While magnetic resonance imaging (MRI) is clinically very valuable, current imaging methods are subject to blurring and artifacts in the presence of physiologic (e.g., respiratory and cardiac) motion, as well as of arrhythmias, thus limiting the practical application of MRI in many patients. The currently used MRI methods are also limited in their ability to study the effects of free breathing and arrhythmias on the heart. The proposed research will further develop and evaluate a new approach to imaging in the presence of physiologic motion, which parameterizes such motions with a variable that is treated as an additional dimension to be reconstructed. This would not be practically feasible with conventional methods, due to the additional associated data acquisition that would be required. However, with the use of sparsity-based image reconstruction methods, the high degree of correlation of the images along these additional dimensions permits good quality image reconstructions, even with heavily undersampled imaging data. We already have made successful initial implementations of this new method for 2D cine imaging and 3D MR angiography. In the proposed research, we will further improve these initial implementations, and we will extend them to include implementations of our methods for other MRI sequences, particularly fully 3D cine data acquisitions. We will evaluate the image quality achievable with these new methods in the presence of free breathing and arrhythmias, as compared with conventional clinical imaging methods, using both numerical phantom simulations and clinical cardiac function analysis in pediatric patients to test the performance. We will also evaluate the potential for extracting new kinds of functional information from these multidimensional image sets, including the effects of free breathing and arrhythmias on the heart, using analysis tools that we will be developing. If this research is successful, these new methods will provide significantly improved MR image quality in the presence of free breathing and arrhythmias, as well as providing potentially valuable new kinds of information on the function of the heart. They may also be able to be used for performing MRI in the presence of exercise, which could be useful for both cardiovascular and musculoskeletal applications, as well as in combination with other kinds of imaging, such as with integrated PET/MRI systems. This research should thus further increase the clinical utility of MR imaging for many patients.

Public Health Relevance

Magnetic resonance imaging (MRI) is clinically very useful; however, with current imaging methods, the image quality is often degraded by respiratory or cardiac motion, lessening its usefulness. The proposed research seeks to develop a new approach to MRI, which is more robust to the effects of such physiologic motions, thus providing better images; it can also provide new kinds of functional information on the heart.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21EB019595-01A1
Application #
8968594
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
Project Start
2015-09-01
Project End
2017-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
New York University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
121911077
City
New York
State
NY
Country
United States
Zip Code
10016