John S Wilson1, Xiaodong Zhong2, Jackson B Hair3, W Robert Taylor4, John Oshinski5. 1. Department of Radiology & Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA. 2. Magnetic Resonance R&D Collaborations, Siemens Healthcare, Atlanta, GA, USA; Department of Radiology & Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA. 3. Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA. 4. Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA; Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA; Division of Cardiology, Department of Medicine, Atlanta VA Medical Center, Decatur, GA, USA. 5. Department of Radiology & Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Abstract
INTRODUCTION: Regional tissue mechanics play a fundamental role in patient-specific cardiovascular function. Nevertheless, regional assessments of aortic kinematics remain lacking due to the challenge of imaging the thin aortic wall. Herein, we present a novel application of DENSE (Displacement Encoding with Stimulated Echoes) MRI to quantify the circumferential Green strain of the thoracic and abdominal aorta. METHODS: 2D spiral cine DENSE and steady-state free procession (SSFP) cine images were acquired at 3T at the infrarenal aorta (IAA), descending thoracic aorta (DTA), or distal aortic arch (DAA) in a pilot study of 6 healthy volunteers. DENSE data was processed with multiple custom noise-reduction techniques to calculate circumferential Green strain across 16 equispaced sectors around the aorta. Each volunteer was scanned twice to evaluate interstudy repeatability. RESULTS: Circumferential strain was heterogeneously distributed in all volunteers and locations. Spatial heterogeneity index by location was 0.37 (IAA), 0.28 (DTA), and 0.59 (DAA). Mean peak strain by DENSE for each cross-section was consistent with the homogenized linearized strain estimated from SSFP cine. The mean difference in peak strain across all sectors following repeat imaging was -0.1±2.2%, with a mean absolute difference of 1.7%. CONCLUSIONS: Aortic cine DENSE MRI is a viable non-invasive technique for quantifying heterogeneous regional aortic wall strain and has significant potential to improve patient-specific clinical assessments of numerous aortopathies, as well as to provide the lacking spatiotemporal data required to refine computational models of aortic growth and remodeling.
INTRODUCTION: Regional tissue mechanics play a fundamental role in patient-specific cardiovascular function. Nevertheless, regional assessments of aortic kinematics remain lacking due to the challenge of imaging the thin aortic wall. Herein, we present a novel application of DENSE (Displacement Encoding with Stimulated Echoes) MRI to quantify the circumferential Green strain of the thoracic and abdominal aorta. METHODS: 2D spiral cine DENSE and steady-state free procession (SSFP) cine images were acquired at 3T at the infrarenal aorta (IAA), descending thoracic aorta (DTA), or distal aortic arch (DAA) in a pilot study of 6 healthy volunteers. DENSE data was processed with multiple custom noise-reduction techniques to calculate circumferential Green strain across 16 equispaced sectors around the aorta. Each volunteer was scanned twice to evaluate interstudy repeatability. RESULTS: Circumferential strain was heterogeneously distributed in all volunteers and locations. Spatial heterogeneity index by location was 0.37 (IAA), 0.28 (DTA), and 0.59 (DAA). Mean peak strain by DENSE for each cross-section was consistent with the homogenized linearized strain estimated from SSFP cine. The mean difference in peak strain across all sectors following repeat imaging was -0.1±2.2%, with a mean absolute difference of 1.7%. CONCLUSIONS:Aortic cine DENSE MRI is a viable non-invasive technique for quantifying heterogeneous regional aortic wall strain and has significant potential to improve patient-specific clinical assessments of numerous aortopathies, as well as to provide the lacking spatiotemporal data required to refine computational models of aortic growth and remodeling.
Authors: Mary T Draney; Robert J Herfkens; Thomas J R Hughes; Norbert J Pelc; Kristin L Wedding; Christopher K Zarins; Charles A Taylor Journal: Ann Biomed Eng Date: 2002-09 Impact factor: 3.934
Authors: Konstantinos Karatolios; Andreas Wittek; Thet Htar Nwe; Peter Bihari; Amit Shelke; Dennis Josef; Thomas Schmitz-Rixen; Josef Geks; Bernhard Maisch; Christopher Blase; Rainer Moosdorf; Sebastian Vogt Journal: Ann Thorac Surg Date: 2013-08-30 Impact factor: 4.330
Authors: Andreas Wittek; Konstantinos Karatolios; Claus-Peter Fritzen; Jürgen Bereiter-Hahn; Bernhard Schieffer; Rainer Moosdorf; Sebastian Vogt; Christopher Blase Journal: Biomech Model Mechanobiol Date: 2016-02-20
Authors: Henrik Haraldsson; Michael Hope; Gabriel Acevedo-Bolton; Elaine Tseng; Xiaodong Zhong; Frederick H Epstein; Liang Ge; David Saloner Journal: J Cardiovasc Magn Reson Date: 2014-01-09 Impact factor: 5.364