The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1)

Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically “all-in-one” CMR, where several contrasts and/or motion states...

Rapid Whole-Knee Quantification of Cartilage Using T ₁, T ₂ ^∗, and T _RAFF2 Mapping With Magnetic Resonance Fingerprinting

Objective: Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T ₁, T ₂ ^∗, and T _RAFF2 with whole-knee coverage....

Sequence optimisation for Magnetic Resonance Fingerprinting

Magnetic Resonance Fingerprinting (MRF) is a relatively new approach for simultaneously estimating multiple quantitative maps in one acquisition. Sequence optimisation for MRF can be a powerful tool in increasing the accuracy an precision of the quantitative results. Multi-component analysis in the MRF framework can distinguish multiple...

Stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries

Objective: To visualize the encoding capability of magnetic resonance fingerprinting (MRF) dictionaries. Materials and methods: High-dimensional MRF dictionaries were simulated and embedded into a lower-dimensional space using t-distributed stochastic neighbor embedding (t-SNE). The embeddings were visualized via colors as a surrogate for...

Accelerated white matter lesion analysis based on simultaneous T₁ and T2∗ quantification using magnetic resonance fingerprinting and deep learning

Purpose: To develop an accelerated postprocessing pipeline for reproducible and efficient assessment of white matter lesions using quantitative magnetic resonance fingerprinting (MRF) and deep learning. Methods: MRF using echo-planar imaging (EPI) scans with varying repetition and echo times were acquired for whole brain quantification of ...

Lesion probability mapping in MS patients using a regression network on MR fingerprinting

Background: To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to T₁, T2∗, NAWM, and GM- probability maps. Methods: We performed MRF-EPI measurements in 42 patients with multiple sclerosis and 6 healthy...

An Efficient Method for Multi-Parameter Mapping in Quantitative MRI Using B-Spline Interpolation

Quantitative MRI methods that estimate multiple physical parameters simultaneously often require the fitting of a computational complex signal model defined through the Bloch equations. Repeated Bloch simulations can be avoided by matching the measured signal with a precomputed signal dictionary on a discrete parameter grid (i.e. lookup table...

Magnetic resonance fingerprinting for simultaneous renal T₁ and T2* mapping in a single breath-hold

Purpose: To evaluate the use of magnetic resonance fingerprinting (MRF) for simultaneous quantification of T₁ and T*₂ in a single breath-hold in the kidneys. Methods: The proposed kidney MRF sequence was based on MRF echo-planar imaging. Thirty-five measurements per slice and overall 4 slices were measured in 15.4...