58 research outputs found
Integrated and efficient diffusion-relaxometry using ZEBRA
The emergence of multiparametric diffusion models combining diffusion and
relaxometry measurements provide powerful new ways to explore tissue
microstructure with the potential to provide new insights into tissue structure
and function. However, their ability to provide rich analyses and the potential
for clinical translation critically depends on the availability of efficient,
integrated, multi-dimensional acquisitions. We propose a fully integrated
sequence simultaneously sampling the acquisition parameter spaces required for
T1 and T2* relaxometry and diffusion MRI. Slice-level interleaved diffusion
encoding, multiple spin/gradient echoes and slice-shuffling are combined for
higher efficiency, sampling flexibility and enhanced internal consistency.
In-vivo data was successfully acquired on healthy adult brains. Obtained
parametric maps as well as clustering results demonstrate the potential of the
technique regarding its ability to provide eloquent data with an acceleration
of roughly 20 compared to conventionally used approaches. The proposed
integrated acquisition, called ZEBRA, offers significant acceleration and
flexibility compared to existing diffusion-relaxometry studies and thus
facilitates wider use of these techniques both for research-driven and clinical
applications
Fetal whole-heart 4D imaging using motion-corrected multi-planar real-time MRI
Purpose: To develop a MRI acquisition and reconstruction framework for
volumetric cine visualisation of the fetal heart and great vessels in the
presence of maternal and fetal motion.
Methods: Four-dimensional depiction was achieved using a highly-accelerated
multi-planar real-time balanced steady state free precession acquisition
combined with retrospective image-domain techniques for motion correction,
cardiac synchronisation and outlier rejection. The framework was evaluated and
optimised using a numerical phantom, and evaluated in a study of 20 mid- to
late-gestational age human fetal subjects. Reconstructed cine volumes were
evaluated by experienced cardiologists and compared with matched ultrasound. A
preliminary assessment of flow-sensitive reconstruction using the velocity
information encoded in the phase of dynamic images is included.
Results: Reconstructed cine volumes could be visualised in any 2D plane
without the need for highly-specific scan plane prescription prior to
acquisition or for maternal breath hold to minimise motion. Reconstruction was
fully automated aside from user-specified masks of the fetal heart and chest.
The framework proved robust when applied to fetal data and simulations
confirmed that spatial and temporal features could be reliably recovered.
Expert evaluation suggested the reconstructed volumes can be used for
comprehensive assessment of the fetal heart, either as an adjunct to ultrasound
or in combination with other MRI techniques.
Conclusion: The proposed methods show promise as a framework for
motion-compensated 4D assessment of the fetal heart and great vessels
Recommended from our members
Resting State fMRI in the moving fetus: A robust framework for motion, bias field and spin history correction
There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, Combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies
- …