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At least 1,351 records · Page 75

SU-E-T-265: Development of Dose-To-Water Conversion Models for Pre-Treatment Verification with the New AS1200 Imager

Purpose: To develop and evaluate models for dose verification of flattened (FF) and flattening filter free (FFF) beams for the new Varian aS1200 backscatter-shielded electronic portal imaging device (EPID). Methods: The model converts EPID images to incident energy fluence using deconvolution of EPID scatter kernels and fluence to dose in water using convolution with dose-to-water kernels. Model parameters were optimized using non-transmission EPID images of varying jaw defined field sizes for energies of 6 and 10 MV FF and FFF beams. Energy fluence was obtained from the Acuros planning system and reference dose profiles and output factors were measured at depths of 5, 10, 15 and 20 cm in a water phantom. Images for 34 IMRT fields acquired at 6 and 10 MV FF energy were converted to dose at 10 cm depth in water and compared to treatment planning system dose plane calculations using gamma criteria. Results: Gamma evaluations for the IMRT fields had mean (1 standard deviation) pass rates of 99.4% (0.8%) and mean gamma scores of 0.32 (0.06) with 2%, 2 mm criteria and 10% of maximum dose threshold. Conclusion: The developed model has been shown to be highly accurate for pre-treatment verification with the new aS1200 imager which does not display support-arm backscatter artefact and has improved dosimetric properties. Further investigation of FFF modes is in progress. The model is currently being evaluated at sites for potential clinical release.

60 APPLIED LIFE SCIENCES↗

Improved quality of intrafraction kilovoltage images by triggered readout of unexposed frames

Purpose: The gantry-mounted kilovoltage (kV) imager of modern linear accelerators can be used for real-time tumor localization during radiation treatment delivery. However, the kV image quality often suffers from cross-scatter from the megavoltage (MV) treatment beam. This study investigates readout of unexposed kV frames as a means to improve the kV image quality in a series of experiments and a theoretical model of the observed image quality improvements. Methods: A series of fluoroscopic images were acquired of a solid water phantom with an embedded gold marker and an air cavity with and without simultaneous radiation of the phantom with a 6 MV beam delivered perpendicular to the kV beam with 300 and 600 monitor units per minute (MU/min). An in-house built device triggered readout of zero, one, or multiple unexposed frames between the kV exposures. The unexposed frames contained part of the MV scatter, consequently reducing the amount of MV scatter accumulated in the exposed frames. The image quality with and without unexposed frame readout was quantified as the contrast-to-noise ratio (CNR) of the gold marker and air cavity for a range of imaging frequencies from 1 to 15 Hz. To gain more insight into the observed CNR changes, the image lag of the kV imager was measured and used as input in a simple model that describes the CNR with unexposed frame readout in terms of the contrast, kV noise, and MV noise measured without readout of unexposed frames. Results: Without readout of unexposed kV frames, the quality of intratreatment kV images decreased dramatically with reduced kV frequencies due to MV scatter. The gold marker was only visible for imaging frequencies ≥3 Hz at 300 MU/min and ≥5 Hz for 600 MU/min. Visibility of the air cavity required even higher imaging frequencies. Readout of multiple unexposed frames ensured visibility of both structures at all imaging frequencies and a CNR that was independent of the kV frame rate. The image lag was 12.2%, 2.2%, and 0.9% in the first, second, and third frame after an exposure. The CNR model predicted the CNR with triggered image readout with a mean absolute error of 2.0% for the gold marker. Conclusions: A device that triggers readout of unexposed frames during kV fluoroscopy was built and shown to greatly improve the quality of intratreatment kV images. A simple theoretical model successfully described the CNR improvements with the device.

60 APPLIED LIFE SCIENCES↗

SU-F-R-17: Advancing Glioblastoma Multiforme (GBM) Recurrence Detection with MRI Image Texture Feature Extraction and Machine Learning

Purpose: To test the potential of early Glioblastoma Multiforme (GBM) recurrence detection utilizing image texture pattern analysis in serial MR images post primary treatment intervention. Methods: MR image-sets of six time points prior to the confirmed recurrence diagnosis of a GBM patient were included in this study, with each time point containing T1 pre-contrast, T1 post-contrast, T2-Flair, and T2-TSE images. Eight Gray-level co-occurrence matrix (GLCM) texture features including Contrast, Correlation, Dissimilarity, Energy, Entropy, Homogeneity, Sum-Average, and Variance were calculated from all images, resulting in a total of 32 features at each time point. A confirmed recurrent volume was contoured, along with an adjacent non-recurrent region-of-interest (ROI) and both volumes were propagated to all prior time points via deformable image registration. A support vector machine (SVM) with radial-basis-function kernels was trained on the latest time point prior to the confirmed recurrence to construct a model for recurrence classification. The SVM model was then applied to all prior time points and the volumes classified as recurrence were obtained. Results: An increase in classified volume was observed over time as expected. The size of classified recurrence maintained at a stable level of approximately 0.1 cm{sup 3} up to 272 days prior to confirmation. Noticeable volume increase to 0.44 cm{sup 3} was demonstrated at 96 days prior, followed by significant increase to 1.57 cm{sup 3} at 42 days prior. Visualization of the classified volume shows the merging of recurrence-susceptible region as the volume change became noticeable. Conclusion: Image texture pattern analysis in serial MR images appears to be sensitive to detecting the recurrent GBM a long time before the recurrence is confirmed by a radiologist. The early detection may improve the efficacy of targeted intervention including radiosurgery. More patient cases will be included to create a generalizable classification model applicable to a larger patient cohort. NIH R43CA183390 and R01CA188300.NSF Graduate Research Fellowship DGE-1144087.

60 APPLIED LIFE SCIENCES↗

The orbit and transit prospects for β pictoris b constrained with one milliarcsecond astrometry

A principal scientific goal of the Gemini Planet Imager (GPI) is obtaining milliarcsecond astrometry to constrain exoplanet orbits. However, astrometry of directly imaged exoplanets is subject to biases, systematic errors, and speckle noise. Here, we describe an analytical procedure to forward model the signal of an exoplanet that accounts for both the observing strategy (angular and spectral differential imaging) and the data reduction method (Karhunen–Loève Image Projection algorithm). We use this forward model to measure the position of an exoplanet in a Bayesian framework employing Gaussian processes and Markov-chain Monte Carlo to account for correlated noise. In the case of GPI data on β Pic b, this technique, which we call Bayesian KLIP-FM Astrometry (BKA), outperforms previous techniques and yields 1σ errors at or below the one milliarcsecond level. We validate BKA by fitting a Keplerian orbit to 12 GPI observations along with previous astrometry from other instruments. The statistical properties of the residuals confirm that BKA is accurate and correctly estimates astrometric errors. Our constraints on the orbit of β Pic b firmly rule out the possibility of a transit of the planet at 10-σ significance. However, we confirm that the Hill sphere of β Pic b will transit, giving us a rare chance to probe the circumplanetary environment of a young, evolving exoplanet. As a result, we provide an ephemeris for photometric monitoring of the Hill sphere transit event, which will begin at the start of April in 2017 and finish at the end of January in 2018.

79 ASTRONOMY AND ASTROPHYSICS↗

Tools for Analysis and Visualization of Large Time-Varying CFD Data Sets

In the second year, we continued to built upon and improve our scanline-based direct volume renderer that we developed in the first year of this grant. This extremely general rendering approach can handle regular or irregular grids, including overlapping multiple grids, and polygon mesh surfaces. It runs in parallel on multi-processors. It can also be used in conjunction with a k-d tree hierarchy, where approximate models and error terms are stored in the nodes of the tree, and approximate fast renderings can be created. We have extended our software to handle time-varying data where the data changes but the grid does not. We are now working on extending it to handle more general time-varying data. We have also developed a new extension of our direct volume renderer that uses automatic decimation of the 3D grid, as opposed to an explicit hierarchy. We explored this alternative approach as being more appropriate for very large data sets, where the extra expense of a tree may be unacceptable. We also describe a new approach to direct volume rendering using hardware 3D textures and incorporates lighting effects. Volume rendering using hardware 3D textures is extremely fast, and machines capable of using this technique are becoming more moderately priced. While this technique, at present, is limited to use with regular grids, we are pursuing possible algorithms extending the approach to more general grid types. We have also begun to explore a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH '96. In our initial implementation, we automatically image the volume from 32 equi-distant positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation. We are studying whether this will give a quantitative measure of the effects of approximation. We have created new tools for exploring the differences between images produced by various rendering methods. Images created by our software can be stored in the SGI RGB format. Our idtools software reads in pair of images and compares them using various metrics. The differences of the images using the RGB, HSV, and HSL color models can be calculated and shown. We can also calculate the auto-correlation function and the Fourier transform of the image and image differences. We will explore how these image differences compare in order to find useful metrics for quantifying the success of various visualization approaches. In general, progress was consistent with our research plan for the second year of the grant.

Wilhelms, Jane↗

Vegetation Classification of Coffea on Hawaii Island using Worldview-2 Satellite Imagery

Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012.

Gaertner, Julie↗

SU-E-I-46: Sample-Size Dependence of Model Observers for Estimating Low-Contrast Detection Performance From CT Images

Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions included two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, σ(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Planar particle/droplet size measurement technique using digital particle image velocimetry image data

A method for determining a mass flux of an entrained phase in a planar two-phase flow records images of particles in the two-phase flow. Respective sizes of the particles (the entrained phase) are determined as a function of a separation between spots identified on the particle images. Respective velocities of the particles are determined. The mass flux of the entrained phase is determined as a function of the size and velocity of the particles.

Wernet, Mark P.↗

Optimal Compression Methods for Floating-point Format Images

We report on the results of a comparison study of different techniques for compressing FITS images that have floating-point (real*4) pixel values. Standard file compression methods like GZIP are generally ineffective in this case (with compression ratios only in the range 1.2 - 1.6), so instead we use a technique of converting the floating-point values into quantized scaled integers which are compressed using the Rice algorithm. The compressed data stream is stored in FITS format using the tiled-image compression convention. This is technically a lossy compression method, since the pixel values are not exactly reproduced, however all the significant photometric and astrometric information content of the image can be preserved while still achieving file compression ratios in the range of 4 to 8. We also show that introducing dithering, or randomization, when assigning the quantized pixel-values can significantly improve the photometric and astrometric precision in the stellar images in the compressed file without adding additional noise. We quantify our results by comparing the stellar magnitudes and positions as measured in the original uncompressed image to those derived from the same image after applying successively greater amounts of compression.

Pence, W. D.↗

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embedded into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.

60 APPLIED LIFE SCIENCES↗

SU-F-I-06: Evaluation of Imaging Dose for Modulation Layer Based Dual Energy Cone-Beam CT

Purpose: Dual energy cone beam CT system is finding a variety of promising applications in diagnostic CT, both in imaging of endogenous materials and exogenous materials across a range of body sites. Dual energy cone beam CT system to suggest in this study acquire image by rotating 360 degree with half of the X-ray window covered using copper modulation layer. In the region that covered by modulation layer absorb the low energy X-ray by modulation layer. Relative high energy X-ray passes through the layer and contributes to image reconstruction. Dose evaluation should be carried out in order to utilize such an imaging acquirement technology for clinical use. Methods: For evaluating imaging dose of modulation layer based dual energy cone beam CT system, Prototype cone beam CT that configured X-ray tube (D054SB, Toshiba, Japan) and detector (PaxScan 2520V, Varian Medical Systems, Palo Alto, CA) is used. A range of 0.5–2.0 mm thickness of modulation layer is implemented in Monte Carlo simulation (MCNPX, ver. 2.6.0, Los Alamos National Laboratory, USA) with half of X-ray window covered. In-house phantom using in this study that has 3 cylindrical phantoms configured water, Teflon air with PMMA covered for verifying the comparability the various material in human body and is implemented in Monte Carlo simulation. The actual dose with 2.0 mm copper covered half of X-ray window is measured using Gafchromic EBT3 film with 5.0 mm bolus for compared with simulative dose. Results: Dose in phantom reduced 33% by copper modulation layer of 2.0 mm. Scattering dose occurred in modulation layer by Compton scattering effect is 0.04% of overall dose. Conclusion: Modulation layer of that based dual energy cone beam CT has not influence on unnecessary scatter dose. This study was supported by the Radiation Safety Research Programs (1305033) through the Nuclear Safety and Security Commission.

60 APPLIED LIFE SCIENCES↗

DETECTING RELATIVISTIC X-RAY JETS IN HIGH-REDSHIFT QUASARS

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift ( z ≥ 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 < z < 2.9) quasars. The data set includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet, and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p -value upper bounds on the significance that an X-ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional six marginally. We also find residual emission in the cores of three quasars and in the background of one quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions are due to the IC/CMB rather than the synchrotron process, or that high-redshift jets are qualitatively different.

79 ASTRONOMY AND ASTROPHYSICS↗

Entropy reduction via simplified image contourization

The process of contourization is presented which converts a raster image into a set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimizes noticeable artifacts in the simplified image.

Turner, Martin J.↗

Convective Melting of Particles in Flow Under Microgravity Conditions

Study of melting of dispersed or packed solid particles in a fluid under gravity and microgravity conditions provides benchmark information for many engineering applications such as material processing, environmental assessment and protection and space fire protection. During such processes, packed or dispersed solid particles are interacting with fluid flow at above-melting temperatures. By unmasking the buoyancy effects in coupled flow, phase change and heat transport phenomena, a better understanding of melting rate in non-thermal equilibrium, convective conditions can be studied. A series of flight experiments were conducted onboard the NASA KC-135 Microgravity Research Airplane. The Particle Melting in Plow (PMF) module was designed to allow flow through the initially packed ice particles at controlled temperature and velocity. To achieve this, a close-loop flow system was designed. Video images were taken to record the visualization of the melting process, from which a time variation of packed particle thickness distribution at different times can be obtained by the image analysis method. The fluid temperature distribution within the melting zone is measured by thermocouples. An infrared camera was mounted from the top of the test section to record the ice-water thermal images at a given location. The results from thermal images yield local temperature variation between melting solid and liquid and local Stephan number. Typical results for a number of cases are presented. The mathematical model, describing mass, energy, and momentum balance equations for the liquid and solid phases, is presented. It is found that melting rate is influenced mainly by the ratio of Reynolds number (based on the initial particle diameter) to the Froud number, and Stephan number. At the absence of gravity, Froud number approaches zero, Reynolds number and Stephan number become dominant factors governing the melting rate. The numerically determined results are compared with the experimental ones. It is found that the discrepancy between the predicted and measured melting rate is largely due to the inaccuracy in the constitutive equations for effective thermal physical properties, such as effective thermal conductivity and diffusivity, and transport properties, such as particle interaction coefficient, and local heat transfer coefficient of particles.

Stewart, C.↗

Metal artifact correction for x-ray computed tomography using kV and selective MV imaging

Purpose: The overall goal of this work is to improve the computed tomography (CT) image quality for patients with metal implants or fillings by completing the missing kilovoltage (kV) projection data with selectively acquired megavoltage (MV) data that do not suffer from photon starvation. When both of these imaging systems, which are available on current radiotherapy devices, are used, metal streak artifacts are avoided, and the soft-tissue contrast is restored, even for regions in which the kV data cannot contribute any information. Methods: Three image-reconstruction methods, including two filtered back-projection (FBP)-based analytic methods and one iterative method, for combining kV and MV projection data from the two on-board imaging systems of a radiotherapy device are presented in this work. The analytic reconstruction methods modify the MV data based on the information in the projection or image domains and then patch the data onto the kV projections for a FBP reconstruction. In the iterative reconstruction, the authors used dual-energy (DE) penalized weighted least-squares (PWLS) methods to simultaneously combine the kV/MV data and perform the reconstruction. Results: The authors compared kV/MV reconstructions to kV-only reconstructions using a dental phantom with fillings and a hip-implant numerical phantom. Simulation results indicated that dual-energy sinogram patch FBP and the modified dual-energy PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in the kV projections. The root-mean-square errors of soft-tissue patterns obtained using combined kV/MV data are 10–15 Hounsfield units smaller than those of the kV-only images, and the structural similarity index measure also indicates a 5%–10% improvement in the image quality. The added dose from the MV scan is much less than the dose from the kV scan if a high efficiency MV detector is assumed. Conclusions: The authors have shown that it is possible to improve the image quality of kV CTs for patients with metal implants or fillings by completing the missing kV projection data with selectively acquired MV data that do not suffer from photon starvation. Numerical simulations demonstrated that dual-energy sinogram patch FBP and a modified kV/MV PWLS method can successfully suppress metal streak artifacts and restore information lost due to photon starvation in kV projections. Combined kV/MV images may permit the improved delineation of structures of interest in CT images for patients with metal implants or fillings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A review of setup error in supine breast radiotherapy using cone-beam computed tomography

Setup error in breast radiotherapy (RT) measured with 3-dimensional cone-beam computed tomography (CBCT) is becoming more common. The purpose of this study is to review the literature relating to the magnitude of setup error in breast RT measured with CBCT. The different methods of image registration between CBCT and planning computed tomography (CT) scan were also explored. A literature search, not limited by date, was conducted using Medline and Google Scholar with the following key words: breast cancer, RT, setup error, and CBCT. This review includes studies that reported on systematic and random errors, and the methods used when registering CBCT scans with planning CT scan. A total of 11 relevant studies were identified for inclusion in this review. The average magnitude of error is generally less than 5 mm across a number of studies reviewed. The common registration methods used when registering CBCT scans with planning CT scan are based on bony anatomy, soft tissue, and surgical clips. No clear relationships between the setup errors detected and methods of registration were observed from this review. Further studies are needed to assess the benefit of CBCT over electronic portal image, as CBCT remains unproven to be of wide benefit in breast RT.

61 RADIATION PROTECTION AND DOSIMETRY↗

Acoustical Imaging Of Defects In Ceramics

Because of their brittle nature, ceramics are extremely sensitive to even slight variations in microstructure. Direct observations show importance of kinds of defects by identifying them as sites of localized failures. Sites cannot be determined priori by optical and x-ray methods. Color images obtained from precise acoustic measurements reveal subtle variations in porosity fractions and mean sizes of pores in ceramics. Velocity and attenuation of ultrasound found related directly to density and mean size of pores, respectively.

Generazio, Edward R.↗

SU-F-303-13: Initial Evaluation of Four Dimensional Diffusion- Weighted MRI (4D-DWI) and Its Effect On Apparent Diffusion Coefficient (ADC) Measurement

Purpose: Diffusion-weighted imaging(DWI) has been shown to have superior tumor-to-tissue contrast for cancer detection.This study aims at developing and evaluating a four dimensional DWI(4D-DWI) technique using retrospective sorting method for imaging respiratory motion for radiotherapy planning,and evaluate its effect on Apparent Diffusion Coefficient(ADC) measurement. Materials/Methods: Image acquisition was performed by repeatedly imaging a volume of interest using a multi-slice single-shot 2D-DWI sequence in the axial planes and cine MRI(served as reference) using FIESTA sequence.Each 2D-DWI image were acquired in xyz-diffusion-directions with a high b-value(b=500s/mm2).The respiratory motion was simultaneously recorded using bellows.Retrospective sorting was applied in each direction to reconstruct 4D-DWI.The technique was evaluated using a computer simulated 4D-digital human phantom(XCAT),a motion phantom and a healthy volunteer under an IRB-approved study.Motion trajectories of regions-of-interests(ROI) were extracted from 4D-DWI and compared with reference.The mean motion trajectory amplitude differences(D) between the two was calculated.To quantitatively analyze the motion artifacts,XCAT were controlled to simulate regular motion and the motions of 10 liver cancer patients.4D-DWI,free-breathing DWI(FB- DWI) were reconstructed.Tumor volume difference(VD) of each phase of 4D-DWI and FB-DWI from the input static tumor were calculated.Furthermore, ADC was measured for each phase of 4D-DWI and FB-DWI data,and mean tumor ADC values(M-ADC) were calculated.Mean M-ADC over all 4D-DWI phases was compared with M-ADC calculated from FB-DWI. Results: 4D-DWI of XCAT,the motion phantom and the healthy volunteer demonstrated the respiratory motion clearly.ROI D values were 1.9mm,1.7mm and 2.0mm,respectively.For motion artifacts analysis,XCAT 4D-DWI images show much less motion artifacts compare to FB-DWI.Mean VD for 4D-WDI and FB-DWI were 8.5±1.4% and 108±15%,respectively.Mean M-ADC for ADC measured from 4D-DWI and M-ADC measured from FB-DWI were (2.29±0.04)*0.001*mm2/s and (3.80±0.01)*0.001*mm2/s,respectively.ADC value ground-truth is 2.24*0.001*mm2/s from the input of the simulation. Conclusion: A respiratory correlated 4D-DWI technique has been initially evaluated in phantoms and a human subject.Comparing to free breathing DWI,4D-DWI can lead to more accurate measurement of ADC.

60 APPLIED LIFE SCIENCES↗