skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Evaluating Passive Myocardial Stiffness Using in vivo cine, cDTI, and Tagged MRI
Increased passive myocardial stiffness is implicated in the pathophysiology of many cardiac diseases, and its in vivo estimation can improve management of heart disease. MRI-driven computational constitutive modeling has been used extensively to evaluate passive myocardial stiffness. This approach requires subject-specific data that is best acquired with different MRI sequences: conventional cine (e.g. bSSFP), tagged MRI (or DENSE), and cardiac diffusion tensor imaging. However, due to the lack of comprehensive datasets and the challenge of incorporating multi-phase and single-phase disparate MRI data, no studies have combined in vivo cine bSSFP, tagged MRI, and cardiac diffusion tensor imaging to estimate passive myocardial stiffness. The objective of this work was to develop a personalized in silico left ventricular model to evaluate passive myocardial stiffness by integrating subject-specific geometric data derived from cine bSSFP, regional kinematics extracted from tagged MRI, and myocardial microstructure measured using in vivo cardiac diffusion tensor imaging. To demonstrate the feasibility of using a complete subject-specific imaging dataset for passive myocardial stiffness estimation, we calibrated a bulk stiffness parameter of a transversely isotropic exponential constitutive relation to match the local kinematic field extracted from tagged MRI. This work establishes a pipeline for developing subject-specific biomechanical ventricular models to probe passive myocardial mechanical behavior, using comprehensive cardiac imaging data from multiple in vivo MRI sequences.  more » « less
Award ID(s):
2205103
PAR ID:
10447284
Author(s) / Creator(s):
; ; ; ; ; ; ;
Editor(s):
Bernard, O.; Clarysse, P.; Duchateau, N.; Ohayon, J.; Viallon, M
Date Published:
Journal Name:
Functional Imaging and Modeling of the Heart. FIMH 2023. Lecture Notes in Computer Science.
Volume:
13958
Page Range / eLocation ID:
527-536
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, Magnetic Resonance in Medicine)
    Abstract PurposeTo determine the feasibility of simultaneous multi‐slice (SMS) real‐time MRI (RT‐MRI) at 0.55T for the evaluation of cardiac function. MethodsCardiac CINE MRI is routinely used to evaluate left‐ventricular (LV) function. The standard is sequential multi‐slice balanced SSFP (bSSFP) over a stack of short‐axis slices using electrocardiogram (ECG) gating and breath‐holds. SMS has been used in CINE imaging to reduce the number of breath‐holds by a factor of 2–4 at 1.5T, 3T, and recently at 0.55T. This work aims to determine if SMS is similarly effective in the RT‐MRI evaluation of cardiac function. We used an SMS bSSFP pulse sequence with golden‐angle spirals at 0.55T with an SMS factor of three. We cover the LV with three acquisitions for SMS, and nine for single‐band (SB). Imaging was performed on 9 healthy volunteers and 1 patient with myocardial fibrosis and sternal wires. A spatio‐temporal constrained reconstruction is used, with regularization parameters selected by a board‐certified cardiologist. Images were quantitatively analyzed with a normalized contrast and an Edge Sharpness (ES) score. ResultsThere was a statistically significant 2‐fold difference in contrast between SMS and SB and no significant difference in ES score. The contrast for SMS and SB were 13.38/29.05 at mid‐diastole and 10.79/22.26 at end‐systole; the ES scores for SMS and SB were 1.77/1.83 at mid‐diastole and 1.50/1.72 at end‐systole. ConclusionsSMS cardiac RT‐MRI at 0.55T is feasible and provides sufficient blood‐myocardium contrast to evaluate LV function in three slices simultaneously without any gating or periodic motion assumptions. 
    more » « less
  2. ; ; ; ; ; (, Magnetic Resonance in Medicine)
    PurposeTo determine if contemporary 0.55 T MRI supports the use of contrast‐optimal flip angles (FA) for simultaneous multi‐slice (SMS) balanced SSFP (bSSFP) cardiac function assessment, which is impractical at conventional field strengths because of excessive SAR and/or banding artifacts. MethodsBlipped‐CAIPI bSSFP was combined with spiral sampling for ventricular function assessment at 0.55 T. Cine movies with single band and SMS factors of 2 and 3 (SMS 2 and 3), and FA ranging from 60° to 160°, were acquired in seven healthy volunteers. Left ventricular blood and myocardial signal intensity (SI) normalized by background noise and blood–myocardium contrast were measured and compared across acquisition settings. ResultsMyocardial SI was slightly higher in single band than in SMS and decreased with an increasing FA. Blood SI increased as the FA increased for single band, and increment was small for FA ≥120°. Blood SI for SMS 2 and 3 increased with an increasing FA up to ∼100°. Blood–myocardium contrast increased with an increasing FA for single band, peaked at FA = 160° (systole: 28.43, diastole: 29.15), attributed mainly to reduced myocardial SI when FA ≥120°. For SMS 2, contrast peaked at 120° (systole: 21.43, diastole: 19.85). For SMS 3, contrast peaked at 120° in systole (16.62) and 100° in diastole (19.04). ConclusionsContemporary 0.55 T MR scanners equipped with high‐performance gradient systems allow the use of contrast‐optimal FA for SMS accelerated bSSFP cine examinations without compromising image quality. The contrast‐optimal FA was found to be 140° to 160° for single band and 100° to 120° for SMS 2 and 3. 
    more » « less
  3. ; ; ; ; ; ; (, Proc. of the 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (EMBC 2021))
    Cardiac Cine Magnetic Resonance (CMR) Imaging has made a significant paradigm shift in medical imaging technology, thanks to its capability of acquiring high spatial and temporal resolution images of different structures within the heart that can be used for reconstructing patient-specific ventricular computational models. In this work, we describe the development of dynamic patient-specific right ventricle (RV) models associated with normal subjects and abnormal RV patients to be subsequently used to assess RV function based on motion and kinematic analysis. We first constructed static RV models using segmentation masks of cardiac chambers generated from our accurate, memory-efficient deep neural architecture - CondenseUNet - featuring both a learned group structure and a regularized weight-pruner to estimate the motion of the right ventricle. In our study, we use a deep learning-based deformable network that takes 3D input volumes and outputs a motion field which is then used to generate isosurface meshes of the cardiac geometry at all cardiac frames by propagating the end-diastole (ED) isosurface mesh using the reconstructed motion field. The proposed model was trained and tested on the Automated Cardiac Diagnosis Challenge (ACDC) dataset featuring 150 cine cardiac MRI patient datasets. The isosurface meshes generated using the proposed pipeline were compared to those obtained using motion propagation via traditional non-rigid registration based on several performance metrics, including Dice score and mean absolute distance (MAD). 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, Science Robotics)
    The complex motion of the beating heart is accomplished by the spatial arrangement of contracting cardiomyocytes with varying orientation across the transmural layers, which is difficult to imitate in organic or synthetic models. High-fidelity testing of intracardiac devices requires anthropomorphic, dynamic cardiac models that represent this complex motion while maintaining the intricate anatomical structures inside the heart. In this work, we introduce a biorobotic hybrid heart that preserves organic intracardiac structures and mimics cardiac motion by replicating the cardiac myofiber architecture of the left ventricle. The heart model is composed of organic endocardial tissue from a preserved explanted heart with intact intracardiac structures and an active synthetic myocardium that drives the motion of the heart. Inspired by the helical ventricular myocardial band theory, we used diffusion tensor magnetic resonance imaging and tractography of an unraveled organic myocardial band to guide the design of individual soft robotic actuators in a synthetic myocardial band. The active soft tissue mimic was adhered to the organic endocardial tissue in a helical fashion using a custom-designed adhesive to form a flexible, conformable, and watertight organosynthetic interface. The resulting biorobotic hybrid heart simulates the contractile motion of the native heart, compared with in vivo and in silico heart models. In summary, we demonstrate a unique approach fabricating a biomimetic heart model with faithful representation of cardiac motion and endocardial tissue anatomy. These innovations represent important advances toward the unmet need for a high-fidelity in vitro cardiac simulator for preclinical testing of intracardiac devices. 
    more » « less
  5. ; ; ; ; ; ; ; ; ; ; et al (, Imaging Neuroscience)
    Abstract Diffusion MRI (dMRI) has become a crucial imaging technique in the field of neuroscience, with a growing number of clinical applications. Although most studies still focus on the brain, there is a growing interest in utilizing dMRI to investigate the healthy or injured spinal cord. The past decade has also seen the development of biophysical models that link MR-based diffusion measures to underlying microscopic tissue characteristics, which necessitates validation through ex vivo dMRI measurements. Building upon 13 years of research and development, we present an open-source, MATLAB-based academic software toolkit dubbed ACID: A Comprehensive Toolbox for Image Processing and Modeling of Brain, Spinal Cord, and Ex Vivo Diffusion MRI Data. ACID is an extension to the Statistical Parametric Mapping (SPM) software, designed to process and model dMRI data of the brain, spinal cord, and ex vivo specimens by incorporating state-of-the-art artifact correction tools, diffusion and kurtosis tensor imaging, and biophysical models that enable the estimation of microstructural properties in white matter. Additionally, the software includes an array of linear and nonlinear fitting algorithms for accurate diffusion parameter estimation. By adhering to the Brain Imaging Data Structure (BIDS) data organization principles, ACID facilitates standardized analysis, ensures compatibility with other BIDS-compliant software, and aligns with the growing availability of large databases utilizing the BIDS format. Furthermore, being integrated into the popular SPM framework, ACID benefits from a wide range of segmentation, spatial processing, and statistical analysis tools as well as a large and growing number of SPM extensions. As such, this comprehensive toolbox covers the entire processing chain from raw DICOM data to group-level statistics, all within a single software package. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email