Accelerated imaging of metallic implants using model-based nonlinear reconstruction

Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand-maximize-compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

Reducing the Complexity of Model-Based MRI Reconstructions via Sparsification

Model-based reconstruction methods have emerged as a powerful alternative to classical Fourier-based MRI techniques, largely because of their ability to explicitly model (and therefore, potentially overcome) moderate field inhomogeneities, streamline reconstruction from non-Cartesian sampling, and even allow for the use of custom designed non-Fourier encoding methods. Their application in such scenarios, however, often comes with a substantial increase in computational cost, owing to the fact that the corresponding forward model in such settings no longer possesses a direct Fourier Transform based implementation. This paper introduces an algorithmic framework designed to reduce the computational burden associated with model-based MRI reconstruction tasks. The key innovation is the strategic sparsification of the corresponding forward operators for these models, giving rise to approximations of the forward models (and their adjoints) that admit low computational complexity application. This enables overall a reduced computational complexity application of popular iterative first-order reconstruction methods for these reconstruction tasks. Computational results obtained on both synthetic and experimental data illustrate the viability and efficiency of the approach.

Dual polarity encoded MRI using high bandwidth radiofrequency pulses for robust imaging with large field inhomogeneity

PURPOSE

The ability to use dual polarity encoded MRI with the missing pulse steady-state free precession (MP-SSFP) sequence is demonstrated to perform robust MRI with low radiofrequency (RF) amplitude, where the field is distorted by embedding metallic screws in an agar phantom. Image-based estimation of the 3D ΔB₀ map and image distortion correction is shown to require ~1 minute to perform.

THEORY AND METHODS

Dual polarity encoded MP-SSFP was implemented at 1.5T and used to image agar phantoms with one stainless steel and one titanium screw embedded inside. A multispectral fast spin-echo acquisition was performed for comparison. Self-consistent ΔB₀ estimation is performed iteratively using a 3D B-spline basis, which is compared to the ΔB₀ estimate generated by the multispectral sequence.

RESULTS

Dual polarity encoded MP-SSFP yields image quality similar to the multispectral sequence used with substantially less imaging time, provided the MP-SSFP experimental parameters are chosen well. The multispectral sequence appears to visualize modestly closer in proximity to the metallic screws used, despite the spectral bins covering the same bandwidth as the pulses used in MP-SSFP. However, MP-SSFP avoids ripple artifacts characteristic of the multispectral sequence. The ΔB₀ estimate generated by MP-SSFP is qualitatively similar to that generated by the multispectral sequence but larger in magnitude.

CONCLUSION

Despite longer processing time compared to multispectral imaging, MP-SSFP yields similar image quality with significantly lower acquisition times in the absence of parallel imaging. The work herein demonstrates the ability to perform 3D ΔB₀ estimation and image correction within a reasonable amount of time, ~1 minute.

Radio-Frequency Vector Magnetic Field Mapping in Magnetic Resonance Imaging

A method is presented to measure the radio-frequency (RF) vector magnetic field inside an object using magnetic resonance imaging (MRI). Conventional " [Formula: see text] mapping" in MRI can measure the proton co-rotating component ( [Formula: see text] of the RF field produced by a transmit coil. Here we show that by repeating [Formula: see text] mapping on the same object and coil at multiple (8) specific orientations with respect to the main magnet, the magnitudes and relative phases of all (x, y, z) Cartesian components of the RF field can be determined unambiguously. We demonstrate the method on a circularly polarized volume coil and a loop coil tuned at 123.25 MHz in a 3 Tesla MRI scanner, with liquid phantoms. The volume coil measurement showed the axial component of the RF field, which is normally unmeasurable in MRI, away from the center of the coil. The measured RF vector field maps of both coils compared favorably with numerical simulation, with volumetric normalized root-mean-square difference in the range of 7~20%. While the proposed method cannot be applied to human imaging at present, applications to phantoms and small animals could provide a useful experimental tool to validate RF simulation and verify certain assumptions in [Formula: see text] map-based electrical properties tomography (EPT).

Spinal Cord Imaging Markers and Recovery of Volitional Leg Movement With Spinal Cord Epidural Stimulation in Individuals With Clinically Motor Complete Spinal Cord Injury

Previous studies have shown that epidural stimulation of the lumbosacral spinal cord (scES) can re-enable lower limb volitional motor control in individuals with chronic, clinically motor complete spinal cord injury (SCI). This observation entails that residual supraspinal connectivity to the lumbosacral spinal circuitry still persisted after SCI, although it was non-detectable when scES was not provided. In the present study, we aimed at exploring further the mechanisms underlying scES-promoted recovery of volitional lower limb motor control by investigating neuroimaging markers at the spinal cord lesion site via magnetic resonance imaging (MRI). Spinal cord MRI was collected prior to epidural stimulator implantation in 13 individuals with chronic, clinically motor complete SCI, and the spared tissue of specific regions of the spinal cord (anterior, posterior, right, left, and total cord) was assessed. After epidural stimulator implantation, and prior to any training, volitional motor control was evaluated during left and right lower limb flexion and ankle dorsiflexion attempts. The ability to generate force exertion and movement was not correlated to any neuroimaging marker. On the other hand, spared tissue of specific cord regions significantly and importantly correlated with some aspects of motor control that include activation amplitude of antagonist (negative correlation) muscles during left ankle dorsiflexion, and electromyographic coordination patterns during right lower limb flexion. The fact that amount and location of spared spinal cord tissue at the lesion site were not related to the ability to generate volitional lower limb movements may suggest that supraspinal inputs through spared spinal cord regions that differ across individuals can result in the generation of lower limb volitional motor output prior to any training when epidural stimulation is provided.