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Cerebral small vessel disease (SVD) is a common cause of strokes and dementia. The pathogenesis of SVD is poorly understood, but imaging and biochemical investigations suggest that subtle blood-brain barrier (BBB) leakage may contribute to tissue damage. The most widely-used imaging method for assessing BBB integrity and other microvascular properties is dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). DCE-MRI has primarily been applied in situations where contrast uptake in tissue is typically large and rapid (e.g. neuro-oncology); the optimal approach for quantifying BBB integrity in diseases where the BBB remains largely intact and the reliability of resulting measurements is unclear. The main purpose of this thesis was to assess and improve the reliability of quantitative assessment of subtle BBB disruption, in order to illuminate its potential role in cerebral SVD. Firstly, a systematic literature review was performed in order to provide an overview of DCE-MRI methods in the brain. This review found large variations in MRI procedures and data analysis methods, resulting in widely varying estimates of tracer kinetic parameters. Secondly, this thesis focused on the analysis of DCE-MRI data acquired in an on-site clinical study of mild stroke patients. After performing basic DCE-MRI processing (e.g. selection of a vascular input function), this work aimed to determine the tracer kinetic modelling approach most suitable for assessing subtle BBB disruption in this cohort. Using data-driven model selection and computer simulations, the Patlak model was found to provide accurate estimates of blood plasma volume and low-level BBB leakage. Thirdly, this thesis aimed to investigate two potential pitfalls in the quantification of subtle BBB disruption. Contrast-free measurements in healthy volunteers revealed that a signal drift of approximately 0.1 %/min occurs during the DCE-MRI acquisition; computer simulations showed that this drift introduces significant systematic errors when estimating low-level tracer kinetic parameters. Furthermore, tracer kinetic analysis was performed in an external patient cohort in order to investigate the inter-study comparability of DCE-MRI measurements. Due to the nature of the acquisition protocol it proved difficult to obtain reliable estimates of BBB leakage, highlighting the importance of study design. Lastly, this thesis examined the relationship between quantitative MRI parameters and clinical measurements in cerebral SVD, with a focus on the estimates of blood volume and BBB leakage obtained in the internal SVD patient cohort. This work did not provide evidence that BBB leakage in normal-appearing tissue increases with SVD burden or predicts disease progression; however, increased BBB leakage was found in white matter hyperintensities. Furthermore, this work raises the possibility of a role for blood plasma volume and dietary salt intake in cerebral SVD. The work described in this thesis has demonstrated that it is possible to estimate subtle BBB disruption using DCE-MRI, provided that the measurement and data analysis strategies are carefully optimised. However, absolute values of tracer kinetic parameters should be interpreted with caution, particularly when making comparisons between studies, and sources of error and their influence should be estimated where possible. The exact roles of BBB breakdown and other microvascular changes in SVD pathology remain to be defined; however, the work presented in this thesis contributes further insights and, together with technical advances, will facilitate improved study design in the future.

This thesis deals with processing of data obtained by DCE-MRI, which uses magnetic resonance to track the propagation of contrast agents in the blo- odstream. Patient is given a contrast agent and then a series of images of the target area is taken. The output is a set of image data and perfusion maps. Work employs segmentation method which uses graph cuts to interactively look for the tumor, and evaluates it according to its shape properties. Study of whole data sets is simplified by image fusion methods.

Simultaneous optical imaging and MRI of a dorsal skin-fold window chamber mouse model is investigated as a novel methodology to study the tumor microenvironment. Simultaneous imaging with two modalities allows for cross-validation of results, integration of the capabilities of the two modalities in one study and mitigation of invasive factors, such as surgery and anesthesia, in an in-vivo experiment. To make this investigation possible, three optical imaging systems were developed that operated inside the MRI scanner. One of the developed systems was applied to estimate vascular kinetic parameters of tumors in a dorsal skin-fold window chamber mouse model with simultaneous optical and MRI imaging. The target of imaging was a molecular agent that was dual labeled with both optical and MRI contrast agents. The labeling of the molecular agent, characteristics of the developed optical systems, the methodologies of measuring vascular kinetic parameters using optical imaging and MRI data, and the obtained results are described and illustrated.

Background: Angiogenesis is the process by which new blood vessels develop from existing vasculature and is a critical step in all tumours to facilitate growth beyond a few millimetres. As this process is largely inactive in physiological circumstances in adults, it represents an attractive therapeutic target in oncology. Drugs that target the angiogenic process are classified as anti-angiogenic agents. The first anti-angiogenic drug to be approved by the FDA was bevacizumab; a recombinant humanized monoclonal antibody against VEGF. Randomised studies in colorectal cancer (and other solid malignancies) have reported prolonged progression free survival and overall survival for bevacizumab. However, standard radiological criteria, Response Evaluation Criteria In Solid Tumours (RECIST), although widely employed to assess response to therapy in clinical trials, are generally insensitive to the predominantly cytostatic effects of anti-angiogenic and other targeted therapies. Alternative methods of predicting or assessing early response to such agents are needed, particularly given the cost and toxicity implications of such treatments. However, biomarkers to aid selection of patients for anti-angiogenic therapies, including bevacizumab, remain elusive. Purpose: To investigate Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI), Diffusion Weighted Imaging (DWI) and circulating angiocytokines, measured using an ELISA multiplex, as prognostic markers in patients with metastatic colorectal cancer treated with bevacizumab and chemotherapy. Results: Seventy patients were treated. DCE-MRI and DWI parameters showed good reproducibility with coefficient of variation between 3.7 to 23% for parameters. The median progression free survival, the primary end point of the trial, was 9.3 months. The overall response rate was 44%. The clinical variables which were significant for progression free survival on univariate analysis were: performance status (p=0.005), CEA (p=0.04) and serum LDH (p=0.005). Biomarkers which were significant for progression free survival on univariate analysis were serum VEGF-A (p=0.02), serum HGF (p=0.005), sVEGFR-2 (p=0.02). In each case, low values of the biomarker were associated with improved outcome. Multivariate analysis identified Ktrans (p=0.015), performance status (p=0.008) and serum HGF (p=0.003) as the most significant predictors of progression free survival. A prolonged progression free survival was associated with a good ECOG performance status, high Ktrans and low serum HGF.Conclusions: Whilst these results are encouraging, future work is required to establish whether HGF and Ktrans are prognostic markers for metastatic colorectal cancer and their precise role in the prediction of patients likely to benefit from treatment with bevacizumab.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第22741号 / 医博第4659号 / 新制||医||1046(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 辻川 明孝, 教授 伊達 洋至, 教授 羽賀 博典 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

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No description available.

This dissertation deals with quantitative perfusion analysis of MRI contrast-enhanced image time sequences. It focuses on two so far separately used methods -- Dynamic contrast-enhanced MRI (DCE-MRI) and Dynamic susceptibility contrast MRI (DSC-MRI). The common problem of such perfusion analyses is the unreliability of perfusion parameters estimation. This penalizes usage of these unique techniques on a regular basis. The presented methods are intended to improve these drawbacks, especially the problems with quantification in DSC in case of contrast agent extravasation and instability of the deconvolution process in DCE using advanced pharmacokinetic models. There are a few approaches in literature combining DCE and DSC to estimate new parameters of the examined tissue, namely the relaxivity of the vascular and of the interstitial space. Originally, in this scheme, the 2CXM DCE model was used. Here various models for DCE analysis are tested keeping in mind the DCE-DSC combination. The ATH model was found to perform better in this setting compared to 2CXM. Finally, the ATH model was used in alternating DCE-DSC optimization algorithm and then in a truly fully simultaneous DCE-DSC. The processing was tested using simulated and in-vivo data. According to the results, the proposed simultaneous algorithm performs better in comparison with sequential DCE-DSC, unleashing full potential of perfusion analysis using MRI.