Coherent systems for indoor optical wireless communications

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Phosphorus MRS of healthy human spleen.

Phosphorus (31 P-) MRS in vivo enables detection and quantification of important phosphorus-containing metabolites in biological tissues. 31 P-MRS of the normal spleen is challenging due to the relatively small volume and the larger distance between the spleen and surface coil. However, reference spectra of the healthy spleen are invaluable in studies of splenic malignancies and benign causes of splenomegaly, as well as in the study of its physiology. The purpose of this work was to investigate the feasibility of localized 31 P-MRS of healthy spleen in situ in a clinically acceptable measurement time using a clinical 3 T MR scanner. In this work, 31 P spectra of five healthy volunteers were measured using single-voxel image-selected in vivo spectroscopy (ISIS). The measurement sequence was augmented by broadband proton decoupling and nuclear Overhauser effect enhancement. It is demonstrated that localized 31 P-MRS of the spleen in situ using single-voxel ISIS is feasible on a clinical 3 T scanner in a clinically acceptable acquisition time. However, results have to be corrected for the transmitter excitation profile, and chemical shift displacement errors need to be taken into consideration during placement of the volume of interest. Results presented here could be used as a reference in future studies of splenomegaly caused by haematological malignancies

Assessment of Geometric Distortion in Six Clinical Scanners Using a 3D-Printed Grid Phantom

A cost-effective regularly structured three-dimensional (3D) printed grid phantom was developed to enable the quantification of machine-related magnetic resonance (MR) distortion. This phantom contains reference features, “point-like” objects, or vertices, which resulted from the intersection of mesh edges in 3D space. 3D distortions maps were computed by comparing the locations of corresponding features in both MR and computer tomography (CT) data sets using normalized cross correlation. Results are reported for six MRI scanners at both 1.5 T and 3.0 T field strengths within our institution. Mean Euclidean distance error for all MR volumes in this study, was less than 2 mm. The maximum detected error for the six scanners ranged from 2.4 mm to 6.9 mm. The conclusions in this study agree well with previous studies that indicated that MRI is quite accurate near the centre of the field but is more spatially inaccurate toward the edges of the magnetic field

Clinical Instability of the Knee and Functional Differences Following Tibial Plateau Fractures Versus Distal Femoral Fractures

Background: Fractures of the knee account for about 6% of all trauma admissions. While its management is mostly focused on fracture treatment, it is not the only factor that defines the final outcome. Objectives: This study aimed to study objective and subjective outcomes after proximal tibial versus distal femoral fractures in terms of knee instability and health-related quality of life. Patients and Methods: This retrospective, cross-sectional, cohort study was carried out on 80 patients with either isolated proximal tibial (n = 42) or distal femoral (n = 38) fractures, who underwent open reduction and internal fixation. All the fractures were classified based on the Schatzker and AO classification for tibial plateau and distal femoral fractures, respectively. The patients were followed and examined by an orthopedic knee surgeon for clinical assessment of knee instability. In their last follow-up visit, these patients completed a Lysholm knee score and the short-form (SF) 36 health survey. Results: Among the 42 tibial plateau fractures, 25% were classified as Schatzker type 2. Of the 38 distal femoral fractures, we did not find any type B1 or B3 fractures. The overall prevalence of anterior and posterior instability was 42% and 20%, respectively. Medial Collateral Ligament (MCL) and Lateral Collateral Ligament (LCL) injuries were detected clinically in 50% and 28%, respectively. The incidence rates of ligament injuries in tibial plateau fractures were as follows: Anterior Collateral Ligament (ACL) 26%, Posterior Collateral Ligament (PCL) 7%, MCL 24%, and LCL 14%. Medial collateral ligament injury was the most common in the Schatzker type 2 (50% of the injuries). Distal femoral fractures were associated with ACL injury in 16%, PCL in 13%, MCL in 26% and LCL in 14%. However, final knee range of motion (ROM) and function (Lysholm score) were not associated with fracture location. No statistically significant difference was observed between the two groups, except for the valgus stress test at 30°knee flexion, which was more positive in tibial fractures. All eight domains of SF-36 score in the distal femoral and proximal tibial fractures were significantly different from the normal values; however, there were no statistically significant differences between femoral and tibial fracture scores. Conclusions: Although ROM is acceptable in knee joint fractures, instability is common. However, it seems that knee function and quality of life are not associated with the location of the fracture

Model free approach to kinetic analysis of real-time hyperpolarized (13)c magnetic resonance spectroscopy data

Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13)C metabolic imaging in humans, where measurement of the input function can be problematic

Representative dynamic ¹³C time-courses from an <i>in vivo</i> HT29 colon carcinoma xenograft at 7 T.

<p>The model fits to pyruvate, lactate and alanine are shown with a solid line and residuals between the data and the plots are displayed.</p

A representation of the fate of hyperpolarized [1-¹³C]pyruvate (P) that is injected into a system with input function <i>P_in</i>(<i>t</i>).

<p>Observable ¹³C signals originating from [1-¹³C]pyruvate are indicated in red. The schematic shows the transport of pyruvate into a cell, facilitated by MCT1 transporters, and its conversion to other metabolites. Solid lines correspond to the cell membrane and dashed lines to the mitochondrial membrane. is the effective relaxation rate of the hyperpolarized signal for metabolite <i>i</i>. Conversion to metabolites [1-¹³C]lactate (L), [1-¹³C]alanine (A), and [1-¹³C]bicarbonate (B) occur with reaction rates (<i>k</i>), and enzymes that catalyze reactions are shown. <i>k_EL</i> and <i>k_LE</i> are the rates of lactate transport into and out of the cell, governed by the MCT4 transporters. Entry of pyruvate into the TCA cycle results in conversion of the 1-¹³C label to CO₂ and then to bicarbonate. Acetyl-CoA is not seen owing to the [1-¹³C] label of pyruvate being utilized in the formation of CO₂. The grey box indicates the terms that need to be considered for the AUC ratio analysis method when the reaction of interest is pyruvate-lactate conversion, whereas kinetic modeling requires fitting of all terms depicted here, except for acetyl-CoA.</p

Representative dynamic spectra from a WM266.4 melanoma cell suspension.

<p>Kinetic modeling was performed using a 2-site (left) and 3-site (right) model. Total (T), intracellular (I) and extracellular (E) [1-¹³C]lactate fits, derived from the 3-site kinetic model are shown. Residuals between the data and the model are shown (central row). The concentration curves (bottom) were generated by correcting data for hyperpolarized relaxation.</p

<i>In vitro</i> AUC ratios plotted against forward rate constant (<i>k_PL</i>), derived from the 2-site model.

<p>Data is normalized to initial pyruvate concentration and cell number. An excellent correlation is observed between AUC ratio and <i>k_PL</i> across a range of cell lines. Clustering between cell types can also be seen, and spread between data points of the same cell type tends to be in the direction of the best-fit line.</p