bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐E‐I‐85: Application of Real‐Time Dosimetry to Characterize the X‐Ray Penetrability of CT Scanners
Authors: McKenney S , Burkett G , Gelskey D , Boone J
Published: November 2011

Purpose: Beam quality measurement on commercial whole body CT scanners generally requires the presence of the service engineer to stop the gantryˈs rotation using a service mode; consequently, the half‐value layer (HVL) is not regularly assessed. An apparatus was constructed and allows for HVL measurements to be performed using a standard axial scan with a prototype real‐time (RT) isotropic dose probe.Method: The HVL apparatus consisted of eight plates of high purity aluminum (type 1100) equally spaced around the probeˈs detective volume. The thickness of the plates ranged from 0.81 mm to 13.51 mm; the x‐ray beam was attenuated by varying amounts as the gantry rotated. From the acquired signal train, the relative signal of the attenuated beam to the unattenuated beam was used to estimate the HVL. The HVL measurements made with the prototype apparatus were validated against conventional methods on a prototype dedicated breast CT (bCT) scanner over a range of x‐ray tube voltages. The energy dependence of the prototype probeˈs output was compared to that of an ion chamber. The HVL measurements were then demonstrated on a clinical whole body CT scanner at four discrete x‐ray tube potentials. Results: The energy dependence of the RT probe was found to be non‐linear as compared to the conventional ion chamber, and a calibration factor for the RT solid‐state probe was produced. After converting the probeˈs signal into units of air kerma, the HVL measurements using the proposed techniques were found to be equivalent to those found using traditional techniques. Conclusions: A proposed new method and apparatus for measurement of the HVL in whole body CT scanners provides for a fast, noninvasive measurement of x‐ray beam quality within a single scan. Using this approach, it is anticipated that HVL measurements across kV settings can be routine in CT scanner evaluation.
SU‐E‐I‐92: Application of Dose Modulation for the Clinic
Authors: Yang Z , Edwards R , Lane B F
Published: November 2011

Purpose: To investigate the application of different CT dose modulation techniques on image quality for general and critical ill patients in the hospital setting. Methods: Automatic current selection (or dose modulation) has been a major dose reduction technique which becomes standard feature available from all major CT scanner vendors. However, each vendor approaches the issue differently, and the effect of this technique for patients with different clinical indications varies dramatically. Abdominal studies present the most challenging situation because the level of contrast detectability required for diagnostic quality of CT images of this region. Tube currents for each image slice have been manually recorded and plotted against the scout images for both angular and longitudinal modulation cases. Results: For most chest/abdomen/pelvis studies, the tube current experiences a minimum below the diaphragm, as the computer system adjust the tube current in real time lacks the anatomy. This poses a risk for oncology patients that are under routine follow up for small metastasis in the liver and/or other upper GI organs. It will be more beneficial not using these techniques for these patients. Outpatient management has been changed to provide better image quality and lower radiation dose for the patients. Conclusions: Specific continued education for operators and quality control is very important for the optimum application of new techniques developed for clinical uses.
SU‐E‐I‐94: Survey of CT Image Quality and Patient Doses in Taiwan
Authors: Tsai HY , Liu HL , Hwang YH , Chen CC , Wan YL
Published: November 2011

Purpose: The purpose of this study is to survey the image quality and patient doses for CT in Taiwan. Methods and Materials: Dedicated researchers conducted on‐site measurements, started from March 2009 to September 2010. An ACR CT accreditation phantom (Model 464, Gammex) was used to evaluate CT image quality, including slice thickness accuracy, CT number accuracy, uniformity, noise, artifact, spatial resolution, and low contrast detectability. CT dose index (CTDI) was measured by a pencil‐type ionization chamber (10X6‐3CT, Radcal) inserted into head and body dosimetry phantoms. Representative patient doses for adult head, adult abdomen, and 5‐years pediatric abdomen examinations were evaluated according to clinical setting and on‐site measured data, including volume CTDI (CTDIvol), dose‐length product (DLP), and effective doses. The diagnostic reference levels for CTDIvol were set at the third quartile from the survey results. The criteria of pass or fail were according to ACR CT accreditation. Results: There are 446 CT scanners, including CT, PET/CT, SPECT/CT, and CT simulator, in 234 hospitals in Taiwan. The survey, which was conducted from March 2009 to September 2010, included 426 units in 226 hospitals (96% completed). The fail rates of each item of image quality ranged from less than 1% to around 80%. The mean value and third quartile value of CTDIvol are 53 and 68 mGy for adult head examinations, 18 and 18 mGy for adult abdomen examinations, and 17 and 28 mGy for 5‐ years pediatric abdomen examinations.Conclusion: The results have compared with ACR CT accreditation and gave us a view of current level of CT image quality and patient doses in Taiwan.
SU‐E‐I‐95: Using Angular Magnitude Evaluate the Spatial Orienations in Computed‐Tomography Simulation System
Authors: Wu M , Ramaseshan R
Published: November 2011

Purpose: To quantify the spatial orientations of the tabletop and external patient positioning lasers with respect to the couch moving direction and imaging plane in a CT simulation system by indicating as angular deviation. Method and Materials:A home‐made cross‐jig is used in this study. The longitudinal arm of the jig is orthogonal with the transverse arm and some BB markers inlaid in the jig to indicate the arms on CT images. We found there are some relationships between the orientations of the jig arms which shown on the images and the orientations among the tabletop, external lasers, couch moving direction, and imaging plane. First, the orientations of CT simulation system had been carefully confirmed by using the approaches mentioned on TG 66. To simulate all possible deviating situations, we designed 8 orientation arrangements for the tabletop and external lasers, respectively, due to these two components cause different effects on CT images. When attaching the cross‐jig on tabletop we can check the orientations between the tabletop, couch moving direction, and imaging plane. While aligning the cross‐jig with the external lasers we will know the angular deviation between the external lasers, couch moving direction, and imaging plane. Results: Based on the preliminary analysis, the maximum error is 0.12 degree. After considering the inherent angular deviations in our CT simulator, image analysis errors due to the size of BB and image spatial resolution, and the jig setup errors we can say all of the results conformed to our expectation. Conclusions: Only two scans, then we will know the spatial orientations in CT simulation. By means of accurately quantifying the deviations we can easily correct the error if it has to be. The method proposed in this study could also be used for detecting an angular deviation in any other orthogonal imaging system.
SU‐E‐I‐102: Enhancement of Registration Accuracy Using Landmark Information
Authors: Shusharina N , Wang Y , Sharp G
Published: November 2011

Purpose: To use point landmarks for rapid, interactive correction of local registration failures caused by significant anatomy changes. Methods: Our landmark‐based method utilizes a semi‐automatic procedure. First, we define mismatched areas on reference and test images using contours, which are converted into corresponding sets of landmarks. Second, a program calculates a landmark displacement field, which is used to update an existing displacement field. We use Gaussian radial basis functions (RBF) to create a vector field which exactly interpolates landmark correspondences in the reference and test images. The calculated field is regularized by penalizing large second derivatives. The solution for regularization is stated analytically and yields an efficient computational scheme. Results: The method was applied to register two pairs of prostate images acquired from patients at different points during treatment. These registrations are challenging due to a significant enlargement of the rectum in one case, and change of bladder filling in the other case. To improve the accuracy of automatic registration, we used an expert‐defined contours of the rectum, bladder and prostate as guidance for landmark placement and applied our matching method. As a result, the organs of interest were accurately matched and the regularization assured a diffeomorphic deformation. Conclusion: We have developed a practical method for correcting or enhancing inadequate automatic registration results for medical images containing large anatomical changes. The method integrates landmark matching and regularization.

Gaussian basis functions are used because they allow an analytical solution, leading to a very efficient computational scheme.
SU‐E‐I‐104: Automatic Labeling of the T1 through T12 Vertebrae in CT
Authors: Sharp G , Li R
Published: November 2011

Purpose: To quickly and automatically identify the slice coordinates of the thoracic vertebrae (T1 through T12) in CT with an accuracy of two vertebrae. Methods: The vertebra identification method uses three stages: (1) thumbnail generation, (2) ridge regression, and (3) application of anatomic constraints. In the first stage, axial slices of the CT are selected from the volume, cropped and resampled into thumbnail images with resolution 16×16 pixels. Next, the thumbnails are assigned a vertebrae number using a ridge regression filter. The filter is trained using hand‐labeled data, and training parameters are tuned using cross‐validation. Finally, the outputs from the regression filter are fit with a linear spline using anatomic constraints on the size and orientation of vertebrae seen in training data. Results: Our method was trained on a data set of twenty thoracic CT scans, and tested using an independent set often scans. The CT images are derived from the RIDER and RIDER Pilot studies, and have slice thickness that range between 1.25 and 5 mm. The ridge regression results were found to be smooth and monotonic in the central region, but became non‐monotonic near the inferior and superior borders of the image where there is no training data. The anatomically constrained fit generally provides a good fit for the ridge regression output. Results from the independent test set demonstrate successful labeling within 2 vertebrae for 60% of the cases, and within 1 vertebra for 40% of the cases. The most common cause of failure was inaccuracy of the ridge regression stage. Conclusions: Ridge regression is a promising approach for assigning anatomic labels to CT images. We envision using this technique as a pre‐processing stage for both image registration and image segmentation.
SU‐E‐I‐105: Development of Semi‐Automatic Bone Age Estimation Method
Authors: Oh Y , Lee H , Kim D , An S , Lee R
Published: November 2011

Purpose: Greulich‐Pyle and Bayley‐Pinneau (GP‐BP) method and Tanner and Whitehouse (TW3) method are used to measure bone age. GP‐BP method is easy, but it has a disadvantage that the detailed of analysis is difficult. It compares radiograph and standard image at a wide interval. TW3 method is derived from a more mathematical base, which scores skeletal maturity. So, subjective errors are reduced, taking 7∼10 minutes to examine. Therefore, we developed algorithm that decides bone stage by matching bone stage with reference image of ROI (Region of Interest) to make a high efficiency of TW3 method. Methods: To reduce time‐consuming, we used only 4 ROI. We detected edges of bone by using Sobel Edge Detection through Input image of the ROI. And then, we mapped them by using Chamfer Distance Transform through reference image of ROI. Next, we compared the edge image to the mapped reference image. Then, the reference image having the minimum distance errors was decided the bone stage that is suitable for input image. And, bone stages of 128 radiographs aged 2 ∼ 17 yrs were evaluated by the algorithm and a clinician, and we compared assessment differences. Results: Differences of bone stage assessment were 0.97∼1.73 in average. Algorithm accuracy of radius, ulna, 3th and 5th middle phalanges were 78%, 55%, 52% and 45% respectively. To improve the lack of accuracy according to maturity variability of the finer region, image quality and conditions, we needed to design a semi‐automatic system to be selected by a clinician. So some occasions that havenˈt been selected could increase the accuracy to 100%. Conclusions: In this study, bone age estimation method was developed semi‐automatically. This is more useful to clinicians since its use is easier and less time‐ consuming than the same level of accuracy of the manual TW3 method contains.
SU‐E‐I‐109: Validating Assisted Registration Tool of UTRS Using CT and PET
Authors: Kim H , Shin J J , Park S B , Monroe J I , Yao M , Ellis R , Sohn J W
Published: November 2011

Purpose: To validate the stability and accuracy of a new image registration assistance tool UTRS (Universal Treatment Plan Review System) [Case Western Reserve University, Cleveland, OH]) for CT and PET images. UTRS was developed to review and manage the DICOM and DICOM‐RT data sets, performing both manual and assisted image registration. Methods: We tested two groups of patients with existing PET/CT fusions performed by a clinical fusion expert. The first group consisted of 17 Head and Neck cancer (HN) cases and the second of 20 Lung cancer (LC) cases. In both groups, each patientˈs PET image set was aligned to the patientˈs CT image set using the assisted registration method in UTRS. For the HN cases, Spatially Weighted Mutual Information with Gaussian Weighting (SWMI‐ GW) was selected as the metric. Mutual Information was used to register the LC cases. The existing MIM (MIM software Inc., Cleveland, OH) fusions are used for comparisons. Results: Visual checks confirmed the assisted registration of UTRS was comparable to the expert manual registration using MIM. Computational comparisons showed the Mean Absolute Differences (MADs) between the two registrations were less than 3.1mm in translation and 1.2 degree in rotation for HN cases. For LC cases, the MADs between MIM and UTRS were less than 2.9mm in translation and 1.5degree in rotation. Conclusions: Since a MIMˈs validation study showed the manual registration of MIM had a comparable variation; up to 2.93mm MADs from their average registration, we concluded that the assisted registration of UTRS is also valid for clinical use. We also found that rotational corrections were necessary for many cases between the image sets from the CT simulator and the diagnostic PET(/CT), even with the same immobilizer. The assisted registration dealt with rotations better since a 3‐ dimensional manual rotation on 2‐dimensional screen is obtuse.
SU‐E‐I‐112: New Algorithm for Identification of Differences between Noisy Medical Images
Authors: Mitev K , Gerganov G , Kawrakow I
Published: November 2011

Purpose: To present a method for image comparisons and detection of statistically significant differences (SSDs) between medical images that contain a significant amount of noise, where standard similarity measures like mutual information do not work very well. Methods: The basic idea is that if there are two noisy images which contain SSDs, these differences will appear as outliers in the distribution of pixel intensities in the difference image. Therefore, the method applies a statistical test and identifies the outliers found as SSDs. The tests for outliers are applied on the entire difference image (global approach), on a part of the image around a tested pixel (local approach), or both (mixed approach). The mixed approach first uses a global approach to exclude a set of outliers before invoking the local approach. For performance assessment, the algorithm is applied to synthetic image pairs with known noise levels and SSDs. It is also tested on PET images reconstructed with different algorithms from the STIR package using sinograms obtained from MC PET simulations using egs_pet, on electron beam dose distributions computed with the VMC++ code, on CT and SPECT images. Results: Best performance is achieved with a mixed approach. For the synthetic images the mixed approach identifies SSDs that are larger than four standard deviations of the noise. Visible differences between pairs of PET, CT, SPECT and dose distribution images are also successfully identified. Conclusions: A new method for automatic detection of significant differences between noisy medical images is presented. The method has potential for application in situations where a quantitative comparison and identification of regions of differences is difficult or not possible due to the presence of significant amount of noise. The algorithm is applicable to PET, SPECT and CT imaging as well as to problems related to comparisons of dose distributions.

Supported by Bulgarian NSF grant DDVU 02/42. We are grateful to A. Kirov and C.R. Schmidtlein for the useful discussions.
SU‐E‐I‐113: A Practical Human‐Observer‐Based Scoring Method for Imaging Performance Assessment in Computed Tomography
Authors: Yadava G , Cohen A , Fan J , Sainath P , Hsieh J
Published: November 2011

Purpose: Standard methods of computed tomography (CT) image‐quality assessment in terms of objective performance parameters (e.g., noise, spatial‐resolution, low contrast resolution, slice‐thickness etc.) may lack in adequately incorporating the effect of patient shape, anatomical noise, and clinically relevant diagnostic task, such as detection of abnormal pathology. Most of the existing psychophysical experiments, e.g., 2‐AFC, ROC, FROC, MRMC etc., are very expensive to conduct and subject to a combinatorial explosion, making routine human experiments impractical. In an effort to develop a realistic practical assessment of imaging‐performance in clinically relevant diagnostic tasks, a practical human‐observer‐based scoring method was developed to quantify not only the probability of true lesion detection, but also an average detection score as an indicator of quality of detection in complex tasks, and applied in comparing two reconstruction technologies.Methods: An anthropomorphic abdomen phantom with multiple simulated hyper‐vascular liver‐lesions of clinically relevant sizes and contrast‐levels was used to evaluate human‐observer‐performance in a low‐contrast‐lesion‐detection task. Human observer‐based imaging performance assessment of the two reconstruction technologies, filtered‐ back‐projection (FBP) and the VeoTM (model‐based‐iterative‐ reconstruction), at two dose levels, “full dose” (corresponding to dose levels in routine clinical practice for abdominal CT) and 1/4th of “full dose”, were carried out. Average lesion detection performance in a task with multiple lesions of different contrast‐levels and sizes, quantified in terms of average‐ probability‐of‐detection and average‐detection‐score as figures‐of‐merit, was evaluated for relative imaging performance comparison with‐respect‐to dose.Results: Results of the study and statistical significance tests indicated that average‐probability‐of‐detection and average‐detection‐score at full dose FBP and 1/4th dose VeoTM are comparable, whereas at the same full dose VeoTM offers improved detection performance Conclusions: The presented human‐observer‐based scoring method has significant potential for practical imaging‐performance comparison of different reconstruction technologies under clinically relevant tasks, where single image may have multiple pathologies of different contrast‐levels, shapes and sizes.
SU‐E‐I‐116: Spatial Frequency Spectrum of the X‐Ray Scatter Distribution in CBCT
Authors: Bootsma G , Verhaegen F , Jaffray D
Published: November 2011

Purpose: X‐ray scatter causes significant diminishing effects to image quality in cone‐beam CT (CBCT) such as: image artifacts, loss in contrast‐ to‐noise ratio, and CT number inaccuracy. The purpose of this study is to examine the spatial frequency content of the scatter distribution in CBCT projection images using the Fourier transform. This work forms the basis for accelerated Monte Carlo scatter estimation. Methods and Materials: A previously validated CBCT MC system is used to generate the resulting scatter distribution for various imaging sites (head and neck, abdomen, and pelvis) and projection angles using a voxelized anthropomorphic phantoms. The spatial frequency is examined by taking the fast Fourier transform (FFT) of the simulated scatter distributions. The effects of using a bowtie filter on the spatial frequencies of the scatter distribution is also examined. Results: The spatial frequency of the scatter distribution, in the horizontal and vertical direction, is largely contained in the lower frequencies of the Fourier transform (<0.1 1/cm). The angular component of the spatial frequency of scatter distribution shows two strong periodic signals with a period of pi and pi/2. The use of the bowtie filter has an effect of decreasing the higher frequency content of the horizontal component of the spatial frequency. Conclusions: The computational time of estimating the scatter distribution using MC can be reduced by simulating fewer photons and using a low‐pass filter. Periodic signals in the projection angle component of the scatter distribution indicate that a significant reduction in number of projection angles simulated to accurately estimate the scatter distribution is also possible.
SU‐E‐I‐121: MRI Detection of Dominant Intraprostatic Lesions and Correlation with Tumor Microenvironment
Authors: Ware S
Published: November 2011

Purpose: To determine if MRI is suitable for planning of intratumoral radionuclide therapy of prostatic cancer by correlation of MRI imaging parameters to histologic parameters Methods: All statistical analysis was performed using GraphPad Prism version 5.00 for Windows, GraphPad Software, San Diego California USA, www.graphpad.com. A total of 22 tumors from 10 patients who underwent 3T endorectal MRI and subsequent prostatectomy were investigated retrospectively. Differences in raw T2 signal, T2 signal ratios, apparent diffusion coefficient (ADC), and ADC ratios were tested for significance using one‐way ANOVA for normal tissue, index lesions and secondary lesions as a function of specific pathology parameters (percent stroma, percent glandular area, percent cellularity, glandular area, glandular perimeter, stromal width). Bonferroni multiple comparisons test was performed to test differences in index and secondary tumors as a part of ANOVA analysis. Pearsons correlation was performed for each MRI parameter and pathology parameter based on tissue type as well. Results: Normal tissue MRI parameters were found to be significantly different (p <.05) from index and secondary tumors for all pathologic parameters. Index and secondary lesions showed no significant differences from one another (p<.05). Significant correlations were seen for normal tissue, index and secondary lesions for T2 signal intensity ratios and raw T2 when looking at glandular area and percent luminal space (p <.05, r >.66). Other moderate to strong correlations were seen for ADC and secondary lesions (r < −.58) Conclusions: These results show that MRI has he ability to distinguish between index lesions and secondary lesions as well as informing on the tissue microenvironment. A larger, randomized prospective trial should be performed to further test this hypothesis. MRI will play a central role in successfully planning intratumoral radionuclide therapy of prostatic index lesions in the future.
SU‐E‐I‐123: Quantification of 1H Magnetic Resonance Spectroscopic Imaging for Breast Cancer with Singular Value Decompsition (SVD) Method
Authors: Feng W , Chu A , Hu J
Published: November 2011

Purpose: To study the feasibility of Singular Value Decomposition (SVD) method to quantify the MRSI data, and the effect of signal to noise ratio on SVD method was studied. Methods: In‐house SVD program was developed with Matlab version 7.6 (Mathworks.com), in frequency domain water signal peak around 4.7ppm is used for referencing shifting. Hankel SVD method is used to compute the signal poles and from them the signal frequencies and damping factors. Known spectrum without noise was analyzed. Then introduce random noise, Gaussian filter of various frequency was used to reduce noise effect, wavelet threshold de‐noise method was also tested with various hard and soft threshold selection methods. Human breast MRSI data were analyzed with optimized parameters.Results: SVD can easily detect the small signal in low noise GSH data at 2.54ppm, GSH signal ratio to NAA is only 0.5%. However SVD can not detect the signal after added random noise of SNR 15. By add Gaussian filter of 2.5Hz, peak could be detected by suppress noise, however if noise level is larger than the signal, fake peak could be resulted. For wavelet threshold method, hard threshold with wavelet principle of Steinˈs Unbiased Risk Estimate (SURE) can generate best results, random noise of SNR 7 can be reliably detected. Typical patient data from breast tumor data was analyzed, even the detected cho peak is only 0.5% of water peak, it can be detected reliably, and the max residue error is 0.2% of water peak. Conclusions: SVD method can be used for human breast MRSI. the SVD method is sensitive to detect the signals as low as 0.5%. However it is suspected to noise, since it has no prior knowledge to reduce noise; improved SVD method with wavelet threshold de‐noise can exploited in MRSI with SNR of 7.
SU‐E‐I‐128: Evaluation of Magnetic Resonance Phase Data of Projection and 2‐D FLASH Acquisition to Estimate the AIF
Authors: Moroz J , Reinsberg S , Kozlowski P
Published: November 2011

Purpose: Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE‐ MRI) is a technique that non‐invasively collects data related to the vasculature of tissue. Quantitative information is derived from the time course concentration of contrast agent in a supplying vessel, known as the arterial input function (AIF). The AIF should have a high temporal resolution, but it often compromises spatial resolution. The phase of MRI signal varies linearly with the concentration of a contrast agent, is independent of the hematocrit and is expected to have an increased signal to noise ratio (SNR) when compared to magnitude based data. The use of phase data from projection images satisfies the requirement for high temporal resolution and may be used to reconstruct a 2D image if projected along different axes. Methods: Data was collected using a 7.0 T Bruker MRI system. 1‐D Projection and 2‐D FLASH images were collected on a phantom for varying concentrations of Gadolinium. Phase information was determined directly from the free induction decay (FID) and unwrapped where appropriate. Results: Calibration of the phase data (2‐D FLASH acquisition) verified that the phase increased linearly with the concentration of contrast agent with a slope of (1.183 ± 0.015) rad/mM. A small phase drift was present ((0.014± 0.019) rad/100 min), but had neglible impact on the calibration curve. The concentration of contrast agent as determined from the projection data was in good agreement with the 2D analysis with a slope of (1.187 ± 0.027) rad/mM. Conclusions: Projection based imaging will significantly increase the temporal resolution of DCE‐MRI studies. The linear relationship between the phase and concentration of contrast agent was consistent between the 2‐D FLASH and projection acquisitions. The results of this study suggest that projection based imaging may be used to accurately estimate the AIF.
SU‐E‐I‐130: Improved Quantification of Cerebral Metabolites in Hepatic Encephalopathy Using 2D L‐COSY and ProFit
Authors: Huda A , Sarma M , Nagarajan R , Hinkin C , Wilson N , Gupta R , Sayre J , Guze B , Han S , Thomas M
Published: November 2011

Purpose: To detect, separate, and quantify more cerebral metabolites than is currently possible with one‐dimensional magnetic resonance spectroscopy (1D MRS) by using 2D localized correlated spectroscopy (2D L‐COSY) with prior‐knowledge fitting algorithm (ProFit). Methods: 14 patients with minimal hepatic encephalopathy (MHE) (mean age ± standard deviation (SD) = 53.3± 10.6 years) and 18 control subjects (52.7±12.6 years) were studied with 1.5T GE MR Scanner. A body coil for transmission and a 3‐ inch surface coil for reception were used. A localizer followed by high‐ resolution T1‐weighted axial images (TR/TE = 800/8 ms, 35 slices, 4 mm thickness with no gap) were collected. We used a CHESS sequence for water suppression. 2D L‐COSY spectra were recorded using the following parameters: TE = 30 ms; TR = 2000 ms; total number of scans = 768 (96 Δt1 increments and 8 averages per Δt1); and spectral width, F1 = 625 Hz and F2 = 2500 Hz. A 27ml voxel was placed on the anterior cingulate gyrus. A battery of neuropsychological tests (NP) was done to correlate the MRS results with the NP data. Results: : The 2D L‐COSY data processed with the ProFit was able to separate and quantify fourteen cerebral metabolites in both healthy controls and patients as opposed to five with 1DMRS. The ratios of myoinositol (mI), glutamate (Glu), total choline, scyllo‐inositol (sI), phosphoethanolamine (PE), and total NAA with respect to creatine (Cr) showed a statistically significant decline in patients compared to healthy controls whereas the ratio of glutamine to Cr (Gln/Cr) was significantly increased. Conclusions: Our technique allows for separation and quantitation of Glu from Gln, strengthening the astrocyte‐ ammonia detoxification hypothesis in HE. In addition, clear separation of glycerol‐phosphocholine (GPC) from total choline in conjunction with the decline in PE, points to a decrease in phospholipid metabolism in HE.

This research was supported by National Institute of Mental Health (NIMH) grant #1R01MH06569501A1
SU‐E‐I‐131: Uniformity Evaluation of GRAPPA and MSENSE Parallel Imaging Reconstruction Algorithm
Authors: Goerner F , Clarke G , Duong T
Published: November 2011

Purpose: Parallel Imaging (PI) MRI protocols lead to image characteristics that differ from conventional MR images. An accurate and simple method for determining image intensity uniformity in PI is lacking. This study examines five methods of uniformity measurement with PI. Accurate uniformity metrics decrease with increasing R‐value. Methods: A phantom was used in a 12 channel head coil and 3T MRI with TR 1200ms, TE 76 ms, 5 slices, 5 mm thickness, 1 mm gap, FOV 220×220 mm, 256×256 matrix, ETL 16, BW 122 Hz/pixel, axially. Non‐PI TSE sequence, PI method GRAPPA and PI method mSENSE with R: 2, 3 and 4 were inspected. Five uniformity measurement methods were investigated using equations involving: A) Minimum (Smin) and maximum signal pixels (Smax) calculated, PIUA B) Mean pixel value computed and each pixel grouped by: Group1=+/−10% of mean, Group2=+/−10%–20% of mean, Group3=more or less than 20% of mean. The number of pixels per group was used to compute: PIUB C) Same as A but Smax and Smin were 0.15% ROIs. D) This was the NAAD method E) The overall mean (S1) and the mean of 17, 7×7 square ROIs dispersed in the phantom were used. The average of each ROI was taken and PIUE was calculated. Two way ANOVA analysis evaluated reconstruction method and R‐value. Results: Methods D and E indicated increase in uniformity with R‐value at R=3. Two‐way ANOVA results indicated that uniformity measurements A–D were dependent on R‐ value. No uniformity method showed reconstruction method dependence. Conclusions: Methods A and C are similar, A is more sensitive. Methods E and D are inaccurate. Method B gives accurate information but is not as sensitive as A. Method A should be used to obtain the most precise uniformity measurement with PI protocols.
SU‐E‐I‐132: Whole‐Brain DCE Quantitative Perfusion Imaging
Authors: Gauderon P , Salluzzi M , Lauzon M , McCreary C , Smith M , Frayne R
Published: November 2011

Purpose: To develop a whole‐brain acquisition protocol based on dynamic contrast enhanced (DCE) MR imaging that is able to provide absolute brain tissue perfusion estimates and to assess, evaluate and minimize the uncertainty in the estimates of contrast agent concentration. Methods: Preliminary in vivo data was collected using a 3D spoiled‐gradient recalled echo (SPGR) sequence with TR/TE/flip angle (FA) = 2.5 ms/1.15 ms/15°. The spatial resolution was 1.7×1.7×4.0 mm3. A variable rate k‐space sampling scheme and view sharing resulted in a temporal resolution of 2.4 s. The perfusion estimates were calculated using indicator‐dilution theory. Based on preliminary data, simulations estimating the uncertainty and sensitivity to misestimated parameters in the concentration measures were performed. Tissue parameters and contrast agent relaxivities were obtained from literature. The SNR before contrast injection was extracted from the preliminary data. Results: Absolute perfusion maps were successfully generated for the whole brain in all three subjects. As predicted, the low signal enhancement in cerebral tissue, especially in white matter, resulted in noisy perfusion maps. The range of the cerebral blood flow (CBF) and cerebral blood volume (CBV) maps corresponded to the range of the values reported in literature. The mean transit times (MTT) however were overestimated. The simulations showed that a FA of 9° minimizes the concentration coefficient of variation in white matter. However, the sensitivity to misestimated parameters was reduced with increasing FA: a FA > 20° was beneficial. For realistic SNR levels, averaging 5 acquisitions of the signal before contrast agent arrival were sufficient. More baseline measurements did not significantly decrease the signal variance. Conclusion: It is possible to acquire qualitatively acceptable whole‐brain bolus tracking data using a DCE sequence. In addition, the FA influences the uncertainty and sensitivity in concentration estimates when using a SPGR sequence.

Grant support from the Canadian Institutes for Health Research, Canada Research Chairs Program and Hopewell Professorship in Brain Imaging.
SU‐E‐I‐135: Image Reconstruction by Derivatives in Frequency Domain
Authors: Shen J
Published: November 2011

Purpose: To demonstrate a novel theorem relating the spatial frequency domain partial derivatives; to show that using autocalibrating signals images can be unwrapped using k space partial derivatives and noise amplification in SENSE reconstruction can be reduced without making any assumptions on the characteristics of images to be reconstructed. Methods: Phantom and human brain images were acquired using a standard GE 3.0 Tesla Excite scanner (General Electric, Waukesha, WI) equipped with eight receive channels. Standard eight‐channel receive‐only head coils and a transmit body coil were used for image data acquisition. Results: As a proof of concept, a gradient echo phantom image was reconstructed in k space using 20 ACS lines for R=2. Partial derivatives for No. 63, 64, 65, 66, and 67 ky lines were measured by fitting the five tightly spaced ky points at each (x,ky) coordinate to a third order polynomial. Two sets of aliased images were obtained: a conventional one described by a sum of products between spin density and coil sensitivity and a new one described by a sum of products among spin density, coil sensitivity and y ordinate of the aliased pixel. There are no visible reconstruction artifacts in the unwrapped individual coil images. In image domain, the new contraints derived from k space partial derivatives were used to improve the conditioning of SENSE encoding matrices. The derivative constraints are different from regularization, the latter leads to loss in spatial resolution. For an MPRAGE brain image with R=6 the first order derivatives alone was found to reduce the largest SENSE g factor by 61% (from 23.1 to 8.9). Conclusions: Derivatives in k space can be used for parallel imaging reconstruction in both k space and image domains.

Funded by NIMH, NIH
SU‐E‐I‐140: A Clinical Study of Dual‐ and Single‐ Spectrum Temporal Subtraction Mammography Techniques Using an Iodine‐Based Contrast Medium
Authors: Brandan M , Villaseñor Y , Benitez‐Bribiesca L , Trujillo F , Perez‐Ponce H , Sanchez‐Suarez P , Galvan H , Bargallo E , Rosado‐Mendez I
Published: November 2011

Purpose: To study iodine uptake in digital mammography images obtained by temporal image subtraction after intravenous administration of contrast medium and use of dual‐energy. Methods: 20 patients classified as BIRADS 4 or 5 were invited to participate in a study of contrast‐medium enhanced subtraction of mammographic images. A Senographe DS digital unit was used, and patients were injected during the procedure with iodine‐based contrast medium. A biopsy was taken after the radiographic procedure. Images were craniocaudal, obtained under a single (weak) compression. For dual‐energy subtraction a low‐energy mask and four post‐contrast high‐ energy images were acquired, the latter at 1, 2, 3 and 5 minutes after the mechanical‐power contrast medium injection. For temporal subtraction a pre‐contrast mask was obtained at high‐energy settings. Two subtraction schemes were employed, one requiring radiologist identification of adipose, healthy glandular and lesion ROIs for normalization before subtraction, and one self‐normalized (for temporal sequences). Samples from biopsies were analyzed with specific immunohistochemical markers to determine vascular and lymphatic neovasculature within the lesion. Results: The procedure was well tolerated by patients. 75% of cases were malignant, mostly invasive ductal carcinomas. An area of enhancement (high iodine contrast) at the suspected lesion location was observed in most of malignant cases. No enhancement was observed in most of benign cases. Iodine contrast was higher for dual‐energy subtraction than single‐spectrum temporal analysis while contrast‐to‐noise ratios were similar. Enhancement kinetic curves showed, for most of malignant cases, rapid uptake followed by slow washout. Correlation between kinetics of enhancement and intratumoral density of vascular and lymphatic vessels is being analyzed. Conclusions: This preliminary analysis corroborates the feasibility of contrast‐enhanced digital mammography and the potential use of the technique to identify breast lesions. Final analysis of our data should indicate the specific advantages of each technique being investigated.
SU‐E‐I‐144: Radiation Dose Reduction in Monochromatic Phase Contrast X‐Ray Mammography Using Equally Sloped Tomography
Authors: Zhao Y , Brun E , Fahimian B , Bravin A , Sztrókay A , Coan P , Miao J
Published: November 2011

Purpose: In mammography, while maintaining the image quality, it is necessary to keep the delivered dose as low as possible since breast is a highly radiosensitive organ. Monochromatic phase contrast X‐ray mammography has shown its potential at higher sensitivity and lower impact in terms of dose delivery compared to absorption based diagnostic X‐ray mammography. An exact Fourier‐based iterative technique termed Equally Sloped Tomography(EST) has been newly developed and implemented on it. Using this technique, we conducted a series of comparative experiments to explore the further more radiation dose reduction in phase contrast mammography through reduction of projection numbers. Methods: Experiment took place at the biomedical beamline at ESRF(ID17). Full Human breasts samples were fixed in 4% formalin solution. Planar imaging and Computed Tomography(CT) modalities were combined to PCI techniques at 60KeV and using a 2kx2k taper optics CCD detector(45 micron pixel). The number of projections scanned was 2000 and digitally removed to 512 for reconstructions. Comparison reconstructions were produced by Filtered‐Back Projection(FBP) with a standard uncropped‐ramp filter. To optimize the result, Non‐local‐means regularization was applied for post‐processing in both cases. Results: Compared to the FBP reconstruction using 2000 projections, EST using 512 projections has comparable SNRs and CNRs, no obvious contrast degradation is observed between tumor and normal glandular tissue. In addition, the collagen exhibit similar visibility. Conclusions: Our results indicate that in the phase contrast mammography, EST technique can reduce the dose up to 50%∼75% by reducing number of projections, while images have comparable quality as the full dose FBP reconstruction. Furthermore, it makes the acquisition time 2∼4 times faster, which is important in in‐vivo imaging. The main reason for this is that EST is an exact Fourier‐based iterative algorithm that can incorporate different physical and mathematical constraints. It is always guided towards a lowest‐possible noisy state while keeping strictly consistent with measurements.

Research sponsored by UC Discovery / TomoSoft Technologies Grant #ITL07‐10166.
SU‐E‐I‐149: Digital Breast Tomosynthesis Using 2D Source Scanning Patterns: A Simulation Study
Authors: Zhong Y , You Z , Shen Y , Liu X , Lai C , Wang T , Ge S , Yi Y , Shaw C
Published: November 2011

Purpose: Digital tomosynthesis (DTS) imaging with 2D scanning patterns may help reduce the artifacts by more effectively blurring the off‐fulcrum objects. In this study, the effects of various source scanning patterns on the reconstructed images are studied via simulation. Methods: The X‐ray source was assumed to be movable following various scanning patterns. The source‐to‐iso‐center and source‐to‐image distances were assumed to be 500 mm and 600 mm, respectively. Projection images were computed using an improved distance‐driven algorithm. The objects studied included a Shepp‐ Logan phantom and a digital breast phantom constructed from segmented cone beam CT images. The X‐ray absorption coefficients were taken of mono‐energetic X‐ray at 19 keV. The x‐ray source was scanned with 1D (1D DTS) and 2D (2D DTS) patterns. The objects were reconstructed using the iterative expectation‐maximization algorithm. The root‐mean‐squared‐ deviation (RSMD) was calculated to indicate the deviation in terms of CT numbers of the reconstructed image to the original phantom. Results: The RMSD of the reconstructed Shepp‐Logan phantom was 243.3 for 1D DTS and 104.7 for 2D DTS. Visual inspection revealed reduced artifacts and better CT number accuracy with 2D DTS than 1D DTS. For the digital breast phantom, the accuracy of the reconstructed tissue structures was assessed using the CT number uniformity in the dense tissue and adipose tissue regions. The RMSD of the digital breast phantom was 113.1 for 1D DTS and 50.0 for 2D DTS. The comparison showed that the 2D DTS resulted in better accuracy in CT number uniformity. Conclusions: Our results demonstrated that the use of 2D source scanning patterns has the potential advantage of more effectively blurring objects in off‐fulcrum planes, thus reducing the artifacts and resulting in more accurate image reconstruction.

This work was supported in part by research grants: CA104759 and CA124585, EB000117 from NIBIB, CA138502A1, and a subcontract from NIST‐ATPs.
SU‐E‐I‐150: Cone‐Beam Artifacts in Dedicated Breast CT
Authors: Vedantham S , Shi L , Noo F , Glick S , Karellas A
Published: November 2011

Purpose: Cone‐beam CT with circular trajectory is susceptible to cone‐angle related artifacts that affect quantitative imaging. These artifacts were quantified under conditions relevant to dedicated breast CT for full and short‐scans. Methods: Three sets of numerical phantoms (0.2‐mm voxels) were used: (1) cylindrical Defrise phantom of 14‐cm diameter and 10.6‐cm length inclusive of 2‐mm skin, with alternating 4‐mm coronal layers of fixed (0.15) and variable (0 to 1, in steps of 0.1) glandular fraction breast tissue; (2) semi‐ellipsoidal Defrise phantom with dimensions matched to the cylindrical phantom for a realistic pendant‐breast geometry; (3) 20 surgical mastectomy specimens based numerical phantoms. Source‐to‐rotational axis and source‐to‐detector distances of 65‐cm and 100‐cm, respectively, were used. Noise‐free simulations were performed at 30‐keV, with the phantoms co‐aligned to rotational axis, using an ideal detector (0.4‐mm pixels), and without the confounding effects of focal spot blur (point source) and x‐ray scatter. Constant angular sampling of 1.2‐degrees was used resulting in 300 and 165 projections for full‐scan and short‐scan (198‐ degrees). Reconstructions were performed using Hamming‐windowed FDK‐algorithm with short‐scan using Parker weights. For the Defrise phantoms, the cone‐angle dependence of the artifacts was analyzed using percent difference at the rotational axis between the reconstructions and phantoms, and by visual inspection. For the mastectomy specimens, power spectral analysis was performed. Results: For Defrise phantoms, increasing attenuation difference between layers resulted in higher inaccuracies (artifacts). Cylinder resulted in higher inaccuracies compared to semi‐ ellipsoid particularly near maximum cone‐angle. Visual inspection and power spectral analysis indicate that the spatial distribution of these artifacts is different between full and short‐scans. Conclusions: Cone‐beam artifacts at breast CT relevant conditions are observed. They depend on object shape, and attenuation difference of the tissues within the object. These artifacts must be remediated as they may impact task‐specific assessment and can profoundly affect quantitative imaging.

Supported by NIH/NCI R01CA128906. The contents are sole responsibility of the authors and do not represent the official views of the NIH or NCI. SG: Research contract with Toshiba Medical Research Institute.
SU‐E‐I‐153: A Method for Fast Generation of High Resolution Software Breast Phantoms
Authors: Pokrajac D , Maidment A , Bakic P
Published: November 2011

Purpose: We have developed a new method for generating anthropomorphic software breast phantoms. The method allows for faster generation of phantoms with small voxel size, and provides better control of simulated anatomical structures. Methods: In this paper we compare the simulation time and quantization artifacts between our previous and the new method. Previously, our breast anatomy simulation was based upon a region growing algorithm. The new method preserves the concept of region growing and is optimized to allow for faster simulation. The new method includes improved thickness control of the simulated skin and Cooperˈs ligaments. For comparison, we generated phantoms simulating a 450 ml breast using both methods. The phantoms were generated with voxel sizes in the range of 25–1000 microns; we recorded the time needed for simulation. The simulation time as function of the voxel size was fitted using a power‐law regression; the regression exponents were compared between the two methods. We also performed a visual comparison of the phantoms generated with different voxel sizes. Results: For the simulated range of voxel sizes the new method yielded a regression exponent of 2.15, compared to 3.89 for the previous method. The new method is faster than the previous method for phantoms with voxels below 200 microns. Generating phantoms with small voxel size is of importance for reducing quantization artifacts in simulated images; commercial mammography systems have detector element pitch as small as 50 microns. The visual comparison of the phantoms generated at different voxel sizes confirmed the improved quality of simulation with smaller voxels, as reflected by reduced quantization artifacts. Conclusions: Our new breast anatomy simulation is substantially improved in terms of simulation time and the quality of the simulated images. This is especially important for the simulation of phantom images with various available detector resolutions.