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Brain Sciences
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Brain Magnetic Resonance Imaging in Neurological Disorders
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Brain Magnetic Resonance Imaging in Neurological Disorders

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: closed (23 July 2024) | Viewed by 12204

Special Issue Editor

Dr. Francesca Benuzzi

E-Mail Website
Guest Editor
Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
Interests: neuroimaging; emotion; neurological disorder; fMRI; neuropsychology; social cognition
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, significant advances in the study of diseases involving the nervous system have been achieved by neuroimaging techniques, and particularly by magnetic resonance imaging (MRI). Structural and functional MRI brain mapping are used to explore the changes associated with several diseases, thus gaining new insight into pathological processes. Moreover, MRI has been found to be a powerful tool in clinical practice, for instance, to define eloquent brain regions that must be preserved during neurosurgery and to identify therapeutic targets and prognostic biomarkers.

This Special Issue of Brain Sciences aims to present a collection of research that describes the most recent advancements in the study of neurological diseases using MRI. Authors are invited to submit cutting-edge research and reviews on diseases that involve the nervous system, including, among others, epilepsy, neurodegenerative diseases, brain tumors and cerebrovascular diseases. Studies on structural and functional MRI brain mapping are also invited for submission.

Dr. Francesca Benuzzi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neurological disorder
  • brain
  • neuroimaging
  • magnetic resonance imaging
  • epilepsy
  • neurodegenerative diseases
  • brain tumors

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Published Papers (6 papers)

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Research

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14 pages, 2755 KiB  
Article
Assessing Language Lateralization through Gray Matter Volume: Implications for Preoperative Planning in Brain Tumor Surgery
by Daniel Solomons, Maria Rodriguez-Fernandez, Francisco Mery-Muñoz, Leonardo Arraño-Carrasco, Francisco Sahli Costabal and Carolina Mendez-Orellana
Brain Sci. 2024, 14(10), 954; https://doi.org/10.3390/brainsci14100954 - 24 Sep 2024
Viewed by 897
Abstract
Background/Objectives: Functional MRI (fMRI) is widely used to assess language lateralization, but its application in patients with brain tumors can be hindered by cognitive impairments, compensatory neuroplasticity, and artifacts due to patient movement or severe aphasia. Gray matter volume (GMV) analysis via voxel-based [...] Read more.
Background/Objectives: Functional MRI (fMRI) is widely used to assess language lateralization, but its application in patients with brain tumors can be hindered by cognitive impairments, compensatory neuroplasticity, and artifacts due to patient movement or severe aphasia. Gray matter volume (GMV) analysis via voxel-based morphometry (VBM) in language-related brain regions may offer a stable complementary approach. This study investigates the relationship between GMV and fMRI-derived language lateralization in healthy individuals and patients with left-hemisphere brain tumors, aiming to enhance accuracy in complex cases. Methods: The MRI data from 22 healthy participants and 28 individuals with left-hemisphere brain tumors were analyzed. Structural T1-weighted and functional images were obtained during three language tasks. Language lateralization was assessed based on activation in predefined regions of interest (ROIs), categorized as typical (left) or atypical (right or bilateral). The GMV in these ROIs was measured using VBM. Linear regressions explored GMV-lateralization associations, and logistic regressions predicted the lateralization based on the GMV. Results: In the healthy participants, typical left-hemispheric language dominance correlated with higher GMV in the left pars opercularis of the inferior frontal gyrus. The brain tumor participants with atypical lateralization showed increased GMV in six right-hemisphere ROIs. The GMV in the language ROIs predicted the fMRI language lateralization, with AUCs from 80.1% to 94.2% in the healthy participants and 78.3% to 92.6% in the tumor patients. Conclusions: GMV analysis in language-related ROIs effectively complements fMRI for assessing language dominance, particularly when fMRI is challenging. It correlates with language lateralization in both healthy individuals and brain tumor patients, highlighting its potential in preoperative language mapping. Further research with larger samples is needed to refine its clinical utility. Full article
(This article belongs to the Special Issue Brain Magnetic Resonance Imaging in Neurological Disorders)
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14 pages, 3194 KiB  
Article
Qualitative and Visual Along-Tract Analysis of Diffusion-Based Parameters in Patients with Diffuse Gliomas
by Markus Fahlström, Sadia Mirza, Åsa Alberius Munkhammar, Maria Zetterling and Francesco Latini
Brain Sci. 2024, 14(3), 213; https://doi.org/10.3390/brainsci14030213 - 26 Feb 2024
Cited by 1 | Viewed by 1452
Abstract
Background: Grade 2–3 diffuse gliomas (DGs) show extensive infiltration through white matter (WM) tracts. Along-tract analysis of WM tracts based on diffusion tensor tractography (DTI) can been performed to assess the microstructural integrity of WM tracts. The clinical implication of these DTI-related findings [...] Read more.
Background: Grade 2–3 diffuse gliomas (DGs) show extensive infiltration through white matter (WM) tracts. Along-tract analysis of WM tracts based on diffusion tensor tractography (DTI) can been performed to assess the microstructural integrity of WM tracts. The clinical implication of these DTI-related findings is still under debate, especially in tumor patients. The aim of this study was to analyze and compare diffusion-based parameters along WM tracts and variables specific to WM -tumor interactions in DGs and correlate them with preoperative neuropsychological assessment. Methods: Fourteen patients with IDH-mutated grade 2–3 DGs were included. Tumor volumes were manually segmented on 3D-FLAIR images after spatial normalisation to MNI space. DTI was acquired using a single-shot echo-planar sequence on a 3T with 48 sampling directions. DTI data were reconstructed within the MNI space using q-space diffeomorphic reconstruction (QSDR) in DSI studio. Five bilateral sets of WM tracts were reconstructed based on the HCP-1065 template. All WM tracts were stretched to the same length of 100 indices, and for each index diffusion-based parameters fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), mean diffusivity (MD) and quantitative anisotropy (QA) were sampled. Tumor-related parameters (TRP); tumor volume (Tv), maximum tumor presence (MTP) and the number of sequential indices in which a tumor is present (Te) were derived based on the along-tract analysis. Normal data were constructed by calculating the average and standard deviations of contralateral and not-affected WM tracts for each diffusion-based parameter, respectively. Affected WM tracts were individually compared to normal data using a z-test. Preoperative neuropsychological assessment was performed in all subjects and correlated to results from the along-tract analysis using correlation and logistic regression models. Results: Abnormalities in diffusion-based parameters were detected in WM tracts. Topographical and quantitative information were presented within the same graph. AD and MD displayed the highest linear correlation with the TRPs. Abnormal QA showed a linear correlation with Tv per WM tract. Neuropsychological impairment was correlated with all the TRPs and with abnormal FA (p < 0.05) and abnormal QA (p < 0.01). Abnormal QA was the only independent variable able to predict the presence of neuropsychological impairment in the patients based on the linear regression analysis. Conclusions: Graphical presentation of the along-tract analysis presented in this study shows that it may be a sensitive and robust method to acquire and display topographical and qualitative information regarding WM tracts in close proximity to DGs. Further studies and refinements to the methods presented herein may advance current clinical methods for evaluating displacement and infiltrations and further aid the efforts of pre-planning surgical interventions with the goal to maximise EOR and tailor oncological treatment. Full article
(This article belongs to the Special Issue Brain Magnetic Resonance Imaging in Neurological Disorders)
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19 pages, 8447 KiB  
Article
Analysis of Functional Neuroplastic Changes in the Cortical Language System in Relation to Different Growth Patterns of Glioblastoma
by Katharina Hense, Daniel Deuter, Mark W. Greenlee, Christina Wendl, Nils Ole Schmidt, Christian Stroszczynski, Christian Doenitz, Christian Ott and Katharina Rosengarth
Brain Sci. 2023, 13(6), 867; https://doi.org/10.3390/brainsci13060867 - 27 May 2023
Viewed by 1702
Abstract
The interpretation of fMRI data in glioblastoma (GB) is challenging as these tumors exhibit specific hemodynamic processes which, together with malignancy, tumor volume and proximity to eloquent cortex areas, may lead to misinterpretations of fMRI signals. The aim of this study was to [...] Read more.
The interpretation of fMRI data in glioblastoma (GB) is challenging as these tumors exhibit specific hemodynamic processes which, together with malignancy, tumor volume and proximity to eloquent cortex areas, may lead to misinterpretations of fMRI signals. The aim of this study was to investigate if different radiologically defined GB tumor growth patterns may also influence the fMRI signal, activation pattern and functional connectivity differently. Sixty-four patients with left-hemispheric glioblastoma were included and stratified according to their radiologically defined tumor growth pattern into groups with a uniform (U-TGP) or diffuse tumor growth pattern (D-TGP). Task-based fMRI data were analyzed using SPM12 with the marsbar, LI and CONN toolboxes. The percent signal change and the laterality index were analyzed, as well as functional connectivity between 23 selected ROIs. Comparisons of both patient groups showed only minor non-significant differences, indicating that the tumor growth pattern is not a relevant influencing factor for fMRI signal. In addition to these results, signal reductions were found in areas that were not affected by the tumor underlining that a GB is not a localized but rather a systemic disease affecting the entire brain. Full article
(This article belongs to the Special Issue Brain Magnetic Resonance Imaging in Neurological Disorders)
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Review

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18 pages, 4716 KiB  
Review
Brain Magnetic Resonance Imaging in Wilson’s Disease—Significance and Practical Aspects—A Narrative Review
by Tomasz Litwin, Barbara Rędzia-Ogrodnik, Agnieszka Antos, Adam Przybyłkowski, Anna Członkowska and Jan Paweł Bembenek
Brain Sci. 2024, 14(7), 727; https://doi.org/10.3390/brainsci14070727 - 19 Jul 2024
Cited by 2 | Viewed by 2623
Abstract
Wilson’s disease (WD) is a genetic disorder of copper metabolism with pathological copper accumulation in many organs, resulting in clinical symptoms, mostly hepatic and neuropsychiatric. As copper accumulates in the brain during WD, and almost 50% of WD patients at diagnosis present with [...] Read more.
Wilson’s disease (WD) is a genetic disorder of copper metabolism with pathological copper accumulation in many organs, resulting in clinical symptoms, mostly hepatic and neuropsychiatric. As copper accumulates in the brain during WD, and almost 50% of WD patients at diagnosis present with neurological symptoms, neuroimaging studies (especially brain magnetic resonance imaging (MRI)) are part of WD diagnosis. The classical sequences (T1, T2, and fluid-attenuated inversion recovery) were used to describe brain MRI; however, with the development of neuroradiology, several papers proposed the use of new MRI sequences and techniques like susceptibility-weighted images, T2*, diffusion MRI, tractography, volumetric assessment and post-processing brain MRI analysis of paramagnetic accumulation—quantitative susceptibility mapping. Based on these neuroradiological data in WD, currently, brain MRI semiquantitative scale and the pathognomonic neuroradiological brain MRI signs in WD were proposed. Further, the volumetric studies and brain iron accumulation MRI analysis suggested brain atrophy and iron accumulation as biomarkers of neurological WD disease severity. All these results highlight the significance of brain MRI examinations in WD. Due to the extreme progress of these studies, based on the available literature, the authors present the current state of knowledge about the significance, practical aspects, and future directions of brain MRI in WD. Full article
(This article belongs to the Special Issue Brain Magnetic Resonance Imaging in Neurological Disorders)
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24 pages, 685 KiB  
Review
Neurofilaments Light Chain in Neurodegenerative Dementias: A Review of Imaging Correlates
by Chiara Gallingani, Chiara Carbone, Manuela Tondelli and Giovanna Zamboni
Brain Sci. 2024, 14(3), 272; https://doi.org/10.3390/brainsci14030272 - 13 Mar 2024
Cited by 7 | Viewed by 2673
Abstract
Neurofilaments light chain (NfLs) are currently recognized as a marker of axonal injury and degeneration. Their measurement in biological fluids has a promising role in the diagnosis, prognosis, and monitoring of the therapeutic response in neurological diseases, including neurodegenerative dementias. In recent years, [...] Read more.
Neurofilaments light chain (NfLs) are currently recognized as a marker of axonal injury and degeneration. Their measurement in biological fluids has a promising role in the diagnosis, prognosis, and monitoring of the therapeutic response in neurological diseases, including neurodegenerative dementias. In recent years, their relationship with clinical phenotypes and measures of disease severity has been extensively studied. Here, we reviewed studies investigating the association between NfLs and imaging measures of grey matter (GM) and white matter (WM) damage in neurodegenerative dementias. We identified a large number of studies investigating this association in Alzheimer’s disease (AD) and disorders of the frontotemporal dementia (FTD) spectrum. Results were heterogeneous, possibly due to different methodological approaches—both in NfL measurements and imaging analyses—and inclusion criteria. However, a positive association between NfL levels and GM atrophy, WM microstructural disruption, glucose hypometabolism, and protein accumulation emerged invariably, confirming the role of NfLs as a reliable biomarker for neurodegenerative dementias, albeit not specific. Full article
(This article belongs to the Special Issue Brain Magnetic Resonance Imaging in Neurological Disorders)
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16 pages, 990 KiB  
Review
Impaired Self-Awareness in Parkinson’s and Huntington’s Diseases: A Literature Review of Neuroimaging Correlates
by Manuela Tondelli, Miriana Manigrasso and Giovanna Zamboni
Brain Sci. 2024, 14(3), 204; https://doi.org/10.3390/brainsci14030204 - 23 Feb 2024
Viewed by 1906
Abstract
Little is known about the brain correlates of anosognosia or unawareness of disease in Parkinson’s Disease (PD) and Huntington’s Disease (HD). The presence of unawareness or impaired self-awareness (ISA) of illness has profound implications for patients and their caregivers; therefore, studying awareness and [...] Read more.
Little is known about the brain correlates of anosognosia or unawareness of disease in Parkinson’s Disease (PD) and Huntington’s Disease (HD). The presence of unawareness or impaired self-awareness (ISA) of illness has profound implications for patients and their caregivers; therefore, studying awareness and its brain correlates should be considered a key step towards developing effective recognition and management of this symptom as it offers a window into the mechanism of self-awareness and consciousness as critical components of the human cognition. We reviewed research studies adopting MRI or other in vivo neuroimaging technique to assess brain structural and/or functional correlates of unawareness in PD and HD across different cognitive and motor domains. Studies adopting task or resting-state functional magnetic resonance imaging, and/or 18-F fluorodeoxyglucose positron emission tomography brain imaging and/or magnetic resonance imaging structural measures were considered. Only six studies investigating neuroimaging features of unawareness in PD and two in HD were identified; there was great heterogeneity in the clinical characteristics of the study participants, domain of unawareness investigated, method of unawareness assessment, and neuroimaging technique used. Nevertheless, some data converge in identifying regions of the salience and frontoparietal networks to be associated with unawareness in PD patients. In HD, the few data are affected by the variability in the severity of motor symptoms. Further studies are needed to better understand the mechanisms and brain correlates of unawareness in PD and HD; in addition, the use of dopaminergic medications should be carefully considered. Full article
(This article belongs to the Special Issue Brain Magnetic Resonance Imaging in Neurological Disorders)
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