The use and value of myocardial strain imaging have been increasing during the past 10 years. Among many applications, the most prominent include (a) the evaluation of cardiotoxicity in cancer patients undergoing chemotherapy, (b) prognosis and risk stratification in aortic stenosis, and (c) diagnosis and prognosis in undifferentiated left ventricular hypertrophy. We have developed Cine Displacement Encoding with Stimulated Echoes (DENSE) strain MRI, shared the method with other sites, and applied it to patient selection and procedure guidance in cardiac resynchronization therapy (CRT) for heart failure (HF). Cine DENSE is highly accurate and reproducible for the quantification of global and segmental myocardial strain, it is emerging as a gold standard technique, and it is being implemented by major manufacturers. However, current cine DENSE imaging requires multiple breathhold acquisitions or inefficient and inconvenient free-breathing acquisitions using diaphragm- based navigators, and neither approach is well suited for a rapid and efficient multiparametric cardiac MRI protocol or for sick patients with difficulty with breathhold-based protocols. In addition, inline strain analysis is not available and thus this task is performed offline on a workstation. With these limitations, more convenient methods such as feature tracking are often used, even though they are less accurate, less reproducible for segmental analysis, and/or less prognostic. This project will develop cine DENSE into a method that retains high accuracy and reproducibility and is also fast and easy-to-use. To achieve this goal, we propose four specific aims.
In Aim 1, we will develop an efficient self-navigated free-breathing cine DENSE method, and in Aim 2 we will develop accelerated cine DENSE using simultaneous multislice methods. The methods in Aims 1 and 2 will be combined to enable accelerated free-breathing imaging.
In Aim 3, we will develop methods for fully automatic displacement and strain analysis, enabling the implementation of inline strain mapping. Finally, in Aim 4 we will validate the methods developed in Aims 1-3 in healthy volunteers and HF patients scheduled to undergo CRT. Altogether, this project will result in a fast, reproducible, convenient and well-validated myocardial strain imaging method that will be broadly useful for the field of cardiac imaging.
The use and value of myocardial strain imaging have been increasing during the past 10 years. We have previously developed a highly accurate and reproducible MRI method for myocardial strain imaging, however the method has limitations with regard to speed and ease of use in sick patients. We propose to develop and validate improved methods that will result in a fast, reproducible, convenient and well-validated myocardial strain imaging method that will be broadly useful for the field of cardiac imaging.
