Individual cognitive traits can be predicted from task-based dynamic functional connectivity with a deep convolutional-recurrent model.

There has been increased interest in understanding the neural substrates of intelligence and several human traits from neuroimaging data. Deep learning can be used to predict different cognitive measures, such as general and fluid intelligence, from different functional magnetic resonance imaging experiments providing information about the main brain areas involved in these predictions. Using neuroimaging and behavioral data from 874 subjects provided by the Human Connectome Project, we predicted various cognitive scores using dynamic functional connectivity derived from language and working memory functional magnetic resonance imaging task states, using a 360-region multimodal atlas. The deep model joins multiscale convolutional and long short-term memory layers and was trained under a 10-fold stratified cross-validation. We removed the confounding effects of gender, age, total brain volume, motion and the multiband reconstruction algorithm using multiple linear regression. We can explain 17.1% and 16% of general intelligence variance for working memory and language tasks, respectively. We showed that task-based dynamic functional connectivity has more predictive power than resting-state dynamic functional connectivity when compared to the literature and that removing confounders significantly reduces the prediction performance. No specific cortical network showed significant relevance in the prediction of general and fluid intelligence, suggesting a spatial homogeneous distribution of the intelligence construct in the brain.

Biophysical contrast sources for magnetic susceptibility and R2* mapping: A combined 7 Tesla, mass spectrometry and electron paramagnetic resonance study.

Iron is the most abundant trace metal in the human brain and consistently shown elevated in prevalent neurological disorders. Because of its paramagnetism, brain iron can be assessed in vivo by quantitative MRI techniques such as R2* mapping and Quantitative Susceptibility Mapping (QSM). While Inductively Coupled Plasma Mass Spectrometry (ICP-MS) has demonstrated good correlations of the total iron content to MRI parameters in gray matter, the relationship to ferritin levels as assessed by Electron Paramagnetic Resonance (EPR) has not been systematically analyzed. Therefore, we included 15 postmortem subjects (age: 26-91 years) which underwent quantitative in-situ MRI at 7 Tesla within a post-mortem interval of 24 h after death. ICP-MS and EPR were used to measure the total iron and ferritin content in 8 selected gray matter (GM) structures and the correlations to R2* and QSM were calculated. We found that R2* and QSM in the iron rich basal ganglia and the red nucleus were highly correlated with iron (R² > 0.7) and ferritin (R² > 0.6), whereas those correlations were lost in cortical regions and the hippocampus. The neuromelanin-rich substantia nigra showed a different behavior with a correlation with total iron only (R² > 0.5) but not with ferritin. Although qualitative results were similar for both qMRI techniques the observed correlation was always stronger for QSM than R2*. This study demonstrated the quantitative correlations between R2*, QSM, total iron and ferritin levels in an in-situ MRI setup and therefore aids to understand how molecular forms of iron are responsible for MRI contrast generation.

Brain morphometry and estimation of aging brain in subjects with congenital untreated isolated GH deficiency.

PURPOSE: Individuals with isolated GH deficiency (IGHD) due to a mutation in the GHRH receptor gene have a normal life expectancy and above 50 years of age, similar total cognitive performance, with better attention and executive function than controls. Our objectives were to evaluate their brain morphometry and brain aging using MRI. METHODS: Thirteen IGHD and 14 controls matched by age, sex, and education, were enrolled. Quantitative volumetric data and cortical thickness were obtained by automatic segmentation using Freesurfer software. The volume of each brain region was normalized by the intracranial volume. The difference between the predicted brain age estimated by MRI using a trained neuronal network, and the chronological age, was obtained. p < 0.005 was considered significant and 0.005 < p < 0.05 as a suggestive evidence of difference. RESULTS: In IGHD, most absolute values of cortical thickness and regional brain volumes were similar to controls, but normalized volumes were greater in the white matter in the frontal pole and in the insula bilaterally, and in the gray matter, in the right insula and in left Caudate (p < 0.005 for all comparisons) We also noticed suggestive evidence of a larger volume in IGHD in left thalamus (p = 0.006), right thalamus (p = 0.025), right caudate (p = 0.046) and right putamen (p = 0.013). Predicted brain ages were similar between groups. CONCLUSION: IGHD is primarily associated with similar absolute brain measurements, and a set of larger normalized volumes, and does not appear to alter the process of brain aging.

Age-related assessment of diffusion parameters in specific brain tracts correlated with cortical thinning.

The aging process is associated with many brain structural alterations. These changes are not associated with neuronal loss but can be due to cortical structural changes that may be related to white matter (WM) structural alterations. In this study, we evaluated age-related changes in WM and gray matter (GM) parameters and how they correlate for specific brain tracts in a cohort of 158 healthy individuals, aged between 18 and 83 years old. In the tract-cortical analysis, cortical regions connected by tracts demonstrated similar thinning patterns for the majority of tracts. Additionally, a significant relationship was found between mean cortical thinning rate with fractional anisotropy (FA) and mean diffusivity (MD) alteration rates. For all tracts, age was the main effect controlling diffusion parameter alterations. We found no direct correlations between cortical thickness and FA or MD, except for in the fornix, for which the subcallosal gyrus thickness was significantly correlated to FA and MD (p < 0.05 FDR corrected). Our findings lead to the conclusion that alterations in the WM diffusion parameters are explained by the aging process, also associated with cortical thickness changes. Also, the alteration rates of the structural parameters are correlated to the different brain tracts in the aging process.

Histogram Analysis of Adrenal Lesions With a Single Measurement for 10th Percentile: Feasibility and Incremental Value for Diagnosing Adenomas.

OBJECTIVE: Our purpose was to assess whether histogram analysis of adrenal lesions from a single measurement of mean attenuation and SD, using a threshold of 10% of negative voxels, can replace voxel counting while maintaining diagnostic accuracy. MATERIALS AND METHODS: In a 4-year period, 325 adrenal lesions were detected on CT examinations of 308 consecutive patients. After exclusions, 91 patients with 108 lesions, including 20 malignant lesions and 88 adenomas (defined by histologic results or follow-up), were enrolled. Two observers retrospectively measured lesion size, mean attenuation value, and SD attenuation value and generated a pixel histogram. The 10th percentile (P10) was obtained from the conventional histogram analysis and was also calculated from the following formula: P10 = mean attenuation - (1.282 × SD). Diagnostic accuracies of the mean attenuation criterion, histogram analysis, and calculated 10th percentile were compared. RESULTS: The study group was composed of 74 patients with 88 adenomas and 17 patients with 20 malignant lesions, including seven adrenocortical carcinomas and 13 metastases; 93.1% of histograms showed normal distribution. The correlation between histogram analysis and calculated 10th percentile was 0.9827 and 0.9843 for reader 1 and 2 (p < 0.00001 for both). For both readers, sensitivity and specificity of the mean attenuation analysis were 65.9% (95% CI, 55.0-75.7%) and 100.0% (95% CI, 83.2-100%). The sensitivity and specificity of histogram analysis and calculated 10th percentile were the same, 87.5% (95% CI, 78.7-93.6%) and 95.0% (95% CI, 75.1-99.8%), for both readers. The increment increase in sensitivity was significant (p < 0.001), whereas the decrease in specificity was not (p = 0.15). CONCLUSION: For most adrenal lesions, the pixel attenuation has a gaussian distribution, allowing estimation of 10th percentile with a single measurement. The accuracy of histogram analysis and calculated 10th percentile outperformed the mean attenuation as a diagnostic criterion for nonfunctioning adenomas.

Individual hippocampal subfield assessment indicates that matrix macromolecules and gliosis are key elements for the increased T2 relaxation time seen in temporal lobe epilepsy.

OBJECTIVE: Increased T2 relaxation time is often seen in temporal lobe epilepsy (TLE) with hippocampal sclerosis. Water content directly affects the effective T2 in a voxel. Our aim was to evaluate the relation between T2 values and two molecules associated with brain water homeostasis aquaporin 4 (AQP4) and chondroitin sulfate proteoglycan (CSPG), as well as cellular populations in the hippocampal region of patients with TLE. METHODS: Hippocampal T2 imaging and diffusion tensor imaging (DTI) were obtained from 42 drug-resistant patients with TLE and 20 healthy volunteers (radiologic controls, RCs). A similar protocol (ex vivo) was applied to hippocampal sections from the same TLE cases and 14 autopsy control hippocampi (histologic and radiologic controls, HRCs), and each hippocampal subfield was evaluated. Hippocampal sections from TLE cases and HRC controls were submitted to immunohistochemistry for neurons (neuron nuclei [NeuN]), reactive astrocytes (glial fibrillary acidic protein [GFAP]), activated microglia (human leukocyte antigen-D-related [HLA-DR]), polarized AQP4, and CSPG. RESULTS: Patients with TLE had higher in vivo and ex vivo hippocampal T2 relaxation time. Hippocampi from epilepsy cases had lower neuron density, higher gliosis, decreased AQP4 polarization, and increased CSPG immunoreactive area. In vivo relaxation correlated with astrogliosis in the subiculum and extracellular CSPG in the hilus. Ex vivo T2 relaxation time correlated with astrogliosis in the hilus, CA4, and subiculum, and with microgliosis in CA1. The difference between in vivo and ex vivo relaxation ratio correlated with mean diffusivity and with the immunopositive area for CSPG in the hilus. SIGNIFICANCE: Our data indicate that astrogliosis, microgliosis, and CSPG expression correlate with the increased T2 relaxation time seen in the hippocampi of patients with TLE.

Environmental enrichment reduces brain damage in hydrocephalic immature rats.

PURPOSE: We investigate the effects of environmental enrichment (EE) on morphological alterations in different brain structures of pup rats submitted to hydrocephalus condition. METHODS: Hydrocephalus was induced in 7-day-old pup rats by injection of 20% kaolin into the cisterna magna. Ventricular dilatation and magnetization transfer to analyze myelin were assessed by magnetic resonance. Hydrocephalic and control rats exposed to EE (n = 10 per group) were housed in cages with a tunnel, ramp, and colored plastic balls that would emit sound when touched. The walls of the housing were decorated with colored adhesive tape. Moreover, tactile and auditory stimulation was performed daily throughout the experiment. Hydrocephalic and control rats not exposed to EE (n = 10 per group) were allocated singly in standard cages. All animals were weighed daily and exposed to open-field conditions every 2 days until the end of the experiment when they were sacrificed and the brains removed for histology and immunohistochemistry. Solochrome cyanine staining was performed to assess the thickness of the corpus callosum. The glial fibrillary acidic protein method was used to evaluate reactive astrocytes, and the Ki67 method to assess cellular proliferation in the subventricular zone. RESULTS: The hydrocephalic animals exposed to EE showed better performance in Open Field tests (p < 0.05), while presenting lower weight gain. In addition, these animals showed better myelination as revealed by magnetization transfer (p < 0.05). Finally, the EE group showed a reduction in reactive astrocytes by means of glial fibrillary acidic protein immunostaining and preservation of the proliferation potential of progenitor cells. CONCLUSION: The results suggest that EE can protect the developing brain against damaging effects caused by hydrocephalus.

A Comparison of Independent Component Analysis (ICA) of fMRI and Electrical Source Imaging (ESI) in Focal Epilepsy Reveals Misclassification Using a Classifier.

Interictal epileptiform discharges (IEDs) can produce haemodynamic responses that can be detected by electroencephalography-functional magnetic resonance imaging (EEG-fMRI) using different analysis methods such as the general linear model (GLM) of IEDs or independent component analysis (ICA). The IEDs can also be mapped by electrical source imaging (ESI) which has been demonstrated to be useful in presurgical evaluation in a high proportion of cases with focal IEDs. ICA advantageously does not require IEDs or a model of haemodynamic responses but its use in EEG-fMRI of epilepsy has been limited by its ability to separate and select epileptic components. Here, we evaluated the performance of a classifier that aims to filter all non-BOLD responses and we compared the spatial and temporal features of the selected independent components (ICs). The components selected by the classifier were compared to those components selected by a strong spatial correlation with ESI maps of IED sources. Both sets of ICs were subsequently compared to a temporal model derived from the convolution of the IEDs (derived from the simultaneously acquired EEG) with a standard haemodynamic response. Selected ICs were compared to the patients' clinical information in 13 patients with focal epilepsy. We found that the misclassified ICs clearly related to IED in 16/25 cases. We also found that the classifier failed predominantly due to the increased spectral range of fMRIs temporal responses to IEDs. In conclusion, we show that ICA can be an efficient approach to separate responses related to epilepsy but that contemporary classifiers need to be retrained for epilepsy data. Our findings indicate that, for ICA to contribute to the analysis of data without IEDs to improve its sensitivity, classification strategies based on data features other than IC time course frequency is required.

Assessment of U-Net in the segmentation of short tracts: Transferring to clinical MRI routine.

Accurately studying structural connectivity requires precise tract segmentation strategies. The U-Net network has been widely recognized for its exceptional capacity in image segmentation tasks and provides remarkable results in large tract segmentation when high-quality diffusion-weighted imaging (DWI) data are used. However, short tracts, which are associated with various neurological diseases, pose specific challenges, particularly when high-quality DWI data acquisition within clinical settings is concerned. Here, we aimed to evaluate the U-Net network ability to segment short tracts by using DWI data acquired in different experimental conditions. To this end, we conducted three types of training experiments involving 350 healthy subjects and 11 white matter tracts, including the anterior, posterior, and hippocampal commissure, fornix, and uncinated fasciculus. In the first experiment, the model was exclusively trained with high-quality data of the Human Connectome Project (HCP) dataset. The second experiment focused on images of healthy subjects acquired from a local hospital dataset, representing a typical clinical routine acquisition. In the third experiment, a hybrid training approach was employed, combining data of the HCP and local hospital datasets. Then, the best model was also tested in unseen DWIs of 10 epilepsy patients of the local hospital and 10 healthy subjects acquired on a scanner from another company. The outcomes of the third experiment demonstrated a notable enhancement in performance when contrasted with the preceding trials. Specifically, the short tracts within the local hospital dataset achieved Dice scores ranging between 0.60 and 0.65. Similar intervals were obtained with HCP data in the first experiment, and a substantial improvement compared to the scores between 0.37 and 0.50 obtained with the local hospital dataset at the same experiment. This improvement persisted when the method was applied to diverse scenarios, including different scanner acquisitions and epilepsy patients. These results indicate that combining datasets from different sources, coupled with resolution standardization strengthens the neural network ability to generalize predictions across a spectrum of datasets. Nevertheless, short tract segmentation performance is intricately linked to the training composition, to validation, and to testing data. Moreover, curved tracts have intricate structural nature, which adds complexities to their segmenting. Although the network training approach tested herein has provided promising results, caution must be taken when extrapolating its application to datasets acquired under distinct experimental conditions, even in the case of higher-quality data or analysis of long or short tracts.

Ectopic fat in muscle and poor glycemic control are negatively associated with trabecular bone score in type 2 diabetes.

INTRODUCTION: Type 2 Diabetes (T2D) is associated with fractures, despite preserved Bone Mineral Density (BMD). This study aimed to evaluate the relationship between BMD and trabecular bone score (TBS) with the reallocation of fat within muscle in individuals with eutrophy, obesity, and T2D. METHODS: The subjects were divided into three groups: eutrophic controls paired by age and sex with the T2D group (n = 23), controls diagnosed with obesity paired by age, sex, and body mass index with the T2D group (n = 27), and the T2D group (n = 29). BMD and body fat percentage were determined using dual-energy X-Ray absorptiometry. TBS was determined using TBS iNsight software. Intra and extramyocellular lipids in the soleus were measured using proton magnetic resonance spectroscopy. RESULTS: TBS was lower in the T2D group than in the other two groups. Glycated hemoglobin (A1c) was negatively associated with TBS. Body fat percentage was negatively associated with TBS and Total Hip (TH) BMD. TH BMD was positively associated with intramuscular lipids. A trend of negative association was observed between intramuscular lipids and TBS. CONCLUSION: This study showed for the first time that the reallocation of lipids within muscle has a negative association with TBS. Moreover, these results are consistent with previous studies showing a negative association between a parameter related to insulin resistance (intramuscular lipids) and TBS.

Evaluation of multi-channel phase reconstruction methods for quantitative susceptibility mapping on postmortem human brain.

Quantitative Susceptibility Mapping (QSM) is an established Magnetic Resonance Imaging (MRI) technique with high potential in brain iron studies associated to several neurodegenerative diseases. Unlike other MRI techniques, QSM relies on phase images to estimate tissue's relative susceptibility, therefore requiring a reliable phase data. Phase images from a multi-channel acquisition should be reconstructed in a proper way. On this work it was compared the performance of combination of phase matching algorithms (MCPC3D-S and VRC) and phase combination methods based on a complex weighted sum of phases, considering the magnitude at different powers (k = 0 to 4) as the weighting factor. These reconstruction methods were applied in two datasets: a simulated brain dataset for a 4-coil array and data of 22 postmortem subjects acquired at a 7T scanner using a 32 channels coil. For the simulated dataset, differences between the ground truth and the Root Mean Squared Error (RMSE) were evaluated. For both simulated and postmortem data, the mean (MS) and standard deviation (SD) of susceptibility values of five deep gray matter regions were calculated. For the postmortem subjects, MS and SD were statistically compared across all subjects. A qualitative analysis indicated no differences between methods, except for the Adaptive approach on postmortem data, which showed intense artifacts. In the 20% noise level case, the simulated data showed increased noise in central regions. Quantitative analysis showed that both MS and SD were not statistically different when comparing k = 1 and k = 2 on postmortem brain images, however visual inspection showed some boundaries artifacts on k = 2. Furthermore, the RMSE decreased (on regions near the coils) and increased (on central regions and on overall QSM) with increasing k. In conclusion, for reconstruction of phase images from multiple coils with no reference available, alternative methods are needed. In this study it was found that overall, the phase combination with k = 1 is preferred over other powers of k.

Preliminary findings on long-term effects of fMRI neurofeedback training on functional networks involved in sustained attention.

INTRODUCTION: Neurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up-regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long-term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long-term learning effects of neurofeedback training remain under-explored. METHODS: Here, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self-regulation runs without feedback (i.e., transfer runs) and during resting-state runs from 15 healthy individuals. RESULTS: Neurally, we found that participants maintained their ability to control the differential activity during follow-up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow-up transfer runs but not during follow-up resting-state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow-up. CONCLUSION: The discrepancy between lasting regulation-related brain changes but transient behavioral and resting-state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain-behavior associations during and after neurofeedback training is needed to develop its full potential as a promising scientific and clinical tool.

Six-point DIXON and Magnetic Resonance Spectroscopy Techniques in Quantifying Bone Marrow Fat in Sickle Cell Disease.

RATIONALE AND OBJECTIVES: To compare bone marrow fat quantification using magnetic resonance spectroscopy (MRS) and six-point DIXON (6PD) techniques in patients with sickle cell disease (SCD) and healthy subjects. MATERIALS AND METHODS: Prospective study, with 43 SCD patients (24 homozygous [SS], 19 double heterozygous [SC), and 41 healthy subjects paired by age, weight and sex with SCD patients. All participants underwent magnetic resonance imaging with 6PD and single voxel MRS in the L3 vertebral body. Pearson's correlation, ROC curve, and bland-altman analysis were performed, p-values ​​≤0.05 were considered statistically significant for all tests. RESULTS: Significant linear correlation was found between fat fraction (FF) by 6PD and Total Lipids (TL) (r = 0.932; p < 0.001) and Saturated Lipids (SL) (r = 0.934; p < 0.001), in all subjects. Strong correlations were also identified considering subjects of the SS/SC subgroups. Despite high correlations, no significant difference was observed only between FF and SL in the SS subgroup (Bland-Altman analysis), indicating excellent agreement between the fat estimations in this specific situation. Significant differences were observed in all variables (FF, TL, SL) comparing the SCD and healthy subjects. The ROC curve between SCD and healthy subjects showed the following areas under the curve: FF(0.924) > TL(0.883) > SL(0.892). CONCLUSIONS: The comparison between fat quantification by the 6PD with MRS demonstrated an excellent correlation in SCD patients, especially in the SS subgroup, which usually has a higher degree of hemolysis. The diagnostic performance of 6PD and MRS is similar, with advantages of shorter imaging processing time and larger studied area with the 6PD.

Applications of the Dixon technique in the evaluation of the musculoskeletal system.

The acquisition of images with suppression of the fat signal is very useful in clinical practice and can be achieved in a variety of sequences. The Dixon technique, unlike other fat suppression techniques, allows the signal of fat to be suppressed in the postprocessing rather than during acquisition, as well as allowing the visualization of maps showing the distribution of water and fat. This review of the Dixon technique aims to illustrate the basic physical principles, to compare the technique with other magnetic resonance imaging sequences for fat suppression or fat quantification, and to describe its applications in the study of diseases of the musculoskeletal system. Many variants of the Dixon technique have been developed, providing more consistent separation of the fat and water signals, as well as allowing correction for many confounding factors. It allows homogeneous fat suppression, being able to be acquired in combination with several other sequences, as well as with different weightings. The technique also makes it possible to obtain images with and without fat suppression from a single acquisition. In addition, the Dixon technique can be used as a quantitative method, allowing the proportion of tissue fat to be determined, and, in more updated versions, can quantify tissue iron.

A aquisição de imagens com supressão do sinal da gordura é um recurso de grande utilidade diagnóstica, existindo várias sequências capazes de realizá-la. A técnica Dixon, ao contrário de outras técnicas de supressão de gordura, permite suprimir a contribuição do sinal de gordura no pós-processamento e não durante a aquisição, além de permitir a visualização de mapas com a distribuição da água e da gordura. Esta revisão sobre a técnica Dixon almeja ilustrar os princípios físicos básicos, comparar a técnica com outras sequências de ressonância magnética para supressão ou quantificação de gordura, e descrever suas aplicações no estudo de doenças do sistema musculoesquelético. Muitas variantes da técnica Dixon foram desenvolvidas, proporcionando separação mais consistente dos sinais de gordura e água e permitindo correção de muitos fatores de confusão. Permite obter supressão homogênea de gordura, podendo ser adquirida de forma combinada com várias outras sequências, bem como com diferentes ponderações. Esta técnica possibilita também a obtenção de imagens com e sem supressão de gordura a partir de uma única aquisição. Adicionalmente, a técnica Dixon pode ser utilizada como recurso quantitativo, pois permite a mensuração do porcentual de gordura e, em versões mais atualizadas, consegue quantificar ferro tecidual.

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data.

Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans.This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and restingstate fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.

Qualitative and quantitative magnetic resonance imaging evaluation of bone tissue vaso-occlusive events in patients with sickle cell disease.

OBJECTIVE: To evaluate the association between bone changes due to vaso-occlusive events in sickle cell disease (SCD) revealed by conventional MRI sequences and the fat fraction obtained using a 6-point DIXON technique (FFdix), in an attempt to use quantitative data as a biomarker for bone complications. METHODS: Cross-sectional study, with 48 SCD patients, 26-homozygous (HbSS), and 22-compound heterozygous (HbSC). Forty-eight healthy individuals paired by age, weight, and sex with SCD patients. All participants underwent lumbar spine and pelvis MRI. Conventional sequences: bone complications related to vaso-occlusive events-femoral head avascular necrosis, bone infarctions, "H"-shaped vertebrae, bone marrow necrosis. Six-point DIXON technique: quantitative evaluation of the bone marrow at pre-established sites (lumbar vertebrae, sacrum, iliacs, femoral heads, greater femoral trochanters, femoral necks). Pearson's correlation, ROC curve, and binary logistic regression analysis were performed. RESULTS: The most frequent findings in the SCD group included femoral head avascular necrosis (75%), bone infarctions (58.3%), "H"-shaped vertebrae (58.3%), and typical imaging findings of bone marrow necrosis (8.3%). Cortical bone thickness in the proximal femoral diaphysis in patients with SCD was moderately negatively correlated with FFdix in lumbar vertebrae, iliacs, femoral necks, and first sacral vertebrae. The ROC curves and odds ratios demonstrated excellent performance of FFdix in all the evaluated anatomical sites and identified patients having bone complications. CONCLUSIONS: FFdix could serve as a potential biomarker in SCD because of its association with bone complications secondary to vaso-occlusive events in patients with SCD, especially in femoral heads, femoral necks, and iliacs.

Association of bone mineral density with bone texture attributes extracted using routine magnetic resonance imaging.

OBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived bone mineral density (BMD) often fails to predict fragility fractures. Quantitative textural analysis using magnetic resonance imaging (MRI) may potentially yield useful radiomic features to predict fractures. We aimed to investigate the correlation between BMD and texture attributes (TAs) extracted from MRI scans and the interobserver reproducibility of the analysis. METHODS: Forty-nine volunteers underwent lumbar spine 1.5-T MRI and DXA. Three-dimensional (3-D) gray-level co-occurrence matrices were measured from routine sagittal T2 fast spin-echo images using the IBEX software. Twenty-two TAs were extracted from 3-D segmented L3 vertebrae. The estimated concordance coefficient was calculated using linear regression analysis. A Pearson correlation coefficient analysis was performed to evaluate the correlation between BMD and the TAs. Interobserver reproducibility was assessed with the concordance coefficient described by Lin. RESULTS: The results revealed a fair-to-moderate significant correlation between BMD and 13 TAs (r=-0.20 to 0.39; p<0.05). Eight TAs (autocorrelation, energy, homogeneity 1, homogeneity 1.1, maximum probability, sum average, sum variance, and inverse difference normalized) negatively correlated with BMD (r=-0.20 to -0.38; p<0.05), whereas five TAs (dissimilarity, difference entropy, entropy, sum entropy, and information measure corr 1) positively correlated with BMD (r=0.29-0.39; p<0.05). The interobserver agreement was almost perfect for all significant TAs (95% confidence interval, 0.92-1.00; p<0.05). CONCLUSION: Specific TAs could be reliably extracted from routine MRI and correlated with BMD. Our results encourage future evaluation of the potential usefulness of quantitative texture measurements from MRI scans for predicting fragility fractures.

Histological correlates of hippocampal magnetization transfer images in drug-resistant temporal lobe epilepsy patients.

OBJECTIVE: Temporal lobe epilepsy patients (TLE) often present with hippocampal atrophy, increased T2 relaxation, and reduced magnetization transfer ratio (MTR) in magnetic resonance images (MRI). The histological correlates of the reduced hippocampal MTR are so far unknown. Since MTR is dependent on the tissue's macromolecules, our aim was to evaluate the correlations between cellular populations, extracellular matrix molecules and the MTR in TLE patients. METHODS: Patients with TLE (n = 26) and voluntaries (=20) were scanned in a 3 Tesla MRI scanner, and MTR images were calculated from 3DT1 sequences with magnetization pulse on resonance. Immunohistochemistry for neurons, reactive astrocytes, activated microglia, and extracellular matrix chondroitin sulfate were performed in formalin fixed, paraffin embedded tissues of TLE and autopsy controls (n = 10). Results were considered significant with adjusted p < 0.05. RESULTS: Compared to the respective controls, TLE patients had reduced hippocampal MTR, increased reactive astrocytes and activated microglia, increased extracellular chondroitin sulfate, and reduced neuron density, compares to controls. MTR correlated positively with neuron density in CA3 and with chondroitin sulfate in CA3 and CA1. Multiple linear regressions reinforced the correlations between chondroitin sulfate and MTR. SIGNIFICANCE: Our data indicate that extracellular matrix molecules are the most significant histological correlates of magnetization transfer ratio in the hippocampus of TLE patients.

Ectopic fat in muscle and poor glycemic control are negatively associated with trabecular bone score in type 2 diabetes

Abstract Introduction: Type 2 Diabetes (T2D) is associated with fractures, despite preserved Bone Mineral Density (BMD). This study aimed to evaluate the relationship between BMD and trabecular bone score (TBS) with the reallocation of fat within muscle in individuals with eutrophy, obesity, and T2D. Methods: The subjects were divided into three groups: eutrophic controls paired by age and sex with the T2D group (n = 23), controls diagnosed with obesity paired by age, sex, and body mass index with the T2D group (n = 27), and the T2D group (n = 29). BMD and body fat percentage were determined using dual-energy X-Ray absorptiometry. TBS was determined using TBS iNsight software. Intra and extramyocellular lipids in the soleus were measured using proton magnetic resonance spectroscopy. Results: TBS was lower in the T2D group than in the other two groups. Glycated hemoglobin (A1c) was negatively associated with TBS. Body fat percentage was negatively associated with TBS and Total Hip (TH) BMD. TH BMD was positively associated with intramuscular lipids. A trend of negative association was observed between intramuscular lipids and TBS. Conclusion: This study showed for the first time that the reallocation of lipids within muscle has a negative association with TBS. Moreover, these results are consistent with previous studies showing a negative association between a parameter related to insulin resistance (intramuscular lipids) and TBS.