Contrast-enhanced proton radiographic sensitivity limits for tumor detection.

Purpose: Proton radiography may guide proton therapy cancer treatments with beam's-eye-view anatomical images and a proton-based estimation of proton stopping power. However, without contrast enhancement, proton radiography will not be able to distinguish tumor from tissue. To provide this contrast, functionalized, high- Z nanoparticles that specifically target a tumor could be injected into a patient before imaging. We conducted this study to understand the ability of gold, as a high- Z , biologically compatible tracer, to differentiate tumors from surrounding tissue. Approach: Acrylic and gold phantoms simulate a tumor tagged with gold nanoparticles (AuNPs). Calculations correlate a given thickness of gold to levels of tumor AuNP uptake reported in the literature. An identity, × 3 , and × 7 proton magnifying lens acquired lens-refocused proton radiographs at the 800-MeV LANSCE proton beam. The effects of gold in the phantoms, in terms of percent density change, were observed as changes in measured transmission. Variable areal densities of acrylic modeled the thickness of the human body. Results: A 1 - µ m -thick gold strip was discernible within 1 cm of acrylic, an areal density change of 0.2%. Behind 20 cm of acrylic, a 40 - µ m gold strip was visible. A 1-cm-diameter tumor tagged with 1 × 10 5 50-nm AuNPs per cell has an amount of contrast agent embedded within it that is equivalent to a 65 - µ m thickness of gold, an areal density change of 0.63% in a tissue thickness of 20 cm, which is expected to be visible in a typical proton radiograph. Conclusions: We indicate that AuNP-enhanced proton radiography might be a feasible technology to provide image-guidance to proton therapy, potentially reducing off-target effects and sparing nearby tissue. These data can be used to develop treatment plans and clinical applications can be derived from the simulations.

Design and implementation of a J-coupled spectrometer for multidimensional structure and relaxation detection at low magnetic fields.

In recent years, it has been realized that low and ultra-low field (mT-nT magnetic field range) nuclear magnetic resonance spectroscopy can be used for molecular structural analysis. However, spectra are often hindered by lengthy acquisition times or require large sample volumes and high concentrations. Here, we report a low field (50 µT) instrument that employs a linear actuator to shuttle samples between a 1 T prepolarization field and a solenoid detector in a laboratory setting. The current experimental setup is benchmarked using water and 13C-methanol with a single scan detection limit of 2 × 1020 spins (3 µl, 55M H2O) and detection limit of 2.9 × 1019 (200 µl, 617 mM 13C-methanol) spins with signal averaging. The system has a dynamic range of >3 orders of magnitude. Investigations of room-temperature relaxation dynamics of 13C-methanol show that sample dilution can be used in lieu of sample heating to acquire spectra with linewidths comparable to high-temperature spectra. These results indicate that the T1 and T2 mechanisms are governed by both the proton exchange rate and the dissolved oxygen in the sample. Finally, a 2D correlation spectroscopy experiment is reported, performed in the strong coupling regime that resolves the multiple resonances associated with the heteronuclear J-coupling. The spectrum was collected using 10 times less sample and in less than half the time from previous reports in the strong coupling limit.

Optimized 3D co-registration of ultra-low-field and high-field magnetic resonance images.

The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization. Thus, for practical usage, a high-field (HF) MRI image is also acquired, and the HF-MRI images are co-registered to the ULF-MRI ones. We address here this issue through an optimized pipeline (SWIM-Sliding WIndow grouping supporting Mutual information). The co-registration is performed by an affine transformation, the parameters of which are estimated using Normalized Mutual Information as the cost function, and Adaptive Simulated Annealing as the minimization algorithm. The sub-voxel resolution of the ULF images is handled by a sliding-window approach applying multiple grouping strategies to down-sample HF MRI to the ULF-MRI resolution. The pipeline has been tested on phantom and real data from different ULF-MRI devices, and comparison with well-known toolboxes for fMRI analysis has been performed. Our pipeline always outperformed the fMRI toolboxes (FSL and SPM). The HF-ULF MRI co-registration obtained by means of our pipeline could lead to an effective integration of ULF MRI with MEG, with the aim of improving localization accuracy, but also to help exploit ULF MRI in tumor imaging.