Development of a compact NMR system to measure pO2 in a tissue-engineered graft.

Cellular macroencapsulation devices, known as tissue engineered grafts (TEGs), enable the transplantation of allogeneic cells without the need for life-long systemic immunosuppression. Islet containing TEGs offer promise as a potential functional cure for type 1 diabetes. Previous research has indicated sustained functionality of implanted islets at high density in a TEG requires external supplementary oxygen delivery and an effective tool to monitor TEG oxygen levels. A proven oxygen-measurement approach employs a 19F oxygen probe molecule (a perfluorocarbon) implanted alongside therapeutic cells to enable oxygen- and temperature- dependent NMR relaxometry. Although the approach has proved effective, the clinical translation of 19F oxygen relaxometry for TEG monitoring will be limited by the current inaccessibility and high cost of MRI. Here, we report the development of an affordable, compact, and tabletop 19F NMR relaxometry system for monitoring TEG oxygenation. The system uses a 0.5 T Halbach magnet with a bore diameter (19 cm) capable of accommodating the human arm, a potential site of future TEG implantation. 19F NMR relaxometry was performed while controlling the temperature and oxygenation levels of a TEG using a custom-built perfusion setup. Despite the magnet's nonuniform field, a pulse sequence of broadband adiabatic full-passage pulses enabled accurate 19F longitudinal relaxation rate (R1) measurements in times as short as ∼2 min (R1 vs oxygen partial pressure and temperature (R2 > 0.98)). The estimated sensitivity of R1 to oxygen changes at 0.5 T was 1.62-fold larger than the sensitivity previously reported for 16.4 T. We conclude that TEG oxygenation monitoring with a compact, tabletop 19F NMR relaxometry system appears feasible.

Correcting image distortions from a nonlinear B 1 + $$ {\boldsymbol{B}}_{\mathbf{1}}

PURPOSE: To correct image distortions that result from nonlinear spatial variation in the transmit RF field amplitude ( B 1 + $$ {B}_1^{+} $$ ) when performing spatial encoding with the method called frequency-modulated Rabi encoded echoes (FREE). THEORY AND METHODS: An algorithm developed to correct image distortion resulting from the use of nonlinear static field (B0 ) gradients in standard MRI is adapted herein to correct image distortion arising from a nonlinear B 1 + $$ {B}_1^{+} $$ -gradient field in FREE. From a B 1 + $$ {B}_1^{+} $$ -map, the algorithm performs linear interpolation and intensity scaling to correct the image. The quality of the distortion correction is evaluated in 1.5T images of a grid phantom and human occipital lobe. RESULTS: An expanded theoretical description of FREE revealed the symmetry between this B 1 + $$ {B}_1^{+} $$ -gradient field spatial-encoding and standard B0 -gradient field spatial-encoding. The adapted distortion-correction algorithm substantially reduced image distortions arising in the spatial dimension that was encoded by the nonlinear B 1 + $$ {B}_1^{+} $$ gradient of a circular surface coil. CONCLUSION: Image processing based on straightforward linear interpolation and intensity scaling, as previously applied in conventional MRI, can effectively reduce distortions in FREE images acquired with nonlinear B 1 + $$ {B}_1^{+} $$ -gradient fields.

Experimental study of photon-counting CT neural network material decomposition under conditions of pulse pileup.

Purpose: We investigated the performance of a neural network (NN) material decomposition method under varying pileup conditions. Approach: Experiments were performed at tube current settings that provided count rates incident on the detector through air equal to 9%, 14%, 27%, 40%, and 54% of the maximum detector count rate. An NN was trained for each count-rate level using transmission measurements through known thicknesses of basis materials (PMMA and aluminum). The NN trained for each count-rate level was applied to x-ray transmission measurements through test materials and to CT data of a rod phantom. Material decomposition error was evaluated as the distance in basis material space between the estimated thicknesses and ground truth. Results: There was no clear trend between count-rate level and material decomposition error for all test materials except neoprene. As an example result, Teflon error was 0.33 cm at the 9% count-rate level and 0.12 cm at the 54% count-rate level for the x-ray transmission experiments. Decomposition error increased with count-rate level for the neoprene test case, with 0.65-cm error at 9% count-rate level and 1.14-cm error at the 54% count-rate level. In the CT study, material decomposition error decreased with increasing incident count rate. For example, the material decomposition error for Teflon was 0.089, 0.066, 0.054 at count-rate levels of 14%, 27%, and 40%, respectively. Conclusions: Results demonstrate over a range of incident count-rate levels that an NN trained at a specific count-rate level can learn the relationship between photon-counting spectral measurements and basis material thicknesses.