Traditional Posters: Body Imaging
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| Endre Grøvik1, Kjell-Inge Gjesdal2, Kathinka Kurz Dæhli3, Atle Bjørnerud4
1University of Oslo, Oslo, Norway; 2Sunnmøre MR-klinikk, Aalesund, Norway; 3Stavanger University Hospital, Stavanger, Norway; 4Rikshospitalet University Hospital, Oslo, Norway This study investigates the influence of spatial heterogeneity on the diagnostic accuracy of DCE-MRI in breast tumor characterization. This is done by comparing the lesions VOI 50th-percentile versus VOI 95th-percentile values for a defined set of pharmacokinetic parameters, based on their ability for differentiating between malignant and benign lesions. Our results suggest that a significant improvement in diagnostic accuracy can be obtained by identifying the 5% region indicating the highest malignancy in the defined tumor VOI. 2484. Preliminary Results of a Physical Phantom for Quantitative Assessment of Breast MRI Melanie Freed1,2, Jacco A. de Zwart3, Jennifer T. Loud4, Riham H. El Khouli5, Mark H. Greene4, Brandon D. Gallas1, Kyle J. Myers1, Jeff H. Duyn3, David A. Bluemke5, Aldo Badano1 1CDRH/OSEL/DIAM, FDA, Silver Spring, MD, United States; 2Department of Bioengineering, University of Maryland, College Park, MD, United States; 3NINDS/LFMI/Advanced MRI Section, National Institutes of Health, Bethesda, MD, United States; 4NCI/Clinical Genetics Branch, National Institutes of Health, Rockville, MD, United States; 5Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, United States We are developing a physical, tissue-mimicking phantom to be used for task-based, quantitative assessment of breast MRI protocols. Here we present initial results of the phantom characterization and comparison to human data. Measured T1 and T2 relaxation values of the adipose- and glandular-mimicking phantom components agree with human values from the literature. The structure of human and phantom images is compared using the covariance kernel and found to match within patient variation. 2485. DSC MR-Mammography: Tumor Characterization Using Quantitative R2* Analysis Endre Grøvik1, Kathinka Kurz Dæhli2, Atle Bjørnerud3, Kjell-Inge Gjesdal4 1University of Oslo, Oslo, Norway; 2Stavanger University Hospital, Stavanger, Norway; 3Rikshospitalet University Hospital, Oslo, Norway; 4Sunnmøre MR-klinikk, Aalesund, Norway This work presents the transverse relaxation rate, R2*, as a quantitative biomarker for distinguishing between malignant and benign breast lesions. R2* was estimated on a pixel-by-pixel basis by assuming a mono-exponential dependence of a double-echo intensity scheme, yielding from a high temporal resolution sequence. The study suggested that the peak change in the transverse relaxation rate is a sensitive biomarker for tumor malignancy in DSC MR-mammography. 2486. Simulation of Breast Tumor Growth from In-Situ to Invasive Cancer Using a Mathematical Model to Correlate with Lesion Phenotypes Shown on MRI Ke Nie1, Jeon-Hor Chen1,2, Orhan Nalcioglu1, Min-Ying Lydia Su1 1Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine, Irvine, CA, United States; 2Department of Radiology, China Medical University, Taichung, Taiwan Mathematical modeling provides a unique means to simulate different cancer growth patterns. However, the current published models included only functional information, few of them considered the effect of environmental structure. In this study, we simulated the breast tumor growth in the duct by coupling tumor growth and duct wall deformation. By varying the key parameters, we could identify key mechanisms for DCIS to progress to invasive cancer. The simulation result is further correlated with the lesion phenotype shown on MRI. Understanding these biological growth patterns of DCIS may be further used to refine diagnostic criteria. 2487. MRI Detection of Small Calcium Crystals in Air Bubble-Free Agarose Phantoms: Potential Applications to Imaging Microcalcifications in Breast Cancer Bo Elizabeth Peng1, Sean Foxley2, Jeremy Palgen1, Robin Holmes2, Elizabeth Hipp2, Gillian Newstead2, Gregory S. Karczmar2, Devkumar Mustafi1,2 1Biochemistry & Molecular Biology, The University of Chicago, Chicago, IL, United States; 2Radiology, The University of Chicago, Chicago, IL, United States We tested several MRI methods for the identification and characterization of small calcium crystals for probing microcalcifications in breast cancer. High-resolution MR images were acquired of small Ca-crystals imbedded in air bubble-free agarose phantoms in clinical and research magnets. Two types of Ca-crystals that are commonly associated with benign and malignant breast lesions, are clearly detectable and distinguishable by MRI, but not distinguishable on x-ray mammograms. The present results lend support to the feasibility of clinical visualization and analysis of microcalcifications by MRI. Detection of microcalcifications by MRI would increase sensitivity and specificity for breast cancer detection. 2488. Microcalcification Detection Using Susceptibility Weighted Phase Imaging: Cross-Correlation and Relative Magnetic Susceptibility Difference Methods Yüklə 458,11 Kb. Dostları ilə paylaş:
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