Engineering topics

Cao, Y

Publications and source records attributed to Cao, Y.

At least 19 records

DOE OSTI2016

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

SU-D-207A-01: Female Pelvic Synthetic CT Generation Based On Joint Shape and Intensity Analysis

Purpose: To develop a method for generating female pelvic synthetic CT (MRCT) images from a single MR scan and evaluate its utility in radiotherapy. Methods: Under IRB-approval, an imaging sequence (T1-VIBE-Dixon) was acquired for 10 patients. This sequence yields 3 useful image volumes of different contrast (“in-phase” T1-weighted, fat and water). A previously published pelvic bone shape model was used to generate a rough bone mask for each patient. A modified fuzzy c-means classification was performed on the multi spectral MR data, with a regularization term that utilizes the prior knowledge provided by the bone mask and addresses the intensity overlap between different tissue types. A weighted sum of classification probabilities with attenuation values yielded MRCT volumes. The mean absolute error (MAE) between MRCT and real CT on various regions was calculated following deformable alignment (Velocity). Intensity modulated Treatment plans based on actual CT and MRCT were made and compared. Results: The average/standard deviation of MAE across 10 patients was 10.1/6.7 HU for muscle, 6.7/4.6 HU for fat, 136.9/53.5 HU for bony tissues under 850 HU (97% of total bone volume), 188.9/119.3 HU for bony tissues above 850 HU and 17.3/13.3 HU for intrapelvic soft tissues. Calculated doses were comparable for plans generated on CT and calculated using MRCT densities or vice versa, with differences in PTV D99% (mean/σ) of (–0.1/0.2 Gy) and (0.3/0.2 Gy), PTV D0.5cc of (–0.3/0.2 Gy) and (–0.4/1.7 Gy). OAR differences were similarly small for comparable structures, with differences in bowel V50Gy of (–0.3/0.2%) and (0.0/0.2%), femur V30Gy of (0.7/1.2%) and (0.2/1.2%), sacrum V20GY of (0.0/0.1%) and (–0.1/1.1%) and mean pelvic V20Gy of (0.0/0.1%) and (0.6/1.8%). Conclusion: MRCT based on a single imaging sequence in the female pelvis is feasible, with acceptably small variations in attenuation estimates and calculated doses to target and critical organs. Work supported by NIHR01EB016079.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-23: Setup Uncertainties for the Lung Stereotactic Body Radiation Therapy

Purpose: The Exactrack X-ray system with six degree-of-freedom (6DoF) adjustment ability can be used for setup of lung stereotactic body radiation therapy. The setup uncertainties from ExacTrack 6D system were analyzed. Methods: The Exactrack X-ray 6D image guided radiotherapy system is used in our clinic. The system is an integration of 2 subsystems: (1): an infrared based optical position system and (2) a radiography kV x-ray imaging system. The infrared system monitors reflective body markers on the patient’s skin to assistant in the initial setup. The radiographic kV devices were used for patient positions verification and adjustment. The position verification was made by fusing the radiographs with the digitally reconstructed radiograph (DRR) images generated by simulation CT images using 6DoF fusion algorithms. Those results were recorded in our system. Gaussian functions were used to fit the data. Results: For 37 lung SBRT patients, the image registration results for the initial setup by using surface markers and for the verifications, were measured. The results were analyzed for 143 treatments. The mean values for the lateral, longitudinal, vertical directions were 0.1, 0.3 and 0.3mm, respectively. The standard deviations for the lateral, longitudinal and vertical directions were 0.62, 0.78 and 0.75mm respectively. The mean values for the rotations around lateral, longitudinal and vertical directions were 0.1, 0.2 and 0.4 degrees respectively, with standard deviations of 0.36, 0.34, and 0.42 degrees. Conclusion: The setup uncertainties for the lung SBRT cases by using Exactrack 6D system were analyzed. The standard deviations of the setup errors were within 1mm for all three directions, and the standard deviations for rotations were within 0.5 degree.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-54: Guidelines to Check Image Registration QA of a Clinical Deformation Registration Software: A Single Institution Preliminary Study

Purpose: The objective of this study is to verify and analyze the accuracy of a clinical deformable image registration (DIR) software. Methods: To test clinical DIR software qualitatively and quantitatively, we focused on lung radiotherapy and analyzed a single (Lung) patient CT scan. Artificial anatomical changes were applied to account for daily variations during the course of treatment including the planning target volume (PTV) and organs at risk (OAR). The primary CT (pCT) and the structure set (pST) was deformed with commercial tool (ImSimQA-Oncology Systems Limited) and after artificial deformation (dCT and dST) sent to another commercial tool (VelocityAI-Varian Medical Systems). In Velocity, the deformed CT and structures (dCT and dST) were inversely deformed back to original primary CT (dbpCT and dbpST). We compared the dbpST and pST structure sets using similarity metrics. Furthermore, a binary deformation field vector (BDF) was created and sent to ImSimQA software for comparison with known “ground truth” deformation vector fields (DVF). Results: An image similarity comparison was made by using “ground truth” DVF and “deformed output” BDF with an output of normalized “cross correlation (CC)” and “mutual information (MI)” in ImSimQA software. Results for the lung case were MI=0.66 and CC=0.99. The artificial structure deformation in both pST and dbpST was analyzed using DICE coefficient, mean distance to conformity (MDC) and deformation field error volume histogram (DFEVH) by comparing them before and after inverse deformation. We have noticed inadequate structure match for CTV, ITV and PTV due to close proximity of heart and overall affected by lung expansion. Conclusion: We have seen similarity between pCT and dbpCT but not so well between pST and dbpST, because of inadequate structure deformation in clinical DIR system. This system based quality assurance test will prepare us for adopting the guidelines of upcoming AAPM task group 132 protocol.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinForms to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-52: Study of Energy Dependent Effect of Dosimetry Systems Used in Therapeutic Soft X-Ray Energy Range

Purpose: To investigate energy dependent effects of different dosimetry systems which can be used as in vivo dosimetry monitoring for intraoperative radiotherapy in therapeutic soft x-ray energy range. Methods: Three dosimetry systems were evaluated in therapeutic soft x-ray energy range: optically stimulated luminescent dosimeter (OSLD) nanoDots, radiochromic EBT2 and EBT3 films. The x-ray photons were produced by a Zeiss Intrabeam 50 kV x-ray radiotherapy system. Solid water and bolus slabs with different thicknesses were used in the process of irradiation. An aluminum filter set was used to measure HVLs of X-rays. Calibration curves were made at different depth of boluses. Results: Half Value Layers at depths of 0, 3, 10, and 20 mm of solid water were measured to represent the energy change versus depth, yielding 0.306, 0.482, 0.865 and 0.901 respectively and indicating nearly unchanged HVL beyond 1 cm depth. The responses of each system at different depths were normalized to the response at 2 cm depth. In film dosimetry, the response is calculated as optical density (OD). The results show that there is nearly the same energy dependence for EBT2 and EBT3. At a HVL of 0.482 mm Al, the relative responses of nanoDots and EBT3 are 0.85 ± 0.04 and 0.89 ± 0.03 compared to those at 0.901 mm Al HVL, respectively, indicating no obvious difference between those two systems within the measurement uncertainty. Conclusion: It was observed that the studied dosimeter response increases about 13% from the x-ray energy of 0.48 mm Al to 0.90 mm Al. Therefore, caution should be exercised in using an appropriate calibration curve, and x-ray beam hardening effect has to be taken into account.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-53: Treatment Planning with Inhomogeneity Correction for Intraoperative Radiotherapy Using KV X-Ray Beams

Purpose: The current standard in dose calculation for intraoperative radiotherapy (IORT) using the ZEISS Intrabeam 50 kV x-ray system is based on depth dose measurements in water and no heterogeneous tissue effect has been taken into account. We propose an algorithm for pre-treatment planning including inhomogeneity correction based on data of depth dose measurements in various tissue phantoms for kV x-rays. Methods: Direct depth dose measurements were made in air, water, inner bone and cortical bone phantoms for the Intrabeam 50 kV x-rays with a needle applicator. The data were modelled by a function of power law combining exponential with different parameters. Those phantom slabs used in the measurements were scanned to obtain CT numbers. The x-ray beam initiated from the source isocenter is ray-traced through tissues. The corresponding doses will be deposited/assigned at different depths. On the boundary of tissue/organ changes, the x-ray beam will be re-traced in new tissue/organ starting at an equivalent depth with the same dose. In principle, a volumetric dose distribution can be generated if enough directional beams are traced. In practice, a several typical rays traced may be adequate in providing estimates of maximum dose to the organ at risk and minimum dose in the target volume. Results: Depth dose measurements and modeling are shown in Figure 1. The dose versus CT number is shown in Figure 2. A computer program has been written for Kypho-IORT planning using those data. A direct measurement through 2 mm solid water, 2 mm inner bone, and 1 mm solid water yields a dose rate of 7.7 Gy/min. Our calculation shows 8.1±0.4 Gy/min, consistent with the measurement within 5%. Conclusion: The proposed method can be used to more accurately calculate the dose by taking into account the heterogeneous effect. The further validation includes comparison with Monte Carlo simulation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-323: A Post-Mastectomy Radiation Therapy Dose Distribution Study Using Nanodots and Films

Purpose: In post-mastectomy radiation therapy (RT), skin dose must be accurately estimated to assess skin reactions such as erythema, desquamation and necrosis. Planning systems cannot always provide accurate dosimetry for target volumes distal to skin. Therefore, in-vivo dosimetry is necessary. A female anthropomorphic phantom was used with optically stimulated luminescence dosimeters (nanoDots) to measure dose to chest wall skin. In addition, EBT2 films was employed to measure dose to left lung and heart in post-mastectomy RT. Methods: Films and nanoDots were calibrated under full buildup conditions at 100cm SAD for 6MV photons. Five pieces of films were placed between slabs of Rando phantom to assess dose to left lung and heart. Two layers of 0.5cm thick bolus were used to cover the whole left chest. Six pairs of nanoDots were placed at medical and lateral aspects on the bolus surface, between the 0.5cm bolus layers, and under the bolus. Three control nanoDots were placed on chest wall to quantify imaging dose. The phantom was CT scanned with all dosimeters in place, and treatment planning was performed with tangential fields (200cGy). All dosimeters were contoured on CT and dose was extracted. NanoDots were read using nanoDot reader and films were scanned using film scanner. The measured and calculated doses were tabulated. Results: Dose to 12 nanoDots were evaluated. Dose variance for surface nanoDots were +3.8%, +2.7%, −5% and −9.8%. Those at lateral positions, with greater beam obliquity had larger variance than the medial positions. A similar trend was observed for other nanoDots (Table1). Point doses from films for heart and the left lung were 112.7cGy and 108.7cGy, with +10.2% and +9.04% deviation from calculated values, respectively. Conclusion: Dosimetry provided by the advanced planning system was verified using NanoDots and films. Both nanoDots and films provided good estimation of dose distribution in post-mastectomy RT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-654: Pacemaker Dose Estimate Using Optically Stimulated Luminescent Dosimeter for Left Breast Intraoperative Radiation Therapy

Purpose: To assess and report the in vivo dose for a patient with a pacemaker being treated in left breast intraoperative radiation therapy (IORT). The ZEISS Intrabeam 50 kVp X-ray beam with a spherical applicator was used. Methods: The optically stimulated luminescent dosimeters (OSLDs) (Landauer nanoDots) were employed and calibrated under the conditions of the Intrabeam 50 kVp X-rays. The nanoDots were placed on the patient at approximately 15 cm away from the lumpectomy cavity both under and above a shield of lead equivalence 0.25 mm (RayShield X-Drape D-110) covering the pacemaker area during IORT with a 5 cm spherical applicator. Results: The skin surface dose near the pacemaker during the IORT with a prescription of 20 Gy was measured as 4.0±0.8 cGy. The dose behind the shield was 0.06±0.01 Gy, demonstrating more than 98% dose reduction. The in vivo skin surface doses during a typical breast IORT at a 4.5 cm spherical applicator surface were further measured at 5, 10, 15, and 20 cm away to be 159±11 cGy, 15±1 cGy, 6.6±0.5 cGy, and 1.8±0.1 cGy, respectively. A power law fit to the dose versus the distance z from the applicator surface yields the dose fall off at the skin surface following z^-2.5, which can be used to estimate skin doses in future cases. The comparison to an extrapolation of depth dose in water reveals an underestimate of far field dose using the manufactory provided data. Conclusion: The study suggests the appropriateness of OSLD as an in vivo skin dosimeter in IORT using the Intrabeam system in a wide dose range. The pacemaker dose measured during the left breast IORT was within a safe limit.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-BRA-01: Abdominal Synthetic CT Generation in Support of Liver SBRT Dose Calculation

Purpose: To demonstrate and validate a technique for generating MRI-derived synthetic CT volumes (MRCTs) in support of adaptive liver SBRT. Methods: Under IRB approval, ten hepatocellular carcinoma patients were scanned using a single MR sequence (T1 Dixon-VIBE), yielding inherently-registered water, fat, and T1-weighted images. Air-containing voxels were identified by intensity thresholding. The envelope of the anterior vertebral bodies was segmented from the fat image by fitting a shape model to vertebral body candidate voxels, then using level sets to expand the contour outward. Fuzzy-C-Means (FCM) was then used to classify each non-air voxel in the image as fat, water, bone, or marrow. Bone and marrow only were classified within the vertebral body envelope. The MRCT was created by integrating the product of the FCM class probability with the assigned class density for each voxel. The resulting MRCTs were deformably aligned with planning CTs and 2-ARC SBRT VMAT plans were optimized on the MRCT density maps. Fluence was copied onto the CT density grids and dose recalculated. Results: The MRCTs faithfully reproduced most of the features visible in the corresponding CT image volumes, with exceptions of ribs and posterior spinous processes. The liver, vertebral bodies, kidneys, spleen and cord all had median HU differences of less than 75 between MRCT and CT images. PTV D99% values had an average 0.2% difference (standard deviation: 0.46%) between calculations on MRCT and CT density grids. The maximum difference in dose to 0.1cc of the PTV was 0.25% (std:0.49%). OAR dose differences were similarly small (mean:0.03Gy, std:0.26Gy). The largest normal tissue complication percentage (NTCP) difference was 1.48% (mean:0.06%, std:0.54%). Conclusions: MRCTs from a single abdominal imaging sequence are promising for use in SBRT dose calculation. Future work will focus on extending models to better define bones in the upper abdomen. Supported by NIHR01EB016079 and NIH1L30CA199594-01.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-D-303-03: Impact of Uncertainty in T1 Measurements On Quantification of Dynamic Contrast Enhanced MRI

Purpose: Quantification of dynamic contrast enhanced (DCE) MRI requires native longitudinal relaxation time (T1) measurement. This study aimed to assess uncertainty in T1 measurements using two different methods. Methods and Materials: Brain MRI scans were performed on a 3T scanner in 9 patients who had low grade/benign tumors and partial brain radiotherapy without chemotherapy at pre-RT, week-3 during RT (wk-3), end-RT, and 1, 6 and 18 months after RT. T1-weighted images were acquired using gradient echo sequences with 1) 2 different flip angles (50 and 150), and 2) 5 variable TRs (100–2000ms). After creating quantitative T1 maps, average T1 was calculated in regions of interest (ROI), which were distant from tumors and received a total of accumulated radiation doses < 5 Gy at wk-3. ROIs included left and right normal Putamen and Thalamus (gray matter: GM), and frontal and parietal white matter (WM). Since there were no significant or even a trend of T1 changes from pre-RT to wk-3 in these ROIs, a relative repeatability coefficient (RC) of T1 as a measure of uncertainty was estimated in each ROI using the data pre-RT and at wk-3. The individual T1 changes at later time points were evaluated compared to the estimated RCs. Results: The 2-flip angle method produced small RCs in GM (9.7–11.7%) but large RCs in WM (12.2–13.6%) compared to the saturation-recovery (SR) method (11.0–17.7% for GM and 7.5–11.2% for WM). More than 81% of individual T1 changes were within T1 uncertainty ranges defined by RCs. Conclusion: Our study suggests that the impact of T1 uncertainty on physiological parameters derived from DCE MRI is not negligible. A short scan with 2 flip angles is able to achieve repeatability of T1 estimates similar to a long scan with 5 different TRs, and is desirable to be integrated in the DCE protocol. Present study was supported by National Institute of Health (NIH) under grant numbers; UO1 CA183848 and RO1 NS064973.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-241: Wavelet-Based Temporal Feature Extraction From DCE-MRI to Identify Sub-Volumes of Low Blood Volume in Head-And-Neck Cancer

Purpose: A previous study showed that large sub-volumes of tumor with low blood volume (BV) (poorly perfused) in head-and-neck (HN) cancers are significantly associated with local-regional failure (LRF) after chemoradiation therapy, and could be targeted with intensified radiation doses. This study aimed to develop an automated and scalable model to extract voxel-wise contrast-enhanced temporal features of dynamic contrastenhanced (DCE) MRI in HN cancers for predicting LRF. Methods: Our model development consists of training and testing stages. The training stage includes preprocessing of individual-voxel DCE curves from tumors for intensity normalization and temporal alignment, temporal feature extraction from the curves, feature selection, and training classifiers. For feature extraction, multiresolution Haar discrete wavelet transformation is applied to each DCE curve to capture temporal contrast-enhanced features. The wavelet coefficients as feature vectors are selected. Support vector machine classifiers are trained to classify tumor voxels having either low or high BV, for which a BV threshold of 7.6% is previously established and used as ground truth. The model is tested by a new dataset. The voxel-wise DCE curves for training and testing were from 14 and 8 patients, respectively. A posterior probability map of the low BV class was created to examine the tumor sub-volume classification. Voxel-wise classification accuracy was computed to evaluate performance of the model. Results: Average classification accuracies were 87.2% for training (10-fold crossvalidation) and 82.5% for testing. The lowest and highest accuracies (patient-wise) were 68.7% and 96.4%, respectively. Posterior probability maps of the low BV class showed the sub-volumes extracted by our model similar to ones defined by the BV maps with most misclassifications occurred near the sub-volume boundaries. Conclusion: This model could be valuable to support adaptive clinical trials with further validation. The framework could be extendable and scalable to extract temporal contrastenhanced features of DCE-MRI in other tumors. We would like to acknowledge NIH for funding support: UO1 CA183848.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-586: Optimal Determination of Tolerance Level for Radiation Dose Delivery Verification in An in Vivo Dosimetry System

Purpose: To statistically determine the optimal tolerance level in the verification of delivery dose compared to the planned dose in an in vivo dosimetry system in radiotherapy. Methods: The LANDAUER MicroSTARii dosimetry system with screened nanoDots (optically stimulated luminescence dosimeters) was used for in vivo dose measurements. Ideally, the measured dose should match with the planned dose and falls within a normal distribution. Any deviation from the normal distribution may be redeemed as a mismatch, therefore a potential sign of the dose misadministration. Randomly mis-positioned nanoDots can yield a continuum background distribution. A percentage difference of the measured dose to its corresponding planned dose (ΔD) can be used to analyze combined data sets for different patients. A model of a Gaussian plus a flat function was used to fit the ΔD distribution. Results: Total 434 nanoDot measurements for breast cancer patients were collected across a period of three months. The fit yields a Gaussian mean of 2.9% and a standard deviation (SD) of 5.3%. The observed shift of the mean from zero is attributed to the machine output bias and calibration of the dosimetry system. A pass interval of −2SD to +2SD was applied and a mismatch background was estimated to be 4.8%. With such a tolerance level, one can expect that 99.99% of patients should pass the verification and at most 0.011% might have a potential dose misadministration that may not be detected after 3 times of repeated measurements. After implementation, a number of new start breast cancer patients were monitored and the measured pass rate is consistent with the model prediction. Conclusion: It is feasible to implement an optimal tolerance level in order to maintain a low limit of potential dose misadministration while still to keep a relatively high pass rate in radiotherapy delivery verification.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

TU-CD-BRB-05: Radiation Damage Signature of White Matter Fiber Bundles Using Diffusion Tensor Imaging (DTI)

Purpose: To develop an automated and scalable approach and identify temporal, spatial and dosimetric patterns of radiation damage of white matter (WM) fibers following partial brain irradiation. Methods: An automated and scalable approach was developed to extract DTI features of 22 major WM fibers from 33 patients with low-grade/benign tumors treated by radiation therapy (RT). DTI scans of the patients were performed pre-RT, 3- and 6-week during RT, and 1, 6 and 18 months after RT. The automated tractography analysis was applied to 198 datasets as: (1) intra-subject registration of longitudinal DTI, (2) spatial normalization of individual-patient DTI to the Johns Hopkins WM Atlas, (3) automatic fiber tracking regulated by the WM Atlas, and (4) segmentation of WM into 22 major tract profiles. Longitudinal percentage changes in fractional anisotropy (FA), and mean, axial and radial diffusivity (MD/AD/RD) of each tract from pre-RT were quantified and correlated to 95%, 90% and 80% percentiles of doses and mean doses received by the tract. Heatmaps were used to identify clusters of significant correlation and reveal temporal, spatial and dosimetric signatures of WM damage. A multivariate linear regression was further carried out to determine influence of clinical factors. Results: Of 22 tracts, AD/MD changes in 12 tracts had significant correlation with doses, especially at 6 and 18 months post-RT, indicating progressive radiation damage after RT. Most interestingly, the DTI-index changes in the elongated tracts were associated with received maximum doses, suggesting a serial-structure behavior; while short association fibers were affected by mean doses, indicating a parallel-structure response. Conclusion: Using an automated DTI-tractography analysis of whole brain WM fibers, we reveal complex radiation damage patterns of WM fibers. Damage in WM fibers that play an important role in the neural network could be associated with late neurocognitive function declines after brain irradiation. NIH NS064973.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-T-638: Evaluation and Comparison of Landauer Microstar (OSLD) Readers

Purpose: To evaluate and compare characteristic performance of a new Landauer nanodot Reader with the previous model. Methods: In order to calibrate and test the reader, a set of nanodots were irradiated using a Varian Truebeam Linac. Solid water slabs and bolus were used in the process of irradiation. Calibration sets of nanodots were irradiated for radiation dose ranges: 0 to 10 and 20 to 1000 cGy, using 6MV photons. Additionally, three sets of nanodots were each irradiated using 6MV, 10MV and 15MV beams. For each beam energy, and selected dose in the range of 3 to 1000 cGy, a pair of nanodots was irradiated and three readings were obtained with both readers. Results: The analysis shows that for 3 photon beam energies and selected ranges of dose, the calculated absorbed dose agrees well with the expected value. The results illustrate that the new Microstar II reader is a highly consistent system and that the repeated readings provide results with a reasonably small standard deviation. For all practical purposes, the response of system is linear for all radiation beam energies. Conclusion: The Microstar II nanodot reader is consistent, accurate, and reliable. The new hardware design and corresponding software contain several advantages over the previous model. The automatic repeat reading mechanism, that helps improve reproducibility and reduce processing time, and the smaller unit size that renders ease of transport, are two of such features. Present study shows that for high dose ranges a polynomial calibration equation provides more consistent results. A 3rd order polynomial calibration curve was used to analyze the readings of dosimeters exposed to high dose range radiation. It was observed that the results show less error compared to those calculated by using linear calibration curves, as provided by Landauer system software for all dose ranges.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

MO-E-12A-01: Quantitative Imaging: Techniques, Applications, and Challenges

The first symposium in the Quantitative Imaging Track focused on the introduction of quantitative imaging (QI) by illustrating the potential of QI in diagnostic and therapeutic applications in research and patient care, highlighting key challenges in implementation of such QI applications, and reviewing QI efforts of selected national and international agencies and organizations, including the FDA, NCI, NIST, and RSNA. This second QI symposium will focus more specifically on the techniques, applications, and challenges of QI. The first talk of the session will focus on modalityagnostic challenges of QI, beginning with challenges of the development and implementation of QI applications in single-center, single-vendor settings and progressing to the challenges encountered in the most general setting of multi-center, multi-vendor settings. The subsequent three talks will focus on specific QI challenges and opportunities in the modalityspecific settings of CT, PET/CT, and MR. Each talk will provide information on modality-specific QI techniques, applications, and challenges, including current efforts focused on solutions to such challenges. Learning Objectives: Understand key general challenges of QI application development and implementation, regardless of modality. Understand selected QI techniques and applications in CT, PET/CT, and MR. Understand challenges, and potential solutions for such challenges, for the applications presented for each modality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-A-BRF-10: Quantification of Subject-Specific Susceptibility-Related Geometric Distortion in Clinical Liver MRI for Radiation Therapy

Purpose: Subject-specific susceptibility-induced B0 inhomogeneity affects the geometric accuracy of MRI images, with potential impact on the accuracy of treatment planning and image guidance. This study quantifies individual distortions for patients with intrahepatic tumors. Methods: Liver MRI scans of 13 patients who were enrolled in an IRB approved study were acquired on a 3T scanner (Skyra, Siemens). Clinical contrast-enhanced images were acquired by a 3D Volume Interpolated Breath-Hold Examination (VIBE) sequence with TE/TR =1.65/4.3ms, voxel size = 2.5×2.5×3mm (axial sets) or 3.5×3.5×5mm (coronal sets), and frequency-encoding (FE) bandwidth of 440Hz/pixel. B0 inhomogeneity was evaluated by acquisition of dual gradient echoes (GRE) with TE1/TE2/TR =4.92/7.38/106ms, a voxel size of 3.5×3.5×3.75mm, a FE bandwidth of 290Hz/pixel and breath-hold. The phase difference maps from the two echoes were unwrapped using a quantitative MRI analysis software package (FSL, FMRIB, Oxford, UK). The resulting calculated B0 inhomogeneity maps (ΔB0 in Hz) were converted to voxel distortion maps in the FE direction (ΔX in mm) corresponding to the VIBE images. Results: Maximum susceptibility-induced distortions were observed in the liver dome near the diaphragm. Using results from coronal VIBE images in this study as examples, we observed clusters of voxels displaced close to or greater than ΔX=3.5mm (440 Hz in ΔB0) in the VIBE images of the liver in 3 patients, and greater than 2 mm but less than 3.5 mm in 12 patients. On average, approximately 14% of imaged liver voxels had distortions ΔX>±1mm (ΔB0>±125Hz) and 1% of the voxels had ΔX>±2mm (ΔB0>±250Hz). Conclusion: Although advanced MRI techniques, like VIBE, permit faster acquisitions allowing for breath-held examinations with limited motion-induced artifacts, this study suggests that localized distortions due to subject-specific susceptibility variations can occur and require additional advanced corrections based on measuring patient-specific B0 inhomogeneity maps. The authors would like to acknowledge funding support from NIH R01EB016079 and NIH/NCI RO1 CA132834.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-A-9A-04: Incorporating Liver Functionality in Radiation Therapy Treatment Planning

Purpose: Liver SBRT patients have both variable pretreatment liver function (e.g., due to degree of cirrhosis and/or prior treatments) and sensitivity to radiation, leading to high variability in potential liver toxicity with similar doses. This work aims to explicitly incorporate liver perfusion into treatment planning to redistribute dose to preserve well-functioning areas without compromising target coverage. Methods: Voxel-based liver perfusion, a measure of functionality, was computed from dynamic contrast-enhanced MRI. Two optimization models with different cost functions subject to the same dose constraints (e.g., minimum target EUD and maximum critical structure EUDs) were compared. The cost functions minimized were EUD (standard model) and functionality-weighted EUD (functional model) to the liver. The resulting treatment plans delivering the same target EUD were compared with respect to their DVHs, their dose wash difference, the average dose delivered to voxels of a particular perfusion level, and change in number of high-/low-functioning voxels receiving a particular dose. Two-dimensional synthetic and three-dimensional clinical examples were studied. Results: The DVHs of all structures of plans from each model were comparable. In contrast, in plans obtained with the functional model, the average dose delivered to high-/low-functioning voxels was lower/higher than in plans obtained with its standard counterpart. The number of high-/low-functioning voxels receiving high/low dose was lower in the plans that considered perfusion in the cost function than in the plans that did not. Redistribution of dose can be observed in the dose wash differences. Conclusion: Liver perfusion can be used during treatment planning potentially to minimize the risk of toxicity during liver SBRT, resulting in better global liver function. The functional model redistributes dose in the standard model from higher to lower functioning voxels, while achieving the same target EUD and satisfying dose limits to critical structures. This project is funded by MCubed and grant R01-CA132834.

60 APPLIED LIFE SCIENCES↗