Detection of Metabolites by Proton Ex Vivo NMR, in Vivo MR Spectroscopy Peaks and Tissue Content Analysis: Biochemical-Magnetic Resonance Correlation: Preliminary Results

*Aim*: Metabolite concentrations by in vivo magnetic resonance spectroscopy and ex vivo NMR spectroscopy were compared with excised normal human tissue relaxation times and tissue homogenate contents.

*Hypothesis*: Biochemical analysis combined with NMR and MR spectroscopy defines better tissue analysis.

*Materials and Methods*: Metabolites were measured using peak area, amplitude and molecular weights of metabolites in the reference solutions. In normal brain and heart autopsy, muscle and liver biopsy tissue ex vivo NMR peaks and spin-lattice (T1) and spin-spin (T2) relaxation times, were compared with diseased tissue NMR data in meningioma brain, myocardial infarct heart, duchene-muscular-dystrophy muscle and diffused-liver-injury liver after respective in vivo proton MR spectroscopy was done. NMR data was compared with tissue homogenate contents and serum levels of biochemical parameters.

*Results*: The quantitation of smaller NMR visible metabolites was feasible for both ex vivo NMR and in vivo MR spectroscopy. Ex vivo H-1 NMR and in vivo MRS metabolite characteristic peaks (disease/normal data represented as fold change), T1 and T2, and metabolites in tissue homogenate and serum indicated muscle fibrosis in DMD, cardiac energy depletion in MI heart, neuronal dysfunction in meningioma brain and carbohydrate-lipid metabolic crisis in DLI liver tissues.

*Conclusion*: This preliminary report highlights the biochemical-magnetic resonance correlation as basis of magnetic resonance spectroscopic imaging data interpretation of disease

Lung Imaging and Function Assessment using Non-Contrast-Enhanced Magnetic Resonance Imaging

Measurement of pulmonary ventilation and perfusion has significant clinical value for the diagnosis and monitoring of prevalent lung diseases. To this end, non-contrast-enhanced MRI techniques have emerged as a promising alternative to scintigraphical measurements, computed tomography, and contrast-enhanced MRI. Although these techniques allow the acquisition of both structural and functional information in the same scan session, they are prone to robustness issues related to imaging artifacts and post-processing techniques, limiting their clinical utilization. In this work, new acquisition and post-processing techniques were introduced for improving the robustness of non-contrast-enhanced MRI based functional lung imaging. Furthermore, pulmonary functional maps were acquired in 2-year-old congenital diaphragmatic hernia (CDH) patients to demonstrate the feasibility of non-contrast-enhanced MRI methods for functional lung imaging. In the first study, a multi-acquisition framework was developed to improve robustness against field inhomogeneity artifacts. This method was evaluated at 1.5T and 3T field strengths via acquisitions obtained from healthy volunteers. The results demonstrate that the proposed acquisition framework significantly improved ventilation map homogeneity p<0.05. In the second study, a post-processing method based on dynamic mode decomposition (DMD) was developed to accurately identify dominant spatiotemporal patterns in the acquisitions. This method was demonstrated on digital lung phantoms and in vivo acquisitions. The findings indicate that the proposed method led to a significant reduction in dispersion of estimated ventilation and perfusion map amplitudes across different number of measurements when compared with competing methods p<0.05. In the third study, the free-breathing non-contrast-enhanced dynamic acquisitions were obtained from 2-year-old patients after CDH repair, and then processed using the DMD to obtain pulmonary functional maps. Afterwards, functional differences between ipsilateral and contralateral lungs were assessed and compared with results obtained using contrast-enhanced MRI measurements. The results demonstrate that pulmonary ventilation and perfusion maps can be generated from dynamic acquisitions successfully without the need for ionizing radiation or contrast agents. Furthermore, lung perfusion parameters obtained with DMD MRI correlate very strongly with parameters obtained using dynamic contrast-enhanced MRI. In conclusion, the presented work improves the robustness and accuracy of non-contrast-enhanced functional lung imaging using MRI. Overall, the methods introduced in this work may serve as a valuable tool in the clinical adaptation of non-contrast-enhanced imaging methods and may be used for longitudinal assessments of pulmonary functional changes

Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging

Improved quantification of perfusion in patients with cerebrovascular disease.

In recent years measurements of cerebral perfusion using bolus-tracking MRI have become common clinical practice in the diagnosis and management of patients with stroke and cerebrovascular disease. An active area of research is the development of methods to identify brain tissue that is at risk of irreversible damage, but amenable to salvage using reperfusion treatments, such as thrombolysis. However, the specificity and sensitivity of these methods are limited by the inaccuracies in the perfusion data. Accurate measurements of perfusion are difficult to obtain, especially in patients with cerebrovascular diseases. In particular, if the bolus of MR contrast is delayed and/or dispersed due to cerebral arterial abnormalities, perfusion is likely to be underestimated using the standard analysis techniques. The potential for such underestimation is often overlooked when using the perfusion maps to assess stroke patients. Since thrombolysis can increase the risk of haemorrhage, a misidentification of 'at-risk' tissue has potentially dangerous clinical implications. This thesis presents several methodologies which aim to improve the accuracy and interpretation of the analysed bolus-tracking data. Two novel data analysis techniques are proposed, which enable the identification of brain regions where delay and dispersion of the bolus are likely to bias the perfusion measurements. In this way true hypoperfusion can be distinguished from erroneously low perfusion estimates. The size of the perfusion measurement errors are investigated in vivo, and a parameterised characterisation of the bolus delay and dispersion is obtained. Such information is valuable for the interpretation of in vivo data, and for further investigation into the effects of abnormal vasculature on perfusion estimates. Finally, methodology is presented to minimise the perfusion measurement errors prevalent in patients with cerebrovascular diseases. The in vivo application of this method highlights the dangers of interpreting perfusion values independently of the bolus delay and dispersion

Robust Low-Dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization

Acute brain diseases such as acute strokes and transit ischemic attacks are the leading causes of mortality and morbidity worldwide, responsible for 9% of total death every year. Time is brain is a widely accepted concept in acute cerebrovascular disease treatment. Efficient and accurate computational framework for hemodynamic parameters estimation can save critical time for thrombolytic therapy. Meanwhile the high level of accumulated radiation dosage due to continuous image acquisition in CT perfusion (CTP) raised concerns on patient safety and public health. However, low-radiation leads to increased noise and artifacts which require more sophisticated and time-consuming algorithms for robust estimation. In this paper, we focus on developing a robust and efficient framework to accurately estimate the perfusion parameters at low radiation dosage. Specifically, we present a tensor total-variation (TTV) technique which fuses the spatial correlation of the vascular structure and the temporal continuation of the blood signal flow. An efficient algorithm is proposed to find the solution with fast convergence and reduced computational complexity. Extensive evaluations are carried out in terms of sensitivity to noise levels, estimation accuracy, contrast preservation, and performed on digital perfusion phantom estimation, as well as in vivo clinical subjects. Our framework reduces the necessary radiation dose to only 8% of the original level and outperforms the state-of-art algorithms with peak signal-to-noise ratio improved by 32%. It reduces the oscillation in the residue functions, corrects over-estimation of cerebral blood flow (CBF) and under-estimation of mean transit time (MTT), and maintains the distinction between the deficit and normal regions

Diffusion and perfusion MRI and applications in cerebral ischaemia

Two MRI techniques, namely diffusion and perfusion imaging, are becoming increasingly used for evaluation of the pathophysiology of stroke. This work describes the use of these techniques, together with more conventional MRI modalities (such as T1, and T2 imaging) in the investigation of cerebral ischaemia. The work was performed both in a paediatric population in a whole-body clinical MR system (1.5 T) and in an animal model of focal ischaemia at high magnetic field strength (8.5 T). For the paediatric studies, a single shot echo planar imaging (EPI) sequence was developed to enable the on-line calculation of maps of the trace of the diffusion tensor. In the process of this development, it was necessary to address two different imaging artefacts in these maps: eddy current induced image shifts, and residual Nyquist ghost artefacts. Perfusion imaging was implemented using an EPI sequence to follow the passage through the brain of a bolus of a paramagnetic contrast agent. Computer simulations were performed to evaluate the limitations of this technique in the quantification of cerebral blood flow when delay in the arrival and dispersion of the bolus of contrast agent are not accounted for. These MRI techniques were applied to paediatric patients to identify acute ischaemic events, as well as to differentiate between multiple acute events, or between acute and chronic events. Furthermore, the diffusion and perfusion findings were shown to contribute significantly to the management of patients with high risk of stroke, and in the evaluation of treatment outcome. In the animal experiments, permanent middle cerebral artery occlusion was performed in rats to investigate longitudinally the acute MRI changes (first 4-6 hours) following an ischaemic event. This longitudinal analysis contributed to the understanding of the evolution of the ischaemic lesion. Furthermore, the findings allowed the acute identification of tissue 'at risk' of infarction