NMR in biomedicine
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This study used quantitative MRI to study normal appearing white matter (NAWM) in patients with clinically isolated syndromes suggestive of multiple sclerosis and relapsing-remitting multiple sclerosis (RRMS). This was done at ultrahigh field (7 T) for greater spatial resolution and sensitivity. 17 CIS patients, 11 RRMS patients, and 20 age-matched healthy controls were recruited. They were scanned using a 3D inversion recovery turbo field echo sequence to measure the longitudinal relaxation time (T1). ⋯ There was no significant correlation between the median of T1, MTR(-), or MTR(+) and the age of healthy controls. Furthermore, no significant correlation was observed between EDSS or disease duration and T1, MTR(-), or MTR(+) for either CIS or RRMS patients. In conclusion, MTR was found to be more sensitive to early changes in MS disease than T1.
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Emphysema is a life-threatening pathology that causes irreversible destruction of alveolar walls. In vivo imaging techniques play a fundamental role in the early non-invasive pre-clinical and clinical detection and longitudinal follow-up of this pathology. In the present study, we aimed to evaluate the feasibility of using high resolution radial three-dimensional (3D) zero echo time (ZTE) and 3D ultra-short echo time (UTE) MRI to accurately detect lung pathomorphological changes in a rodent model of emphysema. ⋯ UTE yielded significantly higher SNR compared with ZTE (14% and 30% higher in PPE-treated and non-PPE-treated lungs, respectively). This study showed that optimized 3D radial UTE and ZTE MRI can provide lung images of excellent quality, with high isotropic spatial resolution (400 µm) and SNR in parenchymal tissue (>25) and negligible motion artifacts in freely breathing animals. These techniques were shown to be useful non-invasive instruments to accurately and reliably detect the pathomorphological alterations taking place in emphysematous lungs, without incurring the risks of cumulative radiation exposure typical of micro-computed tomography.
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Comparative Study
Hemisphere, gender and age-related effects on iron deposition in deep gray matter revealed by quantitative susceptibility mapping.
The purpose of this work was to investigate the effects of hemispheric location, gender and age on susceptibility value, as well as the association between susceptibility value and diffusional metrics, in deep gray matter. Iron content was estimated in vivo using quantitative susceptibility mapping. Microstructure was probed using diffusional kurtosis imaging. ⋯ Notably, the putamen exhibited the highest rate of increase in susceptibility with aging. Correlations between susceptibility value and microstructural measurements were inconclusive. These findings could provide new clues for unveiling mechanisms underlying iron-related neurodegenerative diseases.
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γ-Aminobutyric acid (GABA) has been implicated in several pain conditions, yet no study has systematically evaluated GABA levels in migraine using (1) H-MRS. The accurate detection, separation and quantification of GABA in individuals with migraine could elucidate the role of this neurotransmitter in migraine pathophysiology. Such information may eventually be useful in the diagnosis and development of more effective treatments for migraine. ⋯ These results add to the scarce evidence on the putative role of GABA in migraine and provide a basis to further explore the causal relationship between GABA+ and the pathophysiology of migraine. This study also demonstrates that GABA+ concentration has good diagnostic accuracy for migraine. These findings offer new research and practice directions for migraine diagnosis.
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Multiparametric medical imaging data can be large and are often complex. Machine learning algorithms can assist in image interpretation when reliable training data exist. In most cases, however, knowledge about ground truth (e.g. histology) and thus training data is limited, which makes application of machine learning algorithms difficult. ⋯ We observed an improvement in accuracy with increasing number of imaging parameters used for clustering and SVM training. In particular, including PET SUVs as an additional parameter markedly improved classification results. A variety of applications are conceivable, especially for imaging of tissues without easily available histopathological correlation.