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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-G-BRC-01: A Data-Driven Pre-Optimization Method for Prediction of Achievability of Clinical Objectives in IMRT

Purpose: We propose a novel data-driven method to predict the achievability of clinical objectives upfront before invoking the IMRT optimization. Methods: A new metric called “Geometric Complexity (GC)” is used to estimate the achievability of clinical objectives. Here, GC is the measure of the number of “unmodulated” beamlets or rays that intersect the Region-of-interest (ROI) and the target volume. We first compute the geometric complexity ratio (GCratio) between the GC of a ROI (say, parotid) in a reference plan and the GC of the same ROI in a given plan. The GCratio of a ROI indicates the relative geometric complexity of the ROI as compared to the same ROI in the reference plan. Hence GCratio can be used to predict if a defined clinical objective associated with the ROI can be met by the optimizer for a given case. Basically a higher GCratio indicates a lesser likelihood for the optimizer to achieve the clinical objective defined for a given ROI. Similarly, a lower GCratio indicates a higher likelihood for the optimizer to achieve the clinical objective defined for the given ROI. We have evaluated the proposed method on four Head and Neck cases using Pinnacle3 (version 9.10.0) Treatment Planning System (TPS). Results: Out of the total of 28 clinical objectives from four head and neck cases included in the study, 25 were in agreement with the prediction, which implies an agreement of about 85% between predicted and obtained results. The Pearson correlation test shows a positive correlation between predicted and obtained results (Correlation = 0.82, r2 = 0.64, p < 0.005). Conclusion: The study demonstrates the feasibility of the proposed method in head and neck cases for predicting the achievability of clinical objectives with reasonable accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-JeP3-02: A Novel Setup Approach to Improve C-Spine Curvature Reproducibility for Head and Neck Radiotherapy Using Optical Surface Imaging with Two Regions of Interest

Purpose: To develop a novel approach to improve cervical spine (c-spine) curvature reproducibility for head and neck (HN) patients using optical surface imaging (OSI) with two regions of interests (ROIs). Methods: The OSI-guided, two-step setup procedure requires two ROIs: ROI-1 of the shoulders and ROI-2 of the face. The neck can be stretched or squeezed in superior-inferior (SI) direction using a specially-designed sliding head support. We hypothesize that when these two ROIs are aligned, the c-spine should fall into a naturally reproducible position under same setup conditions. An anthropomorphous phantom test was performed to examine neck pitch angles comparing with the calculated angles. Three volunteers participated in the experiments, which start with conventional HN setup using skin markers and room lasers. An OSI image and lateral photo-picture were acquired as the references. In each of the three replicate tests, conventional setup was first applied after volunteers got on the couch. ROI-1 was aligned by moving the body, followed by ROI-2 alignment via adjusting head position and orientation under real-time OSI guidance. A final static OSI image and lateral picture were taken to evaluate both anterior and posterior surface alignments. Three degrees of freedom can be adjusted if an open-face mask was applied, including head SI shift using the sliding head support and pitch-and-roll rotations using a commercial couch extension. Surface alignment was analyzed comparing with conventional setup. Results: The neck pitch angle measured by OSI is consistent with the calculated (0.2±0.6°). Volunteer study illustrated improved c-spine setup reproducibility using OSI comparing with conventional setup. ROI alignments with 2mm/1° tolerance are achieved within 3 minutes. Identical knee support is important to achieve ROI-1 pitch alignment. Conclusion: The feasibility of this novel approach has been demonstrated for c-spine curvature setup reproducibility. Further evaluation is necessary with bony alignment variation in patient studies. This study is in part supported by the NIH (U54CA137788).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-201-06: Impact of Temporal Image Coregistration Methods On 3D Internal Dose Calculations in Targeted Radionuclide Therapy

Purpose: The calculation of 3D internal dose calculations in targeted radionuclide therapy requires the acquisition and temporal coregistration of a serial PET/CT or SPECT/CT images. This work investigates the dosimetric impact of different temporal coregistration methods commonly used for 3D internal dosimetry. Methods: PET/CT images of four mice were acquired at 1, 24, 48, 72, 96, 144 hrs post-injection of {sup 124}I-CLR1404. The therapeutic {sup 131}I-CLR1404 absorbed dose rate (ADR) was calculated at each time point using a Geant4-based MC dosimetry platform using three temporal image coregistration Methods: (1) no coregistration (NC), whole body sequential CT-CT affine coregistration (WBAC), and individual sequential ROI-ROI affine coregistration (IRAC). For NC, only the ROI mean ADR was integrated to obtain ROI mean doses. For WBAC, the CT at each time point was coregistered to a single reference CT. The CT transformations were applied to the corresponding ADR images and the dose was calculated on a voxel-basis within the whole CT volume. For IRAC, each individual ROI was isolated and sequentially coregistered to a single reference ROI. The ROI transformations were applied to the corresponding ADR images and the dose was calculated on a voxel-basis within the ROI volumes. Results: The percent differences in the ROI mean doses were as large as 109%, 88%, and 32%, comparing the WBAC vs. IRAC, NC vs. IRAC, and NC vs. WBAC methods, respectively. The CoV in the mean dose between the all three methods ranged from 2–36%. The pronounced curvature of the spinal cord was not adequately coregistered using WBAC which resulted in large difference between the WBAC and IRAC. Conclusion: The method used for temporal image coregistration can result in large differences in 3D internal dosimetry calculations. Care must be taken to choose the most appropriate method depending on the imaging conditions, clinical site, and specific application. This work is partially funded by NIH Grant R21 CA198392-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Dynamic Contrast-Enhanced MRI in Head-and-Neck Cancer: The Impact of Region of Interest Selection on the Intra- and Interpatient Variability of Pharmacokinetic Parameters

Purpose: Dynamic contrast-enhanced (DCE) MRI-extracted parameters measure tumor microvascular physiology and are usually calculated from an intratumor region of interest (ROI). Optimal ROI delineation is not established. The valid clinical use of DCE-MRI requires that the variation for any given parameter measured within a tumor be less than that observed between tumors in different patients. This work evaluates the impact of tumor ROI selection on the assessment of intra- and interpatient variability. Method and Materials: Head and neck cancer patients received initial targeted therapy (TT) treatment with erlotinib and/or bevacizumab, followed by radiotherapy and concurrent cisplatin with synchronous TT. DCE-MRI data from Baseline and the end of the TT regimen (Lead-In) were analyzed to generate the vascular transfer function (K{sup trans}), the extracellular volume fraction (v{sub e}), and the initial area under the concentration time curve (iAUC{sub 1min}). Four ROI sampling strategies were used: whole tumor or lymph node (Whole), the slice containing the most enhancing voxels (SliceMax), three slices centered in SliceMax (Partial), and the 5% most enhancing contiguous voxels within SliceMax (95Max). The average coefficient of variation (aCV) was calculated to establish intrapatient variability among ROI sets and interpatient variability for each ROI type. The average ratio between each intrapatient CV and the interpatient CV was calculated (aRCV). Results: Baseline primary/nodes aRCVs for different ROIs not including 95Max were, for all three MR parameters, in the range of 0.14-0.24, with Lead-In values between 0.09 and 0.2, meaning a low intrapatient vs. interpatient variation. For 95Max, intrapatient CVs approximated interpatient CVs, meaning similar data dispersion and higher aRCVs (0.6-1.27 for baseline) and 0.54-0.95 for Lead-In. Conclusion: Distinction between different patient's primary tumors and/or nodes cannot be made using 95Max ROIs. The other three strategies are viable and equivalent for using DCE-MRI to measure head and neck cancer physiology.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Are State-Sponsored New Radiation Therapy Facilities Economically Viable in Low- and Middle-Income Countries?

Purpose: The economic viability of establishing a state-funded radiation therapy (RT) infrastructure in low- and middle-income countries (LMICs) in accordance with the World Bank definition has been assessed through computation of a return on investment (ROI). Methods and Materials: Of the 139 LMICs, 100 were evaluated according to their RT facilities, gross national income (GNI) per capita, and employment/population ratio. The assumption was an investment of US$5 million for a basic RT center able to treat 1000 patients annually. The national breakeven points and percentage of ROI (%ROI) were calculated according to the GNI per capita and patient survival rates of 10% to 50% at 2 years. It was assumed that 50% of these patients would be of working age and that, if employed and able to work after treatment, they would contribute to the country's GNI for at least 2 years. The cumulative GNI after attaining the breakeven point until the end of the 15-year lifespan of the teletherapy unit was calculated to estimate the %ROI. The recurring and overhead costs were assumed to vary from 5.5% to 15% of the capital investment. Results: The %ROI was dependent on the GNI per capita, employment/population ratio and 2-year patient survival (all P<.001). Accordingly, none of the low-income countries would attain an ROI. If 50% of the patients survived for 2 years, the %ROI in the lower-middle and upper-middle income countries could range from 0% to 159.9% and 11.2% to 844.7%, respectively. Patient user fees to offset recurring and overhead costs could vary from “nil” to US$750, depending on state subsidies. Conclusions: Countries with a greater GNI per capita, higher employment/population ratio, and better survival could achieve a faster breakeven point, resulting in a higher %ROI. Additional factors such as user fees have also been considered. These can be tailored to the patient's ability to pay to cover the recurring costs. Certain pragmatic steps that could be undertaken to address these issues are discussed in the present study.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Automated flaw detection scheme for cast austenitic stainless steel weld specimens using Hilbert-Huang transform of ultrasonic phased array data

The objective of this work is to develop processing algorithms to detect and localize flaws using ultrasonic phased-array data. Data was collected on cast austenitic stainless stell (CASS) weld specimens onloan from the U.S. nuclear power industry' Pressurized Walter Reactor Owners Group (PWROG) traveling specimen set. Each specimen consists of a centrifugally cast stainless stell (CCSS) pipe section welded to a statically cst(SCSS) or wrought (WRSS) section. The paper presents a novel automated flaw detection and localization scheme using low frequency ultrasonic phased array inspection singals from the weld and heat affected zone of the based materials. The major steps of the overall scheme are preprocessing and region of interest (ROI) detection followed by the Hilbert-Huang transform (HHT) of A-scans in the detected ROIs. HHT offers time-frequency-energy distribution for each ROI. The Accumulation of energy in a particular frequency band is used as a classification feature for the particular ROI.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-I-39: Combining Conventional Tomographic Imaging Strategy and Interior Tomography for Low Dose Dual-Energy CT (DECT)

Purpose: Dual-energy CT (DECT) affords quantitative information of tissue density and provides a new dimension for disease diagnosis and treatment planning. The technique, however, increases the imaging dose because of the doubled scans, and thus hinders its widespread clinical applications. The purpose of this work is to develop a novel hybrid DECT image acquisition and reconstruction strategy, in which one of the energies is dealt by interior tomography while the other one is obtained using conventional tomography approach. Methods: In the proposed hybrid imaging strategy, the projection data of one of the energies (e.g., high-energy) were acquired and processed in an interior scanning model, whereas the other energy in the conventional tomographic approach. It known that, if the ROI is piecewise constant or polynomial, the interior ROI can be reconstructed with TV or HOT minimization. Here we extend the TV based interior reconstruction method into dual-energy situation. The ROI images so obtained were overlaid in the context of conventional CT of the companion energy. A material based composition in ROI was used in the proposed reconstruction framework. Results: In the simulation experiment with a diagnostic DECT geometry and energies, we were able to derive the densities of soft-tissues and bones in the ROI with high fidelity. In the experimental CBCT study, both kV and MV data were collected using the on-board kV and MV imaging system. The MV data were truncated only across the ROI. Using the interior tomography reconstruction above, we were able to obtain the ROI images as that obtained using un-truncated MV data with known tissue densities. Conclusion: The proposed DECT imaging strategy provides an effective way to extract tissue density information in the ROI and in the context of anatomical images of CT imaging, with much reduced imaging dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-202-03: Statistical Segmentation On Quantitative CT for Assessing Spatial Tumor Response During Radiation Therapy Delivery

Purpose: Develop a method to segment regions of interest (ROIs) in tumor with statistically similar Hounsfield unit (HU) values and/or HU changes during chemoradiation therapy (CRT) delivery, to assess spatial tumor treatment response based on daily CTs during CRT delivery. Methods: Generate a three region map of ROIs with differential HUs, by sampling neighboring voxels around a selected voxel and comparing to the mean of the entire ROI using a t-test. The cumulative distribution function, P, is calculated from the t-test. The P value is assigned to be the value at the selected voxel, and this is repeated over all voxels in the initial ROI. Three regions are defined as: (1-P) < 0.00001 (mid region), and 0.00001 < (1-P) (mean greater than baseline and mean lower than baseline). The test is then expanded to compare daily CT sets acquired during routine CT-guided RT delivery using a CT-on-rails. The first fraction CT is used as the baseline for comparison. We tested 15 pancreatic head tumor cases undergoing CRT, to identify the ROIs and changes corresponding to normal, fibrotic, and tumor tissue. The obtained ROIs were compared with MRI-ADC maps acquired pre- and post-CRT. Results: The ROIs in 13 out of 15 patients’ first fraction CTs and pre-CRT MRIs matched the general region and slices covered, as well as in 6 out of the 9 patients with post-CRT MRIs. The high HU region designated by the t-test was seen to correlate with the tumor region in MR, and these ROIs are positioned within the same region over the course of treatment. In patients with poorly delineated tumors in MR, the t-test was inconclusive. Conclusion: The proposed statistical segmentation technique shows the potential to identify regions in tumor with differential HUs and HU changes during CRT delivery for patients with pancreas head cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Inter-reader agreement of magnetic resonance imaging proton density fat fraction and its longitudinal change in a clinical trial of adults with nonalcoholic steatohepatitis

Purpose: To determine the inter-reader agreement of magnetic resonance imaging proton density fat fraction (PDFF) and its longitudinal change in a clinical trial of adults with nonalcoholic steatohepatitis (NASH). Study type: We performed a secondary analysis of a placebo-controlled randomized clinical trial of a bile acid sequestrant in 45 adults with NASH. A six-echo spoiled gradient-recalled-echo magnitude-based fat quantification technique was performed at 3 T. Three independent readers measured MRI-PDFF by placing one primary and two additional regions of interest (ROIs) in each segment at both time points. Cross-sectional agreement between the three readers was evaluated using intra-class correlation coefficients (ICCs) and coefficients of variation (CV). Additionally, we used Bland–Altman analyses to examine pairwise agreement between the three readers at baseline, end of treatment (EOT), and for longitudinal change. Results: Using all ROIs by all readers, mean PDFF at baseline, at EOT, and mean change in PDFF was 16.1%, 16.0%, and 0.07%, respectively. The 27-ROI PDFF measurements had 0.998 ICC and 1.8% CV at baseline, 0.998 ICC and 1.8% CV at EOT, and 0.997 ICC for longitudinal change. The 9-ROI PDFF measurements had corresponding values of 0.997 and 2.6%, 0.996 and 2.4%, and 0.994. Using 27 ROIs, the magnitude of the bias between readers for whole-liver PDFF measurement ranged from 0.03% to 0.06% points at baseline, 0.01% to 0.07% points at EOT, and 0.01% to 0.02% points for longitudinal change. Conclusion: Inter-reader agreement for measuring whole-liver PDFF and its longitudinal change is high. 9-ROI measurements have only slightly lower agreement than 27-ROI measurements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Chemosaturation Percutaneous Hepatic Perfusion (CS-PHP) with Melphalan: Evaluation of 2D-Perfusion Angiography (2D-PA) for Leakage Detection of the Venous Double-Balloon Catheter

Purpose: To evaluate the feasibility of 2D-perfusion angiography (2D-PA) for detecting leakage of the double-balloon catheter used for chemosaturation percutaneous hepatic perfusion (CS-PHP). Materials and Methods: Overall, 112 CS-PHP (09/2015-09/2018) in 52 patients were retrospectively screened for leakage alongside the double-balloon catheter on standard venograms. Finally, 18 procedures with visually detected leakage were included. Fifteen consecutive procedures without leakage served as control. To evaluate 2D-PA for leakage detection, the acquired digital subtraction venograms were post-processed. For each balloon, two different target ROIs were evaluated to assess a possible impact of localization and shape of the ROIs. Time to peak (TTP), peak density (PD), area under the curve (AUC), and ratios of target ROI/reference ROIs (PD{sub tROI}/PD{sub REF}; AUC{sub tROI}/AUC{sub REF}; and TTP{sub tROI}/TTP{sub REF}) were calculated. Results: Leakages were located as follows: 15/18 cranial and 3/18 caudal. At the cranial balloon both ROIs showed a significant decrease in PD{sub tROI}/PD{sub REF} and AUC{sub tROI}/AUC{sub REF} (ROI1: p < 0.0001; p < 0.0001; ROI2: p < 0.0001; p < 0.0001) and a significant increase in TTP{sub tROI}/TTP{sub REF} (ROI1: p = 0.0009; ROI2: p = 0.0003) after double-balloon correction. Following balloon adjustment, the 2D-PA ratios (PD and AUC) of the tested ROIs differed significantly (p < 0.05). The inter-individual comparison of the 2D-PA parameters of the group with leakage before balloon correction and the non-leakage group showed significantly different 2D-PA values for the cranial balloon in both ROIs (p < 0.05). No significant differences were found for the caudal balloon. Conclusion: 2D-PA provides a feasible tool for detecting leakages alongside the cranial portion of the double-balloon catheter used in CS-PHP. The shape and position of the ROIs used to assess perfusion and flow have an impact on the measurements.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

eBits: Compact stream of mesh refinements for remote visualization

Here, we focus on applications where a remote client needs to visualize or process a complex, manifold triangle mesh, M , but only in a relatively small, user controlled, Region of Interest (RoI) at a time. The client first downloads a coarse base mesh , pre-computed on the server via a series of simplification passes on M , one per Level of Detail (LoD), each pass identifying an independent set of triangles, collapsing them, and, for each collapse, storing, in a Vertex Expansion Record (VER), the information needed to reverse the collapse. On each client initiated RoI modification request, the server pushes to the client a selected subset of these VERs, which, when decoded and applied to refine the mesh locally, ensure that the portion in the RoI is always at full resolution. The eBits approach proposed here offers state of the art compression ratios (using less than 2.5 bits per new full resolution RoI triangle when the RoI has more than 2000 vertices to transmit the connectivity for the selective refinements) and fine-grain control (allowing the user to adjust the RoI by small increments). The effectiveness of eBits results from several novel ideas and novel variations of previous solutions. We represent the VERs using persistent labels so that they can be applied in different orders within a given LoD. The server maintains a shadow copy of the client’s mesh. To avoid sending IDs identifying which vertices should be expanded, we either transmit, for each new vertex, a compact encoding of its death tag –the LoD at which it will be expanded if it lies in the Rol–or transmit vertex masks for the RoI and its neighboring vertices. We also propose a three-step simplification that reduces the overall transmission cost by increasing both the simplification effectiveness and the regularity of the valences in the resulting meshes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Functionalized metal organic frameworks for effective capture of radioactive organic iodides

Highly efficient capture of radioactive organic iodides (ROIs) from off-gas mixtures remains a substantial challenge for nuclear waste treatment. Current materials utilized for ROI sequestration suffer from low capacity, high cost ( e.g. use of noble metals), and poor recyclability. Recently, we have developed a new strategy to tackle this challenge by functionalizing MOF materials with tertiary amines to create molecular traps for the effective capture and removal of ROIs ( e.g. radioactive methyl iodide) from nuclear wastes. To further enhance the uptake capacity and performance of CH 3 I capture by ROI molecular traps, herein, we carry out a systematic study to investigate the effect of different amine molecules on ROI capture. The results demonstrate a record-high CH 3 I saturation uptake capacity of 80% for MIL-101–Cr–DMEDA at 150 °C, which is 5.3 times that of Ag 0 @MOR (15 wt%), a leading adsorbent material for capturing ROIs during nuclear fuel reprocessing. Furthermore, the CH 3 I decontamination factors (DFs) for MIL-101–Cr–DMEDA are as high as 5000 under simulated reprocessing conditions, largely exceeding that of facility regulatory requirements (DF = 3000). In addition, MIL-101–Cr–DMEDA can be recycled without loss of capacity, illustrating yet another advantage compared to known industrial adsorbents, which are typically of a “single-use” nature. Our analysis also shows that both physisorption and chemisorption of CH 3 I occur at the three amine-grafted MOFs. While chemisorption takes place at the amine functionalized sites, the amount of physisorption correlates with the MOF porosity. A possible binding site of amine–CH 3 I interaction has been identified via an in situ IR spectroscopic study. The results suggest that CH 3 I interacts strongly and directly with the tertiary nitrogen of the amine molecules. The CH 3 I uptake amount decreases as the amine chain length increases, in trend with the decreasing pore space of the corresponding framework. The strategy to build MOF-based molecular traps developed in this work not only leads to a new record-high performance for ROI capture, but also offers an effective way of systematically tuning the porosity by varying the length of functionalized amine molecules. This study also demonstrates that MOFs represent a promising new platform for selective capture and removal of radioactive nuclear waste.

Chemistry↗
DOE OSTI2013

Development of a dynamic quality assurance testing protocol for multisite clinical trial DCE-CT accreditation

Purpose: Credentialing can have an impact on whether or not a clinical trial produces useful quality data that is comparable between various institutions and scanners. With the recent increase of dynamic contrast enhanced-computed tomography (DCE-CT) usage as a companion biomarker in clinical trials, effective quality assurance, and control methods are required to ensure there is minimal deviation in the results between different scanners and protocols at various institutions. This paper attempts to address this problem by utilizing a dynamic flow imaging phantom to develop and evaluate a DCE-CT quality assurance (QA) protocol.Methods: A previously designed flow phantom, capable of producing predictable and reproducible time concentration curves from contrast injection was fully validated and then utilized to design a DCE-CT QA protocol. The QA protocol involved a set of quantitative metrics including injected and total mass error, as well as goodness of fit comparison to the known truth concentration curves. An additional region of interest (ROI) sensitivity analysis was also developed to provide additional details on intrascanner variability and determine appropriate ROI sizes for quantitative analysis. Both the QA protocol and ROI sensitivity analysis were utilized to test variations in DCE-CT results using different imaging parameters (tube voltage and current) as well as alternate reconstruction methods and imaging techniques. The developed QA protocol and ROI sensitivity analysis was then applied at three institutions that were part of clinical trial involving DCE-CT and results were compared.Results: The inherent specificity of robustness of the phantom was determined through calculation of the total intraday variability and determined to be less than 2.2 ± 1.1% (total calculated output contrast mass error) with a goodness of fit (R{sup 2}) of greater than 0.99 ± 0.0035 (n= 10). The DCE-CT QA protocol was capable of detecting significant deviations from the expected phantom result when scanning at low mAs and low kVp in terms of quantitative metrics (Injected Mass Error 15.4%), goodness of fit (R{sup 2}) of 0.91, and ROI sensitivity (increase in minimum input function ROI radius by 146 ± 86%). These tests also confirmed that the ASIR reconstruction process was beneficial in reducing noise without substantially increasing partial volume effects and that vendor specific modes (e.g., axial shuttle) did not significantly affect the phantom results. The phantom and QA protocol were finally able to quickly (<90 min) and successfully validate the DCE-CT imaging protocol utilized at the three separate institutions of a multicenter clinical trial; thereby enhancing the confidence in the patient data collected.Conclusions: A DCE QA protocol was developed that, in combination with a dynamic multimodality flow phantom, allows the intrascanner variability to be separated from other sources of variability such as the impact of injection protocol and ROI selection. This provides a valuable resource that can be utilized at various clinical trial institutions to test conformance with imaging protocols and accuracy requirements as well as ensure that the scanners are performing as expected for dynamic scans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography

Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-497: Semi-Automated in Vivo Radiochromic Film Dosimetry Using a Novel Image Processing Algorithm

Purpose: To validate an automated image processing algorithm designed to detect the center of radiochromic film used for in vivo film dosimetry against the current gold standard of manual selection. Methods: An image processing algorithm was developed to automatically select the region of interest (ROI) in *.tiff images that contain multiple pieces of radiochromic film (0.5x1.3cm{sup 2}). After a user has linked a calibration file to the processing algorithm and selected a *.tiff file for processing, an ROI is automatically detected for all films by a combination of thresholding and erosion, which removes edges and any additional markings for orientation. Calibration is applied to the mean pixel values from the ROIs and a *.tiff image is output displaying the original image with an overlay of the ROIs and the measured doses. Validation of the algorithm was determined by comparing in vivo dose determined using the current gold standard (manually drawn ROIs) versus automated ROIs for n=420 scanned films. Bland-Altman analysis, paired t-test, and linear regression were performed to demonstrate agreement between the processes. Results: The measured doses ranged from 0.2-886.6cGy. Bland-Altman analysis of the two techniques (automatic minus manual) revealed a bias of -0.28cGy and a 95% confidence interval of (5.5cGy,-6.1cGy). These values demonstrate excellent agreement between the two techniques. Paired t-test results showed no statistical differences between the two techniques, p=0.98. Linear regression with a forced zero intercept demonstrated that Automatic=0.997*Manual, with a Pearson correlation coefficient of 0.999. The minimal differences between the two techniques may be explained by the fact that the hand drawn ROIs were not identical to the automatically selected ones. The average processing time was 6.7seconds in Matlab on an IntelCore2Duo processor. Conclusion: An automated image processing algorithm has been developed and validated, which will help minimize user interaction and processing time of radiochromic film used for in vivo dosimetry.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-F-18C-02: Evaluations of the Noise Power Spectrum of a CT Iterative Reconstruction Technique for Radiation Therapy

Purpose: To quantitatively assess the noise power spectrum (NPS) of the new, commercially released CT iterative reconstruction technique, iDose{sup 4} from Philips, to compare it with filtered back-projection techniques (FBP), and to provide clinical practice suggestions for radiation therapy. Methods: A uniform phantom was CT imaged with 120kVp tube potential over a range of mAs (250-3333). The image sets were reconstructed using two reconstruction algorithms (FBP and iDose{sup 4} with noise reduction levels 1, 3, and 6) and three reconstruction filters (standard B, smooth A, and sharp C), after which NPS variations were analyzed and compared on region of interest (ROI) sizes (16×16 to 128×128 pixels), ROI radii (0–65 mm), reconstruction algorithms, reconstruction filters, and mAs. Results: The NPS magnitude and shape depended considerably on ROI size and location for both reconstruction algorithms. Regional noise variance became more stationary as ROI size decreased, minimizing NPS artifacts. The optimal 32×32-pixel ROI size balanced the trade-off between stationary noise and adequate sampling. NPS artifacts were greatest at the center of reconstruction space and decreased with increasing ROI distance from the center. The optimal ROI position was located near the phantom's radial midpoint (∼40mm). For sharper filters, the NPS magnitude and the maximum magnitude frequency increased. Higher dose scans yielded lower NPS magnitudes for both reconstruction algorithms and all filters. Compared to FBP, the iDose{sup 4} algorithm reduced the NPS magnitude while preferentially reducing noise at mid-range spatial frequencies, altering noise texture. This reduction was more significant with increasing iDose{sup 4} noise reduction level. Conclusion: Compared to pixel standard deviation, NPS has greater clinical potential for task-based image quality assessment, describing both the magnitude and spatial frequency characteristics of image noise. While iDose{sup 4} reduces the NPS magnitude more dramatically than FBP, further studies are needed to assess the impacts of noise texture alteration on its clinical usage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

TU-C-12A-12: Differentiating Bone Lesions and Degenerative Joint Disease in NaF PET/CT Scans Using Machine Learning

Purpose: [F-18]NaF PET can be used to image bone metastases; however, tracer uptake in degenerative joint disease (DJD) often appears similar to metastases. This study aims to develop and compare different machine learning algorithms to automatically identify regions of [F-18]NaF scans that correspond to DJD. Methods: 10 metastatic prostate cancer patients received whole body [F-18]NaF PET/CT scans prior to treatment. Image segmentation resulted in 852 ROIs, 69 of which were identified by a nuclear medicine physician as DJD. For all ROIs, various PET and CT textural features were computed. ROIs were divided into training and testing sets used to train eight different machine learning classifiers. Classifiers were evaluated based on receiver operating characteristics area under the curve (AUC), sensitivity, specificity, and positive predictive value (PPV). We also assessed the added value of including CT features in addition to PET features for training classifiers. Results: The training set consisted of 37 DJD ROIs with 475 non-DJD ROIs, and the testing set consisted of 32 DJD ROIs with 308 non-DJD ROIs. Of all classifiers, generalized linear models (GLM), decision forests (DF), and support vector machines (SVM) had the best performance. AUCs of GLM (0.929), DF (0.921), and SVM (0.889) were significantly higher than the other models (p<0.001). GLM and DF, overall, had the best sensitivity, specificity, and PPV, and gave a significantly better performance (p<0.01) than all other models. PET/CT GLM classifiers had higher AUC than just PET or just CT. GLMs built using PET/CT information had superior or comparable sensitivities, specificities and PPVs to just PET or just CT. Conclusion: Machine learning algorithms trained with PET/CT features were able to identify some cases of DJD. GLM outperformed the other classification algorithms. Using PET and CT information together was shown to be superior to using PET or CT features alone. Research supported by the Prostate Cancer Foundation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Harmonic analysis for the characterization and correction of geometric distortion in MRI

Purpose: Magnetic resonance imaging (MRI) is gaining widespread use in radiation therapy planning, patient setup verification, and real-time guidance of radiation delivery. Successful implementation of these technologies relies on the development of simple and efficient methods to characterize and monitor the geometric distortions arising due to system imperfections and gradient nonlinearities. To this end, the authors present the theory and validation of a novel harmonic approach to the quantification of system-related distortions in MRI. Methods: The theory of spatial encoding in MRI is applied to demonstrate that the 3D distortion vector field (DVF) is given by the solution of a second-order boundary value problem (BVP). This BVP is comprised of Laplace’s equation and a limited measurement of the distortion on the boundary of a specified region of interest (ROI). An analytical series expansion solving this BVP within a spherical ROI is obtained, and a statistical uncertainty analysis is performed to determine how random errors in the boundary measurements propagate to the ROI interior. This series expansion is then evaluated to obtain volumetric DVF mappings that are compared to reference data obtained on a 3 T full-body scanner. This validation is performed within two spheres of 20 cm diameter (one centered at the scanner origin and the other offset +3 cm along each of the transverse directions). Initially, a high-order mapping requiring measurements at 5810 boundary points is used. Then, after exploring the impact of the boundary sampling density and the effect of series truncation, a reduced-order mapping requiring measurements at 302 boundary points is evaluated. Results: The volumetric DVF mappings obtained from the harmonic analysis are in good agreement with the reference data. Following distortion correction using the high-order mapping, the authors estimate a reduction in the mean distortion magnitude from 0.86 to 0.42 mm and from 0.93 to 0.39 mm within the central and offset ROIs, respectively. In addition, the fraction of points with a distortion magnitude greater than 1 mm is reduced from 35.6% to 2.8% and from 40.4% to 1.5%, respectively. Similarly, following correction using the reduced-order mapping, the mean distortion magnitude reduces to 0.45–0.42 mm within the central and offset ROIs, and the fraction of points with a distortion magnitude greater than 1 mm is reduced to 2.8% and 1.5%, respectively. Conclusions: A novel harmonic approach to the characterization of system-related distortions in MRI is presented. This method permits a complete and accurate mapping of the DVF within a specified ROI using a limited measurement of the distortion on the ROI boundary. This technique eliminates the requirement to exhaustively sample the DVF at a dense 3D array of points, thereby permitting the design of simple, inexpensive phantoms that may incorporate additional modules for auxiliary quality assurance objectives.

62 RADIOLOGY AND NUCLEAR MEDICINE↗