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Brain Sciences
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Using Neuroimaging to Explore Neurodegenerative Diseases
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Using Neuroimaging to Explore Neurodegenerative Diseases

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurodegenerative Diseases".

Deadline for manuscript submissions: 15 June 2026 | Viewed by 6556

Special Issue Editor

Dr. Ting Shen

E-Mail Website
Guest Editor
Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
Interests: neurodegenerative diseases; multi-omics research; neuroimaging; imaging-omics study; data-driven subtyping and disease tracking

Special Issue Information

Dear Colleagues,

Neuroimaging advancements have revolutionized our understanding of neurodegenerative diseases, offering unprecedented insights into pathophysiology, early diagnosis, and therapeutic innovation. This Special Issue, “Using Neuroimaging to Explore Neurodegenerative Diseases” aims to compile cutting-edge research and interdisciplinary perspectives on the application of neuroimaging to unravel the complexities of neurodegeneration. We welcome contributions addressing: (1) emerging technologies; (2) novel biomarkers for diagnosing and disease tracking; (3) multimodal integration; (4) AI-driven analytics for subtype classification or prognostic modeling; (5) clinical translation of imaging findings; and (6) cross-disciplinary synergies with genomics, proteomics, and digital health tools. Submissions may include original research articles, reviews articles, systematic reviews, short communications that bridge technical advancements with clinical or mechanistic insights.

Dr. Ting Shen
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 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

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

  • neuroimaging
  • neurodegenerative diseases
  • multidisciplinary research
  • imaging-omics study
  • multimodal integration
  • AI-driven analytics

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Published Papers (4 papers)

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Research

Jump to: Review

16 pages, 751 KB  
Article
Frontal Lobe and Subregional Volumetric Alterations Across Alzheimer’s Disease, Amnestic Mild Cognitive Impairment, and Vascular Dementia: An MRI Volumetry Study
by Stefan Stojanoski, Katarina Karher, Duško Kozić, Siniša S. Babović, Miloš Vuković and Katarina Koprivšek
Brain Sci. 2026, 16(3), 317; https://doi.org/10.3390/brainsci16030317 - 16 Mar 2026
Viewed by 670
Abstract
Background: Frontal lobe involvement represents an important but heterogeneously expressed feature across neurodegenerative and vascular cognitive disorders. While frontal atrophy has been described in Alzheimer’s disease (AD), detailed volumetric assessment of frontal subregions across Alzheimer’s disease, amnestic mild cognitive impairment (aMCI), and vascular [...] Read more.
Background: Frontal lobe involvement represents an important but heterogeneously expressed feature across neurodegenerative and vascular cognitive disorders. While frontal atrophy has been described in Alzheimer’s disease (AD), detailed volumetric assessment of frontal subregions across Alzheimer’s disease, amnestic mild cognitive impairment (aMCI), and vascular dementia (VaD) remains insufficiently characterized. The aim of this study was to evaluate frontal lobe and frontal subregional volumetric alterations across these diagnostic groups using automated MRI-based volumetry. Methods: This cross-sectional study included 120 participants divided into four groups: AD, VaD, aMCI, and cognitively healthy controls (n = 30 per group). All participants underwent standardized neuropsychological assessment and 3T brain MRI. Automated volumetric analysis of the frontal lobe and its subregions was performed using the Vol2Brain pipeline. Group differences in total intracranial volume–adjusted frontal volumes were assessed using analysis of covariance, controlling for age and sex, followed by Bonferroni-corrected post hoc comparisons. False discovery rate (FDR) correction was applied across subregional comparisons. Results: A significant main effect of diagnostic group was observed for total frontal lobe volume, with lower adjusted volumes in patients with AD compared with aMCI and cognitively healthy controls. After correction for multiple comparisons, only total frontal lobe volume remained statistically significant. At the nominal level, group differences were observed in several frontal subregions, predominantly involving prefrontal and orbitofrontal areas. However, these findings did not survive FDR correction and should be interpreted as exploratory. No consistent frontal volumetric pattern was observed in VaD. Receiver operating characteristic analysis demonstrated moderate discriminatory ability of total frontal lobe volume for distinguishing AD from cognitively healthy controls. Conclusions: Automated MRI-based volumetry revealed global frontal lobe reduction in Alzheimer’s disease, whereas subregional findings were exploratory after correction for multiple testing. Frontal volumetric measures did not demonstrate a characteristic pattern in VaD. Global frontal volume may provide complementary structural information within clinically define cognitive disorders. Full article
(This article belongs to the Special Issue Using Neuroimaging to Explore Neurodegenerative Diseases)
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16 pages, 1542 KB  
Article
Volumetric MRI Markers of Cognitive Impairment in Relapsing-Remitting Multiple Sclerosis: Cerebellar White Matter Loss, Pallidum Atrophy, and Choroid Plexus Enlargement
by Weronika Galus, Katarzyna Zawiślak-Fornagiel, Julia Wyszomirska, Oskar Bożek, Daniel Ledwoń, Patrycja Romaniszyn-Kania, Aleksandra Tuszy, Joanna Siuda and Andrzej W. Mitas
Brain Sci. 2026, 16(2), 214; https://doi.org/10.3390/brainsci16020214 - 11 Feb 2026
Cited by 1 | Viewed by 783
Abstract
Cognitive impairment (CI) is a common and disabling manifestation of multiple sclerosis (MS), yet it remains underdiagnosed in clinical settings. This study aims to identify the volumetric MRI markers of CI in MS patients. A total of 79 MS patients were enrolled; after [...] Read more.
Cognitive impairment (CI) is a common and disabling manifestation of multiple sclerosis (MS), yet it remains underdiagnosed in clinical settings. This study aims to identify the volumetric MRI markers of CI in MS patients. A total of 79 MS patients were enrolled; after exclusions, 63 with relapsing-remitting MS (RRMS) and 7 with primary progressive MS were analyzed. All participants underwent neuropsychological testing (CVLT, BVRT, CTT, VFT, VST, and SDMT). Brain volumes were analyzed using FreeSurfer. In RRMS, 59% had CI (35% single-domain, 24% multidomain). Multidomain CI was linked to reduced left cerebellar white matter and bilateral pallidum volumes, slight choroid plexus enlargement, and higher lesion volume versus cognitively preserved patients. Significant correlations were found between brain volumes and cognitive test scores: cerebellar and cerebral white matter, corpus callosum, subcortical gray matter, and thalamus volumes correlated positively with measures of processing speed, memory, and verbal fluency, while higher lesion load and larger choroid plexus volumes were associated with poorer cognitive performance. CI in MS is linked to both global and regional brain atrophy, as well as lesion load. Volumetric MRI, including choroid plexus analysis, may represent candidate imaging correlates of CI; however, longitudinal and externally validated studies are needed to confirm their predictive value and clinical utility. Full article
(This article belongs to the Special Issue Using Neuroimaging to Explore Neurodegenerative Diseases)
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20 pages, 3404 KB  
Article
Dynamic Synergy Network Analysis Reveals Stage-Specific Regional Dysfunction in Alzheimer’s Disease
by Xiaoyan Zhang, Chao Han, Jingbo Xia, Lingli Deng and Jiyang Dong
Brain Sci. 2025, 15(6), 636; https://doi.org/10.3390/brainsci15060636 - 12 Jun 2025
Viewed by 1565
Abstract
Background: Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neurodegeneration and connectivity deterioration. While resting-state functional magnetic resonance imaging (fMRI) provides critical insights into brain network abnormalities, traditional mutual information-based methods exhibit inherent limitations in characterizing the dynamic synergistic mechanisms [...] Read more.
Background: Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neurodegeneration and connectivity deterioration. While resting-state functional magnetic resonance imaging (fMRI) provides critical insights into brain network abnormalities, traditional mutual information-based methods exhibit inherent limitations in characterizing the dynamic synergistic mechanisms between cerebral regions. Method: This study pioneered the application of an Integrated Information Decomposition (ΦID) framework in AD brain network analysis, constructing single-sample network models based on ΦID-derived synergy metrics to systematically compare their differences with mutual information-based methods in pathological sensitivity, computational robustness, and network representation capability, while detecting brain regions with declining dynamic synergy during AD progression through intergroup t-tests. Result: The key finding are as follows: (1) synergy metrics exhibited lower intra-group coefficient of variation than mutual information metrics, indicating higher computational stability; (2) single-sample reconstruction significantly enhanced the statistical power in intergroup difference detection; (3) synergy metrics captured brain network features that are undetectable by traditional mutual information methods, with more pronounced differences between networks; (4) key node analysis demonstrated spatiotemporal degradation patterns progressing from initial dysfunction in orbitofrontal–striatal–temporoparietal pathways accompanied by multi-regional impairments during prodromal stages, through moderate-phase decline located in the right middle frontal and postcentral gyri, to advanced-stage degeneration of the right supramarginal gyrus and left inferior parietal lobule. ΦID-driven dynamic synergy network analysis provides novel information integration theory-based biomarkers for AD progression diagnosis and potentially lays the foundation for pathological understanding and subsequent targeted therapy development. Full article
(This article belongs to the Special Issue Using Neuroimaging to Explore Neurodegenerative Diseases)
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Review

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19 pages, 570 KB  
Review
Imaging of Cerebral Iron as an Emerging Marker for Brain Aging, Neurodegeneration, and Cerebrovascular Diseases
by Chi-Heng Zhou and Yi-Cheng Zhu
Brain Sci. 2025, 15(9), 944; https://doi.org/10.3390/brainsci15090944 - 29 Aug 2025
Cited by 4 | Viewed by 2644
Abstract
Iron is critical for brain development, metabolism, and function; however, dysregulated iron disposition contributes to neurological diseases. Many neuroimaging techniques have enabled detection of iron susceptibility, and quantitative susceptibility mapping (QSM) offers a sensitive magnetic resonance imaging (MRI) technique for quantifying brain iron. [...] Read more.
Iron is critical for brain development, metabolism, and function; however, dysregulated iron disposition contributes to neurological diseases. Many neuroimaging techniques have enabled detection of iron susceptibility, and quantitative susceptibility mapping (QSM) offers a sensitive magnetic resonance imaging (MRI) technique for quantifying brain iron. To elucidate the functional role of cerebral iron and clarify the utility of QSM in establishing iron as a potential biomarker, this review synthesizes cellular and regional behaviours of iron from physiological aging to disease conditions, with a focus on neurodegeneration such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS), as well as cerebral small vessel disease (CSVD) as cerebrovascular manifestation. Distinct patterns of iron distribution in deep gray matter and selective cortical regions are associated with motor and cognitive impairment, while the interaction between iron, vascular integrity, and glial function further stresses its pathological relevance. QSM of iron may, thereby, serve as a marker to monitor iron-related disease progression and facilitate intervention. Temporal dynamics of iron in brain pathology remain underexplored, and we emphasized the need for longitudinal mapping and multi-modality biomarker integration. Establishing iron as a clinically relevant imaging biomarker requires continued investigation into its topographical, molecular, and functional correlates across aging and disease trajectories. Full article
(This article belongs to the Special Issue Using Neuroimaging to Explore Neurodegenerative Diseases)
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