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Abstract Introduction Multiple Sclerosis (MS) is a neurodegenerative disease characterized by inflammatory demyelination in the central nervous system. Quantitative Magnetic Resonance Imaging (qMRI) enables a detailed characterization of brain tissue, but generates a large number of numerical results. In this study, we elucidated the main qMRI techniques and the brain regions that allow the identification of MS patients from neuroimaging data and pattern recognition techniques. Methods The data came from the combination of computational tools of image processing and neuroimaging acquired in a 3 Tesla scanner using different techniques: Diffusion, T2 Relaxometry, Magnetization Transfer Ratio (MTR) and Structural Morphometry. Data from 126 brain regions of 203 healthy individuals and 124 MS patients were separated into two groups and processed in a data-mining program using the k-nearest-neighbor (KNN) algorithm. Results The most relevant anatomical structures in the classification procedure were: corpus callosum, precuneus, left cerebellum and fusiform. Among the quantitative techniques the most relevant was the MTR, being indicated for longitudinal studies of this disease. KNN with 5 neighbors and pre-selected attributes had a better performance with an area under the ROC curve (97.3%) and accuracy (95.7%). A restricted classification considering only brain regions previously reported in the literature as affected by MS brought slightly lower scores, area: 97.1% and accuracy: 93.2%. Conclusion The use of standard recognition techniques from quantitative neuroimaging techniques has confirmed that the white matter of the brain is the most affected tissue by MS following a global pattern with greater involvement of the left hemisphere.
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<p><b>Background</b>Magnetic resonance (MR) imaging provides a unique, noninvasive diagnostic platform to quantify the physiological and biochemical variables of skeletal muscle at rest. This study was to investigate the difference in thigh skeletal muscles between snowboarding halfpipe athletes and healthy volunteers via multiparametric MR imaging.</p><p><b>Methods</b>A comparative study was conducted between 12 healthy volunteers and 14 snowboarding halfpipe athletes. MR scanning targeted the left leg at the level of the proximal thigh on a 3.0T MR system. The measured parameters compared between the two groups included T1, T2, T2* relaxation times, fat fraction (FF), and cross-sectional area (CSA) of the quadriceps femoris and the hamstring muscles. Statistical analysis was carried out using independent sample t-test. Interrater reliability was also assessed with intraclass correlation coefficients (ICCs).</p><p><b>Results</b>It was statistically equivalent between two groups in age, body mass index, thigh circumference, calf circumference, systolic blood pressure, and resting heart rate (all P > 0.05). However, the T1 and T2 values of the hamstring muscles in the athlete group were found to be significantly shorter than those in control group (T1: 1063.3 ± 24.1 ms vs. 1112.0 ± 38.2 ms in biceps femoris, 1050.4 ± 31.2 ms vs. 1095.0 ± 39.5 ms in semitendinosus, 1053.1 ± 31.7 ms vs. 1118.4 ± 40.0 ms in semimembranosus, respectively; T2: 33.4 ± 0.7 ms vs. 36.1 ± 1.9 ms in biceps femoris, 34.6 ± 2.0 ms vs. 37.0 ± 1.9 ms in semitendinosus, 36.9 ± 1.5 ms vs. 38.9 ± 2.4 ms in semimembranosus, respectively; all P < 0.05) although T2* relaxation time was detected with no significant difference. The FF of the hamstring muscles was obviously less than the control group (5.5 ± 1.9% vs. 10.7 ± 4.7%, P < 0.001). In addition, the quadriceps' CSA in the athlete group was substantially larger than the control group (8039.0 ± 1072.3 vs. 6258.2 ± 852.0 mm, P < 0.001). Interrater reliability was excellent (ICC: 0.758-0.994).</p><p><b>Conclusion</b>Multiple MR imaging parameters indicated significant differences between snowboarding halfpipe athletes and healthy volunteers in the thigh skeletal muscles.</p>
Subject(s)
Adolescent , Adult , Humans , Male , Young Adult , Athletes , Cross-Sectional Studies , Healthy Volunteers , Magnetic Resonance Imaging , Muscle, Skeletal , Diagnostic Imaging , Physiology , Skiing , Physiology , Thigh , Diagnostic Imaging , PhysiologyABSTRACT
Brain iron deposition has been proposed to play an important role in the pathophysiology of Alzheimer disease (AD).The aim of this study was to investigate the correlation of brain iron accumulation with the severity of cognitive impairment in patients with AD by using quantitative MR relaxation rate R2' measurements.Fifteen patients with AD,15 age- and sex-matched healthy controls,and 30 healthy volunteers underwent 1.5T MR multi-echo T2 mapping and T2* mapping for the measurement of transverse relaxation rate R2'(R2'=R2*-R2).We statistically analyzed the R2' and iron concentrations of bilateral hippocampus (HP),parietal cortex (PC),frontal white matter (FWM),putamen (PU),caudate nucleus (CN),thalamus (TH),red nucleus (RN),substantia nigra (SN),and dentate nucleus (DN)of the cerebellum for the correlation with the severity of dementia.Two-tailed t-test,Student-Newman-Keuls test (ANOVA) and linear correlation test were used for statistical analysis.In 30 healthy volunteers,the R2' values of bilateral SN,RN,PU,CN,globus pallidus (GP),TH,and FWM were measured.The correlation with the postmortem iron concentration in normal adults was analyzed in order to establish a formula on the relationship between regional R2' and brain iron concentration.The iron concentration of regions of interest (ROI) in AD patients and controls was calculated by this formula and its correlation with the severity of AD was analyzed.Regional R2' was positively correlated with regional brain iron concentration in normal adults (r=0.977,P＜0.01).Iron concentrations in bilateral HP,PC,PU,CN,and DN of patients with AD were significantly higher than those of the controls (P＜0.05); Moreover,the brain iron concentrations,especially in parietal cortex and hippocampus at the early stage of AD,were positively correlated with the severity of patients' cognitive impairment (P＜0.05).The higher the R2' and iron concentrations were,the more severe the cognitive impairment was.Regional R2' and iron concentration in parietal cortex and hippocampus were positively correlated with the severity of AD patients' cognitive impairment,indicating that it may be used as a biomarker to evaluate the progression of AD.