One-millimeter isotropic breast diffusion-weighted imaging: Evaluation of a superresolution strategy in terms of signal-to-noise ratio, sharpness and apparent diffusion coefficient.

PURPOSE: To quantitatively evaluate a superresolution technique for 3D, one-millimeter isotropic diffusion-weighted imaging (DWI) of the whole breasts. METHODS: Isotropic 3D DWI datasets are obtained using a combination of (i) a readout-segmented diffusion-weighted-echo-planar imaging (DW-EPI) sequence (rs-EPI), providing high in-plane resolution, and (ii) a superresolution (SR) strategy, which consists of acquiring 3 datasets with thick slices (3 mm) and 1-mm shifts in the slice direction, and combining them into a 1 × 1 × 1-mm3 dataset using a dedicated reconstruction. Two SR reconstruction schemes were investigated, based on different regularization schemes: conventional Tikhonov or Beltrami (an edge-preserving constraint). The proposed SR strategy was compared to native 1 × 1 × 1-mm3 acquisitions (i.e. with 1-mm slice thickness) in 8 healthy subjects, in terms of signal-to-noise ratio (SNR) efficiency, using a theoretical framework, Monte Carlo simulations and region-of-interest (ROI) measurements, and image sharpness metrics. Apparent diffusion coefficient (ADC) values in normal breast tissue were also compared. RESULTS: The SR images resulted in an SNR gain above 3 compared to native 1 × 1 × 1-mm3 using the same acquisition duration (acquisition gain 3 and reconstruction gain >1). Beltrami-SR provided the best results in terms of SNR and image sharpness. The ADC values in normal breast measured from Beltrami-SR were preserved compared to low-resolution images (1.91 versus 1.97 ×10-3 mm2 /s, P = .1). CONCLUSION: A combination of rs-EPI and SR allows 3D, 1-mm isotropic breast DWI data to be obtained with better SNR than a native 1-mm isotropic acquisition. The proposed DWI protocol might be of interest for breast cancer monitoring/screening without injection.

Flow MRI simulation in complex 3D geometries: Application to the cerebral venous network.

PURPOSE: Develop and evaluate a complete tool to include 3D fluid flows in MRI simulation, leveraging from existing software. Simulation of MR spin flow motion is of high interest in the study of flow artifacts and angiography. However, at present, only a few simulators include this option and most are restricted to static tissue imaging. THEORY AND METHODS: An extension of JEMRIS, one of the most advanced high performance open-source simulation platforms to date, was developed. The implementation of a Lagrangian description of the flow allows simulating any MR experiment, including both static tissues and complex flow data from computational fluid dynamics. Simulations of simple flow models are compared with real experiments on a physical flow phantom. A realistic simulation of 3D flow MRI on the cerebral venous network is also carried out. RESULTS: Simulations and real experiments are in good agreement. The generality of the framework is illustrated in 2D and 3D with some common flow artifacts (misregistration and inflow enhancement) and with the three main angiographic techniques: phase contrast velocimetry (PC), time-of-flight, and contrast-enhanced imaging MRA. CONCLUSION: The framework provides a versatile and reusable tool for the simulation of any MRI experiment including physiological fluids and arbitrarily complex flow motion.