Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Body MRI: Applications & Evaluations

 
Tuesday May 10th
Exhibition Hall  13:30 - 15:30

2623.   Evaluation of the Recipient Vessels after Orthotopic Liver Transplantation by Non-Contrast Magnetic Resonance Angiography: a SLEEK sequence  
yigang pei1, and daoyu hu2
1Department of Radiology, Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology, wuhan, Hubei, China, People's Republic of, 21Department of Radiology, Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology

 
The recipient vessels after orthotopic liver transplantation (OLT) are often evaluated by CT and MRI, but the recipient vessels either may be contaminated by other vessel or may not be presented distinctly due to the individual hemodynamics changes. In addition, Gd or iodine contrast media are applied on CT and MRI for displaying the recipient vessel which may cause nephrogenic systemic fibrosis (NSF) or contrast-Induced Nephropathy. Therefore, a non-contrast magnetic resonance angiography (NC-MRA) is desirable to develop for presenting the recipient vessels. In this study, a new NC-MRA (Spatial LabEling with multiple invErsion pulses, SLEEK) has been applied to delineate the recipient vessel after OLT.

 
2624.   Robust Renal MRA using Breath-hold, IR-prep, Dixon bSSFP at 3T 
Pauline Wong Worters1, Manojkumar Saranathan1, Alan Xu1, and Shreyas Vasanawala1
1Stanford University, Stanford, CA, United States

 
A sequence is developed to provide high spatial resolution renal angiograms within breath-holding times. Balanced SSFP has good flow properties, and high T2/T1 contrast and SNR efficiency. IR preparation provides inflow sensitivity, while Dixon technique allows for excellent fat suppression. An efficient k-space trajectory enabled acquisition in 20-30 seconds. We evaluated IR-prep, Dixon bSSFP by comparing it to a commercially available, respiratory-gated technique Inhance IFIR (2-5 min) in 9 patients at 3T. No significant difference in artery visualization or image quality was found between Inhance IFIR and ECG-gated, breath-hold IR-prep, Dixon bSSFP. We have shown a robust sequence that provides diagnostic-quality renal angiograms comparable to a commercially available sequence, with significantly shorter scan times and without compromising spatial coverage and resolution.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Analysis of Breast Images

 
Wednesday May 11th
Exhibition Hall  13:30 - 15:30

2625.   The effect of acquisition parameter changes on the outcome of texture analysis using a clinical breast MRI sequence on a foam phantom at 1.5T 
Shelley Waugh1,2, Richard Lerski1,2, L. Bidaut2, and Alastair Thompson2,3
1Medical Physics, Ninewells Hospital, Dundee, United Kingdom, 2University of Dundee, Dundee, United Kingdom, 3Department of Surgery, Ninewells Hospital, United Kingdom

 
The aim of this study was to identify whether four different grades of reticulated foam, which appeared visually identical when imaged on a 1.5T MRI scanner using a gradient echo sequence, could be distinguished using texture analysis. The influence of changing the sequence parameters on the outcome of texture analysis was also assessed. Results showed that foams could be reliably differentiated using the wavelet transform, with no data misclassification. The co-occurrence matrix also produced moderately good results. Sequence parameter changes appeared to have little influence on the classification accuracy for this particular protocol and foam phantom.

 
2626.   Computerized Classification of Benign and Malignant Breast Lesions on DCE-MRI Utilizing Novel Shape Descriptors 
Rachel Evonne Sparks1, and Anant Madabhushi1
1Biomedical Engineering, Rutgers University, Piscataway, NJ, United States

 
The abstract presents a computerized decision support tool which utilizes novel morphologic descriptors for distinguishing benign from malignant breast lesions as they appear on DCE-MRI. The computerized decision support tools were evaluated on 41 suspicious breast lesions and gave a classification accurate of 83.0 ± 4.5 %.

 
2627.   Two non-linear parametric models of enhancement for breast DCE-MRI that can be fitted using linear least squares 
Andrew Mehnert1, Michael Wildermoth1, Stuart Crozier1, Ewert Bengtsson2, and Dominic Kennedy3
1School of ITEE, The University of Queensland, Brisbane, Qld, Australia, 2Centre for Image Analysis, Uppsala University, Sweden, 3Queensland X-Ray, Greenslopes Private Hospital, Greenslopes, Australia

 
Two non-linear empirical parametric models are proffered for use in quantitatively characterizing contrast enhancement in dynamic contrast enhanced MRI of the breast: linear-slope and Ricker. The advantage of these models over existing pharmacokinetic and empirical models is that they can be fitted using linear least squares which means that fitting is quick, there is no need to specify initial parameter estimates, and there are no convergence issues. An empirical evaluation of the goodness-of-fit of these two models relative to the Hayton and the simplified gamma-variate model is also presented.

 
2628.   The influence of field strength and different clinical breast MRI protocols on the outcome of texture analysis using foam phantoms 
Shelley Waugh1,2, Richard Lerski1,2, L. Bidaut2, and Alastair Thompson2,3
1Medical Physics, Ninewells Hospital, Dundee, Angus, United Kingdom, 2University of Dundee, Dundee, Angus, United Kingdom, 3Department of Surgery, Ninewells Hospital, United Kingdom

 
The aim of this study was to assess the impact of different imaging protocols and field strengths on classification accuracy of texture analysis in differentiating four different grades of reticulated foam when imaged using MRI gradient-echo sequences. A high spatial resolution protocol with matched acquisition parameters was used at 1.5T and 3.0T and a high temporal resolution sequence (lower spatial resolution) also used at 3.0T. Results showed that the wavelet transform resulted in perfect differentiation of the four foams across all protocols. The co-occurrence matrix results were improved at 3.0T compared to 1.5T, particularly for the high spatial resolution protocol.

 
2629.   Optimization of Breast Tissue Segmentation: Comparison of Support Vector Machine and Fuzzy C-mean Clustering Algorithms 
Yi Wang1,2, Glen Morrell2, Allison Payne2, and Dennis L. Parker1,2
1Bioengineering, University of Utah, Salt Lake City, UT, United States, 2Utah Center for Advanced Imaging Research, Salt Lake City, UT, United States

 
We compare two methods of breast tissue segmentation: 1) fuzzy c-mean clustering, an unsupervised learning method that classifies voxels into a specified number of clusters by iteratively minimizing intra-cluster variation, and 2) the support vector machine method, a supervised learning method that uses training data to construct hyper-planes to minimize the margin between classes. We also investigate the effect of varying the number of output clusters and the combinations of input image types. Our goal is to segment breast images into fibroglandular tissue, fat, lesions, and skin. Among other uses, segmentation aids magnetic resonance guided high-intensity focused ultrasound therapy by improving the accuracy of proton resonant frequency thermal mapping and improving the modeling of the simulated ultrasound beam patterns.

 
2630.   A comparative study of undersampling schemes for magnetic resonance dynamic contrast enhanced imaging 
Sairam Geethanath1, Praveen K Gulaka1, and Vikram D Kodibagkar1,2
1Joint graduate program in biomedical engineering, UT Arlington and UT Southwestern Medical Center, Dallas, Texas, United States, 2Radiology, UT Southwestern Medical Center

 
Fast imaging is a prerequisite for dynamic contrast enhanced (DCE) magnetic resonance imaging as high temporal resolution is required for accurate estimation of the pharmacokinetic parameters. This study involves the investigation of the comparison of two acceleration methods: keyhole imaging and compressed sensing (CS) as applied to DCE. Comparison has been done with respect to data quality and pharmacokinetic parameters for a range of undersampling schemes. CS provides better data quality and reproducible parametric maps at acceleration factors of up to 5X while keyhole performs comparably up to 3X

 
2631.   Image registration and pharmacokinetic parameter estimation for 3D DCE-MR mammography 
Andrew Melbourne1, John Hipwell1, Marc Modat1, Thomy Mertzanidou1, Henkjan Huisman2, Sebastien Ourselin1, and David Hawkes1
1University College London, London, United Kingdom, 2Radboud University Nijmegen Medical Centre, Netherlands

 
This work investigates the impact of motion artefacts by inspecting the results of pharmacokinetic modelling before, during and after automatic image alignment.

 
2632.   Influence of Fat-sat and Non-fat-sat Imaging Sequences, Spatial Resolution, and Breast Morphological Types on Density Measurements 
Daniel Han-en Chang1,2, Jeon-Hor Chen1,3, Muqing Lin1,2, Shadfar Bahri1,2, Hon J Yu1,2, Rita S Mehta4, Ke Nie1,2, David J.B Hsiang5, Orhan Nalcioglu1,2, and Min-Ying Lydia Su1,2
1Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine, CA, United States, 2Department of Radiological Sciences, University of California, Irvine, CA, United States,3Department of Radiology, China Medical University Hospital, Taichung, Taiwan, 4Department of Medicine, University of California, Irvine, CA, United States, 5Department of Surgery, University of California, Irvine, CA, United States

 
The differences in breast density parameters and the intra-rater variability analyzed on fat-sat vs. non-fat-sat imaging sequences in women presenting central and mixed breast morphological types were investigated. The measured breast volume on fat-sat and non-fat-sat sequences was almost identical; but there was a small (<5%) difference in fibroglandular volume and percent density, higher on fat-sat sequence. Intra-operator variability was within 4% for both sequences and different breast morphological types. Analysis based on images at original and reduced spatial resolution showed a small yet significant difference, indicating the potential influence of partial volume effect on density measurements.

 
2633.   Supervised Multispectral Analysis of Breast Density in MRI 
Hsian-Min Chen1, Siwa Chan2, Jyh-Wen Chai2, Clayton Chi-Chang Chen2, San-Kan Lee2, Chein-I Chang3, Min-Ying Su4, Orhan Nalcioglu4, and Jeon-Hor Chen4,5
1Department of Biomedical Engineering, HungKuang University, Taichung, Taiwan, 2Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan, 3Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore, United States, 4Center for Functional Onco-Imaging, University of California Irvine, California, United States, 5Department of Radiology, China Medical University Hospital, Taichung, Taiwan

 
A supervised multispectral analysis of breast density in MRI using ICA+SVM technique was developed. With this approach, two sets of images (T1WI and T2WI in this study) were needed for the analysis. ICA was used to enhance the image contrast and used as a preprocessing method to separate different tissue. SVM was used as a binary classifier to maximize the margin between two classes of data samples. In this study we have shown that the intra- and inter-operator measurement variation is very small. The high consistency of this method can be potentially applied for evaluation of small breast density change in longitudinal follow-up study.

 
2634.   Computational Simulation of Effects of the Morphology of Fibroglandular Tissues on Projected Breast Density Changes After Breast Compression Based on 3D MRI 
Tzu-Ching Shih1,2, Jeon-Hor Chen2,3, Muqing Lin3, Daniel Chang3, Ke Nie3, Orhan Nalcioglu3,4, and Min-Ying Su3
1Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, 40402, Taiwan, 2Department of Radiology, China Medical University Hospital, Taichung, 40402, Taiwan, 3Tu & Yuen Center for Functional Onco-Imaging and Department of Radiological Sciences, University of California, Irvine, Irvine, CA 92697, United States, 4Department of Cogno-Mechatronics Engineering, Pusan National University, Busan 609-735, Korea, Republic of

 
Usually, a breast tumor is harder than any tissue around it and the shape of benign masses is round or oval. By contrast, a malignant tumor is irregular in shape and has the invasive characteristics. Little is known about the influence of the morphology of fiborglandular tissues on breast density. Fibroglandular tissues would affect breast density. Breast compression changes breast density that indirectly influences the assessment of breast cancer risk. Thus, the purpose of this study is to investigate the effect of the morphology of fibroglandular tissue on the projected breast density after the breast compression based on a non-linear deformation using patient-specific magnetic resonance images.

 
2635.   Deformable Registration with Tumor Volume Preservation in Dynamic Contrast Enhanced MR Breast Images 
Hyun Hee Jo1, and Helen Hong1
1Division of Multimedia Engineering, Seoul Women's University, Seoul, Korea, Republic of

 
To preserve tumor volume in DCE-MR breast images, we propose a demon-based deformable registration with rigidity constraint and density correction. First, the breast skin is extracted by using maximum gradient profile searching and the other breast tissues are classified into fat, muscle, glandular tissue and tumor using k-means clustering. Then the density of each breast tissue except tumor region is corrected by using histogram matching. Second, the tumor is localized in the subtracted images and is segmented in post-contrast enhanced images. Finally, tumor regions are rigidly transformed by averaging the magnitudes of deformation vector fields in narrow band and the other breast tissues are deformed by using demon-based deformable registration. As a result, the proposed deformable registration significantly reduces the effect of movement artifacts in subtracted contrast-enhanced images as well as efficiently preserves the tumor volume. Our deformable registration can be used for distinguishing benign lesions from malignancies and monitoring therapy.

 
2636.   Evaluation of Spatial Changes of Fibroglandular Tissue in the Breast between Two Scans Using Non-rigid Registration Method 
Muqing Lin1, Jeon-Hor Chen1,2, Shadfar Bahri1, Siwa Chan3, Tzu-Ching Shih4, Ke Nie1, Orhan Nalcioglu1, and Min-Ying Lydia Su1
1Tu & Yuen Center for Functional Onco-Imaging and Department of Radiological Sciences, University of California, Irvine, CA, United States, 2Department of Radiology, China Medical University, Taichung, Taiwan, 3Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan, 4Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan

 
The purpose is to evaluate changes of fibroglandular tissue in two breast MRI scans taken at different times, to provide information about spatial change pattern of breast density with virtual display. The registration method is based on rigid alignment followed by non-rigid Demons algorithm. The methods are applied to cases that show different degrees of changes. The tool reveals breast density atrophy in patients receiving chemotherapy, and shows very little change between two scans of normal volunteers with 1-week apart. This co-registration method may provide a very useful tool for comparing screening MRI’s taken yearly for detection of early abnormality.

 
2637.   Novel Variable Voxel Intensity Correction Scheme and Application to Breast Imaging 
Anderson N Nnewihe1,2, Kyung H Sung1, Bruce L Daniel1, and Brian A Hargreaves1
1Radiology, Stanford University, Stanford, CA, United States, 2Bioengineering, Stanford University, Stanford, CA, United States

 
High-density surface coil arrays have been used for attaining highly accelerated, high resolution images for brain, breast and cardiac MRI studies. Due to the layout and size of the coil elements, these arrays usually exhibit sensitivity variations across the field of view. In this study, we introduce a novel variable voxel size intensity correction method that reduces intensity variations across the image while keeping the desired noise profile.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Analysis of Prostate Images

 
Thursday May 12th
Exhibition Hall  13:30 - 15:30

2638.   Prostate Cancer Probability Estimation Based on DCE-DTI Features and Support Vector Machine Classification 
Mehdi Moradi1, Septimiu E Salcudean1, Silvia D Chang2, Edward C Jones3, S Larry Goldenberg4,5, and Piotr Kozlowski2,6
1Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, 2Radiology, University of British Columbia, 3Pathology and Laboratory Medicine, University of British Columbia, 4Urologic Sciences, University of British Columbia, 5Vancouver Prostate Centre, University of British Columbia, 6MRI Research Centre, University of British Columbia, Vancouver, Canada

 
We use five parameters extracted from Diffusion Tensor Imaging (DTI) and Dynamic Contrast Enhanced (DCE) MRI for prostate cancer detection. 29 patients were involved. The method is based on support vector machine classification and calculation of posterior class probabilities. These cancer probability estimates are used for creating cancer maps validated based on histopathologic analysis of biopsy samples. We also found a correlation between the proposed measure of cancer probability and the Gleason grade of the tumors. The average probability value was 0.555 for tumors of grade 3+3, 0.778 for tumors of grades 3+4 and 4+3, and 0.963 for grade 4+5.

 
2639.   Multifarious Kinetic Analysis for Differentiation of Prostate Cancer and Benign Prostatic Hyperplasia in DCE-MRI 
Sang Ho Lee1, Jong Hyo Kim1,2, Jeong Yeon Cho2,3, Sang Youn Kim2,3, In Chan Song3, Hyeon Jin Kim3, and Seung Hyup Kim2,3
1Interdisciplinary Program in Radiation Applied Life Science, Seoul National University College of Medicine, Seoul, Korea, Republic of, 2Department of Radiology, Seoul National University College of Medicine, Seoul, Korea, Republic of, 3Department of Radiology, Seoul National University Hospital, Seoul, Korea, Republic of

 
DCE-MRI plays an essential role for cancer detection and characterization. The significant tissue parameters for lesion classification may take the form of synergistic subsets in the combinatorial space of multifarious kinetic features. In this study, we postulate that extending the individual analysis schemes of contrast enhancement kinetics to a hybrid analysis scheme and that selecting a meaningful feature subset from a combined feature pool may allow an improved performance for lesion classification. Based on this postulation, we presented a novel approach to prostate MRI computer-aided diagnosis (CAD) using multifarious kinetic parameters in DCE-MR images.

 
2640.   Computerized quantitative data integration of multi-protocol MRI for identification of high grade prostate cancer in vivo. 
Pallavi Tiwari1, John Kurhanewicz2, and Anant Madabhushi1
1Biomedical Engineering, Rutgers University, Piscataway, NJ, United States, 2Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, United States

 
In this work we present a novel multi-protocol MRI classifier, semi-supervised multi-kernel (SeSMiK), for quantitatively combining features from T2-w magnetic resonance (MR) imaging (T2 -w MRI) and MR spectroscopy (MRS) data to identify high grade prostate cancer (CaP) in vivo. High grade CaP is known to be correlated with more biologically aggressive prostate cancer; low grade CaP is typically associated with indolent disease. A computerized decision support (CDS) tool that can distinguish high grade from low grade prostate cancer in vivo could help identify those patients who might benefit from a “wait and watch policy” as opposed to those who might be better suited to application of more aggressive treatment strategies. The objective of this work is to build a CDS system that can distinguish high from low grade CaP in vivo, on a per voxel basis, using quantitative integration of T2 -w MRI and MRS. The SeSMiK strategy leverages multi-kernel learning (MKL) and dimensionality reduction (DR) to provide a unified framework for quantitative integration of T2-w MRI and MRS. Texture and metabolic features are extracted from T2-w MRI and MRS respectively. Extracted features are transformed to a similarity kernel space and then combined using MKL. The combined T2-w MRI, MRS data is then reduced to a low dimensional space using a DR scheme. A probabilistic boosting tree classifier which individually evaluated (1) T2-w MRI texture features, (2) MRS metabolic features, and (3) combined low dimensional features obtained via SeSMiK, suggest a higher accuracy and area under the receiver operating curve from SeSMiK compared to the individual T2-w MRI,MRS modalities. Our results suggest that the SeSMiK classifier might be able to ultimately identify biologically aggressive CaP in vivo.

 
2641.   Accuracy Enhancement of Automatic Prostate Tumor Detection using Additional Deformable Registration based Atlas Information: Automated Classifier using Permeability Parameters. 
Namkug Kim1, and JeongKon Kim1
1Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Seoul, Korea, Republic of

 
The prostate is anatomically composed of central, peripheral, and transitional zones. In the peripheral zone, 70% of prostate cancers arise. In addition, 20% of prostate cancers arise in the transitional zone. To exploit this tumor occurrence information, we evaluated accuracy enhancement for prostate tumor detection of automated classifier using deformable registration based atlas information as well as permeability parameters. In thirty seven patients with radical prostatectomy, MR images were obtained, including T2WI and dynamic contrast enhanced MR imaging for Brix permeability analysis. Each prostate was manually segmented into transitional zone and other zone by an expert radiologist and registered by FSL FNIRT deformable registration method. Sensitivity, specificity, accuracy, and AUC of ROC were significantly greater in automated classifier with atlas information (86.5¡¾0.02%, 95.5¡¾0.01%, 92.2¡¾1.08%, 92.9¡¾0.00 respectively) than in that without atlas information.

 
2642.   EMPrAvISE: A Computerized Decision Support System for Automated Prostate Cancer Detection from Multi-Protocol MRI 
Satish Viswanath1, B. Nicolas Bloch2, Jonathan Chappelow1, Pratik Patel1, Neil Rofsky3, Robert Lenkinski4, Elisabeth Genega4, and Anant Madabhushi1
1Biomedical Engineering, Rutgers University, Piscataway, NJ, United States, 2Boston Medical Center, 3UT Southwestern Medical Center, 4Beth Israel Deaconess Medical Center

 
We present a novel technique, Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE), for building a computerized meta-classifier to predict the spatial extent of prostate cancer (CaP) in vivo via multi-protocol (T2-weighted, Dynamic Contrast Enhanced, Diffusion-weighted) MRI data. We employ automated registration, quantitative image descriptors, and a novel ensemble representation technique in our methodology. Evaluation of our automated predictions for spatial extent of CaP at a pixel level (against registered extents of CaP on MRI) results in EMPrAvISE showing a statistically significant improvement (AUC=0.73) over individual protocols (T2w, DCE,DWI), as well as simple multi-protocol feature concatenation.

 
2643.   Accurate Prostate Volume Determination from T2-w MRI using Statistical Shape Models 
Robert James Toth1, B Nicholas Bloch2, Elizabeth M Genega3, Neil M Rofsky3, Robert E Lenkinski3, Mark A Rosen4, and Anant Madabhushi1
1Biomedical Engineering, Rutgers University, New Brunswick, NJ, United States, 2Boston Medical Center, Bostom, MA, United States, 3Beth Israel Deaconess Medical Center, Boston, MA, United States, 4Hospital at the University of Pennsylvania, Philadelphia, PA, United States

 
We present a method for using an advanced Active Shape Model based segmentation scheme to determine prostate volume on T2-weighted MR imagery. Our method was compared to the clinically standard ellipsoid technique and showed volume estimates more consistent with the ground truth volumes over 34 studies.

 
2644.   Exploration of BOLD-MRI in Prostate Cancer using Principal Component Analysis 
Aravinthan Jegatheesan1, Michael D Noseworthy1,2, Colm Boylan3, Robert Shayegan4, and John F MacGregor5
1School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada, 2Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada, 3St. Joseph's Healthcare, Hamilton, Ontario, Canada, 4Dept. of Urology, St. Joseph's Healthcare, Hamilton, Ontario, Canada, 5Chemical Engineering, McMaster University, Hamilton, Ontario, Canada

 
Principal component analysis was used to analyze BOLD-MRI of 5 patients with prostate tumors. The analysis attempts to identify the most significant temporal signatures to attempt to differentiate normal and tumor tissue. The results indicate that while the method maybe sensitive to a subset of tumors, it is not robust for detecting all tumors.

 
2645.   Determining histology-MRI slice correspondences for mapping prostate cancer extent in vivo 
Gaoyu Xiao1, B. Nicolas Bloch2, Jonathan Chappelow1, Elizabeth Genega3, Neil Rofsky3, Robert Lenkinski3, John Tomaszewski4, Michael Feldman4, Mark Rosen4, Arjun Kalyanpur5, and Anant Madabhushi1
1Rutgers University, Piscataway, NJ, United States, 2Boston Medical Center, MA, USA, 3Beth Israel Deaconess Medical Center, MA, USA, 4University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, USA., 5Teleradiology Solutions Pvt. Ltd. Whitefield, Bangalore, 560048, India

 
We present an automated computerized system to automatically determine slice correspondence between images from histology and MRI for the purpose of mapping spatial prostate cancer extent from wholemount histology slices to their corresponding in vivo T2 MRI slices. The mapping of prostate cancer extent is important in constructing computer-aided-diagnosis system and training radiology residents. The explicit determination of the histology-MRI slice correspondences is indispensable when an accurate 3D reconstruction of the histological volume cannot be achieved because of limited tissue slices with unknown inter-slice spacing, and histological image. The image slice correspondences obtained using our method were very close to the ground truth by medical experts.

 
2646.   Automatic Arterial Input Function Detection for Prostate Dynamic Contrast Enhanced MRI 
Yingxuan Zhu1, Ming-Ching Chang2, Fiona M Fennessy3, and Sandeep Narendra Gupta4
1Dept. of EECS, Syracuse University, Syracuse, NY, United States, 2Vis. and Comp. Vision Lab, GE Global Research Center, Niskayuna, NY, United States, 3Dept. of Radiology, Brigham and Women's Hospital, Boston, MA, United States, 4Functional Imaging Lab, GE Global Research Center, Niskayuna, NY, United States

 
Dynamic Contrast Enhanced MRI has shown promise in non-invasive assessment of tumor vascular properties for prostate cancer staging and treatment monitoring. Accurate quantification from DCEMRI requires the determination of arterial input function. AIF is commonly measured manually by selecting an ROI, which is time consuming and subjective. Automated ways of measuring AIF would be useful. This is challenging because of extreme intensity non-uniformity. Therefore existing methods do not perform well. Here, we use both temporal and spatial information to determine the AIF. We validate our method on clinical data and compare our approach with expert user defined manual AIFs.

 
2647.   CADOnc: A Computerized Decision Support System for Quantifying Radiation Therapy Changes in the Prostate via Multi-Parametric MRI 
Satish Viswanath1, Jonathan Chappelow1, Pallavi Tiwari1, John Kurhanewicz2, and Anant Madabhushi1
1Biomedical Engineering, Rutgers University, Piscataway, NJ, United States, 2University of California, San Francisco

 
We present CADOnc©, a novel computerized segmentation, registration, and classification framework for quantifying changes in the prostate due to radiation therapy (RT) via multi-parametric MRI (Magnetic Resonance Spectroscopy, T2-weighted, Diffusion-weighted). On a small preliminary cohort of patient data, CADOnc© accurately quantified changes in specific multi-parametric MRI biomarkers, for both pre- and post-RT data. Further, quantitatively integrating these markers shows excellent utility in (1) predicting disease extent on pre-RT data, and (2) quantifying both residual and possible new foci of disease, post-RT.

 
2648.   Rapid Quantitative T2 imaging of prostate cancer using a reduced FOV single-shot fast-spin-echo sequence 
Lawrence Patrick Panych1, Renxin Chu1, Yi Tang1, Stephan E Maier1, Clare M Tempany1, and Robert V Mulkern2
1Radiology, Brigham and Womens Hospital, Boston, MA, United States, 2Radiology, Children's Hospital, Boston, MA, United States

 
A reduced field-of-view single-shot fast-spin-echo sequence was implemented and applied for T2 quantification in the prostate. Six patients with biopsy-proven prostate cancer were imaged, acquiring whole-gland multiple-TE images in around one minute. Apparent T2 values were estimated from the multi-TE data for regions selected as being suspected healthy (SH) and suspected cancerous (SC). The apparent T2 in the SH regions was estimated at 224 +/- 67 msec and 129 +/- 25 msec in the SC regions. Sensitivity and specificity for detection of cancerous tissue is estimated to be 82% and 80% with this sequence.

 

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Neuro MRI: Applications & Evaluations

 
Monday May 9th
Exhibition Hall  14:00 - 16:00

2649.   Real-FLAIR: Real-part Imaging for Fluid Attenuated Inversion Recovery Sequence 
Tokunori Kimura1, and Mitsukazu Kamata1
1MRI development department, Toshiba Medical Systems corp., Otawara, Tochigi, Japan

 
A real-part imaging for inversion recovery (real-IR) is known that clinically useful to provide higher T1W contrasts than the magnitude-based IR especially for brain. Fluid attenuated inversion recovery (FLAIR) is one of inversion recovery (IR) sequences. In this study, we applied real-IR technique to Fast-Spin echo (FSE) based interleaved FLAIR sequence and assessed for tissue contrasts by volunteer brain study on 1.5T and 3T. We concluded that real-FLAIR imaging has more advantageous than the magnitude-based FLAIR imaging from the points of tissue contrast enhancement, robust against TI setting, and in addition, reducing CSF inflow artifacts.

 
2650.   3D Flow-dephased Fast Spin Echo for MR Neurography: a Feasibility Study 
Zhikui Xiao1, Lou Xin2, Shen Hao1, and Cao Guang1
1Global Applied Science Laboratory, GE Healthcare, Beijing, Beijing, China, People's Republic of, 2Department of Radiology, PLA General Hospital, Beijing, Beijing, China, People's Republic of

 
In this work, we implemented a 3D flow-dephasing prepared FSE sequence by adding a flow dephasing preparation pulse prior to 3D-FSE acquisition. This enables better blood signal suppression for isotropic high spatial resolution nerve imaging at 3.0T. In-vivo lumbosacral plexus results are shown to evaluate the proposed scheme. We show that flow-dephasing prepared image present significantly better blood vessel signal suppression with high spatial resolution.

 
2651.   EVALUATION OF NEONATAL PATHOLOGY USING T1 WEIGHTED TECHNIQUES, SNAPIR AND GRADIENT ECHO 
Amy Kathleen McGuinness1, Christina Malamateniou1, Joanna M Allsop1, Serena J Counsell1, Rita G Nunes1, Zhi Q Wu1, Nora Tusor2, Ash Ederies2, Jo V Hajnal1, and Mary A Rutherford1
1Imaging Sciences Department, MRC Clinical Sciences Centre, Hammersmith Hospital, Imperial College London, London, United Kingdom, 2Neonatal Imaging Group, Hammersmith Hospital, Imperial College London, London, United Kingdom

 
SNAPIR, an optimized single-shot T1-weighted acquisition, improves normal brain anatomy delineation in cases of fetal motion compared to a standard T1-weighted gradient echo (T1W-GE) protocol. However, the role of SNAPIR in neonatal imaging where motion may also be an issue has not yet been established. The aim of this study was to evaluate and compare neonatal brain pathology delineation using SNAPIR and a standard T1W-GE protocol, the MP-RAGE. In the absence of motion MP-RAGE is the preferred sequence. However, SNAPIR is almost as sensitive in many pathologies and is a robust technique when motion degrades T1W GE protocols.

 
2652.   3D DIR: 3D Double Inversion Recovery in Multiple Sclerosis 
Paul Polak1, Robert Zivadinov1,2, and Guy Poloni1
1Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, United States, 2The Jacobs Neurological Institute, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, United States

 
Multiple Sclerosis is believed to be a chronic, autoimmune, neurodegenerative disease of the CNS. Approaches that monitor disease progression in the white matter tissue via T2-weighed imaging suffer from the clinical/radiological paradox, in that poor or no correlation is found between clinical outcomes and MR metrics. We propose using an experimental method to optimize lesion contrast in white and grey matter tissues, using regions of interest analysis. Using the resulting data we propose a set of 3D DIR sequence parameters designed to improve the detection of clinically significant lesions in both white and grey matter.

 
2653.   3D FLAIR-ED: 3D Fluid Attenuated Inversion Recovery for Enhanced Detection of Lesions in Multiple Sclerosis 
Paul Polak1, Robert Zivadinov1,2, and Guy Poloni1
1Buffalo Neuroimaging Analysis Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, United States, 2The Jacobs Neurological Institute, Department of Neurology, University at Buffalo, State University of New York, Buffalo, NY, United States

 
Detection of brain tissue lesions via T2-weighted imaging is standard clinical practice in diagnosing and prognosis of multiple sclerosis. However, these methods suffer from the clinical/radiological paradox, in that poor or no correlation is found between clinical outcomes and MR metrics. Improving lesion sensitivity in MR techniques may help resolve this conflict. We propose an experimental method to optimize lesion contrast in a 3D FLAIR sequence using a region of interest analysis to optimize sequence parameters. The derived 3D FLAIR imaging sequence is superior to current clinical 2D and 3D FLAIR sequences, in both detection power and resolution.

 
2654.   Signal and Contrast Optimized Inversion Prepared Imaging 
Albert Kir1,2, and Alan Blair McMillan1
1Magnetic Resonance Research Center, Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States, 2Electrical Engineering and Computer Science, University of Maryland Baltimore County, Baltimore, MD, United States

 
Previous studies investigating optimized rapid 3D inversion-prepared gradient echo imaging sequences have relied upon the assumption of ideal radio-frequency (RF) spoiling. In this work, a new simulation approach based on the extended phase graph (EPG) formalism, which considers the effect of residual transverse magnetization, is used to predict both signal levels and contrast. We conducted phantom and in vivo brain studies to validate and verify the improvement of the proposed approach over approaches based on ideal RF spoiling, to generate images with optimal SNR, tissue contrast, and acquisition time.

 
2655.   Correlation of Phase values with CT Hounsfield and R2* values in calcified Neurocysticercosis 
Bhashwati Roy1, Sanjay Verma2, Rishi Awasthi1, Ram KS Rathore2, Ramesh Venkatesan3, SA Yoganathan4, KJ Maria Das4, Kashi Nath Prasad5, and Rakesh Kumar Gupta1
1Radiodiagnosis, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India, 2Mathematics & Statistics, Indian Institute of Technology, Kanpur, Kanpur, Uttar Pradesh, India, 3Wipro-GE Healthcare, Bangalore, Karnataka, India, 4Radiotherapy, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India, 5Microbiology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India, Lucknow, Uttar Pradesh, India

 
A total of 35 patients having fifty two calcified cysts were imaged using conventional and T2 star weighted angiography, used for extracting phase images. A significant correlation between CT-Hounsfield values and phase values proves the sensitivity of phase imaging in detecting presence calcification in a lesion as that of CT. In addition its ability to differentiate between diamagnetic and paramagnetic minerals gives phase imaging an edge over CT in demonstrating these lesions.

 
2656.   Single Phase 3D contrast-enhanced Intracranial Magnetic Resonance Angiography With Undersampled SWIRLS Trajectory at 3T 
Yunhong Shu1, Joshua D Trzasko1, John III Huston1, Armando Manduca1, and Matt A Bernstein1
1Radiology, Mayo Clinic, Rochester, MN, United States

 
The purpose of this work is to explore the feasibility of applying an undersampled spherical SWIRLS trajectory to CE-MRA applications at 3T. NUFFT reconstruction and off-resonance correction was used to further improve the image quality.

Traditional Posters : Pulse Sequences, Reconstruction & Analysis
Click on to view the abstract pdf and click on to view the pdf of the poster viewable in the poster hall.
Susceptibility MRI: Applications & Evaluations

 
Tuesday May 10th
Exhibition Hall  13:30 - 15:30

2657.   Harmonic phase subtraction methods are prone to B1 background components 
Ferdinand Schweser1,2, Marie Atterbury1,3, Andreas Deistung1, Berengar Wendel Lehr1, Karsten Sommer1,4, and Jürgen R. Reichenbach1
1Medical Physics Group, Dept. of Diagnostic and Interventional Radiology 1, Jena University Hospital, Jena, Germany, 2School of Medicine, Friedrich Schiller University of Jena, Jena, Germany,3Dept. of Physics, Brown University, Providence, RI, Germany, 4School of Physics and Astronomy, Friedrich Schiller University of Jena, Jena, Germany

 
In this contribution we investigate the effect of the B1 radio frequency (RF) signal induced phase offset on the results of two recently presented preprocessing methods for GRE phase data, namely SHARP and PDF. Furthermore, it is shown that these methods are mathematically equivalent.

 
2658.   Whole-brain voxel-based Susceptibility-Weighted Imaging (SWI) analysis: normal cortical and subcortical values, and preliminary results in post-traumatic epilepsy 
Hugo Alexandre Ferreira1, Alexandre Andrade1, Rui M Manaças2,3, and Pedro Miguel Gonçalves-Pereira3,4
1Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Lisboa, Portugal, 2Serviço de Neurorradiologia, Hospital dos Capuchos, Lisboa, Portugal, 3Serviço de Radiologia, Hospital dos Lusíadas, Lisboa, Portugal, 4Escola Superior de Tecnologias da Saúde, Instituto Politécnico de Lisboa, Lisboa, Portugal

 
An automated voxel-based analysis method of Susceptibility-Weighted Imaging (SWI) data was developed in combination with automated masks of brain structures to determine normal tissue values. Significant changes were observed with age and gender. A preliminary study comparing normal subjects to post-traumatic epilepsy (PTE) patients demonstrated changes in tissue magnetic susceptibility within limbic and mesencephalic structures.

 
2659.   Comparison of susceptibility gradient mapping and off-resonance excitation for quantitative positive contrast MRI of magnetotactic bacteria 
Sonal Josan1,2, Amanda Hamilton3, Michael Benoit3, Charles Cunningham4, Daniel Spielman2, A.C. Matin3, and Dirk Mayer1,2
1SRI International, Menlo Park, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States, 3Microbiology and Immunology, Stanford University, Stanford, CA, United States,4Sunnybrook Health Sciences Center, Toronto, ON, Canada

 
This work compares two positive contrast imaging techniques for quantitative detection of endogenous magnetite particles generaated by magnetotactic bacteria: off-resonance excitation and susceptibility gradient mapping (SGM). Off-resonance excitation uses spectral-spatial pulses to excite and refocus the off-resonant water protons near the magnetite particles while the SGM method involves post-processing of conventional 3D gradient echo images to calculate susceptibility gradients induced by the particles. Both techniques visualize the magnetite spots and provide good background suppression. Both methods demonstrated a linear correlation, but with different slopes, between iron concentration and the integrated signal intensity of “positive contrast voxels” at the spot location.

 
2660.   Orientation effects on the local magnetic field or phase and T2*-weighted hypointensity of gradient echo imaging and their removal in quantitative susceptibility mapping 
Jianqi Li1, Tian Liu2,3, Deqi Cui2,3, Qianfeng Wang1, Mengchao Pei1, Ming Zhang1, and Yi Wang2,3
1Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, Shanghai, China, People's Republic of, 2Radiology, Weill Medical College of Cornell University, New York, NY, United States, 3Biomedical Engineering, Cornell University, Ithaca, NY, United States

 
GRE is a commonly used pulse sequence in MRI. Both T2*-weighted hypointensity and phase contrast in the GRE images depend on relative orientation with respect to B0, and on the relative geometry between observation voxel and susceptibility source. We here illustrate the orientation effects on the induced local field or phase, T2* hypointensity, susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM). The shapes measured by the magnitude image and SWI and the induced field pattern varied strong with the orientation w.r.t. B0 or the blooming artifacts were strongly orientation-depended. The QSM removed the blooming artifacts and the calculated shapes didn¡¯t depend on the orientations.

 
2661.   Fast whole brain susceptibility imaging using 3D spiral 
bing Wu1, Wei Li1, Alex Avram1, Arnaud Guidon1, and Chunlei Liu1
1Brain imaging and analysis center, Duke University, Durham, NC, United States

 
Quantitative susceptibility mapping are usually calculated using the phase information obtained using 3D SPGR, which features long scan time due to the long echo time required and the line by line sample acquisition nature. We show the use of a 3D stack-of-spiral sequence may be a much more time efficient substitute to 3D SPGR. In an experiment conducted, very similar susceptibility maps, both qualitatively and quantitatively, are obtained using 3D SPGR and 3D spiral. However the 3D spiral sequence features a 13 times shorter scan time comparing to 3D SPGR for the same brain region coverage.

 
2662.   Quantitative Susceptibility Mapping of Cerebral Microbleeds 
Tian Liu1,2, Krishna Surapaneni3, Min Lou4, Liuquan Cheng5, Jianzhong Sun6, Cynthia Wisnieff1,2, Craig Horenstein3, Minming Zhang6, and Yi Wang1,2
1Biomedical Engineering, Cornell University, Ithaca, NY, United States, 2Radiology, Weill Cornell Medical College, New York, NY, United States, 3Radiology, Columbia University, New York, NY, United States, 4Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hang Zhou, Zhe Jiang, China, People's Republic of, 5Radiology, PLA General Hospital, Beijing, China, People's Republic of, 6Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hang Zhou, Zhe Jiang, China, People's Republic of

 
Gradient echo(GRE) MRI is the method of choice for detecting cerebral microbleeds(CMB) due to its sensitivity to the paramagnetic intreaparenchymal hemosiderin deposits. However, the hypointensity associated with CMB on a GRE image is highly dependent on the choice of echo time. In this study, we propose to use quantitative susceptibility mapping(QSM) as a more objective measurement of CMBs because the underlying susceptibility is theoretically independent of imaging parameter. Comparison of the T2* weighted image (T2*w), susceptibility weighted image (SWI) and R2* map showed the total susceptibility of a CMB varies the least with varying TEs.