Magnetic Resonance Imaging of Atherosclerotic Manifestations in Familial Hypercholesterolemia

Cardiovascular diseases (CVD) are, in developed countries, the leading cause of mortality. The majority of premature deaths and disability caused by CVD are due to atherosclerosis, a degenerating inflammatory disease affecting arterial walls. Early identification of lesions and initiation of treatment is crucial because the first manifestations quite often are major disabling cardiovascular events. Methods of finding individuals at high risk for these events are under development. Because magnetic resonance imaging (MRI) is an excellent non-invasive tool to study the structure and function of vascular system, we sought to discover whether existing MRI methods are able to show any difference in aortic and intracranial atherosclerotic lesions between patients at high risk for atherosclerosis and healthy controls. Our younger group (age 6-48) comprised 39 symptomless familial hypercholesterolemia (FH) patients and 25 healthy controls. Our older group (age 48-64) comprised 19 FH patients and 18 type 2 diabetes mellitus (DM) patients with coronary heart disease (CHD) and 29 healthy controls. Intracranial and aortic MRI was compared with carotid and femoral ultrasound (US). In neither age-group did MRI reveal any difference in the number of ischemic brain lesions or white matter hyperintensities (WMHIs) - possible signs of intracranial atherosclerosis - between patients and controls. Furthermore, MRI showed no difference in the structure or function of the aorta between FH patients and controls in either group. DM patients had lower compliance of the aorta than did controls, while no difference appeared between DM and FH patients. However, ultrasound showed greater plaque burden and increased thickness of carotid arterial walls in FH and DM patients in both age-groups, suggesting a more advanced atherosclerosis. The mortality of FH patients has decreased substantially after the late 1980´s when statin treatment became available. With statins, the progression of atherosclerotic lesions slows. We think that this, in concert with improvements in treatment of other risk factors, is one reason for the lack of differences between FH patients and controls in MRI measurements of the aorta and brain despite the more advanced disease of the carotid arteries assessed with US. Furthermore, whereas atherosclerotic lesions between different vascular territories correlate, differences might still exist in the extent and location of these lesions among different diseases. Small (<5 mm in diameter) WMHIs are more likely a phenomenon related to aging, but the larger ones may be the ones related to CVD and may be intermediate surrogates of stroke. The image quality in aortic imaging, although constantly improving, is not yet optimal and thus is a source of bias.

Proton magnetic resonance spectroscopy of a boron neutron capture therapy 10B-carrier, L-p-boronophenylalanine-fructose complex

Boron neutron capture therapy (BNCT) is a radiotherapy that has mainly been used to treat malignant brain tumours, melanomas, and head and neck cancer. In BNCT, the patient receives an intravenous infusion of a 10B-carrier, which accumulates in the tumour area. The tumour is irradiated with epithermal or thermal neutrons, which result in a boron neutron capture reaction that generates heavy particles to damage tumour cells. In Finland, boronophenylalanine fructose (BPA-F) is used as the 10B-carrier. Currently, the drifting of boron from blood to tumour as well as the spatial and temporal accumulation of boron in the brain, are not precisely known. Proton magnetic resonance spectroscopy (1H MRS) could be used for selective BPA-F detection and quantification as aromatic protons of BPA resonate in the spectrum region, which is clear of brain metabolite signals. This study, which included both phantom and in vivo studies, examined the validity of 1H MRS as a tool for BPA detection. In the phantom study, BPA quantification was studied at 1.5 and 3.0 T with single voxel 1H MRS, and at 1.5 T with magnetic resonance imaging (MRSI). The detection limit of BPA was determined in phantom conditions at 1.5 T and 3.0 T using single voxel 1H MRS, and at 1.5 T using MRSI. In phantom conditions, BPA quantification accuracy of ± 5% and ± 15% were achieved with single voxel MRS using external or internal (internal water signal) concentration references, respectively. For MRSI, a quantification accuracy of <5% was obtained using an internal concentration reference (creatine). The detection limits of BPA in phantom conditions for the PRESS sequence were 0.7 (3.0 T) and 1.4 mM (1.5 T) mM with 20 × 20 × 20 mm3 single voxel MRS, and 1.0 mM with acquisition-weighted MRSI (nominal voxel volume 10(RL) × 10(AP) × 7.5(SI) mm3), respectively. In the in vivo study, an MRSI or single voxel MRS or both was performed for ten patients (patients 1-10) on the day of BNCT. Three patients had glioblastoma multiforme (GBM), and five patients had a recurrent or progressing GBM or anaplastic astrocytoma gradus III, and two patients had head and neck cancer. For nine patients (patients 1-9), MRS/MRSI was performed 70-140 min after the second irradiation field, and for one patient (patient 10), the MRSI study began 11 min before the end of the BPA-F infusion and ended 6 min after the end of the infusion. In comparison, single voxel MRS was performed before BNCT, for two patients (patients 3 and 9), and for one patient (patient 9), MRSI was performed one month after treatment. For one patient (patient 10), MRSI was performed four days before infusion. Signals from the tumour spectrum aromatic region were detected on the day of BNCT in three patients, indicating that in favourable cases, it is possible to detect BPA in vivo in the patient’s brain after BNCT treatment or at the end of BPA-F infusion. However, because the shape and position of the detected signals did not exactly match the BPA spectrum detected in the in vitro conditions, assignment of BPA is difficult. The opportunity to perform MRS immediately after the end of BPA-F infusion for more patients is necessary to evaluate the suitability of 1H MRS for BPA detection or quantification for treatment planning purposes. However, it could be possible to use MRSI as criteria in selecting patients for BNCT.

2(n)-SEMA-a robust solid state nuclear magnetic resonance experiment for measuring heteronuclear dipolar couplings in static oriented systems using effective transverse spin-lock

Separated local field (SLF) spectroscopy is a powerful technique to measure heteronuclear dipolar couplings. The method provides site-specific dipolar couplings for oriented samples such as membrane proteins oriented in lipid bilayers and liquid crystals. A majority of the SLF techniques utilize the well-known Polarization Inversion Spin Exchange at Magic Angle (PISEMA) pulse scheme which employs spin exchange at the magic angle under Hartmann-Hahn match. Though PISEMA provides a relatively large scaling factor for the heteronuclear dipolar coupling and a better resolution along the dipolar dimension, it has a few shortcomings. One of the major problems with PISEMA is that the sequence is very much sensitive to proton carrier offset and the measured dipolar coupling changes dramatically with the change in the carrier frequency. The study presented here focuses on modified PISEMA sequences which are relatively insensitive to proton offsets over a large range. In the proposed sequences, the proton magnetization is cycled through two quadrants while the effective field is cycled through either two or four quadrants. The modified sequences have been named as 2(n)-SEMA where n represents the number of quadrants the effective field is cycled through. Experiments carried out on a liquid crystal and a single crystal of a model peptide demonstrate the usefulness of the modified sequences. A systematic study under various offsets and Hartmann-Hahn mismatch conditions has been carried out and the performance is compared with PISEMA under similar conditions.

The proton magnetic resonance study of the structure of Na2Zn(SO4)2·4H2O

The proton magnetic resonance spectra of single crystals of Na2Zn(SO4)2·4H2O have been investigated and the orientations of the water molecules have been determined. Using the heavy atom structure determined by X-rays a system of hydrogen bonds between water and sulphate oxygens has been proposed.

Proton magnetic resonance study of the structure of two tutton's salts

Proton magnetic resonance spectra of single crystals of two Tutton's salts, K2Zn (SO4)2.6H22O and K2Mg (SO4)2.6H2O, have been studied and the orientations of the water molecules in the structure have been determined. Using the heavy-atom structure of (NH4) 2Mgt(SO4)2.6H2O as determined by x-ray diffraction, a system of hydrogen bonds between the water and sulfate oxygens in Tutton's salts has been proposed. It appears that the x-ray structure needs considerable refinement.

Studies in sesquiterpenes-XVIII. The proton magnetic resonance spectra of some sesquiterpenes and the structure of humulene

The nuclear magnetic resonance spectra of longifolene, zerumbone, humulene, and their hydroderivatives have been studied in order to gauge the potentialities of this new tool in the field of sesquiterpenes. On the basis of present study, it has been possible to unequivocally fix the positions of the ethylene linkages in humulene and thus provide a straightforward solution of this hitherto unsolved problem.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.