Purpose A retrospective study was performed to study the effect of fetal surgery on brain development measured by MRI in fetuses with myelomeningocele (MMC). Methods MRI scans of 12 MMC fetuses before and after surgery were compared to 24 age-matched controls without central nervous system abnormalities. An automated super-resolution reconstruction technique generated isotropic brain volumes to mitigate 2D MRI fetal motion artefact. Unmyelinated white matter, cerebellum and ventricles were automatically segmented, and cerebral volume, shape and cortical folding were thereafter quantified. Biometric measures were calculated for cerebellar herniation level (CHL), clivus-supraocciput angle (CSO), transverse cerebellar diameter (TCD) and ventricular width (VW). Shape index (SI), a mathematical marker of gyrification, was derived. We compared cerebral volume, surface area and SI before and after MMC fetal surgery versus controls. We additionally identified any relationship between these outcomes and biometric measurements. Results MMC ventricular volume/week (mm3/week) increased after fetal surgery (median: 3699, interquartile range (IQR): 1651–5395) compared to controls (median: 648, IQR: 371–896); P = 0.015. The MMC SI is higher pre-operatively in all cerebral lobes in comparison to that in controls. Change in SI/week in MMC fetuses was higher in the left temporal lobe (median: 0.039, IQR: 0.021–0.054), left parietal lobe (median: 0.032, IQR: 0.023–0.039) and right occipital lobe (median: 0.027, IQR: 0.019–0.040) versus controls (P = 0.002 to 0.005). Ventricular volume (mm3) and VW (mm) (r = 0.64), cerebellar volume and TCD (r = 0.56) were moderately correlated. Conclusions Following fetal myelomeningocele repair, brain volume, shape and SI were significantly different from normal in most cerebral layers. Morphological brain changes after fetal surgery are not limited to hindbrain herniation reversal. These findings may have neurocognitive outcome implications and require further evaluation.
To develop a fully data-driven retrospective intrascan motion-correction framework for volumetric brain MRI at ultrahigh field (7 Tesla) that includes modeling of pose-dependent changes in polarizing magnetic (B 0 ) fields. Theory and Methods: Tissue susceptibility induces spatially varying B 0 distributions in the head, which change with pose. A physics-inspired B 0 model has been deployed to model the B 0 variations in the head and was validated in vivo. This model is integrated into a forward parallel imaging model for imaging in the presence of motion. Our proposal minimizes the number of added parameters, enabling the developed framework to estimate dynamic B 0 variations from appropriately acquired data without requiring navigators. The effect on data-driven motion correction is validated in simulations and in vivo. Results:The applicability of the physics-inspired B 0 model was confirmed in vivo. Simulations show the need to include the pose-dependent B 0 fields in the reconstruction to improve motion-correction performance and the feasibility of estimating B 0 evolution from the acquired data. The proposed motion and B 0 correction showed improved image quality for strongly corrupted data at 7 Tesla in simulations and in vivo. Conclusion:We have developed a motion-correction framework that accounts for and estimates pose-dependent B 0 fields. The method improves current state-of-the-art data-driven motion-correction techniques when B 0 dependencies cannot be neglected. The use of a compact physics-inspired B 0 model together with leveraging the parallel imaging encoding redundancy and previously proposed optimized sampling patterns enables a purely data-driven approach.
3D FatNavs were used to provide a rapid, robust pre-scan to calibrate motion estimation from pilot-tone. The amount of training data required to make reliable forward predictions was investigated. This method robustly predicts motion within a dataset and can be applied to other datasets with lower accuracy. Improving the accuracy and speed of this method is ongoing work. This independent method of motion estimation shows promise for rapid calibration as part of routine examinations and paves the way to offer motion correction at ultra-high field where motion-correction is particularly relevant.
DISORDER is an established retrospective data driven motion correction approach that uses optimised phase encoding, but otherwise unmodified 3D acquisitions. It is highly effective, but requires multiple lines of k-space to be grouped together for each motion state to be estimated, and this limits temporal resolution. At 7T, head motion can also be detected by “Pilot Tone”, which is an injected RF signal picked up by each coil in the head receiver array, but a calibration step is required. Here we combine DISORDER and Pilot Tone to achieve integrated calibration and show that improved motion correction can result.
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