In vivo cardiac diffusion tensor imaging in free-breathing conditions

Abstract

Background The fiber structure of the human heart contributes significantly to efficient ventricular function in the presence of disease. DTI provides a non-invasive approach for the three-dimensional depiction of the myocardial fiber architecture. The biggest problem for in vivo cardiac DTI is the signal loss caused by motion. Recently, to cope with human physiological motion problem, a robust method called PCATMIP was proposed (Rapacchi, Invest radiol 2011) that uses principal component analysis (PCA) filtering to improve the signal-to-noise ratio (SNR) and temporal maximum intensity projection (TMIP) approach to compensate the signal loss. While performing cardiac DTI during subject’s breath-hold may be not realistic to apply in clinical routine, achieving acquisitions during subject free-breathing represents an ultimate objective. In this study, our objective was to obtain in vivo DTI parameters of the human heart with free-breathing. Methods To cope with intensity fluctuations arising due to motion, our strategy was to acquire multiple diffusion weighted (DW) images at different time points during the diastole in each consecutive cardiac cycle; after each time frame was acquired, the trigger delay was increased by 10ms. At each trigger delay, we obtained 12 direction DW images and b=0. We acquired 10 DT-MRI slices across the whole heart. The total scan time is about 20 minutes at an average heart rate of 60bpm. The MRI parameters are: TE/TR=51/100ms, spatial resolution=2.6x2.6x6mm3, acceleration rate=2 (GRAPPA), partial Fourier=6/8, base resolution matrix=90x160, and b=200s/mm2. Free-breathing DWI scans were then registered using a non-rigid registration algorithm that preserves high accuracy and consistency of the data. Finally, PCATMIP algorithm was applied to the registered images to obtain motion-reduced ones.