as physicians try to eliminate radiation-induce fibrosis and improve the therapeutic ratio of cancer radiotherapy. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.

60 APPLIED LIFE SCIENCES↗

WE-EF-210-08: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in Ultrasound Images Using Patch-Based Anatomical Feature

Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage. During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a useful tool for image-guided interventions in prostate-cancer diagnosis and treatment. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.

60 APPLIED LIFE SCIENCES↗

WE-G-207-06: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Physical Phantom and Clinical Patient Images

Purpose: Respiratory-correlated cone-beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra- and inter-fractional changes. We develop a method to generate patient-specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery. Methods: Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCA coefficients iteratively through comparison of the cone-beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions. Results: 4DCBCT-based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time. Conclusion: This study showed the feasibility of deriving 4DCBCT-based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT-based motion models were found to account for the 3D non-rigid motion of the patient anatomy during treatment and have the potential to localize tumor and other patient anatomical structures at treatment time even when inter-fractional changes occur. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc., Palo Alto, CA. The project was also supported, in part, by Award Number R21CA156068 from the National Cancer Institute.

60 APPLIED LIFE SCIENCES↗

SU-C-202-05: Pilot Study of Online Treatment Evaluation and Adaptive Re-Planning for Laryngeal SBRT

Purpose: We have instigated a phase I trial of 5-fraction stereotactic body radiotherapy (SBRT) for advanced-stage laryngeal cancer. We conducted this pilot dosimetric study to confirm the potential utility of online adaptive re-planning to preserve treatment quality. Methods: Ten cases of larynx cancer were evaluated. Baseline and daily SBRT treatment plans were generated per trial protocol. Daily volumetric images were acquired prior to every fraction of treatment. Reference simulation CT images were deformably registered to daily volumetric images using Eclipse. Planning contours were then deformably propagated to daily images. Reference SBRT plans were directly copied to calculate delivered dose distributions on deformed reference CT images. In-house software platform has been developed to calculate cumulative dose over a course of treatment in four steps: 1) deforming delivered dose grid to reference CT images using deformation information exported from Eclipse; 2) generating tetrahedrons using deformed dose grid as vertices; 3) resampling dose to a high resolution within every tetrahedron; 4) calculating dose-volume histograms. Our inhouse software was benchmarked with a commercial software, Mirada. Results: In all ten cases including 49 fractions of treatments, delivered daily doses were completely evaluated and treatment could be re-planned within 10 minutes. Prescription dose coverage of PTV was less than intended in 53% of fractions of treatment (mean: 94%, range: 84%–98%) while minimum coverage of CTV and GTV was 94% and 97%, respectively. Maximum bystander point dose limits to arytenoids, parotids, and spinal cord remained respected in all cases, although variances in carotid artery doses were observed in a minority of cases. Conclusion: Although GTV and CTV coverage is preserved by in-room 3D image guidance of larynx SBRT, PTV coverage can vary significantly from intended plans. Online adaptive treatment evaluation and re-planning is potentially necessary and our procedure is clinically applicable to fully preserve treatment quality. This project is supported by CPRIT Individual Investigator Research Award RP150386.

60 APPLIED LIFE SCIENCES↗

SU-D-201-06: Remote Dosmetric Auditing of VMAT Deliveries for Clinical Trials Using EPID

Purpose: To develop a method for remote dosimetric auditing the delivery of VMAT using EPID which allows for simple, inexpensive and time efficient dosimetric credentialing for clinical trials. Methods: Remote centers are provided with CT datasets and planning guidelines to produce VMAT plans for a head and neck and a post-prostatectomy treatment. Plans are transferred in the planning system to two virtual water equivalent phantoms, one flat and one cylindrical. Cine images are acquired during VMAT delivery to the EPID in air with gantry angle recorded in image headers. Centers also deliver provided calibration plans to enable EPID signal to dose conversion, determination of the central axis, and correction of EPID sag prior to analysis. EPID images and planned doses are sent to the central site. EPID cine images are converted to dose in the virtual phantoms using an established backprojection method (King et al., Med.Phys. 2012) with EPID backscatter correction. Individual arcs (with gantry angles collapsed to zero) are evaluated at 10 cm depth in the flat phantom using 2D gamma, and total doses are evaluated in the cylindrical phantom using 3D gamma. Results are reported for criteria of 3%,3mm, 3%,2mm and 2%,2mm for all points greater than 10% of global maximum. Results: The pilot study for Varian centers has commenced, and three centers have been audited for head and neck plans and two for post-prostatectomy plans to date. The mean pass rate for arc-by-arc 2D analysis at 3%,3mm is 99.5% and for 3D analysis is 95.8%. A method for Elekta linacs using an inclinometer for gantry angle information is under development. Conclusion: Preliminary results for this new method are promising. The method takes advantage of EPID equipment available at most centers and clinically established software to provide a feasible, low cost solution to credentialing centers for clinical trials. Funding has been provided from Calvary Mater Newcastle Department of Radiation Oncology, TROG Cancer Research and the University of Newcastle. Kimberley Legge is the recipient of an Australian Postgraduate Award. Narges Miri is a recipient of a University of Newcastle postgraduate scholarship.

60 APPLIED LIFE SCIENCES↗

SU-F-R-27: Use Local Shape Descriptor Based On Geodesic Distance to Predict Survival in Non-Small Cell Lung Cancer After Radiotherapy

Purpose: The shape of the Positron Emission Tomography (PET) image represents the heterogeneity of tumor growth in various directions, and thus could be associated with tumor malignancy. We have proposed a median geodesic distance (MGD) to represent the local complexity of the shape and use a normalized MGD (NMGD) to quantify the shape, and found a potential correlation of NMGD to survival in a 20-patient pilot study. This study was to verify the finding in a larger patient cohort. Methods: Geodesic distance of two vertices on a surface is defined as the shortest path on the surface connecting the two vertices. The MGD was calculated for each vertex on the surface to display the local complexity of the shape. The NMGD was determined as: NMGD = 100*standard deviation(MGDs)/mean(MGDs). We applied the NMGD to 40 NSCLC patients who were enrolled in prospective PET image protocols and received radiotherapy. Each patient had a pre-treatment PET scan with the resolution of 4mm*4mm*5mm. Tumors were contoured by a professional radiation oncologist and triangulation meshes were built up based on the contours. Results: The mean and standard deviation of NMGD was 6.4±3.0. The OS was 33.1±16.9 months for low NMGD group, and 15.4±15.6 months for the high NMGD group. The low NMGD group had significant better OS than the high NMGD group (p=0.0013). Conclusion: NMGD could be used as a shape biomarker to predict survival and the MGD could be combined with image texture in future to increase prediction accuracy. This study was supported by Award Number 1R01CA166948 from the NIH and National Cancer Institute.

60 APPLIED LIFE SCIENCES↗

SU-F-R-42: Association of Radiomic and Metabolic Tumor Volumes in Radiation Treatment of Glioblastoma Multiforme

Purpose: High-throughput extraction of imaging and metabolomic quantitative features from MRI and MR Spectroscopy Imaging (MRSI) of Glioblastoma Multiforme (GBM) results in tens of variables per patient. In radiotherapy (RT) of GBM, the relevant metabolic tumor volumes (MTVs) are related to aberrant levels of N-acetyl Aspartate (NAA) and Choline (Cho). Corresponding Clinical Target Volumes (CTVs) for RT planning are based on Contrast Enhancing T1-weighted MRI (CE-T1w) and T2-weighted/Fluid Attenuated Inversion Recovery (FLAIR) MRI. The objective is to build a framework for investigation of associations between imaging, CTV, and MTV features better understanding of the underlying information in the CTVs and dependencies between these volumes. Methods: Necrotic portions, enhancing lesion and edema were manually contoured on T1w/T2w images for 17 GBM patients. CTVs and MTVs for NAA (MTV{sub NAA}) and Cho (MTV{sub Cho}) were constructed. Tumors were scored categorically for ten semantic imaging traits by neuroradiologist. All features were investigated for redundancy. Two-way correlations between imaging and RT/MTV features were visualized as heat maps. Associations between MTV{sub NAA}, MTV{sub Cho} and imaging features were studied using Spearman correlation. Results: 39 imaging features were computed per patient. Half of the imaging traits were replaced with automatically extracted continuous variables. 21 features were extracted from MTVs/CTVs. There were a high number (43) of significant correlations of imaging with CTVs/MTV{sub NAA} while very few (10) significant correlations were with CTVs/MTV{sub Cho}. MTV{sub NAA} was found to be closely associated with MRI volumes, MTV{sub Cho} remains elusive for characterization with imaging. Conclusion: A framework for investigation of co-dependency between MRI and RT/metabolic features is established. A series of semantic imaging traits were replaced with automatically extracted continuous variables. The approach will allow for exploration of relationships between sizes and intersection of imaging features of tumors, RT volumes, metabolite concentrations and comparing those to therapy outcome, quality of life evaluation and overall survival rate. This publication was supported by Grant 10BN03 from Bankhead Coley Cancer Research Program, R01EB000822, R01EB016064, and R01CA172210 from the National Institutes of Health, and Indo-US Science & Technology Forum award #20-2009. Bhaswati Roy received financial assistance from University Grant Commission, New Delhi, India.

60 APPLIED LIFE SCIENCES↗

SU-F-I-01: Normalized Mean Glandular Dose Values for Dedicated Breast CT Using Realistic Breast-Shaped Phantoms

Purpose: To estimate normalized mean glandular dose values for dedicated breast CT (DgN-CT) using breast CT-derived phantoms and compare to estimations using cylindrical phantoms. Methods: Segmented breast CT (bCT) volume data sets (N=219) were used to measure effective diameter profiles and were grouped into quintiles by volume. The profiles were averaged within each quintile to represent the range of breast sizes found clinically. These profiles were then used to generate five voxelized computational phantoms (V1, V2, V3, V4, V5 for the small to large phantom sizes, respectively), and loaded into the MCNP6 lattice geometry to simulate normalized mean glandular dose coefficients (DgN-CT) using the system specifications of the Doheny-prototype bCT scanner in our laboratory. The DgN-CT coefficients derived from the bCT-derived breast-shaped phantoms were compared to those generated using a simpler cylindrical phantom using a constant volume, and the following constraints: (1) Length=1.5*radius; (2) radius determined at chest wall (Rcw), and (3) radius determined at the phantom center-of-mass (Rcm). Results: The change in Dg-NCT coefficients averaged across all phantom sizes, was - 0.5%, 19.8%, and 1.3%, for constraints 1–3, respectively. This suggests that the cylindrical assumption is a good approximation if the radius is taken at the breast center-of-mass, but using the radius at the chest wall results in an underestimation of the glandular dose. Conclusion: The DgN-CT coefficients for bCT-derived phantoms were compared against the assumption of a cylindrical phantom and proved to be essentially equivalent when the cylinder radius was set to r=1.5/L or Rcm. While this suggests that for dosimetry applications a patient’s breast can be approximated as a cylinder (if the correct radius is applied), this assumes a homogenous composition of breast tissue and the results may be different if the realistic heterogeneous distribution of glandular tissue is considered. Research reported in this paper was supported in part by the National Cancer Institute of the National Institutes of Health under award R01CA181081. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institue of Health.

60 APPLIED LIFE SCIENCES↗

SU-F-J-67: Dosimetric Changes During Radiotherapy in Lung Cancer Patients with Atelectasis

Purpose: Large geometric changes which occur during thoracic radiotherapy alter normal anatomy and target position and may induce clinically important dose changes. This study investigates variation of organ-at-risk (OAR) dose caused by atelectasis resolution during radiotherapy. Methods: 3D IMRT treatment plans were obtained for 14 non-small-cell lung cancer patients. Dose of the clinical plan was recalculated on a baseline scan in which lung was collapsed and on a midtreatment scan in which lung re-aeration had occurred. The changes in OAR doses were compared between the two time points. RTOG-0617 and inhouse dose-volume constraints were chosen for investigation and included spinal cord, esophagus, heart, and healthy lung. Results: 17 dose metrics were evaluated. The mean (SD) of change in mean lung dose, from baseline to mid-treatment (average taken across all patients), was 0.2 Gy (2.2 Gy) and ranged from −3.2 Gy to 6.0 Gy. 50% of patients experienced relative changes in mean lung dose of greater than 5% of baseline value. The mean (SD) of changes in heart V{sub 40}, V{sub 45}, and V{sup 60} were 3.2% (3.4%), 3.0% (2.9%), and 1.4% (2.1%), respectively, and were significant for the study cohort (Wilcoxon signed-rank test, p=0.0107 for V{sub 40}, p=0.0052 for V{sub 45}, and p= 0.0353 for V{sub 60}. Ranges in changes of Heart V{sub 40}, V{sub 45}, and V{sub 60} were −1.9% to 8.6%, −1.7% to 7.5%, and −2.1% to 4.5%, respectively. The mean (SD) of changes in Esophagus PRV Dmean and V{sub 60} were 0.3 Gy (3.3 Gy) and 0.8% (7.7%), respectively, and ranged from −4.8 Gy to 6.8 Gy for Dmean and −15.2% to 14.6% for V{sub 60}. Conclusion: Patients with atelectasis present at the start of radiotherapy experience significant increases in heart dose. Substantial increases in mean lung dose also occur in a subset of patients. This work supported by the National Cancer Institute of National Institutes of Health under Award Number R01CA166119. Disclosures: Phillips Medical systems (Hugo, Weiss), National Institutes of Health (Hugo, Weiss, Christensen), and Roger Koch (Christensen) support, UpToDate (Weiss) royalties, and Varian Medical Systems (Hugo, Weiss) license. No potential conflicts of interest.

60 APPLIED LIFE SCIENCES↗

SU-F-T-127: Charged Particle Transport in Condensed Media

Purpose: Provide quality interaction cross sections for charged particle Monte Carlo (MC) track structure codes and evaluate low energy electron transport in condensed media. Methods: MC methods and codes are often used to model or simulate charged particle radiation transport in matter. Detailed (or event-by-event) track structure simulations are of special interest for the modeling of the physical and chemical stages of radiation action with matter and the initial radiation damage to biological systems. They require reliable interaction cross sections of all radiation qualities considered (e.g., electrons, protons, alpha particles, light and heavy ions) with the target material under consideration, mainly in the condensed phase, including liquids and solids. Interaction cross sections are calculated using the dielectric formalism, a mixture of first principles, theoretical modeling and experimental information for bulk and surface transport and implemented into MC track structure codes. Secondary electron emission yields from amorphous solid water (ASW) and thin metal foils (copper and gold) after fast proton impact are simulated and measured experimentally. Results: After considering different transport models for bulk and surface transport and a careful modeling of the experimental geometry, simulated secondary electron emission yields follow the trends of experimental data well. Furthermore, yields for electron emissions below 50 eV are sensitive to differential elastic scattering cross sections. Conclusion: Low-energy electron transport in condensed media is still a challenge for detailed track structure simulation codes. Interaction cross-sections, transport models, and target geometry need to be considered adequately. The research was funded in part by NSF Major Research Instrumentation Program 2009, Award Number: 0923270 and by NIH/NCI R01 CA93351.

60 APPLIED LIFE SCIENCES↗