Electronic Posters: Cardiovascular


Wednesday 13:30-15:30 Computer 38



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Wednesday 13:30-15:30 Computer 38

13:30 3720. 4D Right Ventricular Strain in Pulmonary Hypertension and Normals

Bharath Ambale Venkatesh1, Steven G. Lloyd2, Mustafa I. Ahmed2, Himanshu Gupta2, Louid Dell'Italia2, Thomas S. Denney Jr. 1

1Electrical and Computer Engineering, Auburn University, Auburn, AL, United States; 2University of Alabama at Birmingham

Accurate assessment of right ventricular (RV) function is clinically important – particularly in patients with pulmonary hypertension (PHTN). Compared to the left ventricle (LV), however, analysis of RV function is relatively difficult because of relatively thin walls and lack of geometric symmetry. Also in PHTN, higher systolic blood pressure in the RV can cause excursion of the interventricular septum into the LV cavity causing it to lose its geometric symmetry. This abstract presents a method for reconstructing three-dimensional biventricular strain from tagged MRI in each imaged time frame through mid-diastole. This method is validated on normal volunteers and PHTN patients.



14:00 3721. A Novel Centerline Model for Cardiac Long Axis Wall Motion Analysis

Ting Song1,2, Jeffrey A. Stainsby3, Maureen N. Hood2,4, Vincent B. Ho2,4

1GE Healthcare Applied Science Laboratory, Rockville, MD, United States; 2Radiology, Uniformed Services University of the Health Sciences, Bethesda, MD, United States; 3GE Healthcare Applied Science Laboratory, Toronto, ON, Canada; 4Radiology, National Navy Medical Center, Bethesda, MD, United States

A novel long axis wall motion quantification model is proposed to provide a reliable and simple solution to cardiac function calculations. Using only routine clinical MR cine images, functional parameters can be quantified determined retrospectively.



14:30 3722. Automated Synchronization of Cardiac Phases for Myocardial BOLD MRI

Sotirios A. Tsaftaris1,2, Xiangzhi Zhou2, Richard Tang2, Rachel Klein2, Aggelos Katsaggelos1, Rohan Dharmakumar2

1Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, United States; 2Radiology, Northwestern University, Chicago, IL, United States

It is particularly important for the evaluation of cardiac phase-resolved myocardial blood-oxygen-level-dependent (BOLD) MRI studies, to robustly and reproducibly synchronize images from rest and stress studies. The possibility of visualizing BOLD signal changes in multiple cardiac phases is expected to increase the diagnostic confidence for identifying the affected myocardial territories. The purpose of this work is to develop automated statistical methods to facilitate in the robust and reproducible evaluation of cardiac phase-resolved myocardial BOLD MRI through temporal synchronization of rest and stress images acquired at different heart rates, without resorting to LV segmentation.



15:00 3723. Using Vector Velocity Imaging (VVI) to Measure Left Ventricular Systolic Strain and Diastolic Strain Rate in Cine MRI

Nicholas M. Dunn1, Subha Raman2, Helene Houle3, Gianni Pedrizzetti4, Mani Vannan2, Orlando Simonetti2

1The Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, United States; 2Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH, United States; 3Siemens Medical Solutions, Mountain View, CA, United States; 4The University of Trieste, Trieste, Italy

Quantification of systolic strain and diastolic strain rate provide more sensitive indicators of myocardial dysfunction than subjective image interpretation. Vector Velocity Imaging (VVI) is a processing method developed to calculate myocardial strain and strain rate in echocardiography images. Its feasibility to calculate strain and strain rate in cine MR images was tested by analyzing short and long axis SSFP cine MR images of normal, healthy subjects and comparing the acquired values to literature values attained using other MR tissue-tagging methods. The results show that VVI may be used to calculate strain and strain rate in SSFP cine MRI.




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