京都大学 / 新制・課程博士 / 博士(医科学) / 甲第23117号 / 医科博第128号 / 新制||医科||8(附属図書館) / 京都大学大学院医学研究科医科学専攻 / (主査)教授 花川 隆, 教授 中本 裕士, 教授 溝脇 尚志 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

The subject of my thesis is a design of the methods optimizing, the acquisition of MR signals when small objects measure. The thesis is divided into several parts in order to give a deeper knowledge of the problem. The first part focuses on the theory associated with NMR (Nuclear Magnetic Resonance) and SNR (signal-to-noise ratio). The practical verification of the theory follows. The conclusion of this work is focused on MR images filtering by use of wavelet transform to suppress a noise in the image. The method optimization of MR acquisition parameters for the measurement of small objects is then distributed to the entire work.

This diploma thesis was focused on the preparation of magnetic and fluorescently labelled spinel type nanoparticles, specifically nanoparticles of zinc-doped cobalt ferrite intended for application in magnetic resonance imaging and fluorescence microscopy in experimental practice. In previous studies, various ferrite nanoparticles exhibited relatively high transverse relaxation times and strong negative T2 contrast. These properties were also supposed for the zinc-doped cobalt ferrite nanoparticles. This assumption was confirmed by studying their magnetic and contrasting properties. Fluorescence properties of the prepared nanoparticles were also successfully studied. With respect to the intended applications of these particles, the issue of suitable surface modification of magnetic cores, their colloidal stabilization in an aqueous suspension and toxicity in biological systems were studied. Key words: nanoparticles, ferrites, MRI, relaxation

Non-invasive measurement of pH provides multiple potential benefits in oncology such as better identifying the type of drug that can be more effective in chemotherapy, potentially identifying tumors that are more likely to metastasize and also better assessing the treatment effects. Chemical Exchange Saturation Transfer (CEST) Magnetic Resonance Imaging (MRI) is a versatile non-invasive technique for molecular imaging. AcidoCEST MRI techniques have been developed over the recent years to perform tumor pH measurements by utilizing a contrast agent for which chemical exchange saturation transfer effects depend on the pH of the microenvironment. Quantitative description of CEST MRI signals are generally done via modeling Bloch-McConnell equations by incorporating pH as a parameter or by fitting Lorentzian line shapes to observed z-spectra and then computing a log ratio of the CEST effects from multiple labile protons of the same molecule (ratiometric method). Modeling using Bloch-McConnell equations is complicated and requires careful inclusion of many scan parameters to infer pH. The ratiometric method requires contrast agents that have multiple labile protons, thus making it unsuitable to use for molecules with a single labile proton. Furthermore, depending on the pH, sometimes it might not be possible to numerically compute the ratio due to the inability of detecting signal peaks for certain labile protons. Our aim here is to develop a machine learning based method that learns the CEST signal patterns from observed z-spectra on temperature and concentration-controlled contrast agent phantoms independent of the type of the contrast agent. Our results indicate that the machine learning method provides more general and accurate prediction of pH in comparison to the ratiometric method based on the phantom CEST dataset. Our method is more general in the sense that it does not require explicit modeling of signal peaks that are dependent on the type of contrast agent. We also describe a state of the art variational autoencoder based algorithm extending our machine learning method to measure tumor pH in vivo using AcidoCEST MRI on mouse tumor models.

Every year more than fourteen-thousand adults in the United States are diagnosed with glioma, the most common malignant tumor of the central nervous system. Gliomas arise from glue like glial cells and present with a range of grade and prognosis. Glioblastoma multiforme (GBM), a grade IV glioma, is the most common glioma subtype and carries dismal prognosis with fewer than one half of patients surviving one year after diagnosis. The standard treatment for GBM is resection followed by a cocktail of chemo and radiation therapy. Unfortunately, complete surgical resection is impossible for GBM, and intra-tumor heterogeneity, a GBM hallmark, negatively impacts chemo and radiation therapy efficacy. This thesis contains six chapters that evaluate advanced imaging and statistical methods that may be used to improve glioma management. Chapter one presents background information to establish the relationship of four subsequent studies with ranging topics on advanced imaging techniques, biopsy sampling, and radiomic analysis. In chapter two, a case report is presented that demonstrates the importance of advanced magnetic resonance imaging (MRI) such as arterial spin labeled (ASL) perfusion sequences. In this case, a patient with a benign cerebral lesion presents with receptive aphasia and of the imaging data acquired, only ASL showed decrease cerebral aphasia. Chapter three describes the impact biopsy selection has on correlation between prognostic and histologic features in 35 patients with GBM. Multiple biopsy selection methods were compared, resulting in a wide range in correlation significance. Chapter four presents different voxel-wise radiomic models in adult glioma patients. From one voxel-wise radiomic model, predicted disease compositions (PDC) were computed in 17 glioma patients and were able to significantly (α = 0.05) predict overall survival, tumor grade, and endothelial proliferation. Chapter five describes the feasibility and hardware constraints of simultaneous PET/MR imaging protocols. A dynamic infusion of fluorodeoxyglucose (FDG) was administered with simultaneous MR imaging including echo planar imaging (EPI) based sequences used for functional MRI (fMRI). Heat from the EPI sequences deposited in the PET detector hardware and resulted in significant hardware failure. Finally, chapter six provides outlook and application to glioma clinical management considering the methods and findings presented in each study.<br>

Trait mindfulness refers to the tendency of being mindful in everyday life. Individuals characterized with high trait mindfulness have reported high subjective wellbeing and are less prone to depression and stress. The aim with this systematic review was to investigate the neural correlates of trait mindfulness. Also, to compare the neural correlates underlying trait mindfulness with those related to mindfulness practices. A systematic search, screening and selection was conducted, resulting in twelve articles included for data extraction and discussion. All studies investigated resting state brain activity or brain structure, measured by fMRI or MRI, in relation to individual scores in trait mindfulness measures. Trait mindfulness was characterized by reduced connectivity within the DMN (between the PCC, the medial PFC, the STG and the thalamus e.g.) and increased functional connectivity between the insula and the ACC within the SN. Further, decreased functional connectivity between the DMN and the SN was observed. No consistent structural correlates characterizing trait mindfulness were reported. Reduced connectivity within the DMN is thought to associate with reduced vulnerability to rumination and depression. Increased connectivity within the SN has been linked to enhanced body awareness and interoception. Decreased functional connectivity between the DMN and the SN has been suggested to facilitate enhanced attention. Trait mindfulness appears to share some neural characteristics with those linked to mindfulness practices: weaker functional connectivity within the DMN, increased involvement of the insula and the ACC within the SN, and weaker connectivity between the DMN and the SN.

Spinal cord injury (SCI) leads to axonal damage and limits the ability of the brain to communicate with the rest of the body. Several bioengineered approaches have been developed for the recovery of SCI. Among these techniques, degradable guidance tubes have shown promising results. However, design of nerve guide tubes requires several design considerations and has been a significant challenge. To assess the efficacy of a prototypical implanted nerve guide tubes, it is essential to perform continuous monitoring. In this respect, magnetic resonance imaging (MRI) is one of the most reliable imaging techniques as it offers the ability to achieve extraordinary high temporal and spatial resolution in addition to its non-invasive features. In spite of the excellent image quality of non-enhanced MRI various types of contrast agents have been developed to further enhance the contrast and allow improved visualization. The MRI contrast agents principally work by shortening the T1 or T2 relaxation times of protons located nearby. The presented study was intended to evaluate the in vitro degradation of the nerve guide tubes made of poly (lactic-co-glycolic acid) (PLGA). PLGA tubes incorporated with different concentrations of superparamagnetic iron oxide (SPIO) were scanned by MRI 3T on weekly basis during the degradation period. Spin-echo (SE) sequence with various echo times (TEs) ranged from 13.3 to 314.4 msec was applied. T2 mapping was computed using in-house algorithm developed in Matlab. Least square fit was used to find the slope of the decay curve by plotting log intensity on the y-axis and echo time on the x-axis. The average T2 values were calculated. Mass loss and water uptake of the degrading tubes were also measured weekly. Moreover, the micro-structural changes of the tubes were investigated using the scanning electron microscope (SEM). The MRI results showed that the concentration of SPIO affects the signal intensity of the T2 weighted images reducing the T2 relaxation time value. Accordingly, a linear correlation between SPIO concentration and T2 relaxation time was found. At the beginning of degradation, the SPIO nanoparticles were trapped within the polymeric network. Therefore, water penetration was the predominant factor affecting the T2 relaxation times. At week 5, a significant mass loss was observed. From this stage onwards, the trapped SPIO were released from the polymeric network increasing T2 relaxation time dramatically. According to SEM images, the size of the pores in PLGA guide tubes was increased with the degradation. Approaching the end of degradation, shrinkage of the tubes was observed and the degraded nerve guide tubes were shown to be collapsed. Similar shape variation was observed in T2 weighted MR images. In summary, this study provided an approach to non-invasive monitoring of degradation behavior of nerve guide tubes using contrast enhancement. The developed technique is of great importance since it opened an insight to non-invasive monitoring of tissue engineered scaffolds for in vivo studies.

The purpose of this experiment is to study as a model the gelation phase transition of agarose solutions with transverse relaxation (T2) quantitative magnetic resonance imaging (qMRI). The focus is on the reduction of T2 of agarose solution upon gelation. The sol-to-gel phase transition of agarose may provide a useful and controllable experimental model of tissue formation. Furthermore, it may provide the basis for exact mathematical models useful for understanding the much reduced transverse relaxation times (T2) observed in solid tissues relative to simple liquids. In this context, the purpose of this work was to monitor dynamically with T2 quantitative MRI the liquid-to-gel phase transition of pure agarose as a function of gel concentration. Samples of agarose at various concentrations were allowed to cool down while scanning dynamically with T2 qMRI, 32 x 10milliseconds (ms) echoes, CarrPurcell-Meiboom-Gill (CPMG), 3Tesla.T2 versus; (temperature).curves of each agarose solution show a distinct phase transition region characterized by a sharp T2 reduction. Four agarose solutions were sequentially prepared by dissolving agarose powder in distilled water at concentrations of 1%, 2%, 3%, and 4% by weight/volume. Immediately after preparation and boiling at 98°C, each liquid agarose solution was poured into a plastic container and scanned dynamically at 3.0T as it cooled down with a whole body MRI scanner (Achieva, Philips Medical Systems, Cleveland, OH). A single axial slice multi spin echo CPMG pulse sequence with the following parameters was used: 32 echoes, 10ms echo spacing, 1.5s repetition time (TR), 160 x 160 matrix size, and 2 SENSE factor. The time per dynamic scan was 1minute. The DICOM images were further processed with an adaptive T2 qMRI algorithm programed in Mathcad (Parametric Technology Corporation, Needham, MA) whereby the number of echoes used in the semi-logarithmic linear regression varies automatically from pixel to pixel depending on noise level. The T2 values of agarose gels have been measured during the entire gelation phase transition process at four different concentrations. The T2 versus time (temperature) curves of all the four concentrations shows a rapid drop at about 24 minutes (T~40°C) at which time the gelation phase transition begins. At all temperatures, T2 decreases as a function of increasing agarose concentration. The data shows similar behaviors for all concentrations with a phase transition characterized by a drastic drop in T2 occurring while the temperature drops by approximately 8°C. These results may be useful for testing theoretical models of the Nuclear Magnetic Resonance (NMR) T2 relaxation properties during tissue formation. Quantitative magnetic resonance imaging (qMRI) differs sharply from conventional directly acquired MRI in that objective measures [such as the trio of the basis MR properties: longitudinal relaxation (T1), T2 and Proton Density (PD)] are used for analysis as well as further post-processing rather than relative signal intensities. Q-MRI portrays the spatial distribution of absolute biophysical parameter measurements on a pixel-by-pixel basis; Kevin J. Chang et al 2005

Background: The aim of this study was to describe the morphological signs of the central nervous system lymphoma (CNSL) in magnetic resonance imaging (MRI). We compared morphological characteristics of primary CNSL (PCNSL) and secondary CNSL (SCNSL) and also of PCNSL and glioblastoma (GBM). Methods: We included 64 patients with PCNSL (ten of them were immunocompromised), 21 patients with SCNSL and 54 patients with GBM. The diagnosis was confirmed histologically in all patients. We evaluated morphological signs on the first MRI examination. Additionally, in patients with PCNSL, we evaluated the development of the disease on follow-up examination before histological confirmation of the diagnosis, if available. Results: In most patients with PCNSL (62.5%) the tumor was localized supratentorially and presented as multiple lesions (53.1%) or as a diffuse infiltrative lesion (23.4%). In 87.5% of the patients the lesions reached the brain surface. Infiltration of ependyma was seen in 56.3%, infiltration of meninges in 39.1% and infiltration of cranial nerves in 48.5% of patients. Restriction of diffusion in some part of the tumor was apparent in nearly all patients (97.6%) with PCNSL. After administration of contrast media, marked enhancement was usually seen. In immunocompetent patients, homogenous...

No description available.