The electric form factor of the neutron was determined from studies of the reaction ${\mathrm{}}^3\overrightarrow{\mathrm{He}}(\overrightarrow{e},e^{\prime }n)pp$ in quasielastic kinematics in Hall A at Jefferson Lab. Longitudinally polarized electrons were scattered off a polarized target in which the nuclear polarization was oriented perpendicular to the momentum transfer. The scattered electrons were detected in a magnetic spectrometer in coincidence with neutrons that were registered in a large-solid-angle detector. More than doubling the $Q^2$ range over which it is known, we find $G_E^n=0.0236\pm 0.0017(\mathrm{stat})\pm 0.0026(\mathrm{syst})$, $0.0208\pm 0.0024\pm 0.0019$, and $0.0147\pm 0.0020\pm 0.0014$ for $Q^2=1.72$, 2.48, and $3.41{\mathrm{GeV}}^2$, respectively.

Rapid progress in the development of multispectral optoacoustic tomography techniques has enabled unprecedented insights into biological dynamics and molecular processes in vivo and noninvasively at penetration and spatiotemporal scales not covered by modern optical microscopy methods. Ultrasound imaging provides highly complementary information on elastic and functional tissue properties and further aids in enhancing optoacoustic image quality. We devised the first hybrid transmission–reflection optoacoustic ultrasound (TROPUS) small animal imaging platform that combines optoacoustic tomography with both reflection- and transmission-mode ultrasound computed tomography. The system features full-view cross-sectional tomographic imaging geometry for concomitant noninvasive mapping of the absorbed optical energy, acoustic reflectivity, speed of sound, and acoustic attenuation in whole live mice with submillimeter resolution and unrivaled image quality. Graphics-processing unit (GPU)-based algorithms employing spatial compounding and bent-ray-tracing iterative reconstruction were further developed to attain real-time rendering of ultrasound tomography images in the full-ring acquisition geometry. In vivo mouse imaging experiments revealed fine details on the organ parenchyma, vascularization, tissue reflectivity, density, and stiffness. We further used the speed of sound maps retrieved by the transmission ultrasound tomography to improve optoacoustic reconstructions via two-compartment modeling. The newly developed synergistic multimodal combination offers unmatched capabilities for imaging multiple tissue properties and biomarkers with high resolution, penetration, and contrast.

Ultrasound computed tomography (USCT) is a non-invasive imaging technique that provides information about the acoustic properties of soft tissues in the body, such as the speed of sound (SS) and acoustic attenuation (AA). Knowledge of these properties can improve the discrimination between benign and malignant masses, especially in breast cancer studies. Full wave inversion (FWI) methods for image reconstruction in USCT provide the best image quality compared to more approximate methods. Using FWI, the SS is usually recovered in the time domain, and the AA is usually recovered in the frequency domain. Nevertheless, as both properties can be obtained from the same data, it is desirable to have a common framework to reconstruct both distributions. In this work, an algorithm is proposed to reconstruct both the SS and AA distributions using a time domain FWI methodology based on the fractional Laplacian wave equation, an adjoint field formulation, and a gradient-descent method. The optimization code employs a Compute Unified Device Architecture version of the software k-Wave, which provides high computational efficiency. The performance of the method was evaluated using simulated noisy data from numerical breast phantoms. Errors were less than 0.5% in the recovered SS and 10% in the AA.

Attenuation correction in hybrid PET/MR scanners is still a challenging task. This paper describes a methodology for synthesizing a pseudo-CT volume from a single T1 weighted volume, thus allowing us to create correct AC maps. Methods: We propose a fast pseudo-CT generation from a patient-specific MRI T1-weighted image using a group-wise patch-based approach and a MRI-CT atlas dictionary. For every voxel in the input MR image, we compute the similarity of the patch containing that voxel with the patches of all MR images in the database, that lie in a certain anatomical neighborhood. The pseudo-CT is obtained as a local weighted linear combination of the CT values of the corresponding patches. The algorithm was implemented in a Graphical Processing Unit. Results: We evaluated our method both qualitatively and quantitatively for PET/MR correction. The approach performed successfully in all cases considered. We compared the SUVs of the PET image obtained after attenuation correction using the patient specific CT volume, and using the corresponding computed pseudo-CT volume. The voxel by voxel correlation between SUV obtained with both methods was very high (R2=0.9980, p<0.0001), while the Bland-Altman test showed that the average of the differences was very low (0.0006±0.0594). A region of interest analysis was also performed. The correlation between mean SUV value and maximum SUV value of every region was very high (R2=0.9989, p<0.0001 and R2=0.9904, p<0.0001, respectively). Conclusion: Results indicate how our method can accurately approximate the patient-specific CT and may serve as a potential solution for accurate attenuation correction in hybrid PET/MR systems. The quality of the corrected PET using our pseudo-CT is comparable to having acquired a patient-specific CT, thus, improving the results obtained with the UTE-based attenuation correction maps currently used in the mMR scanner. The GPU implementation led to a substantial decrease in computational time making the approach suitable for real applications.