Articles de revues : « Brain, Magnetic Resonance Imaging, Neuroscience, Diffusion-weighted MRI »

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van der Voort, Sebastian R., Marion Smits et Stefan Klein. « DeepDicomSort : An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data ». Neuroinformatics 19, n^o 1 (5 juillet 2020) : 159–84. http://dx.doi.org/10.1007/s12021-020-09475-7.

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AbstractWith the increasing size of datasets used in medical imaging research, the need for automated data curation is arising. One important data curation task is the structured organization of a dataset for preserving integrity and ensuring reusability. Therefore, we investigated whether this data organization step can be automated. To this end, we designed a convolutional neural network (CNN) that automatically recognizes eight different brain magnetic resonance imaging (MRI) scan types based on visual appearance. Thus, our method is unaffected by inconsistent or missing scan metadata. It can recognize pre-contrast T1-weighted (T1w),post-contrast T1-weighted (T1wC), T2-weighted (T2w), proton density-weighted (PDw) and derived maps (e.g. apparent diffusion coefficient and cerebral blood flow). In a first experiment,we used scans of subjects with brain tumors: 11065 scans of 719 subjects for training, and 2369 scans of 192 subjects for testing. The CNN achieved an overall accuracy of 98.7%. In a second experiment, we trained the CNN on all 13434 scans from the first experiment and tested it on 7227 scans of 1318 Alzheimer’s subjects. Here, the CNN achieved an overall accuracy of 98.5%. In conclusion, our method can accurately predict scan type, and can quickly and automatically sort a brain MRI dataset virtually without the need for manual verification. In this way, our method can assist with properly organizing a dataset, which maximizes the shareability and integrity of the data.

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Shibata, Yasushi, Masayuki Goto et Sumire Ishiyama. « Analysis of Migraine Pathophysiology by Magnetic Resonance Imaging ». OBM Neurobiology 6, n^o 1 (25 octobre 2021) : 1. http://dx.doi.org/10.21926/obm.neurobiol.2201115.

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Magnetic resonance imaging (MRI) has been used to investigate migraine pathophysiology because it is a non-invasive technique. The main aim of clinical imaging for patients with headaches is to exclude secondary headaches due to organic lesions. Conventional structural imaging techniques such as routine MRI demonstrate white matter lesions, changes in gray matter volume or cortical thickness, and cerebral blood flow in patients with migraine. Changes in metabolite levels are observed by magnetic resonance spectroscopy. Diffusion tensor imaging, neurite orientation dispersion, density imaging, and functional MRI reveal dynamic real-time functional changes in brain microstructures. These analyses have been applied not only for comparing patients with migraine and healthy controls but also for understanding the dynamic changes in brain function during the cyclic migraine ictal phase. Although these analyses have demonstrated migraine pathophysiology, there are still many limitations. Following the improvement in imaging technology, further research on this topic is in progress.

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Silvagni, Ettore, Alessandra Bortoluzzi, Massimo Borrelli, Andrea Bianchi, Enrico Fainardi et Marcello Govoni. « Cerebral Microstructure Analysis by Diffusion-Based MRI in Systemic Lupus Erythematosus : Lessons Learned and Research Directions ». Brain Sciences 12, n^o 1 (31 décembre 2021) : 70. http://dx.doi.org/10.3390/brainsci12010070.

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Diffusion-based magnetic resonance imaging (MRI) studies, namely diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), have been performed in the context of systemic lupus erythematosus (SLE), either with or without neuropsychiatric (NP) involvement, to deepen cerebral microstructure alterations. These techniques permit the measurement of the variations in random movement of water molecules in tissues, enabling their microarchitecture analysis. While DWI is recommended as part of the initial MRI assessment of SLE patients suspected for NP involvement, DTI is not routinely part of the instrumental evaluation for clinical purposes, and it has been mainly used for research. DWI and DTI studies revealed less restricted movement of water molecules inside cerebral white matter (WM), expression of a global loss of WM density, occurring in the context of SLE, prevalently, but not exclusively, in case of NP involvement. More advanced studies have combined DTI with other quantitative MRI techniques, to further characterize disease pathogenesis, while brain connectomes analysis revealed structural WM network disruption. In this narrative review, the authors provide a summary of the evidence regarding cerebral microstructure analysis by DWI and DTI studies in SLE, focusing on lessons learned and future research perspectives.

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Linden, Annemie Van der, Marleen Verhoye et Göran E. Nilsson. « Does Anoxia Induce Cell Swelling in Carp Brains ? In Vivo MRI Measurements in Crucian Carp and Common Carp ». Journal of Neurophysiology 85, n^o 1 (1 janvier 2001) : 125–33. http://dx.doi.org/10.1152/jn.2001.85.1.125.

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Although both common and crucian carp survived 2 h of anoxia at 18°C, the response of their brains to anoxia was quite different and indicative of the fact that the crucian carp is anoxia tolerant while the common carp is not. Using in vivo T2 and diffusion-weighted magnetic resonance imaging (MRI), we studied anoxia induced changes in brain volume, free water content (T2), and water homeostasis (water diffusion coefficient). The anoxic crucian carp showed no signs of brain swelling or changes in brain water homeostasis even after 24 h except for the optic lobes, where cellular edema was indicated. The entire common carp brain suffered from cellular edema, net water gain, and a volume increase (by 6.5%) that proceeded during 100 min normoxic recovery (by 10%). The common carp recovered from this insult, proving that the changes were reversible and suggesting that the oversized brain cavity allows brain swelling during energy deficiency without a resultant increase in intracranial pressure and global ischemia. It is tempting to suggest that this is a function of the large brain cavity seen in many ectothermic vertebrates.

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Esposito, Romina, Marta Bortoletto, Domenico Zacà, Paolo Avesani et Carlo Miniussi. « An integrated TMS-EEG and MRI approach to explore the interregional connectivity of the default mode network ». Brain Structure and Function 227, n^o 3 (4 février 2022) : 1133–44. http://dx.doi.org/10.1007/s00429-022-02453-6.

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AbstractExplorations of the relation between brain anatomy and functional connections in the brain are crucial for shedding more light on network connectivity that sustains brain communication. In this study, by means of an integrative approach, we examined both the structural and functional connections of the default mode network (DMN) in a group of sixteen healthy subjects. For each subject, the DMN was extracted from the structural and functional resonance imaging data; the areas that were part of the DMN were defined as the regions of interest. Then, the target network was structurally explored by diffusion-weighted imaging, tested by neurophysiological means, and retested by means of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG). A series of correlational analyses were performed to explore the relationship between the amplitude of early-latency TMS-evoked potentials and the indexes of structural connectivity (weighted number of fibres and fractional anisotropy). Stimulation of the left or right parietal nodes of the DMN-induced activation in the contralateral parietal and frontocentral electrodes within 60 ms; this activation correlated with fractional anisotropy measures of the corpus callosum. These results showed that distant secondary activations after target stimulation can be predicted based on the target’s anatomical connections. Interestingly, structural features of the corpus callosum predicted the activation of the directly connected nodes, i.e., parietal-parietal nodes, and of the broader DMN network, i.e., parietal-frontal nodes, as identified with functional magnetic resonance imaging. Our results suggested that the proposed integrated approach would allow us to describe the contributory causal relationship between structural connectivity and functional connectivity of the DMN.

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Smit, Dirk J. A., Dennis van ‘t Ent, Greig de Zubicaray et Jason L. Stein. « Neuroimaging and Genetics : Exploring, Searching, and Finding ». Twin Research and Human Genetics 15, n^o 3 (juin 2012) : 267–72. http://dx.doi.org/10.1017/thg.2012.20.

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This issue on the genetics of brain imaging phenotypes is a celebration of the happy marriage between two of science's highly interesting fields: neuroscience and genetics. The articles collected here are ample evidence that a good deal of synergy exists in this marriage. A wide selection of papers is presented that provide many different perspectives on how genes cause variation in brain structure and function, which in turn influence behavioral phenotypes (including psychopathology). They are examples of the many different methodologies in contemporary genetics and neuroscience research. Genetic methodology includes genome-wide association (GWA), candidate-gene association, and twin studies. Sources of data on brain phenotypes include cortical gray matter (GM) structural/volumetric measures from magnetic resonance imaging (MRI); white matter (WM) measures from diffusion tensor imaging (DTI), such as fractional anisotropy; functional- (activity-) based measures from electroencephalography (EEG), and functional MRI (fMRI). Together, they reflect a combination of scientific fields that have seen great technological advances, whether it is the single-nucleotide polymorphism (SNP) array in genetics, the increasingly high-resolution MRI imaging, or high angular resolution diffusion imaging technique for measuring WM connective properties.

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Wang, Yun, Zejin Jia, Yuelei Lyu, Qian Dong, Shujuan Li et Wenli Hu. « Multimodal magnetic resonance imaging analysis in the characteristics of Wilson’s disease : A case report and literature review ». Open Life Sciences 16, n^o 1 (1 janvier 2021) : 793–99. http://dx.doi.org/10.1515/biol-2021-0071.

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Abstract Wilson’s disease (WD) is an inherited disorder of copper metabolism. Multimodal magnetic resonance imaging (MRI) has been reported to provide evidence of the extent and severity of brain lesions. However, there are few studies related to the diagnosis of WD with multimodal MRI. Here, we reported a WD patient who was subjected to Sanger sequencing, conventional MRI, and multimodal MRI examinations, including susceptibility-weighted imaging (SWI) and arterial spin labeling (ASL). Sanger sequencing demonstrated two pathogenic mutations in exon 8 of the ATP7B gene. Slit-lamp examination revealed the presence of Kayser–Fleischer rings in both eyes, as well as low serum ceruloplasmin and high 24-h urinary copper excretion on admission. Although the substantia nigra, red nucleus, and lenticular nucleus on T1-weighted imaging and T2-weighted imaging were normal, SWI and ASL showed hypointensities in these regions. Besides, decreased cerebral blood flow was found in the lenticular nucleus and the head of caudate nucleus. The patient recovered well after 1 year and 9 months of follow-up, with only a Unified Wilson Disease Rating Scale score of 1 for neurological symptom. Brain multimodal MRI provided a thorough insight into the WD, which might make up for the deficiency of conventional MRI.

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Reddy, Ravikanth. « Magnetic Resonance Imaging Evaluation of Perinatal Hypoxic Ischemic Encephalopathy : An Institutional Experience ». Journal of Neurosciences in Rural Practice 13, n^o 01 (janvier 2022) : 087–94. http://dx.doi.org/10.1055/s-0041-1742157.

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Abstract Background Hypoxic–ischemic encephalopathy (HIE) is the most commonly diagnosed neurological abnormality affecting children leading to severe neurological deficits and a cause of neonatal mortality. HIE constitutes a diagnostic challenge in the prematurely born and full-term neonates. HIE causes severe neurological deficit in children and many a times goes unnoticed in early stages. The various patterns of central nervous system (CNS) involvement in HIE are dependent on factors, such as severity and duration of hypoxia, and brain maturity in preterm and full-term patients. Magnetic resonance imaging (MRI) has prognostic significance in detecting patterns of HIE secondary to mild-to-moderate and severe hypoxias and the imaging findings are highly dependent on the time at which imaging is done. MRI helps determine the prognosis of brain development in patients with HIE. Objective This retrospective study elucidates the spectrum of MRI findings in preterm and full-term patients with HIE on MRI. Materials and Methods This retrospective descriptive study was conducted at a tertiary care center between April 2017 and May 2019 on 50 patients with a clinical diagnosis of HIE using a General Electric (GE) 1.5-Tesla MRI scanner. Various patterns of HIE were evaluated on MRI in preterm and full-term patients. Results This retrospective study evaluated MRI findings in 50 infants diagnosed with HIE. Eighteen (36%) were preterm and 32 (64%) were full-term patients. Thirty-five (70%) were male and 15 (30%) were female patients. In the current study, developmental delay was the most commonly associated clinical entity in both preterm and full-term patients. In preterm patients, periventricular leukomalacia was the most prevalent MRI finding, and in full-term patients, subcortical and periventricular white matter hyperintensities on T2-weighted and fluid-attenuated inversion recovery (FLAIR) sequences were most commonly encountered. Conclusion MRI is the primary imaging modality of choice in preterm and full-term patients with HIE, as it helps determine the severity of hypoxic–ischemic injury by understanding the pattern of brain involvement. In the current study, distinguishable patterns of MRI findings secondary to birth asphyxia and ischemic insult were elucidated in both preterm and full-term patients who are highly dependent on the level of brain maturity at the time of imaging. Regular MRI follow-up has a prognostic significance in HIE with accurate prediction of neurodevelopmental outcome on follow-up studies.

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Dennis, Emily L., Talin Babikian, Christopher C. Giza, Paul M. Thompson et Robert F. Asarnow. « Neuroimaging of the Injured Pediatric Brain : Methods and New Lessons ». Neuroscientist 24, n^o 6 (28 février 2018) : 652–70. http://dx.doi.org/10.1177/1073858418759489.

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Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

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Richards, Todd L. « Functional Magnetic Resonance Imaging and Spectroscopic Imaging of the Brain : Application of fmri and fmrs to Reading Disabilities and Education ». Learning Disability Quarterly 24, n^o 3 (août 2001) : 189–203. http://dx.doi.org/10.2307/1511243.

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This tutorial/review covers functional brain-imaging methods and results used to study language and reading disabilities. Although the main focus is on functional MRI and functional MR spectroscopy, other imaging techniques are discussed briefly such as positron emission tomography (PET), electroencephalography (EEG), magnetoencepholography (MEG), and MR diffusion imaging. These functional brain-imaging studies have demonstrated that dyslexia is a brain-based disorder and that serial imaging studies can be used to study the effect of treatment on functional brain activity.

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Baghchechi, Mohsen, Amy Plaia, Mary Hamer, Nirmalya Ghosh, Stephen Ashwal et Andre Obenaus. « Susceptibility-Weighted Imaging Identifies Iron-Oxide-Labeled Human Neural Stem Cells : Automated Computational Detection ». Developmental Neuroscience 38, n^o 6 (2016) : 445–57. http://dx.doi.org/10.1159/000455837.

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Neonatal hypoxic-ischemic brain injury (HII) can lead to devastating neurological outcomes such as cerebral palsy, epilepsy, and mental retardation. Human neural stem cell (hNSC) therapy provides new hope for the treatment of neonatal HII. These multipotent cells can aid in HII recovery by activating multiple reparative mechanisms including secretion of neurotrophic factors that enhance brain repair and plasticity. For clinical use of implanted hNSCs, methods are required to identify, quantify, track, and visualize migration and replication in an automated and reproducible fashion. In the current study, we used a model of unilateral HII in 10-day-old rat pups that were implanted with 250,000 Feridex-labeled hNSCs into the contralateral ventricle 3 days after HII. In addition to standard noninvasively acquired serial magnetic resonance imaging (MRI) sequences (11.7 and 4.7 T) that included diffusion-weighted imaging and T2-weighted imaging, we also acquired susceptibility-weighted imaging (SWI) 1-90 days after hNSC implantation. SWI is an advanced MRI method that enhances the visualization of iron-oxide-labeled hNSCs within affected regions of the injured neonatal brain. hNSC contrast was further enhanced by creating minimal intensity projections from the raw SWI magnitude images combined with phase information. Automated computational analysis using hierarchical region splitting (HRS) was applied for semiautomatic detection of hNSCs from SWI images. We found hNSCs in the ipsilateral HII lesion within the striatum and cortex adjacent to the lesion that corresponded to histological staining for iron. Quantitative phase values (radians) obtained from SWI revealed temporally evolving increased phase which reflects a decreased iron oxide content that is possibly related to cell division and the replicative capacity of the implanted hNSCs. SWI images also revealed hNSC migration from the contralateral injection site towards the ipsilateral HII lesion. Our results demonstrate that MRI-based SWI can monitor iron-labeled hNSCs in a clinically relevant manner and that automated computational methods such as HRS can rapidly identify iron-oxide-labeled hNSCs.

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Alotaibi, Abdulmajeed, Christopher Tench, Rebecca Stevenson, Ghadah Felmban, Amjad Altokhis, Ali Aldhebaib, Rob A. Dineen et Cris S. Constantinescu. « Investigating Brain Microstructural Alterations in Type 1 and Type 2 Diabetes Using Diffusion Tensor Imaging : A Systematic Review ». Brain Sciences 11, n^o 2 (22 janvier 2021) : 140. http://dx.doi.org/10.3390/brainsci11020140.

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Type 1 and type 2 diabetes mellitus have an impact on the microstructural environment and cognitive functions of the brain due to its microvascular/macrovascular complications. Conventional Magnetic Resonance Imaging (MRI) techniques can allow detection of brain volume reduction in people with diabetes. However, conventional MRI is insufficiently sensitive to quantify microstructural changes. Diffusion Tensor Imaging (DTI) has been used as a sensitive MRI-based technique for quantifying and assessing brain microstructural abnormalities in patients with diabetes. This systematic review aims to summarise the original research literature using DTI to quantify microstructural alterations in diabetes and the relation of such changes to cognitive status and metabolic profile. A total of thirty-eight published studies that demonstrate the impact of diabetes mellitus on brain microstructure using DTI are included, and these demonstrate that both type 1 diabetes mellitus and type 2 diabetes mellitus may affect cognitive abilities due to the alterations in brain microstructures.

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Postans, M., G. D. Parker, H. Lundell, M. Ptito, K. Hamandi, W. P. Gray, J. P. Aggleton, T. B. Dyrby, D. K. Jones et M. Winter. « Uncovering a Role for the Dorsal Hippocampal Commissure in Recognition Memory ». Cerebral Cortex 30, n^o 3 (29 juillet 2019) : 1001–15. http://dx.doi.org/10.1093/cercor/bhz143.

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Abstract The dorsal hippocampal commissure (DHC) is a white matter tract that provides interhemispheric connections between temporal lobe brain regions. Despite the importance of these regions for learning and memory, there is scant evidence of a role for the DHC in successful memory performance. We used diffusion-weighted magnetic resonance imaging (DW-MRI) and white matter tractography to reconstruct the DHC in both humans (in vivo) and nonhuman primates (ex vivo). Across species, our findings demonstrate a close consistency between the known anatomy and tract reconstructions of the DHC. Anterograde tract-tracer techniques also highlighted the parahippocampal origins of DHC fibers in nonhuman primates. Finally, we derived diffusion tensor MRI metrics from the DHC in a large sample of human subjects to investigate whether interindividual variation in DHC microstructure is predictive of memory performance. The mean diffusivity of the DHC correlated with performance in a standardized recognition memory task, an effect that was not reproduced in a comparison commissure tract—the anterior commissure. These findings highlight a potential role for the DHC in recognition memory, and our tract reconstruction approach has the potential to generate further novel insights into the role of this previously understudied white matter tract in both health and disease.

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Han, Meizhen, Guoyuan Yang, Hai Li, Sizhong Zhou, Boyan Xu, Jun Jiang, Weiwei Men et al. « Individualized Cortical Parcellation Based on Diffusion MRI Tractography ». Cerebral Cortex 30, n^o 5 (9 décembre 2019) : 3198–208. http://dx.doi.org/10.1093/cercor/bhz303.

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Abstract The spatial topological properties of cortical regions vary across individuals. Connectivity-based functional and anatomical cortical mapping in individuals will facilitate research on structure–function relationships. However, individual-specific cortical topographic properties derived from anatomical connectivity are less explored than those based on functional connectivity. We aimed to develop a novel individualized anatomical connectivity-based parcellation framework and investigate individual differences in spatial topographic features of cortical regions using diffusion magnetic resonance imaging (dMRI) tractography. Using a high-quality, repeated-session dMRI dataset (42 subjects, 2 sessions per subject), cortical parcels were derived through in vivo anatomical connectivity-based parcellation. These individual-specific parcels demonstrated good within-individual reproducibility and reflected interindividual differences in anatomical brain organization. Connectivity in these individual-specific parcels was significantly more homogeneous than that based on the group atlas. We found that the position, size, and topography of these anatomical parcels were highly variable across individuals and demonstrated nonredundant information about individual differences. Finally, we found that intersubject variability in anatomical connectivity was correlated with the diversity of anatomical connectivity patterns. Overall, we identified cortical parcels that show homogeneous anatomical connectivity patterns. These parcels displayed marked intersubject spatial variability, which may be used in future functional studies to reveal structure–function relationships in the human brain.

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Donadieu, Maxime, Hannah Kelly, Diego Szczupak, Jing-Ping Lin, Yeajin Song, Cecil C. C. Yen, Frank Q. Ye et al. « Ultrahigh-resolution MRI Reveals Extensive Cortical Demyelination in a Nonhuman Primate Model of Multiple Sclerosis ». Cerebral Cortex 31, n^o 1 (8 septembre 2020) : 439–47. http://dx.doi.org/10.1093/cercor/bhaa235.

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Abstract Cortical lesions are a primary driver of disability in multiple sclerosis (MS). However, noninvasive detection of cortical lesions with in vivo magnetic resonance imaging (MRI) remains challenging. Experimental autoimmune encephalomyelitis (EAE) in the common marmoset is a relevant animal model of MS for investigating the pathophysiological mechanisms leading to brain damage. This study aimed to characterize cortical lesions in marmosets with EAE using ultrahigh-field (7 T) MRI and histological analysis. Tissue preparation was optimized to enable the acquisition of high-spatial resolution (50-μm isotropic) T2*-weighted images. A total of 14 animals were scanned in this study, and 70% of the diseased animals presented at least one cortical lesion on postmortem imaging. Cortical lesions identified on MRI were verified with myelin proteolipid protein immunostaining. An optimized T2*-weighted sequence was developed for in vivo imaging and shown to capture 65% of cortical lesions detected postmortem. Immunostaining confirmed extensive demyelination with preserved neuronal somata in several cortical areas of EAE animals. Overall, this study demonstrates the relevance and feasibility of the marmoset EAE model to study cortical lesions, among the most important yet least understood features of MS.

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Rieu, ZunHyan, JeeYoung Kim, Regina EY Kim, Minho Lee, Min Kyoung Lee, Se Won Oh, Sheng-Min Wang et al. « Semi-Supervised Learning in Medical MRI Segmentation : Brain Tissue with White Matter Hyperintensity Segmentation Using FLAIR MRI ». Brain Sciences 11, n^o 6 (28 mai 2021) : 720. http://dx.doi.org/10.3390/brainsci11060720.

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White-matter hyperintensity (WMH) is a primary biomarker for small-vessel cerebrovascular disease, Alzheimer’s disease (AD), and others. The association of WMH with brain structural changes has also recently been reported. Although fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) provide valuable information about WMH, FLAIR does not provide other normal tissue information. The multi-modal analysis of FLAIR and T1-weighted (T1w) MRI is thus desirable for WMH-related brain aging studies. In clinical settings, however, FLAIR is often the only available modality. In this study, we thus propose a semi-supervised learning method for full brain segmentation using FLAIR. The results of our proposed method were compared with the reference labels, which were obtained by FreeSurfer segmentation on T1w MRI. The relative volume difference between the two sets of results shows that our proposed method has high reliability. We further evaluated our proposed WMH segmentation by comparing the Dice similarity coefficients of the reference and the results of our proposed method. We believe our semi-supervised learning method has a great potential for use for other MRI sequences and will encourage others to perform brain tissue segmentation using MRI modalities other than T1w.

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Takao, Hidemasa, Shiori Amemiya et Osamu Abe. « Reproducibility of Brain Volume Changes in Longitudinal Voxel-Based Morphometry Between Non-Accelerated and Accelerated Magnetic Resonance Imaging ». Journal of Alzheimer's Disease 83, n^o 1 (31 août 2021) : 281–90. http://dx.doi.org/10.3233/jad-210596.

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Background: Scan acceleration techniques, such as parallel imaging, can reduce scan times, but reliability is essential to implement these techniques in neuroimaging. Objective: To evaluate the reproducibility of the longitudinal changes in brain morphology determined by longitudinal voxel-based morphometry (VBM) between non-accelerated and accelerated magnetic resonance images (MRI) in normal aging, mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Methods: Using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 2 database, comprising subjects who underwent non-accelerated and accelerated structural T1-weighted MRI at screening and at a 2-year follow-up on 3.0 T Philips scanners, we examined the reproducibility of longitudinal gray matter volume changes determined by longitudinal VBM processing between non-accelerated and accelerated imaging in 50 healthy elderly subjects, 54 MCI patients, and eight AD patients. Results: The intraclass correlation coefficient (ICC) maps differed among the three groups. The mean ICC was 0.72 overall (healthy elderly, 0.63; MCI, 0.75; AD, 0.63), and the ICC was good to excellent (0.6–1.0) for 81.4%of voxels (healthy elderly, 64.8%; MCI, 85.0%; AD, 65.0%). The differences in image quality (head motion) were not significant (Kruskal–Wallis test, p = 0.18) and the within-subject standard deviations of longitudinal gray matter volume changes were similar among the groups. Conclusion: The results indicate that the reproducibility of longitudinal gray matter volume changes determined by VBM between non-accelerated and accelerated MRI is good to excellent for many regions but may vary between diseases and regions.

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Marcus, Daniel S., Tracy H. Wang, Jamie Parker, John G. Csernansky, John C. Morris et Randy L. Buckner. « Open Access Series of Imaging Studies (OASIS) : Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults ». Journal of Cognitive Neuroscience 19, n^o 9 (septembre 2007) : 1498–507. http://dx.doi.org/10.1162/jocn.2007.19.9.1498.

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The Open Access Series of Imaging Studies is a series of magnetic resonance imaging data sets that is publicly available for study and analysis. The initial data set consists of a cross-sectional collection of 416 subjects aged 18 to 96 years. One hundred of the included subjects older than 60 years have been clinically diagnosed with very mild to moderate Alzheimer's disease. The subjects are all right-handed and include both men and women. For each subject, three or four individual T1-weighted magnetic resonance imaging scans obtained in single imaging sessions are included. Multiple within-session acquisitions provide extremely high contrast-to-noise ratio, making the data amenable to a wide range of analytic approaches including automated computational analysis. Additionally, a reliability data set is included containing 20 subjects without dementia imaged on a subsequent visit within 90 days of their initial session. Automated calculation of whole-brain volume and estimated total intracranial volume are presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.

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Phukan, Pranjal, Kalyan Sarma, Barun Kumar Sharma, Deb K. Boruah, Bidyut Bikash Gogoi et Daniala Chuunthang. « MRI Spectrum of Japanese Encephalitis in Northeast India : A Cross-Sectional Study ». Journal of Neurosciences in Rural Practice 12, n^o 02 (24 mars 2021) : 281–89. http://dx.doi.org/10.1055/s-0041-1722820.

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Abstract Objective Japanese encephalitis (JE) is an arthropod-borne flavivirus infection having high mortality and morbidity. This study was performed to evaluate the conventional magnetic resonance imaging (MRI) findings in JE and to find out any difference between pediatric and adult JE. Materials and Methods This retrospective study was performed on serologically positive 54 JE patients presented to a tertiary care hospital with acute encephalitic symptoms between April 2016 and October 2019. Relevant neurological examination, cerebrospinal fluid analysis, and MRI scan of the brain were performed. Results Fifty-four JE patients (n = 31 males and n = 23 females) having 32 pediatric and 22 adult JE were included in the study sample. Group 1 JE (n = 16) patients had encephalitic symptoms with duration less than 15 days up to the day of MRI scan and group 2 JE (n = 38) had symptoms more than 15 days. Group 1 JE had mean apparent diffusion coefficient (ADC) value of 0.563 ± 0.109 (standard deviation [SD]) × 10–3 mm2/sec and group 2 JE had 1.095 ± 0.206 (SD) × 10–3 mm2/sec. The mean ADC value of pediatric JE was 0.907 ± 0.336 (SD) × 10–3 mm2/sec and adult JE was 0.982 ± 0.253 (SD) × 10–3 mm2/sec. Conclusion The majority of the JE patient shows abnormal signal alterations in bilateral thalami and substantia nigra. Diffusion-weighted imaging with ADC mapping helps in evaluating the stage of the JE. No statistical significance of the various conventional MRI findings was found between the pediatric JE and adult JE.

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Oh, Sung Suk, Eun-Hee Lee, Jong-Hoon Kim, Young Beom Seo, Yoo Jin Choo, Juyoung Park et Min Cheol Chang. « The Use of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Evaluation of Blood-Brain Barrier Disruption in Traumatic Brain Injury : What Is the Evidence ? » Brain Sciences 11, n^o 6 (11 juin 2021) : 775. http://dx.doi.org/10.3390/brainsci11060775.

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(1) Background: Blood brain barrier (BBB) disruption following traumatic brain injury (TBI) results in a secondary injury by facilitating the entry of neurotoxins to the brain parenchyma without filtration. In the current paper, we aimed to review previous dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies to evaluate the occurrence of BBB disruption after TBI. (2) Methods: In electronic databases (PubMed, Scopus, Embase, and the Cochrane Library), we searched for the following keywords: dynamic contrast-enhanced OR DCE AND brain injury. We included studies in which BBB disruption was evaluated in patients with TBI using DCE-MRI. (3) Results: Four articles were included in this review. To assess BBB disruption, linear fit, Tofts, extended Tofts, or Patlak models were used. KTrans and ve were increased, and the values of vp were decreased in the cerebral cortex and predilection sites for diffusion axonal injury. These findings are indicative of BBB disruption following TBI. (4) Conclusions: Our analysis supports the possibility of utilizing DCE-MRI for the detection of BBB disruption following TBI.

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Zdanovskis, Nauris, Ardis Platkājis, Andrejs Kostiks, Guntis Karelis et Oļesja Grigorjeva. « Brain Structural Connectivity Differences in Patients with Normal Cognition and Cognitive Impairment ». Brain Sciences 11, n^o 7 (18 juillet 2021) : 943. http://dx.doi.org/10.3390/brainsci11070943.

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Advances in magnetic resonance imaging, particularly diffusion imaging, have allowed researchers to analyze brain connectivity. Identification of structural connectivity differences between patients with normal cognition, cognitive impairment, and dementia could lead to new biomarker discoveries that could improve dementia diagnostics. In our study, we analyzed 22 patients (11 control group patients, 11 dementia group patients) that underwent 3T MRI diffusion tensor imaging (DTI) scans and the Montreal Cognitive Assessment (MoCA) test. We reconstructed DTI images and used the Desikan–Killiany–Tourville cortical parcellation atlas. The connectivity matrix was calculated, and graph theoretical analysis was conducted using DSI Studio. We found statistically significant differences between groups in the graph density, network characteristic path length, small-worldness, global efficiency, and rich club organization. We did not find statistically significant differences between groups in the average clustering coefficient and the assortativity coefficient. These statistically significant graph theory measures could potentially be used as quantitative biomarkers in cognitive impairment and dementia diagnostics.

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Zhou, Qian, Meiqun Tian, Huan Yang et Yue-Bei Luo. « Adult-Onset Neuronal Intranuclear Inclusion Disease with Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke-like (MELAS-like) Episode : A Case Report and Review of Literature ». Brain Sciences 12, n^o 10 (11 octobre 2022) : 1377. http://dx.doi.org/10.3390/brainsci12101377.

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Neuronal intranuclear inclusion disease (NIID) is a rare neurodegenerative disease with highly heterogeneous manifestations. Curvilinear hyperintensity along the corticomedullary junction on diffusion-weighted images (DWI) is a vital clue for diagnosing NIID. DWI hyperintensity tends to show an anterior-to-posterior propagation pattern as the disease progresses. The rare cases of its disappearance may lead to misdiagnosis. Here, we reported a NIID patient with mitochondrial encephalomyopathy, lactic acidosis and stroke-like (MELAS-like) episode, and reversible DWI hyperintensities. A review of the literature on NIID with MELAS-like episodes was conducted. A 69-year-old woman stated to our clinics for recurrent nausea/vomiting, mixed aphasia, altered mental status, and muscle weakness for 2 weeks. Neurological examination showed impaired mental attention and reaction capacity, miosis, mixed aphasia, decreased muscle strength in limbs, and reduced tendon reflex. Blood tests were unremarkable. The serological examination was positive for antibody against dipeptidyl-peptidase-like protein 6 (DPPX) (1:32). Brain magnetic resonance imaging (MRI) revealed hyperintensities in the left temporal occipitoparietal lobe on DWI and correspondingly elevated lactate peak in the identified restricted diffusion area on magnetic resonance spectroscopy, mimicking the image of MELAS. Skin biopsy and genetic testing confirmed the diagnosis of NIID. Pulse intravenous methylprednisolone and oral prednisolone were administered, ameliorating her condition with improved neuroimages. This case highlights the importance of distinguishing NIID and MELAS, and reversible DWI hyperintensities can be seen in NIID.

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Bobić-Rasonja, Mihaela, Ivana Pogledić, Christian Mitter, Andrija Štajduhar, Marija Milković-Periša, Sara Trnski, Dieter Bettelheim et al. « Developmental Differences Between the Limbic and Neocortical Telencephalic Wall : An Intrasubject Slice-Matched 3 T MRI-Histological Correlative Study in Humans ». Cerebral Cortex 31, n^o 7 (11 mars 2021) : 3536–50. http://dx.doi.org/10.1093/cercor/bhab030.

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Abstract The purpose of the study was to investigate the interrelation of the signal intensities and thicknesses of the transient developmental zones in the cingulate and neocortical telencephalic wall, using T2-weighted 3 T-magnetic resonance imaging (MRI) and histological scans from the same brain hemisphere. The study encompassed 24 postmortem fetal brains (15–35 postconceptional weeks, PCW). The measurements were performed using Fiji and NDP.view2. We found that T2w MR signal-intensity curves show a specific regional and developmental stage profile already at 15 PCW. The MRI-histological correlation reveals that the subventricular-intermediate zone (SVZ-IZ) contributes the most to the regional differences in the MRI-profile and zone thicknesses, growing by a factor of 2.01 in the cingulate, and 1.78 in the neocortical wall. The interrelations of zone or wall thicknesses, obtained by both methods, disclose a different rate and extent of shrinkage per region (highest in neocortical subplate and SVZ-IZ) and stage (highest in the early second half of fetal development), distorting the zones’ proportion in histological sections. This intrasubject, slice-matched, 3 T correlative MRI-histological study provides important information about regional development of the cortical wall, critical for the design of MRI criteria for prenatal brain monitoring and early detection of cortical or other brain pathologies in human fetuses.

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Movahedian Attar, Fakhereh, Evgeniya Kirilina, Daniel Haenelt, Kerrin J. Pine, Robert Trampel, Luke J. Edwards et Nikolaus Weiskopf. « Mapping Short Association Fibers in the Early Cortical Visual Processing Stream Using In Vivo Diffusion Tractography ». Cerebral Cortex 30, n^o 8 (8 avril 2020) : 4496–514. http://dx.doi.org/10.1093/cercor/bhaa049.

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Abstract Short association fibers (U-fibers) connect proximal cortical areas and constitute the majority of white matter connections in the human brain. U-fibers play an important role in brain development, function, and pathology but are underrepresented in current descriptions of the human brain connectome, primarily due to methodological challenges in diffusion magnetic resonance imaging (dMRI) of these fibers. High spatial resolution and dedicated fiber and tractography models are required to reliably map the U-fibers. Moreover, limited quantitative knowledge of their geometry and distribution makes validation of U-fiber tractography challenging. Submillimeter resolution diffusion MRI—facilitated by a cutting-edge MRI scanner with 300 mT/m maximum gradient amplitude—was used to map U-fiber connectivity between primary and secondary visual cortical areas (V1 and V2, respectively) in vivo. V1 and V2 retinotopic maps were obtained using functional MRI at 7T. The mapped V1–V2 connectivity was retinotopically organized, demonstrating higher connectivity for retinotopically corresponding areas in V1 and V2 as expected. The results were highly reproducible, as demonstrated by repeated measurements in the same participants and by an independent replication group study. This study demonstrates a robust U-fiber connectivity mapping in vivo and is an important step toward construction of a more complete human brain connectome.

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Königs, Marsh, Petra JW Pouwels, LW Ernest van Heurn, Roel Bakx, R. Jeroen Vermeulen, J. Carel Goslings, Bwee Tien Poll-The, Marleen van der Wees, Coriene E. Catsman-Berrevoets et Jaap Oosterlaan. « Relevance of neuroimaging for neurocognitive and behavioral outcome after pediatric traumatic brain injury ». Brain Imaging and Behavior 12, n^o 1 (14 janvier 2017) : 29–43. http://dx.doi.org/10.1007/s11682-017-9673-3.

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Abstract This study aims to (1) investigate the neuropathology of mild to severe pediatric TBI and (2) elucidate the predictive value of conventional and innovative neuroimaging for functional outcome. Children aged 8–14 years with trauma control (TC) injury (n = 27) were compared to children with mild TBI and risk factors for complicated TBI (mildRF+, n = 20) or moderate/severe TBI (n = 17) at 2.8 years post-injury. Neuroimaging measures included: acute computed tomography (CT), volumetric analysis on post-acute conventional T1-weighted magnetic resonance imaging (MRI) and post-acute diffusion tensor imaging (DTI, analyzed using tract-based spatial statistics and voxel-wise regression). Functional outcome was measured using Common Data Elements for neurocognitive and behavioral functioning. The results show that intracranial pathology on acute CT-scans was more prevalent after moderate/severe TBI (65%) than after mildRF+ TBI (35%; p = .035), while both groups had decreased white matter volume on conventional MRI (ps ≤ .029, ds ≥ −0.74). The moderate/severe TBI group further showed decreased fractional anisotropy (FA) in a widespread cluster affecting all white matter tracts, in which regional associations with neurocognitive functioning were observed (FSIQ, Digit Span and RAVLT Encoding) that consistently involved the corpus callosum. FA had superior predictive value for functional outcome (i.e. intelligence, attention and working memory, encoding in verbal memory and internalizing problems) relative to acute CT-scanning (i.e. internalizing problems) and conventional MRI (no predictive value). We conclude that children with mildRF+ TBI and moderate/severe TBI are at risk of persistent white matter abnormality. Furthermore, DTI has superior predictive value for neurocognitive out-come relative to conventional neuroimaging.

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Baek, Hyeon-Man. « Diffusion Measures of Subcortical Structures Using High-Field MRI ». Brain Sciences 13, n^o 3 (24 février 2023) : 391. http://dx.doi.org/10.3390/brainsci13030391.

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The pathology of Parkinson’s disease (PD) involves the death of dopaminergic neurons in the substantia nigra (SN), which slowly influences downstream basal ganglia pathways as dopamine transport diminishes. Diffusion magnetic resonance imaging (MRI) has been used to diagnose PD by assessing white matter connectivity in some brain areas. For this study, we applied Lead-DBS to human connectome project data to automatically segment 11 subcortical structures of 49 human connectome project subjects, reducing the reliance on manual segmentation for more consistency. The Lead-connectome pipeline, which utilizes DSI Studio to generate structural connectomes from each 3T and 7T diffusion image, was applied to 3T and 7T data to investigate possible differences in diffusion measures due to different acquisition protocols. Significantly higher fractional anisotropy (FA) values were found in the 3T left SN; significantly higher MD values were found in the 3T left SN and the right amygdala, SN, and subthalamic nucleus (STN); significantly higher AD values were found in the right RN and STN; and significantly higher RD values were found in the left RN and right amygdala. We illustrate a methodology for obtaining diffusion measures of basal ganglia and basal ganglia connectivity using diffusion images, as well as show possible differences in diffusion measures that can arise due to the differences in MRI acquisitions.

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Nagarajan, Elanagan, Lakshmi P. Digala, Manjamalai Sivaraman et Pradeep C. Bollu. « Is Magnetic Resonance Imaging Diffusion Restriction of the Optic Disc Head a New Marker for Idiopathic Intracranial Hypertension ? » Journal of Neurosciences in Rural Practice 11, n^o 01 (27 décembre 2019) : 170–74. http://dx.doi.org/10.1055/s-0039-3402621.

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Abstract Background Idiopathic intracranial hypertension (IIH) is a headache syndrome due to raised intracranial pressure of unknown etiology. Before making the diagnosis of IIH, secondary causes of raised intracranial pressure must be ruled out. The radiological features associated with this condition have variable sensitivity and specificity. In this case series, we aim to describe a potential new radiological marker of IIH, that is, diffusion restriction, in the optic disc head and propose that this can be a specific finding in the appropriate clinical picture. Importance IIH causes vision loss and disabling daily headaches. The diagnosis of this condition is based on history and physical examination findings. Magnetic resonance imaging (MRI) is used to exclude other causes, but specific radiological markers for the diagnosis of IIH are lacking. Observations Five patients presented with the main complaint of headache, which was associated with blurry vision. All of our patients had a formal neuro-ophthalmological evaluation that confirmed the presence of optic disc edema in both eyes. They also underwent an MRI of the brain that showed diffusion restriction in the optic nerve head in either eye or both eyes. Patients underwent lumbar puncture in the lateral decubitus position, which revealed cerebrospinal fluid opening pressures > 25 cm H2O. They all responded well to standard treatments, with the resolution of symptoms in their follow-up appointments. Conclusion and Relevance The MRI diffusion restriction in the optic nerve head may be a reliable noninvasive marker for the diagnosis of IIH in the appropriate clinical picture.

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Mukherjee, Soumava, Bhavesh Solanki, Goutam Guha et Shankar Prasad Saha. « White matter changes in Wilson’s disease : A radiological enigma ». Journal of Neurosciences in Rural Practice 07, n^o 03 (juillet 2016) : 447–49. http://dx.doi.org/10.4103/0976-3147.176195.

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ABSTRACTWilson's disease is a metabolic disorder which presents with hepatitis or hepatic decompensation commonly. Neurologic manifestations are late and include movement disorders, personality changes, and seizures. Magnetic resonance imaging (MRI) brain shows high signal changes in putamen, lentiform nucleus, thalamus, and brainstem. White matter lesions are rare. We report a child of Wilson's disease who presented to us with dystonia, rigidity, myoclonus and had symmetrical white matter changes in the fronto-parietooccipital region. Diffusion restriction in bilateral frontoparietal areas was also seen which is rare in chronic cases like ours. Atypical MRI characteristics should be considered in patients with clinical signs of neurological involvement in Wilson's disease as it is a devastating but treatable disease.

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Lucignani, Martina, Daniela Longo, Elena Fontana, Maria Camilla Rossi-Espagnet, Giulia Lucignani, Sara Savelli, Stefano Bascetta et al. « Morphometric Analysis of Brain in Newborn with Congenital Diaphragmatic Hernia ». Brain Sciences 11, n^o 4 (2 avril 2021) : 455. http://dx.doi.org/10.3390/brainsci11040455.

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Congenital diaphragmatic hernia (CDH) is a severe pediatric disorder with herniation of abdominal viscera into the thoracic cavity. Since neurodevelopmental impairment constitutes a common outcome, we performed morphometric magnetic resonance imaging (MRI) analysis on CDH infants to investigate cortical parameters such as cortical thickness (CT) and local gyrification index (LGI). By assessing CT and LGI distributions and their correlations with variables which might have an impact on oxygen delivery (total lung volume, TLV), we aimed to detect how altered perfusion affects cortical development in CDH. A group of CDH patients received both prenatal (i.e., fetal stage) and postnatal MRI. From postnatal high-resolution T2-weighted images, mean CT and LGI distributions of 16 CDH were computed and statistically compared to those of 13 controls. Moreover, TLV measures obtained from fetal MRI were further correlated to LGI. Compared to controls, CDH infants exhibited areas of hypogiria within bilateral fronto-temporo-parietal labels, while no differences were found for CT. LGI significantly correlated with TLV within bilateral temporal lobes and left frontal lobe, involving language- and auditory-related brain areas. Although the causes of neurodevelopmental impairment in CDH are still unclear, our results may suggest their link with altered cortical maturation and possible impaired oxygen perfusion.

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Webb, Christina E., Karen M. Rodrigue, David A. Hoagey, Chris M. Foster et Kristen M. Kennedy. « Contributions of White Matter Connectivity and BOLD Modulation to Cognitive Aging : A Lifespan Structure-Function Association Study ». Cerebral Cortex 30, n^o 3 (22 octobre 2019) : 1649–61. http://dx.doi.org/10.1093/cercor/bhz193.

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Abstract The ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20–94) underwent magnetic resonance imaging (MRI) scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered blood-oxygen-level-dependent (BOLD) modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty-related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.

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Hoogenboom, Wouter S., Todd G. Rubin, Kenny Ye, Min-Hui Cui, Kelsey C. Branch, Jinyuan Liu, Craig A. Branch et Michael L. Lipton. « Diffusion Tensor Imaging of the Evolving Response to Mild Traumatic Brain Injury in Rats ». Journal of Experimental Neuroscience 13 (janvier 2019) : 117906951985862. http://dx.doi.org/10.1177/1179069519858627.

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Mild traumatic brain injury (mTBI), also known as concussion, is a serious public health challenge. Although most patients recover, a substantial minority suffers chronic disability. The mechanisms underlying mTBI-related detrimental effects remain poorly understood. Although animal models contribute valuable preclinical information and improve our understanding of the underlying mechanisms following mTBI, only few studies have used diffusion tensor imaging (DTI) to study the evolution of axonal injury following mTBI in rodents. It is known that DTI shows changes after human concussion and the role of delineating imaging findings in animals is therefore to facilitate understanding of related mechanisms. In this work, we used a rodent model of mTBI to investigate longitudinal indices of axonal injury. We present the results of 45 animals that received magnetic resonance imaging (MRI) at multiple time points over a 2-week period following concussive or sham injury yielding 109 serial observations. Overall, the evolution of DTI metrics following concussive or sham injury differed by group. Diffusion tensor imaging changes within the white matter were most noticeable 1 week following injury and returned to baseline values after 2 weeks. More specifically, we observed increased fractional anisotropy in combination with decreased radial diffusivity and mean diffusivity, in the absence of changes in axial diffusivity, within the white matter of the genu corpus callosum at 1 week post-injury. Our study shows that DTI can detect microstructural white matter changes in the absence of gross abnormalities as indicated by visual screening of anatomical MRI and hematoxylin and eosin (H&E)-stained sections in a clinically relevant animal model of mTBI. Whereas additional histopathologic characterization is required to better understand the neurobiological correlates of DTI measures, our findings highlight the evolving nature of the brain’s response to injury following concussion.

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Silhan, David, Olga Pashkovska et Ales Bartos. « Hippocampo-Horn Percentage and Parietal Atrophy Score for Easy Visual Assessment of Brain Atrophy on Magnetic Resonance Imaging in Early- and Late-Onset Alzheimer’s Disease ». Journal of Alzheimer's Disease 84, n^o 3 (23 novembre 2021) : 1259–66. http://dx.doi.org/10.3233/jad-210372.

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Background: Magnetic resonance imaging (MRI) visual scales of brain atrophy are important for differential diagnosis of dementias in routine clinical practice. Atrophy patterns in early- and late-onset Alzheimer’s disease (AD) can be different according to some studies. Objective: Our goal was to assess brain atrophy patterns in early- and late-onset AD using our recently developed simple MRI visual scales and evaluate their reliability. Methods: We used Hippocampo-horn percentage (Hip-hop) and Parietal Atrophy Score (PAS) to compare mediotemporal and parietal atrophy on brain MRI among 4 groups: 26 patients with early-onset AD, 21 younger cognitively normal persons, 32 patients with late-onset AD, and 36 older cognitively normal persons. Two raters scored all brain MRI to assess reliability of the Hip-hop and PAS. Brain MRIs were obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Results: The patients with early-onset AD had significantly more pronounced mediotemporal and also parietal atrophy bilaterally compared to the controls (both p < 0.01). The patients with late-onset AD had significantly more pronounced only mediotemporal atrophy bilaterally compared to the controls (p < 0.000001), but parietal lobes were the same. Intra-rater and inter-rater reliability of both visual scales Hip-hop and PAS were almost perfect in all cases (weighted-kappa value ranged from 0.90 to 0.99). Conclusion: While mediotemporal atrophy detected using Hip-hop is universal across the whole AD age spectrum, parietal atrophy detected using PAS is worth rating only in early-onset AD. Hip-hop and PAS are very reliable MRI visual scales.

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Guild, Emma B., et Brian Levine. « Functional Correlates of Midline Brain Volume Loss in Chronic Traumatic Brain Injury ». Journal of the International Neuropsychological Society 21, n^o 8 (7 août 2015) : 650–55. http://dx.doi.org/10.1017/s1355617715000600.

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AbstractTraumatic brain injury (TBI) is associated with long-term changes in daily life functioning, yet the neuroanatomical correlates of these changes are poorly understood. This study related outcome assessed across several domains to brain structure derived from quantitative magnetic resonance imaging (MRI). Sixty individuals spanning a wide range of TBI severity participated 1-year post-injury as part of the Toronto TBI study. Volumetric data over 38 brain regions were derived from high resolution T1-weighted MRI scans. Functioning was assessed with a battery of self- and significant-other rated measures. Multivariate analysis (partial least squares) was used to identify shared variance between the neuroimaging and outcome measures. TBI was associated with item endorsement on outcome questionnaires without strong evidence for severity or focal lesion effects. Prefrontal midline, cingulate, medial temporal, right inferior parietal and basal ganglia/thalamic volumes were associated with measures of initiative, energization, and physical complaints. In the chronic stage of TBI, self-initiation, energization, and physical complaints related to a specific pattern of volume loss in midline and lateral regions known to be involved in motivation, apathy, and attention. These results suggest that crucial functional changes in chronic TBI may be associated with volume loss in established midline-frontal and attentional circuits. (JINS, 2015,21, 650–655)

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Szalkai, Balázs, Bálint Varga et Vince Grolmusz. « The Graph of Our Mind ». Brain Sciences 11, n^o 3 (8 mars 2021) : 342. http://dx.doi.org/10.3390/brainsci11030342.

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Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study of the connections of the human brain. By the development of diffusion magnetic resonance imaging (diffusion MRI), it is possible today to map the connections between the 1–1.5 cm2 regions of the gray matter of the human brain. These connections can be viewed as a graph. We have computed 1015-vertex graphs with thousands of edges for hundreds of human brains from one of the highest quality data sources: the Human Connectome Project. Here we analyze the male and female braingraphs graph-theoretically and show statistically significant differences in numerous parameters between the sexes: the female braingraphs are better expanders, have more edges, larger bipartition widths, and larger vertex cover than the braingraphs of the male subjects. These parameters are closely related to the quality measures of highly parallel computer interconnection networks: the better expanding property, the large bipartition width, and the large vertex cover characterize high-quality interconnection networks. We apply the data of 426 subjects and demonstrate the statistically significant (corrected) differences in 116 graph parameters between the sexes.

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Rasmussen, Ingrid Daae, Nya Mehnwolo Boayue, Matthias Mittner, Martin Bystad, Ole K. Grønli, Torgil Riise Vangberg, Gábor Csifcsák et Per M. Aslaksen. « High-Definition Transcranial Direct Current Stimulation Improves Delayed Memory in Alzheimer’s Disease Patients : A Pilot Study Using Computational Modeling to Optimize Electrode Position ». Journal of Alzheimer's Disease 83, n^o 2 (14 septembre 2021) : 753–69. http://dx.doi.org/10.3233/jad-210378.

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Background: The optimal stimulation parameters when using transcranial direct current stimulation (tDCS) to improve memory performance in patients with Alzheimer’s disease (AD) are lacking. In healthy individuals, inter-individual differences in brain anatomy significantly influence current distribution during tDCS, an effect that might be aggravated by variations in cortical atrophy in AD patients. Objective: To measure the effect of individualized HD-tDCS in AD patients. Methods: Nineteen AD patients were randomly assigned to receive active or sham high-definition tDCS (HD-tDCS). Computational modeling of the HD-tDCS-induced electric field in each patient’s brain was analyzed based on magnetic resonance imaging (MRI) scans. The chosen montage provided the highest net anodal electric field in the left dorsolateral prefrontal cortex (DLPFC). An accelerated HD-tDCS design was conducted (2 mA for 3×20 min) on two separate days. Pre- and post-intervention cognitive tests and T1 and T2-weighted MRI and diffusion tensor imaging data at baseline were analyzed. Results: Different montages were optimal for individual patients. The active HD-tDCS group improved significantly in delayed memory and MMSE performance compared to the sham group. Five participants in the active group had higher scores on delayed memory post HD-tDCS, four remained stable and one declined. The active HD-tDCS group had a significant positive correlation between fractional anisotropy in the anterior thalamic radiation and delayed memory score. Conclusion: HD-tDCS significantly improved delayed memory in AD. Our study can be regarded as a proof-of-concept attempt to increase tDCS efficacy. The present findings should be confirmed in larger samples.

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Xu, Guoping, Yogesh Rathi, Joan A. Camprodon, Hanqiang Cao et Lipeng Ning. « Rapid whole-brain electric field mapping in transcranial magnetic stimulation using deep learning ». PLOS ONE 16, n^o 7 (30 juillet 2021) : e0254588. http://dx.doi.org/10.1371/journal.pone.0254588.

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Transcranial magnetic stimulation (TMS) is a non-invasive neurostimulation technique that is increasingly used in the treatment of neuropsychiatric disorders and neuroscience research. Due to the complex structure of the brain and the electrical conductivity variation across subjects, identification of subject-specific brain regions for TMS is important to improve the treatment efficacy and understand the mechanism of treatment response. Numerical computations have been used to estimate the stimulated electric field (E-field) by TMS in brain tissue. But the relative long computation time limits the application of this approach. In this paper, we propose a deep-neural-network based approach to expedite the estimation of whole-brain E-field by using a neural network architecture, named 3D-MSResUnet and multimodal imaging data. The 3D-MSResUnet network integrates the 3D U-net architecture, residual modules and a mechanism to combine multi-scale feature maps. It is trained using a large dataset with finite element method (FEM) based E-field and diffusion magnetic resonance imaging (MRI) based anisotropic volume conductivity or anatomical images. The performance of 3D-MSResUnet is evaluated using several evaluation metrics and different combinations of imaging modalities and coils. The experimental results show that the output E-field of 3D-MSResUnet provides reliable estimation of the E-field estimated by the state-of-the-art FEM method with significant reduction in prediction time to about 0.24 second. Thus, this study demonstrates that neural networks are potentially useful tools to accelerate the prediction of E-field for TMS targeting.

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Shiohama, Tadashi, et Keita Tsujimura. « Quantitative Structural Brain Magnetic Resonance Imaging Analyses : Methodological Overview and Application to Rett Syndrome ». Frontiers in Neuroscience 16 (5 avril 2022). http://dx.doi.org/10.3389/fnins.2022.835964.

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Congenital genetic disorders often present with neurological manifestations such as neurodevelopmental disorders, motor developmental retardation, epilepsy, and involuntary movement. Through qualitative morphometric evaluation of neuroimaging studies, remarkable structural abnormalities, such as lissencephaly, polymicrogyria, white matter lesions, and cortical tubers, have been identified in these disorders, while no structural abnormalities were identified in clinical settings in a large population. Recent advances in data analysis programs have led to significant progress in the quantitative analysis of anatomical structural magnetic resonance imaging (MRI) and diffusion-weighted MRI tractography, and these approaches have been used to investigate psychological and congenital genetic disorders. Evaluation of morphometric brain characteristics may contribute to the identification of neuroimaging biomarkers for early diagnosis and response evaluation in patients with congenital genetic diseases. This mini-review focuses on the methodologies and attempts employed to study Rett syndrome using quantitative structural brain MRI analyses, including voxel- and surface-based morphometry and diffusion-weighted MRI tractography. The mini-review aims to deepen our understanding of how neuroimaging studies are used to examine congenital genetic disorders.

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Liu, Yin, Liyan Lu, Fengfang Li et Yu-Chen Chen. « Neuropathological Mechanisms of Mild Traumatic Brain Injury : A Perspective From Multimodal Magnetic Resonance Imaging ». Frontiers in Neuroscience 16 (17 juin 2022). http://dx.doi.org/10.3389/fnins.2022.923662.

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Mild traumatic brain injury (mTBI) accounts for more than 80% of the total number of TBI cases. The mechanism of injury for patients with mTBI has a variety of neuropathological processes. However, the underlying neurophysiological mechanism of the mTBI is unclear, which affects the early diagnosis, treatment decision-making, and prognosis evaluation. More and more multimodal magnetic resonance imaging (MRI) techniques have been applied for the diagnosis of mTBI, such as functional magnetic resonance imaging (fMRI), arterial spin labeling (ASL) perfusion imaging, susceptibility-weighted imaging (SWI), and diffusion MRI (dMRI). Various imaging techniques require to be used in combination with neuroimaging examinations for patients with mTBI. The understanding of the neuropathological mechanism of mTBI has been improved based on different angles. In this review, we have summarized the application of these aforementioned multimodal MRI techniques in mTBI and evaluated its benefits and drawbacks.

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Hu, Ling, Siyu Yang, Bo Jin et Chao Wang. « Advanced Neuroimaging Role in Traumatic Brain Injury : A Narrative Review ». Frontiers in Neuroscience 16 (13 avril 2022). http://dx.doi.org/10.3389/fnins.2022.872609.

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Traumatic brain injury (TBI) is a common source of morbidity and mortality among civilians and military personnel. Initial routine neuroimaging plays an essential role in rapidly assessing intracranial injury that may require intervention. However, in the context of TBI, limitations of routine neuroimaging include poor visualization of more subtle changes of brain parenchymal after injury, poor prognostic ability and inability to analyze cerebral perfusion, metabolite and mechanical properties. With the development of modern neuroimaging techniques, advanced neuroimaging techniques have greatly boosted the studies in the diagnosis, prognostication, and eventually impacting treatment of TBI. Advances in neuroimaging techniques have shown potential, including (1) Ultrasound (US) based techniques (contrast-enhanced US, intravascular US, and US elastography), (2) Magnetic resonance imaging (MRI) based techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion weighted imaging, magnetic resonance elastography and functional MRI), and (3) molecular imaging based techniques (positron emission tomography and single photon emission computed tomography). Therefore, in this review, we aim to summarize the role of these advanced neuroimaging techniques in the evaluation and management of TBI. This review is the first to combine the role of the US, MRI and molecular imaging based techniques in TBI. Advanced neuroimaging techniques have great potential; still, there is much to improve. With more clinical validation and larger studies, these techniques will be likely applied for routine clinical use from the initial research.

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Mao, Yanyan, Chao Chen, Zhenjie Wang, Dapeng Cheng, Panlu You, Xingdan Huang, Baosheng Zhang et Feng Zhao. « Generative adversarial networks with adaptive normalization for synthesizing T2-weighted magnetic resonance images from diffusion-weighted images ». Frontiers in Neuroscience 16 (14 novembre 2022). http://dx.doi.org/10.3389/fnins.2022.1058487.

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Recently, attention has been drawn toward brain imaging technology in the medical field, among which MRI plays a vital role in clinical diagnosis and lesion analysis of brain diseases. Different sequences of MR images provide more comprehensive information and help doctors to make accurate clinical diagnoses. However, their costs are particularly high. For many image-to-image synthesis methods in the medical field, supervised learning-based methods require labeled datasets, which are often difficult to obtain. Therefore, we propose an unsupervised learning-based generative adversarial network with adaptive normalization (AN-GAN) for synthesizing T2-weighted MR images from rapidly scanned diffusion-weighted imaging (DWI) MR images. In contrast to the existing methods, deep semantic information is extracted from the high-frequency information of original sequence images, which are then added to the feature map in deconvolution layers as a modality mask vector. This image fusion operation results in better feature maps and guides the training of GANs. Furthermore, to better preserve semantic information against common normalization layers, we introduce AN, a conditional normalization layer that modulates the activations using the fused feature map. Experimental results show that our method of synthesizing T2 images has a better perceptual quality and better detail than the other state-of-the-art methods.

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Ni, Ruiqing. « Magnetic Resonance Imaging in Tauopathy Animal Models ». Frontiers in Aging Neuroscience 13 (25 janvier 2022). http://dx.doi.org/10.3389/fnagi.2021.791679.

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The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer’s disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.

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Szeles, Dana M., Nicholas J. Milano, Hunter J. Moss, Maria Vittoria Spampinato, Jens H. Jensen et Andreana Benitez. « Brain Reserve in a Case of Cognitive Resilience to Severe Leukoaraiosis ». Journal of the International Neuropsychological Society, 16 juin 2020, 1–10. http://dx.doi.org/10.1017/s1355617720000569.

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Abstract Objective: Leukoaraiosis, or white matter rarefaction, is a common imaging finding in aging and is presumed to reflect vascular disease. When severe in presentation, potential congenital or acquired etiologies are investigated, prompting referral for neuropsychological evaluation in addition to neuroimaging. T2-weighted imaging is the most common magnetic resonance imaging (MRI) approach to identifying white matter disease. However, more advanced diffusion MRI techniques may provide additional insight into mechanisms that influence the abnormal T2 signal, especially when clinical presentations are discrepant with imaging findings. Method: We present a case of a 74-year-old woman with severe leukoaraoisis. She was examined by a neurologist, neuropsychologist, and rheumatologist, and completed conventional (T1, T2-FLAIR) MRI, diffusion tensor imaging (DTI), and advanced single-shell, high b-value diffusion MRI (i.e., fiber ball imaging [FBI]). Results: The patient was found to have few neurological signs, no significant cognitive impairment, a negative workup for leukoencephalopathy, and a positive antibody for Sjogren’s disease for which her degree of leukoaraiosis would be highly atypical. Tractography results indicate intact axonal architecture that was better resolved using FBI rather than DTI. Conclusions: This case illustrates exceptional cognitive resilience in the face of severe leukoaraiosis and the potential for advanced diffusion MRI to identify brain reserve.

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Hsu, Li-Ming, Shuai Wang, Lindsay Walton, Tzu-Wen Winnie Wang, Sung-Ho Lee et Yen-Yu Ian Shih. « 3D U-Net Improves Automatic Brain Extraction for Isotropic Rat Brain Magnetic Resonance Imaging Data ». Frontiers in Neuroscience 15 (16 décembre 2021). http://dx.doi.org/10.3389/fnins.2021.801008.

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Brain extraction is a critical pre-processing step in brain magnetic resonance imaging (MRI) analytical pipelines. In rodents, this is often achieved by manually editing brain masks slice-by-slice, a time-consuming task where workloads increase with higher spatial resolution datasets. We recently demonstrated successful automatic brain extraction via a deep-learning-based framework, U-Net, using 2D convolutions. However, such an approach cannot make use of the rich 3D spatial-context information from volumetric MRI data. In this study, we advanced our previously proposed U-Net architecture by replacing all 2D operations with their 3D counterparts and created a 3D U-Net framework. We trained and validated our model using a recently released CAMRI rat brain database acquired at isotropic spatial resolution, including T2-weighted turbo-spin-echo structural MRI and T2*-weighted echo-planar-imaging functional MRI. The performance of our 3D U-Net model was compared with existing rodent brain extraction tools, including Rapid Automatic Tissue Segmentation, Pulse-Coupled Neural Network, SHape descriptor selected External Regions after Morphologically filtering, and our previously proposed 2D U-Net model. 3D U-Net demonstrated superior performance in Dice, Jaccard, center-of-mass distance, Hausdorff distance, and sensitivity. Additionally, we demonstrated the reliability of 3D U-Net under various noise levels, evaluated the optimal training sample sizes, and disseminated all source codes publicly, with a hope that this approach will benefit rodent MRI research community.Significant Methodological Contribution: We proposed a deep-learning-based framework to automatically identify the rodent brain boundaries in MRI. With a fully 3D convolutional network model, 3D U-Net, our proposed method demonstrated improved performance compared to current automatic brain extraction methods, as shown in several qualitative metrics (Dice, Jaccard, PPV, SEN, and Hausdorff). We trust that this tool will avoid human bias and streamline pre-processing steps during 3D high resolution rodent brain MRI data analysis. The software developed herein has been disseminated freely to the community.

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Banstola, Ashik, et John N. J. Reynolds. « Mapping sheep to human brain : The need for a sheep brain atlas ». Frontiers in Veterinary Science 9 (29 juillet 2022). http://dx.doi.org/10.3389/fvets.2022.961413.

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A brain atlas is essential for understanding the anatomical relationship between neuroanatomical structures. Standard stereotaxic coordinates and reference systems have been developed for humans, non-human primates and small laboratory animals to contribute to translational neuroscience research. Despite similar neuroanatomical and neurofunctional features between the sheep and human brain, little is known of the sheep brain stereotaxy, and a detailed sheep atlas is scarce. Here, we briefly discuss the value of using sheep in neurological research and the paucity of literature concerning the coordinates system during neurosurgical approaches. Recent advancements such as computerized tomography, positron emission tomography, magnetic resonance imaging, functional magnetic resonance imaging and diffusion tensor imaging are used for targeting and localizing the coordinates and brain areas in humans. Still, their application in sheep is rare due to the lack of a 3D stereotaxic sheep atlas by which to map sheep brain structures to its human counterparts. More recently, a T1- and T2-weighted high-resolution MRI 3D stereotaxic atlas of the sheep brain has been generated, however, the journey to create a sheep brain atlas by which to map directly to the human brain is still uncharted. Therefore, developing a detailed sheep brain atlas is valuable for the future to facilitate the use of sheep as a large animal experimental non-primate model for translational neurological research.

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Hou, Yanbing, et Huifang Shang. « Magnetic Resonance Imaging Markers for Cognitive Impairment in Parkinson’s Disease : Current View ». Frontiers in Aging Neuroscience 14 (25 janvier 2022). http://dx.doi.org/10.3389/fnagi.2022.788846.

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Cognitive impairment (CI) ranging from mild cognitive impairment (MCI) to dementia is a common and disturbing complication in patients with Parkinson’s disease (PD). Numerous studies have focused on neuropathological mechanisms underlying CI in PD, along with the identification of specific biomarkers for CI. Magnetic resonance imaging (MRI), a promising method, has been adopted to examine the changes in the brain and identify the candidate biomarkers associated with CI. In this review, we have summarized the potential biomarkers for CI in PD which have been identified through multi-modal MRI studies. Structural MRI technology is widely used in biomarker research. Specific patterns of gray matter atrophy are promising predictors of the evolution of CI in patients with PD. Moreover, other MRI techniques, such as MRI related to small-vessel disease, neuromelanin-sensitive MRI, quantitative susceptibility mapping, MR diffusion imaging, MRI related to cerebrovascular abnormality, resting-state functional MRI, and proton magnetic resonance spectroscopy, can provide imaging features with a good degree of prediction for CI. In the future, novel combined biomarkers should be developed using the recognized analysis tools and predictive algorithms in both cross-sectional and longitudinal studies.

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Dubois, Marine, Antoine Legouhy, Isabelle Corouge, Olivier Commowick, Baptiste Morel, Patrick Pladys, Jean-Christophe Ferré, Christian Barillot et Maïa Proisy. « Multiparametric Analysis of Cerebral Development in Preterm Infants Using Magnetic Resonance Imaging ». Frontiers in Neuroscience 15 (13 avril 2021). http://dx.doi.org/10.3389/fnins.2021.658002.

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ObjectivesThe severity of neurocognitive impairment increases with prematurity. However, its mechanisms remain poorly understood. Our aim was firstly to identify multiparametric magnetic resonance imaging (MRI) markers that differ according to the degree of prematurity, and secondly to evaluate the impact of clinical complications on these markers.Materials and MethodsWe prospectively enrolled preterm infants who were divided into two groups according to their degree of prematurity: extremely preterm (<28 weeks’ gestational age) and very preterm (28–32 weeks’ gestational age). They underwent a multiparametric brain MRI scan at term-equivalent age including morphological, diffusion tensor and arterial spin labeling (ASL) perfusion sequences. We quantified overall and regional volumes, diffusion parameters, and cerebral blood flow (CBF). We then compared the parameters for the two groups. We also assessed the effects of clinical data and potential MRI morphological abnormalities on those parameters.ResultsThirty-four preterm infants were included. Extremely preterm infants (n = 13) had significantly higher frontal relative volumes (p = 0.04), frontal GM relative volumes (p = 0.03), and regional CBF than very preterm infants, but they had lower brainstem and insular relative volumes (respectively p = 0.008 and 0.04). Preterm infants with WM lesions on MRI had significantly lower overall GM CBF (13.3 ± 2 ml/100 g/min versus 17.7 ± 2.5, < ml/100 g/min p = 0.03).ConclusionMagnetic resonance imaging brain scans performed at term-equivalent age in preterm infants provide quantitative imaging parameters that differ with respect to the degree of prematurity, related to brain maturation.

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Yebga Hot, Raïssa, Marine Siwiaszczyk, Scott A. Love, Frédéric Andersson, Ludovic Calandreau, Fabrice Poupon, Justine Beaujoin et al. « A novel male Japanese quail structural connectivity atlas using ultra-high field diffusion MRI at 11.7 T ». Brain Structure and Function, 31 mars 2022. http://dx.doi.org/10.1007/s00429-022-02457-2.

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AbstractThe structural connectivity of animal brains can be revealed using post-mortem diffusion-weighted magnetic resonance imaging (MRI). Despite the existence of several structural atlases of avian brains, few of them address the bird’s structural connectivity. In this study, a novel atlas of the structural connectivity is proposed for the male Japanese quail (Coturnix japonica), aiming at investigating two lines divergent on their emotionality trait: the short tonic immobility (STI) and the long tonic immobility (LTI) lines. The STI line presents a low emotionality trait, while the LTI line expresses a high emotionality trait. 21 male Japanese quail brains from both lines were scanned post-mortem for this study, using a preclinical Bruker 11.7 T MRI scanner. Diffusion-weighted MRI was performed using a 3D segmented echo planar imaging (EPI) pulsed gradient spin-echo (PGSE) sequence with a 200 $$\upmu$$ μ m isotropic resolution, 75 diffusion-encoding directions and a b-value fixed at 4500 s/mm2. Anatomical MRI was likewise performed using a 2D anatomical T2-weighted spin-echo (SE) sequence with a 150 $$\upmu$$ μ m isotropic resolution. This very first anatomical connectivity atlas of the male Japanese quail reveals 34 labeled fiber tracts and the existence of structural differences between the connectivity patterns characterizing the two lines. Thus, the link between the male Japanese quail’s connectivity and its underlying anatomical structures has reached a better understanding.

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Tang, Fei, Hui Liu, Xiao Jie Zhang, Hui Hui Zheng, Yong Ming Dai, Li Yun Zheng, Wen Han Yang, Yan Yao Du et Jun Liu. « Evidence for Dopamine Abnormalities Following Acute Methamphetamine Exposure Assessed by Neuromelanin-Sensitive Magnetic Resonance Imaging ». Frontiers in Aging Neuroscience 14 (30 mai 2022). http://dx.doi.org/10.3389/fnagi.2022.865825.

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BackgroundNeuromelanin-sensitive magnetic resonance imaging (NM-MRI) is a newly developed MRI technique that provides a non-invasive way to indirectly measure of dopamine (DA) function. This study aimed to determine NM concentrations in brain regions following acute methamphetamine (MA) administration using NM-MRI and to explore whether NM-MRI can be used as a biomarker of DA function in non-neurodegenerative diseases.MethodsBaseline NM-MRI, T1-weighted and T2-weighted images were acquired from 27 rats before drug/placebo injection. The control group (n = 11) received acute placebo (Normal saline), while the experimental group (n = 16) received acute MA. NM-MRI scans were performed 5, 30, 60 and 90 min after injection. Regions of interest (ROIs), including the caudate putamen (CP), nucleus accumbens (NAc), hippocampus (HIP), substantia nigra (SN) and crus cerebri (CC), were manually drawn by an experienced radiologist. NM-MRI signal intensity in five brain regions at different time points (baseline and 5, 30, 60, and 90 min) were analyzed.ResultsIn both the control and experimental groups, at each time point (baseline and 5, 30, 60, and 90 min), the SN exhibited significantly higher NM-MRI signal intensity than the other brain regions (P < 0.05). In addition, acute MA administration resulted in a continuous upward trend in NM-MRI signal intensity in each brain region over time. However, there was no such trend over time in the control group. The NM-MRI signal intensity of SN in the experimental group was significantly higher at the 60 and 90 min compared with that in the control group (P values were 0.042 and 0.042 respectively). Within experimental group, the NM-MRI signal intensity of SN was significantly higher at the 60 and 90 min compared with that before MA administration (P values were 0.023 and 0.011 respectively). Increased amplitudes and rates of NM-MRI signal intensity were higher in the SN than in other brain regions after MA administration.ConclusionOur results indicated that NM was mainly deposited in the SN, and the conversion of DA to NM was most significant in the SN after acute MA exposure. Increased DA release induced by acute MA exposure may lead to increased accumulation of NM in multiple brain regions that can be revealed by NM-MRI. NM-MRI may serve as a powerful imaging tool that could have diverse research and clinical applications for detecting pathological changes in drug addiction and related non-neurodegenerative diseases.

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Huang, Jiayuan, Pengfei Ke, Xiaoyi Chen, Shijia Li, Jing Zhou, Dongsheng Xiong, Yuanyuan Huang et al. « Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients ». Frontiers in Aging Neuroscience 14 (3 mars 2022). http://dx.doi.org/10.3389/fnagi.2022.823502.

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Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20–60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.

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Wang, Jianan, Emily S. Nichols, Megan E. Mueller, Barbra de Vrijer, Roy Eagleson, Charles A. McKenzie, Sandrine de Ribaupierre et Emma G. Duerden. « Semi-automatic segmentation of the fetal brain from magnetic resonance imaging ». Frontiers in Neuroscience 16 (11 novembre 2022). http://dx.doi.org/10.3389/fnins.2022.1027084.

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BackgroundVolumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings.MethodsAdult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9–36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB’s Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman’s test for repeated measures.ResultsComparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6–0.8] and 0.54 (IQR = 0.4–0.6), respectively. A Friedman’s test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p < 0.001).ConclusionDeformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development.

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